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Topic: A – SWOT Analysis and B – Knowledge Management Memo

Format/Length: 4-5 (1-2 SWOT Anaylsis/2-3 Knowledge Memo) pages | APA Format | MUST REFERENCE 2-3 COURSE RESOURCES 

Due: Friday, November 12, 2021

Info: Please see attached detailed assignment instructions, case study, referenced week 1 assignment, and course resources attached.  

Week 4: Understanding the Industry and Its Environment

Skill #4: Collect knowledge and information about current events, technology,
the business environment, the client’s business, your company and consider
this when making decisions.

Looking back to week one and the recommendations you made in the week one
assessment in conjunction with this week’s material consider EC’s position in the
industry, their current customers and those in the future and identify trends, ideas,
and technology that you feel Dwight should consider in growing the company. For this
skill, Dwight wants to see how well you can judge the external trends for the business
by measuring your understanding of a SWOT analysis. Below is the SWOT chart that
Dwight has developed.

Strengths Weaknesses

• Strong Internet growth
• Sound financial status
• Use of state-of-the-art technology to

produce competitive products
• Made in America Qualified
• Employment of Wounded American

Veterans

• Medical Insurance is very high because
of the wounded employees

• revenue based on individual buyers
rather than larger industry customers

• Sourcing material is becoming harder
• More leadership is needed
• No KM department
• Understaffed IT department

Opportunities Threats
• AI in Production and Customer Service
• New Engineering of Wheel Chairs is

leading to new in-home products (EC
can diversify)

• Expanding EC workforce by dropping
the Wounded American Vet Hire policy

• Regulations making lithium batteries
safer will make new product line
possible

• AI in Production and Customer Service
• Many large companies are buying

smaller companies and becoming one
stop shops for medical accessories

• Law suits for engineering and design
flaws are increasing dramatically

• Losing larger heath center customers
• Sourcing material is becoming harder

Skill #5: Know the basics of knowledge management.

Inga Swanson was one of the first employees Dwight and Ike hired. She runs the
customer relations department and now the online returns and rewards programs as
well. Recently she has gone to Dwight and Ike with the idea that her commitments to
the webstore are getting so demanding that she needs help in several areas. She
wants to hire people to take over the customer relations department and online
returns so she can focus on the webstore and move into a marketing role. She thinks
that Dwight and Ike should consider this move for two important reasons; better
decision making and should anything happen to her the whole online and customer
relations departments would shut down. Ike agreed immediately and Dwight was right
behind him. The problem Dwight realized almost immediately was how would the
transition work with all that knowledge in Inga’s head? and all the tools she uses to
measure her marketing goals etc. How can we make good decisions without them?

Dwight wants you to look at the idea of collecting and storing the knowledge Inga and
the others have in the business. Using the course material and prior business class
experience complete a brief 2–3 page memo outlining the steps a manager might
take to make the transition go smoothly. In the outline include:

• Explain how to capture, collect, and store knowledge for the company.
• Explain how these actions will affect performance in the company.
• Describe how you go about collecting knowledge from Inga.
• Explain how the knowledge will affect the hiring decisions for the new

departments or should it be teams?
• Explain how it could affect Inga’s new role.

Weekly Brainstorming Projects
Easy Chairs Training Program
The Leaders of Easy Chairs (EC), Dwight Rickenbacker and Ike Omar, have decided
that they want to customize their management training program to fit the company both
stateside, abroad and online. They have tasked your group, BMGT 485 Class
Consulting Firm, to create a program that features the top ten skills they believe an
Easy Chairs manager should possess in a contemporary business arena. Rickenbacker
and Omar are confident that if their managers have these skills the company will profit
immensely.
Dwight, who is guiding this project, has given you a course outline, the list of skills, and
course material he believes will enhance the managerial candidates in their training. He
has also given you some of the most common examples of the skill in action so that he
can see those candidates that apply the skill well and those who need improvement. He
wants your firm to develop the best answers to these scenarios and present them
to him for evaluation. This way he can determine if the candidates are a good fit for
EC and where he can help them to improve going forward.
Dwight envisions the program class to work as follows:

• Each week the firm will be given a small project, case study or activity to
complete that relates to one of the skills he deems important to company
success.

• The firm, and you as a member, will brainstorm the activity answer discussing as
a team the best way the manager can employ the skill to complete the activity.

To help the firm better Dwight has supplied a corporate history of Easy Chairs.

Company History

Dwight Rickenbacker and Ike Omar were two American Army Veterans who
wanted to make a difference for their fellow wounded veterans. They decided
that they wanted to make semi-customized wheelchairs. After researching the
idea, the two vets agreed that they were going to do something unique with
the wheelchairs. Dwight and Ike decided to make the wheelchairs with 3-D
printing with easily replaceable parts so repairs could be done by someone
with basic mechanical skills. They also agreed that they would only hire
veterans as employees.

Dwight and Ike started their business, EC’s five years ago in Birmingham,
Alabama. Since then, the business has grown exponentially. Last year gross
sales were over $7 million and was projected that the business will reach $9
million by the end of next year.

A significant part of Easy Chairs’ success has been through Internet sales.
The company website is geared to the American market. The average cost of
a non-motorized chair is $59.00, half of the cost of a simple product found at
Walmart. The battery-operated models average between $500 and $600,
almost a quarter of the traditionally produced models. Prices for parts for the
chairs are varied but the most expensive part is the battery for the mobile
units, which is priced at one-fifteenth the price of an average battery. The
company can customize colors, add oxygen container carriers and other
features that improve the wheelchair-bound person’s life for minimal cost
because their computer program allows the chair to be designed to each
person’s specifications before manufacturing. Last year, Rickenbacker
decided to sell their products overseas both via the internet and through
licensed distributors. Currently, they have agreements with distributors
in Japan and South Korea. They hope to expand more abroad and are
considering adding manufacturing operations abroad as well.

Easy Chair Memo

To: Dwight Rickenbacker, Ike Omar

From: Kyami Clarke

CC: Amer Yaqub

Date: Wednesday, November 10, 2021

Re: Easy Chair “Manufacturing Abroad

Due to the profound changes in the business field, many business entities have sought the
global mindset. Understandably, pursuing the global mindset has been made easier
through the use of technology. Over time, businesses have grown internationally simply
through embracing technology. For Easy Chairs to embrace international marketing and
expand their manufacturing operations abroad, the managers should consider the
following.

The planning and decision-making process, organizing process, leading process, Staffing
and controlling process are fundamental. Easy Chair managers should be able to make
quality decisions regarding their plans. In Planning Easy Chairs should choose the
appropriate strategies and actions and the resources to achieve its goals and objectives of
manufacturing abroad. The organizing process mostly involves worker engagement and
relationships (Gleeson, 2017). Workers, therefore, need to work together to achieve
organizational goals. According to Peter Drucker’s management principle, the leading
process requires managers to have desirable leadership qualities. Easy Chairs managers
should be able to motivate, inspire and create good communication with their employees.
Additionally, the management should ensure proper division of labour and specialization
when staffing (Trapp, 2014). Lastly, in the controlling process, the managers should
ensure monitoring and evaluation to help achieve their set goals of manufacturing abroad.

To achieve global manufacturing goals, I would advise Easy Chairs managers to ensure
skills such as cultural knowledge. This is a critical area as culture clash hinders business
growth (Colvin, 2006). Culture knowledge can be attained through social rules, ethics
and norms, political systems, history and beliefs. Flexibility and adaptability are key too.
This would be helpful when it comes to quality production. The managers must learn to
adapt fast (Gleeson, 2017). If the quality aspect is a threat in the USA, then the necessary
courses of actions should be anticipated. Similarly, on the fear of business becoming too
large to handle, I propose that Proper effective management skills such as effective
communication and balance be embraced. Additionally, curiosity is a critical skill in
developing a global mindset. The art of spreading risks as a leader and an investor is
encouraged. It is through curiosity that attempts are made.

2

Generally, Easy Chairs should consider manufacturing abroad in cities as compared to
rural. Understandably, this is because the cities cover a wider marketing scope hence
popularity as compared to rural areas. Research has it that there are 61% machine experts
in the USA. The following are some of the advantages of going global; learning and
adapting new methods. Carrying out business in many countries helps in learning
different approaches and cultures (Cavusgil, Knight, Riesenberger, Rammal, & Rose,
2014). Similarly, going global reduces the vulnerabilities that may be associated with a
given country. In case of disastrous events in a given country, the business still stands a
chance in another country (Cavusgil, Knight, Riesenberger, Rammal, & Rose, 2014).
Growth opportunity and lesser competition are equally associated with business
globalization. However, the major disadvantages associated with manufacturing abroad
are the language barriers, cultural differences, employees and quality aspects.
Nevertheless, cultural, language and quality challenges can be embraced gradually and
necessary courses of action taken to help the business fit through aggressive and focused
management.

Bibliography

Cavusgil, T. S., Knight, G., Riesenberger, J. R., Rammal, H. G., & Rose, E. L. (2014).
Part 4 Entering and operating in international markets. In International Business
(pp. 393-516). Australia: Pearson Australia. Retrieved May 20, 2021, from
https://books.google.co.ke/books?id=KcSaBQAAQBAJ&pg=PA1&dq=advantage
s+and+disadvantages+of+global+business&lr=&source=gbs_toc_r&cad=3#v=on
epage&q=advantages%20and%20disadvantages%20of%20global%20business&f
=false

Colvin, G. (2006, October 2). Managing in chaos. Fortune, 154(7). Retrieved May 2,
2021, from
https://archive.fortune.com/magazines/fortune/fortune_archive/2006/10/02/83874
17/index.htm

Gleeson, B. (2017, March 27). The Future Of Leadership And Management In The 21st-
Century Organization. Retrieved May 20, 2021, from Forbes:
https://www.forbes.com/sites/brentgleeson/2017/03/27/the-future-of-leadership-
and-management-in-the-21st-century-organization/?sh=9317af3218ff

Trapp, R. (2014, March 23). Successful Organizations Need Leaders At All Levels.
Retrieved May 20, 2021, from Forbes:
https://www.forbes.com/sites/rogertrapp/2014/03/23/organizations-need-leaders-
at-all-levels/?sh=10249a743ab1

3

  • Bibliography

11/10/21, 1:48 PM Disruptive Innovation Definition

https://www.investopedia.com/terms/d/disruptive-innovation.asp 1/11

BUSINESS BUSINESS ESSENTIALS

What Is Disruptive Innovation?
Disruptive innovation refers to the innovation that transforms expensive or highly
sophisticated products or services—previously accessible to a high-end or more-skilled
segment of consumers—to those that are more affordable and accessible to a broader
population. This transformation disrupts the market by displacing long-standing, established
competitors.

Disruptive Innovation

By Updated August 23, 2021ALEXANDRA TWIN
Reviewed by ERIC ESTEVEZ

TABLE OF CONTENTS

EXPAND

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Click Play to Learn What Disruptive Innovation Is

KEY TAKEAWAYS

Disruptive innovation refers to innovations and technologies that make expensive or
sophisticated products and services accessible and more affordable to a broader
market.
Disruptive innovation refers to the use of technology that upsets a structure, as
opposed to “disruptive technology”, which refers to the technology itself.
Amazon, launched as an online bookstore in the mid-1990s, is an example of
disruptive innovation.
Disruptive innovation requires enabling technology, an innovative business model,
and a coherent value network.
Sustaining innovation is the process of innovating to improving products and
services for existing customers.

2:03

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Understanding Disruptive Innovation
Disruptive innovation is not the process of improving or enhancing products for the same
target group; rather, it involves the technologies used to make them easy to use and
available to the larger, non-targeted market. An example of disruptive innovation is the
introduction of digital music downloads, which have, by far, replaced compact discs (CDs).

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Clayton Christensen popularized the idea of disruptive innovation in the book The
Innovator’s Solution, which was a follow up to his The Innovators Dilemma published in
1997. 1Christensen posited that there were two types of technologies that businesses dealt
with. Sustainable technologies were those that allowed a business to incrementally improve
its operations on a predictable timeframe.

These technologies and the way they were incorporated into the business were primarily
designed to allow companies to remain competitive, or at least maintain a status quo.
Disruptive technologies and the way they are integrated—the disruptive innovations—were
less easy to plan for and potentially more devastating to companies that did not pay enough
attention to them.

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Investing in a disruptive innovation can be complicated. It requires an investor to focus on
how companies will adapt to disruptive technology, instead of focusing on the development
of the technology itself. Companies such as Amazon, Google (GOOGL), and Facebook (FB)
are examples of companies that have heavily focused on the internet as a disruptive
technology.

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The internet has become so ingrained in the modern world that the companies that failed to
integrate disruptive innovation into their business models have been pushed aside. Artificial
intelligence (AI) and its potential to learn from employees and perform their jobs may be a
disruptive innovation for the job market as a whole soon.

What makes a technology or innovation “disruptive” is a point of contention. The term may be
used to describe technologies that are not truly disruptive. The internet was disruptive
because it was not an iteration of previous technology. It was something new that created
unique models for making money that never existed before. Of course, that created losses
for other business models.

People using smartphones instead of laptops and desktops for their computing needs,
including web browsing and streaming, is another example of disruptive innovation.
Technological enhancements have enabled cell phones to be equipped with small
processors, chips, and software applications that support these functions.

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Smartphone developers targeted the broad market of mobile consumers who have cellular
devices and find it inconvenient to carry and access laptops when wanting to surf the net (not
to mention an impossible task for desktops). Smartphones are small, easily storable and
accessible, and relatively affordable as compared to laptops and desktops.

In contrast, the Model T car is not considered to be a classic example of disruptive
innovation because it was an improvement on existing technology and it wasn’t widely
adopted upon its release. The auto industry didn’t take off until mass production brought
prices down, moving the entire transportation system from hooves to wheels. In that sense,
the system of mass production does meet the criteria for disruptive innovation.

Requirements for Disruptive Innovation
Disruptive innovation requires access to ignored or overlooked markets and technology that
can transform a product into a more accessible and affordable one. To be disruptive, the
network of partners—suppliers, contractors, and distributors—must also benefit from the
new, disruptive business model. Certain core requirements include:

Enabling Technology: In business, enabling technology is defined as the technologies and
innovations that substantially change or improve processes or how people do things.
Specific to disruptive innovation, enabling technology is the technology or innovation that
makes possible the affordability and availability of a product to a broader market.
Basically, the speed with which a market can be disrupted depends on how quickly the
technology is developed and subsequently improved upon. However, the speed of the
disruption is not necessarily a metric used to gauge the success of the disruption.
Innovative Business Model: The innovative business model is a business model that uses
innovations to target new or bottom-tier customers. 1 These segments generally don’t
drive profits for established companies nor do they buy their offerings because they either
could not afford them or the products were too sophisticated for use. This business model
—a model not adopted by incumbents because of the disruptor’s initial low-profit margins
—seeks to present easy-to-use, economical solutions.
Coherent Value Network: The coherent value network includes the upstream and
downstream business partners that benefit from a successful disruption. 1 The
distributors, suppliers, and vendors may require process changes or reorganization to
adapt or conform to the new business model. Members of the network must subscribe to
the new business model to prevent failure. Otherwise, old network processes will yield
undesirable results by not prescribing to the goal of disruption.

Disruptive innovation is differentiated from disruptive technology in that it focuses
on the use of the technology rather than the technology itself.

Disruptive Innovation Vs. Sustaining Innovation
Disruptive innovation is an innovation that simplifies and makes more affordable products
and services to undesirable or ignored markets. Established companies typically strive to
improve their products and services for their profitable customer base, largely ignoring the

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needs and desires of untapped segments. This lack of attention gives smaller companies or
new entrants ground to target this ignored population with simpler, more affordable options.

Sustaining innovation, on the other hand, is the process of innovating to make existing
products and services better for the existing customer base, either based on customer or
market demands. Sustaining innovation does not target untapped or ignored markets; rather,
it’s innovating to remain relevant and competitive. CD makers making CDs with the capacity
to hold large volumes of music and that are scratch-resistant is sustaining innovation. A
company introducing digital downloads via the internet, making CDs obsolete, is disruptive
innovation.

Amazon
A classic example of the disruptive innovation of the internet being unleashed was the
restructuring of the bookselling industry. The big bookselling chains lost out to Amazon
(AMZN) because it could display its inventory without having to own a physical store in every
town and then ship the book to the buyer’s home. Before online shopping became widely
popular, books were sold in traditional bookstores, such as Barnes and Nobles and the now-
defunct Borders.

Amazon’s popularity grew along with its profits and market share, moving many bookstores
to the back of the shelf or out of business. Since its launch, Amazon has been successful in
using the internet to create an online shopping platform, whereby most of what’s offered in a
physical store—including groceries—can be ordered from Amazon’s website. And it all
began with a small, garage-born company using the power of the internet to attend to the
needs of a niche market of online shopping, book enthusiasts.

Netflix
Netflix (NFLX) is another disruptive innovator. During a time when VHS tapes and DVDs
were rented in abundance from thousands of video stores, new-entrant Netflix saw an
opening to cater to an overlooked market of online shoppers. Utilizing the growing power of
the internet, they offered consumers the ability to peruse their catalog of DVDs, rent
unencumbered by someone else’s choice to rent the same selection, and have their
selections sent directly to their home.

Not long after offering mail-delivered DVD rentals, they revised their business model, finding
an avenue to disrupt themselves in the market by offering online-streamed entertainment.
However, today, competitors have successfully duplicated this business model, taking away
from Netflix’s market share. Time will tell how long Netflix can remain dominant, but there is
no doubt about the disruption that they brought about.

After Netflix disrupted the media industry, Blockbuster went from having more
than 9,000 Blockbuster brick-and-mortar stores to 1, which is now an Airbnb. 2

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The Bottom Line
Disruptive innovation involves the innovative processes used to transform products and
services into simple and affordable options for bottom-tier or traditionally unmarketable
consumers. Unlike sustaining innovation, it does not involve improving existing products for
current customers.

Disruptive innovation requires technology that can transform the product or service into
something more affordable and easy-to-use, a business model that supports the disruptive
innovation, and a network of upstream and downstream partners who support and will
benefit from the success of the disruption. Amazon and Netflix are examples of market
disruptors that began as new entrants in industries dominated by well-known, established
companies.

What Is the Meaning of Disruptive Innovation?
Disruptive innovation refers to the process of transforming an expensive or highly
sophisticated product, offering, or service into one that is simpler, more affordable, and
accessible to a broader population. It explains the process of how innovation and technology
can change markets by presenting affordable, simple, and accessible solutions and after
doing so, disrupts the market from which its predecessors were born.

What Are Examples of Disruptive Innovation?
Amazon provides a clear example of disruptive innovation. Jeff Bezos, in 1995, subscribing
to the notion that the internet could significantly boost commerce, launched Amazon to sell
books to a growing, but largely ignored online shopping community. In doing so, he forced
many bookstores to go out of business. Netflix is another prime example. After they
disrupted the media industry, the dominant player, Blockbuster, went from having 9,000+
brick-and-mortar stores to 1, which is now an Airbnb.

What Are the Key Requirements for Disruptive Innovation?
To be a successful disruptor, the network of partners—suppliers, contractors, and distributors
—must also benefit from the new business model. Certain core requirements include having
enabling technology, an innovative business model, and a coherent value network where
upstream and downstream business partners benefit from a successful disruption.

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11/10/21, 1:48 PM Disruptive Innovation Definition

https://www.investopedia.com/terms/d/disruptive-innovation.asp 11/11

ARTICLE SOURCES

Investopedia requires writers to use primary sources to support their work. These include
white papers, government data, original reporting, and interviews with industry experts.
We also reference original research from other reputable publishers where appropriate.
You can learn more about the standards we follow in producing accurate, unbiased
content in our editorial policy.

Christensen Institute. ” .” Accessed April 5, 2021.

Insider. ” ” Accessed April 5, 2021.

Disruptive Innovation

The rise and fall of Blockbuster.

11/10/21, 1:51 PM How Is Artificial Intelligence Changing the Workplace?

https://www.shrm.org/resourcesandtools/legal-and-compliance/employment-law/pages/artificial-intelligence-is-changing-the-workplace.aspx 1/2

How Is Arti�cial Intelligence Changing
the Workplace?

By Lisa Nagele-Piazza, J.D., SHRM-SCP

November 13, 2018

SAN FRANCISCO—A workplace run by arti�cial intelligence (AI) and robotics is not a futuristic concept. Such technology is already a part of

the workplace and will continue to shape the labor market. Therefore, employers need to anticipate changes in job functions and be aware

of legal pitfalls associated with evolving technology.

In the past, automation was prevalent in manufacturing and other industrial settings, but AI and robotics are being introduced in the service

industry, too, said Gerlind Wisskirchen, an attorney with CMS Hasche Sigle in Cologne, Germany.

Eighty percent of U.S. jobs are service-oriented (https://www.bls.gov/emp/tables/employment-by-major-industry-sector.htm), according to

the Bureau of Labor Statistics. AI developments in the service sector will have a dramatic impact on the labor market and the types of jobs

that will be available in the future, Wisskirchen said Nov. 8 at the American Bar Association’s 2018 Labor and Employment Law Conference.

“In the past, we saw trends coming slowly,” she said. But now, new technology is disrupting whole industry sectors, and business leaders

may not see it coming. “That’s scary for companies.”

Here’s what business leaders should be thinking about now to anticipate changes and stay ahead of the curve.

Tasks Are Changing

Robots don’t just passively do what someone programmed them to do anymore, said Brian Koncius, an attorney with Bogas & Koncius in

Bingham Farms, Mich.

Historically, robots were used in a fenced-o� area of a factory to perform physical tasks, but they can now work beside people to do

complex and intelligent job duties. Algorithms are able to determine patterns, learn from them and make decisions.

But Wisskirchen said she doesn’t think that intelligent robots will eliminate a lot of jobs overnight. “A high percentage of tasks—not jobs—

will be changing soon,” she said. Repetitive, monotonous tasks will be replaced. Even lawyers, journalists and other professionals perform

tasks that are repetitive and monotonous that AI can take over, she noted.

It will be a gradual move for many businesses, but certain jobs and industries will see rapid change, she added. For example, labor-

replacing technology for cashiers is already out there. Some casual-dining establishments and retail stores use kiosks to take orders and

payments from customers. Making the switch to technology is a matter of investment for large retailers—and many leaders are waiting to

see what their competitors do—but the change is already happening, she said.

What skills will still be needed in the future? Creativity, problem solving, critical thinking and teamwork will be important as the workplace

evolves, Wisskirchen said. Education and training programs will need to focus on these skills.

AI will also impact workforce design, Wisskirchen said. For example, businesses will likely increase the number of freelancers they use.

“From a business perspective, it’s a new form of outsourcing,” she noted. Employers will look at what tasks have to be done internally and

what can be done through crowdsourcing.

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SHRM provides content as a service to its readers and members. It does not o�er legal advice, and cannot guarantee the accuracy or suitability of its content for a particular

purpose.

Disclaimer (www.shrm.org/about-shrm/Pages/Terms-of-Use.aspx#Disclaimer)

Legal Issues

Compliance issues will inevitably arise as the workplace changes and the use of AI becomes commonplace. Challenges have already

popped up when businesses use AI in the hiring process, said Heather Morgan, an attorney with Grube Brown & Geidt in Los Angeles.

Job applicants have claimed that employment screening systems that appear neutral have a disparate impact based on protected

characteristics, such as national origin, sex and race. For example, a recruiting tool that screens out applicants who live more than 10 miles

away from the worksite may have a disparate impact based on race or ethnicity, depending on the demographics of surrounding

neighborhoods.

If the disparate impact is statistically signi�cant, the burden is on the employer to show that the screening criteria is consistent with

business necessity, Morgan said. Algorithms have been challenged in this context and continue to be a risk when they are used to make

decisions, she noted.

The use of advanced technology in the workplace can also lead to age discrimination if there is a reduction in force and older workers are

let go because they are not perceived as tech-savvy, she added.

Koncius noted that certain job requirements may unintentionally screen out older workers. What if a job description requires a degree in a

�eld that didn’t exist 20 years ago? Will that have a disparate impact on older workers?

Jobs are changing, and technology is leading the way. It is critical for employers to understand how these changes impact the workplace

and to make sure that the criteria they use to hire, transfer, promote and �re workers are legally defensible, Morgan said.

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11/10/21, 1:53 PM SWOT Analysis Model and Examples – Strategy Skills

https://www.mindtools.com/pages/article/newTMC_05.htm 1/9

 13 MIN READ

SWOT Analysis

Understanding Your Business, Informing Your Strategy

What is a SWOT analysis? SWOT stands for Strengths, Weaknesses, Opportunities, and
Threats, and so a SWOT analysis is a technique for assessing these four aspects of your
business.

SWOT Analysis is a simple tool that can help you to analyze what your company does best
right now, and to devise a successful strategy for the future. SWOT can also reveal areas of
the business that are holding you back, or that your competitors could exploit if you don’t
protect yourself.

In this article, video and infographic, we explore how to carry out a SWOT analysis, and
how to put your findings into action. We also include a worked example and a template to
help you get started on a SWOT analysis in your own workplace.

How to Write a SWOT Analysis

First, draw up a SWOT Analysis matrix, or use our free downloadable template.

A SWOT matrix is a 2×2 grid, with one square for each of the four aspects of SWOT. Figure
1 shows what it should look like.

Figure 1. A SWOT Analysis Matrix.

Strengths
What do you do well?
What unique resources can you draw on?
What do others see as your strengths?

Weaknesses
What could you improve?
Where do you have fewer resources than
others?
What are others likely to see as weaknesses?

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Strengths
What do you do well?
What unique resources can you draw on?
What do others see as your strengths?

Weaknesses
What could you improve?
Where do you have fewer resources than
others?
What are others likely to see as weaknesses?

Opportunities
What opportunities are open to you?
What trends could you take advantage of?
How can you turn your strengths into
opportunities?

Threats
What threats could harm you?
What is your competition doing?
What threats do your weaknesses expose to
you?

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How to Do a SWOT Analysis

Gather a team of people from a range of functions and levels in your organization and use
Brainstorming techniques to build a list of ideas about where your organization
currently stands. Every time you identify a Strength, Weakness, Opportunity, or Threat,
write it down in the relevant part of the SWOT analysis grid.

Let’s look at each area in more detail and consider what fits where, and what questions you
could ask as part of your analysis.

Strengths

Strengths are things that your organization does particularly well, or in a way that
distinguishes you from your competitors. Think about the advantages your organization
has over other organizations. These might be the motivation of your staff, access to certain
materials, or a strong set of manufacturing processes.

Your strengths are an integral part of your organization, so think about what makes it
“tick.” What do you do better than anyone else? What values drive your business? What
unique or lowest-cost resources can you draw upon that others can’t? Identify and analyze
your organization’s Unique Selling Proposition (USP), and add this to the Strengths
section.

Then turn your perspective around and ask yourself what your competitors might see as
your strengths. What factors mean that you get the sale ahead of them?

Remember, any aspect of your organization is only a strength if it brings you a clear
advantage. For example, if all of your competitors provide high-quality products, then a
high-quality production process is not a strength in your market: it’s a necessity.

Weaknesses

Weaknesses, like strengths, are inherent features of your organization, so focus on your
people, resources, systems, and procedures. Think about what you could improve, and the
sorts of practices you should avoid.

Once again, imagine (or find out) how other people in your market see you. Do they notice
weaknesses that you tend to be blind to? Take time to examine how and why your
competitors are doing better than you. What are you lacking?

Be honest! A SWOT analysis will only be valuable if you gather all the information you
need. So, it’s best to be realistic now, and face any unpleasant truths as soon as possible.

Opportunities

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Opportunities are openings or chances for something positive to happen, but you’ll need to
claim them for yourself!

They usually arise from situations outside your organization, and require an eye to what
might happen in the future. They might arise as developments in the market you serve, or
in the technology you use. Being able to spot and exploit opportunities can make a huge
difference to your organization’s ability to compete and take the lead in your market.

Think about good opportunities you can exploit immediately. These don’t need to be game-
changers: even small advantages can increase your organization’s competitiveness. What
interesting market trends are you aware of, large or small, which could have an impact?

You should also watch out for changes in government policy related to your field. And
changes in social patterns, population profiles, and lifestyles can all throw up interesting
opportunities.

Threats

Threats include anything that can negatively affect your business from the outside, such as
supply-chain problems, shifts in market requirements, or a shortage of recruits. It’s vital to
anticipate threats and to take action against them before you become a victim of them and
your growth stalls.

Think about the obstacles you face in getting your product to market and selling. You may
notice that quality standards or specifications for your products are changing, and that
you’ll need to change those products if you’re to stay in the lead. Evolving technology is an
ever-present threat, as well as an opportunity!

Always consider what your competitors are doing, and whether you should be changing
your organization’s emphasis to meet the challenge. But remember that what they’re doing
might not be the right thing for you to do. So avoid copying them without knowing how it
will improve your position.

Be sure to explore whether your organization is especially exposed to external challenges.
Do you have bad debt or cash-flow problems, for example, that could make you vulnerable
to even small changes in your market? This is the kind of threat that can seriously damage
your business, so be alert.

Tip:

Use PEST Analysis to ensure that you don’t overlook threatening external factors. And
PMESII-PT is an especially helpful check in very unfamiliar or uncertain environments.

How to Use a SWOT Analysis

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Use a SWOT Analysis to assess your organization’s current position before you decide on
any new strategy. Find out what’s working well, and what’s not so good. Ask yourself where
you want to go, how you might get there – and what might get in your way.

Once you’ve examined all four aspects of SWOT, you’ll want to build on your strengths,
boost your weaker areas, head off any threats, and exploit every opportunity. In fact, you’ll
likely be faced with a long list of potential actions.

But before you go ahead, be sure to develop your ideas further. Look for potential
connections between the quadrants of your matrix. For example, could you use some of
your strengths to open up further opportunities? And, would even more opportunities
become available by eliminating some of your weaknesses?

Finally, it’s time to ruthlessly prune and prioritize your ideas, so that you can focus time
and money on the most significant and impactful ones. Refine each point to make your
comparisons clearer. For example, only accept precise, verifiable statements such as, “Cost
advantage of $30/ton in sourcing raw material x,” rather than, “Better value for money.”

Remember to apply your learnings at the right level in your organization. For example, at a
product or product-line level, rather than at the much vaguer whole-company level. And
use your SWOT analysis alongside other strategy tools (for example, USP Analysis and
Core Competencies Analysis ), so that you get a comprehensive picture of the situation
you’re dealing with.

Note:

You could also consider using the TOWS Matrix . Like SWOT, it explores Threats,
Opportunities, Weaknesses, and Strengths, but it emphasizes the external environment,
while SWOT leads with the internal factors.

A SWOT Analysis Example

Imagine this scenario: a small start-up consultancy wants a clear picture of its current
situation, to decide on a future strategy for growth. The team gathers, and draws up the
SWOT Analysis shown in Figure 2.

Figure 2. A Completed SWOT Analysis.

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Strengths
What do you do well?
What unique resources can you draw on?
What do others see as your strengths?

Weaknesses
What could you improve?
Where do you have fewer resources than
others?
What are others likely to see as weaknesses?

Strengths
What do you do well?
What unique resources can you draw on?
What do others see as your strengths?

Weaknesses
What could you improve?
Where do you have fewer resources than
others?
What are others likely to see as weaknesses?

We are able to respond very quickly as we
have no red tape, and no need for higher
management approval.

We are able to give really good customer
care, as the current small amount of work
means we have plenty of time to devote to
customers.

Our lead consultant has a strong
reputation in the market.

We can change direction quickly if we find
that our marketing is not working.

We have low overheads, so we can offer
good value to customers.

Our company has little market presence or
reputation.

We have a small staff, with a shallow skills
base in many areas.

We are vulnerable to vital staff being sick
or leaving.

Our cash flow will be unreliable in the
early stages.

Opportunities
What opportunities are open to you?
What trends could you take advantage of?
How can you turn your strengths into
opportunities?

Threats
What threats could harm you?
What is your competition doing?
What threats do your weaknesses expose to
you?

Our business sector is expanding, with
many future opportunities for success.

Local government wants to encourage
local businesses.

Our competitors may be slow to adopt new
technologies.

Developments in technology may change
this market beyond our ability to adapt.

A small change in the focus of a large
competitor might wipe out any market
position we achieve.

As a result of the team’s analysis, it’s clear that the consultancy’s main strengths lie in its
agility, technical expertise, and low overheads. These allow it to offer excellent customer
service to a relatively small client base.

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The company’s weaknesses are also to do with its size. It will need to invest in training, to
improve the skills base of the small staff. It’ll also need to focus on retention, so it doesn’t
lose key team members.

There are opportunities in offering rapid-response, good-value services to local businesses
and to local government organizations. The company can likely be first to market with new
products and services, given that its competitors are slow adopters.

The threats require the consultancy to keep up-to-date with changes in technology. It also
needs to keep a close eye on its largest competitors, given its vulnerability to large-scale
changes in its market. To counteract this, the business needs to focus its marketing on
selected industry websites, to get the greatest possible market presence on a small
advertising budget.

Note:

It’s also possible to carry out a Personal SWOT Analysis . This can be useful for
developing your career in ways that take best advantage of your talents, abilities and
opportunities.

SWOT Analysis Infographic

Click on the image below to see SWOT Analysis represented in an infographic:

Key Points

11/10/21, 1:53 PM SWOT Analysis Model and Examples – Strategy Skills

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SWOT Analysis enables you to identify your organization’s Strengths and Weaknesses,
possible Opportunities and potential Threats.

It helps you to build on what you do well, address what you’re lacking, and minimize risks.
Use a SWOT Analysis to assess your organization’s position before you decide on any new
strategy.

Start by assessing your Strengths, Weaknesses, Opportunities, and Threats, with a team of
people from a range of functions and levels in your organization. This will help build a
clear picture of where you stand.

Find out what’s working well, and what’s not so good. Ask yourself where you want to go,
how you might get there – and what might get in your way.

When carrying out your analysis, be realistic and rigorous. Prune and prioritize your ideas,
to focus time and money on the most significant and impactful actions and solutions.

Note:

Many people attribute SWOT Analysis to Albert S. Humphrey. However, there has been
some debate on the originator of the tool, as discussed in the International Journal of
Business Research.

Download Template

atings

Free login needed. Login / Create Log i

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© Emerald Works Limited 2021. All rights reserved. “Mind Tools” is a
registered trademark of Emerald Works Limited.

IAMTHAT 2021-10-05 11:48:53

 

Clear what this is and how to apply it. The completed SWOT analysis was great.

sie4986744 2021-08-26 11:37:33

 
fihinumase 2021-04-21 10:39:12

 
Non Member 2021-04-08 22:58:08

 
Ace_Me 2021-03-29 20:02:20

 

Great!

23…991

Module 1 Readings: Knowledge Management Basics: Concepts,
Objects, Principles and Expectations

Introduction

Along with the unprecedented pace of development of information and communication
technologies (ICTs) the human society has evolved into the knowledge ear. Today, no
one doubts that better management of knowledge within the organization will lead to
improved efficiency, effectiveness, innovation and competitive edge. As customers
demand and receive more customization at ever diminishing costs from knowledge-
oriented private sector firms, people have come to expect similar benefits from the public
sector. As a result, individuals, institutions and governments are being forced to deal
with the changing nature of work and learning, as well as with their own changing
expectations.

Knowledge management in its current form probably first received significant attention in
1990s, with leading private sector companies developing procedures to guarantee
effective generation, capture and dissemination of information and know-how and the
promotion of knowledge. Public sector organizations, especially government entities, are
typically thought to be later adopters to this knowledge management wave. However,
due to the ever-increasing pressure for higher efficiency and effectiveness and the
growing needs for sharing knowledge among different government entities at different
levels as well as coping with this inevitable trend, government is quickly catching up and
is fully prepared to reap the benefits generated from knowledge management programs.

The following material is designed as a brief introduction and guidance for better
understanding and implementing knowledge management projects in government
organizations.

What is Knowledge?

Definition

As a starting point of exploring into the realm of Knowledge Management, let’s first take
a close look at the definition of knowledge itself and the definition of the so-called
organizational knowledge.

Throughout history, knowledge has always been viewed from multiple perspectives —
abstract, philosophical, religious and practical etc. As the result, the discourse of
knowledge over the human history has generated various definitions. Plato in his Meno,
Phaedo and Theaetetus first defined the concept of knowledge as “justified true belief”,
which has been predominant during the history of western philosophy ever since.
Beckman (1998) has compiled a number of other definitions of knowledge and
organizational knowledge, some of which are quoted in the following1:

• Knowledge is organized information applicable to program solving (Woolf,
1990).

• Knowledge is information that has been organized and analyzed to make
it understandable and applicable to problem solving or decision making
(Turban, 1992)

• Knowledge consists of truths and beliefs, perspectives and concepts,
judgments and expectations, methodologies and ‘know-how’ (Wiig, 1993).

• Knowledge is the whole set of insights, experiences and procedures
which are considered correct and true and which, therefore, guide the
thoughts, behaviors and communication of people (Van der Spek and
Spijkervet, 1997).

• Knowledge is reasoning about information to actively guide task
execution, problem-solving and decision making in order to perform, learn
and teach (Beckman, 1997).

• Organizational knowledge is processed information embedded in routines
and processes which enable actions. It is also knowledge captured by
organization’s systems, processes, products, rules and culture (Myers,
1996).

• Organizational knowledge is the collective sum of human-centered
assets, intellectual property assets, infrastructure assets and market
assets (Brooking, 1996).

1 Beckman T. (1998), Knowledge management: a technical review. GWU Working Paper,
Washington.

2

It seems that the attempts to define knowledge has reflected the multifaceted nature of
knowledge itself and it is almost impossible to have one single definition that covers all
aspects of knowledge and at the same time receive unanimous consensus, especially
when the embodiment of knowledge changes at different individual, organizational and
social levels. This is the reason why many authors have pointed out the difficulty of
succinctly defining the concept of knowledge, suggesting that it would seem appropriate
to avoid imposing a strict definition but rather regarding knowledge as a “multi-layered,
multifaceted concept” 2 that “can impact different organizations in very different ways’3.
However, at least, borrowing from these various definitions put forward by different
scholars, we can conclude that knowledge is a fluent mix of structured experience,
beliefs, relevant information and intuition of experts and, besides residing in human
minds, knowledge can also exist in such forms as organization’s systems, processes,
products and culture etc..

Knowledge Taxonomy

Knowledge can be characterized in many ways. Popular taxonomies include the
following:

Propositional and Perspective Knowledge

According to Joe Mokyr,4 useful knowledge can be partitioned into two subsets: one is
the knowledge that catalogues natural phenomena and regularities, which he calls
propositional knowledge. The other is the knowledge that prescribes certain actions that
constitute the manipulation of natural phenomena for human material needs, which is
called perspective knowledge.

Propositional knowledge contains what people usually call “science” as a subset, but
at the same time it contains a great deal more than science. Propositional knowledge
also contains practical informal knowledge about nature; an intuitive grasp of basic
mechanics; regularities of nature and even things as informal as folk wisdoms etc.

Perspective knowledge has the form of techniques or instructions. They reside either in
people’s brains or in storage devices. They consist of designs and directions for how to
adapt means to a well-defined end. They can all be taught, imitated, communicated, and
improved upon. A “how-to” manual is a codified set of techniques. An addition to the
perspective knowledge set of a society would be regarded as an “invention”.

2 Scarbrough, H. (1999), Knowledge Management: A Literature Review, Issues in People
Management Series, Institute of Personnel and Development: London.
3 Kelleher, D. and Levene, S. (2001), Knowledge Management: A Guide to Good Practice, British
Standards Institute: London.
4 Joel Mokyr (2003), The Knowledge Society: Theoretical and Historical Underpinnings,
Expanding Public Space for the Development of the Knowledge Society, Report of the Ad Hoc
Expert Group Meeting on Knowledge Systems for Development 4-5 September 2003.

3

For example: Propositional knowledge contains practical informal
knowledge about nature such as the properties of materials, heat, motion,
plants, and animals; an intuitive grasp of basic mechanics (including the
six “basic machines” of classical antiquity: the lever, pulley, screw,
balance, wedge, and wheel); regularities of ocean currents and the
weather; and folk wisdoms in the “an-apple-a-day-keeps-the-doctor-away”
tradition. Geography is very much part of it: knowing where things are
logically prior to the set of instructions of how to go from here to there.
Prescriptive knowledge has the form of techniques or instructions: the
archetypical technique is the recipe, which instructs one how to prepare a
certain dish. In principle, all techniques are such sets, although vastly
more complex and often full with nested do-loops, if-then statements and
so on. It is the technique, not the artifact that is the fundamental unit of
analysis in evolutionary accounts of technology. They are sets of
executable instructions or recipes for how to manipulate nature.

Explicit and Tacit Knowledge

A more widely accepted taxonomy on knowledge, first introduced by Polanyi in 19665
and popularized by Nonaka and Takeuchi, is their categorization of explicit and tacit
knowledge. According to these two:

Explicit knowledge is that which:6
“can be expressed in words and numbers and can be easily communicated and shared
in the form of hard data, scientific formulae, codified procedures or universal principles”

whereas tacit knowledge is:
“highly personal and hard to formalize. Subjective insights, intuitions and hunches fall
into this category of knowledge.”

Thus, explicit knowledge in organizations is typically found in documents and databases,
while tacit knowledge is that which is in the heads of people. More than often, tacit
knowledge is even based on the subjective insights, intuitions, and hunches and is
deeply rooted in an individual’s actions and experience and even ideals, values and
emotions. According to Polanyi knowledge that can be expressed in words and numbers
only represents the tip of the iceberg of the entire body of possible knowledge7. Explicit
knowledge is also sometimes called formal knowledge while tacit knowledge is called
informal knowledge. However, it should be pointed out that, the associated names do
not automatically suggest their different levels of importance. Many times, due to
reasons to be discussed later, for organizations to build their strategic competitiveness
and long-term development, tacit knowledge is actually more important than explicit
knowledge and should consequently be the focus of knowledge management programs.
The following table has better illustrated some of the key characteristics of these two
forms of knowledge as suggested by Nonaka and Takeuchi8:

5 Polanyi, M. (1966), The Tacit Dimension, London, Routledge & Kegan Paul.
6 Ikujiro Nonaka and Hirotaka Takeuchi (1995), The Knowledge Creating Company,Oxford
University Press.
7 Polanyi, M. (1966), The Tacit Dimension, London, Routledge & Kegan Paul.
8 Ikujiro Nonaka and Hirotaka Takeuchi (1995), The Knowledge Creating Company,Oxford
University Press.

4

Table 1: Tacit and explicit knowledge

Tacit Knowledge (subjective) Explicit Knowledge (objective)
Knowledge of experience (body) Knowledge of rationality (mind)

Simultaneous knowledge (here and now) Sequential knowledge (there and then)
Analog knowledge (practice) Digital knowledge (theory)

Core, Advanced and Innovative Knowledge
Besides the above-mentioned two knowledge taxonomies, there are many other different
types. For example, Michael H. Zach9, from the perspective of knowledge’s specific
function to an organization’s competitive edge, classified knowledge according to
whether it is core, advanced or innovative. To him:

Core knowledge is that minimum scope and level of knowledge required just to “play
the game”. Having that level of knowledge and capability will not assure the long-term
competitive viability of an organization, but does present a basic industry knowledge
barrier to entry. Core knowledge tends to be commonly held by members of an industry
and therefore provides little advantage other than over nonmembers.

Advanced knowledge enables an organization to be competitively viable. The
organization may have generally the same level, scope or quality of knowledge as its
competitors although the specific knowledge content will often vary among competitors,
enabling knowledge differentiation. Organizations may choose to compete on knowledge
head-on in the same strategic position, hoping to know more than a competitor. They
instead may choose to compete for that position by differentiating their knowledge.

Innovative knowledge is that knowledge that enables an organization to lead its
industry and competitors and to significantly differentiate itself from its competitors.
Innovative knowledge often enables an organization to change the rule of the game.

For example: For Honda Motor Co., Ltd., to compete in the car industry it
definitely needs to know how to design, manufacture and market cars,
which is the core knowledge that allows itself to stay in the game.
However in order to survive and make profits in this highly competitive
industry it also needs to have certain advantages compared with its
competitors so as to entice customers to buy their products, which
requires such advanced knowledge about manufacturing cars with
relatively low-cost yet higher-than-average fuel economy. But for long-
term development and competitive edge all these are just not enough.
Consequently Honda cultivates its innovative knowledge in the area of
engines. It claims itself not just simply a car manufacturer, rather it is the
maker of perfect engines. And armed with this innovative knowledge,
besides passenger cars, it has other series of highly successful products
lines that revolves around its engines, and thus makes the company
become one of the most successful and profitable player within the
industry.

9 Michael H. Zach (1999), Developing a Knowledge Strategy, California Management Review,
Vol. 41, No. 3, Spring, 1999, pp. 125-145.

5

We feel that no matter how knowledge is categorized, there is always a part of “special
knowledge” which is more difficult to be systematically codified and accessed by the
whole organization. It is precisely this kind of intangibility that constitutes an
organization’s core competency and makes it competitive, and consequently, it is what a
successful knowledge management program should focus on, even though
unfortunately, in reality people tend to neglect this part of knowledge due to various
reasons.

During the presentation of this material we are going to stick with Nonaka and
Takeuchi’s categorization of knowledge through explicit and tacit knowledge. This is
partly because their categorization is the most popular among mainstream knowledge
management researches and practices. More importantly, we feel that their description
would do a better job in grasping and revealing the actual phenomenon and problems of
current knowledge management reality.

Knowledge Dimensions and Levers

Opining on the above definitions and classifications of knowledge, four dimensions of
knowledge are commonplace, which include:

Focus: Is the knowledge operational or strategic? Obviously operational and strategic
knowledge need to be treated differently under the knowledge management process. At
the same time operational or strategic knowledge could also have external or internal
manifestations respectively.

Complexity: The complexity degree of context that gives meaning and makes
knowledge useful, which is also where different taxonomies schemes come into place
(i.e. tacit knowledge vs. explicit knowledge).

Life span: The validity and criteria of knowledge. People tend to forget that although the
“truthfulness” of knowledge may remain the same, its “usefulness” most likely will
change or diminish as time goes by and environment changes. This needs to be put into
consideration for the design of any successful knowledge management programs; and

Dynamics: How knowledge evolves. The very definition of knowledge reveals that it is
highly dynamic. A successful knowledge management program needs to have certain
mechanisms built into it so as to manage and capture this dynamic dimension of
knowledge.

Because knowledge is complex and dynamic, although one might easily find explicit
knowledge exists in various ready-to-access forms (i.e. books, ‘databases’, CDs, tapes
etc.), tacit knowledge exists in places that may not so easily be identified. David J.
Skyrme introduced seven, what he called, levers as the common embodiment of
knowledge that exists within the organization or is embedded into the process of its
various operations, as well as the associated key knowledge management activities in
the following table10:

10 David J. Skyrme (1988), Developing A Knowledge Strategy, Strategy, January 1998 edition.

6

Table 2: Seven Knowledge Levers

Lever Key Activities
Customer

Knowledge
Developing deep knowledge sharing relationships. Understanding
the needs of your customers’ customers. Articulating unmet needs.
Identifying new opportunities.

Stakeholder
Relationships

Improving knowledge flows between suppliers, employees,
shareholders, and community etc. using this knowledge to inform
key strategies.

Business
Environment

Insights

Systematic environmental scanning, including political, economic,
technology, social and environmental trends. Competitor analysis.
Market intelligence systems.

Organizational
Memory

Knowledge sharing. Best practice databases. Directories of
expertise. Online documents, procedures and discussion forums.
Intranets.

Knowledge in
Processes

Knowledge sharing. Best practice databases. Directories of
expertise. Online documents, procedures and discussion forums.
Intranets.

Knowledge in
Products and

Services

Knowledge embedded in products. Surround products with
knowledge e.g. in user guides, and enhanced knowledge-intensive
services.

Knowledge in
People

Knowledge sharing fairs. Innovation workshops. Expert and
learning networks. Communities of knowledge practice.

With the combined understanding of these two aspects, it would be up to the
successfulness of the knowledge management program to mine these specific areas
and to link the findings with the organization’s long-term strategic development.

Differences Between Knowledge, Information and Data

One of the annoying trends in the current practice of knowledge management arena is
that the concepts of knowledge and information tend to be used almost interchangeably
throughout the literature and praxis. For example, the management of information
captured on organization’s databases is often considered as an example of
organizational knowledge and knowledge management. Information and data
management are important pillars of knowledge management. However, knowledge
management encompasses broader issues and, in particular, creation of processes,
environment and behaviors that allow people to transform information into the
organization and create and share knowledge. Thus, knowledge management needs to
encompass people, process, technology and culture. Moreover, organizational
databases and connectivity do not guarantee the sharing of information over time11. In
some instances, databases and connectivity result in too much information, or
information overload, posing a threat to aspects of knowledge quality such as
relevance.12

11 Nada K. Kakabadse, Alexander Kouzmin and Andrew Kakabadse (2001), From Tacit
Knowledge to Knowledge Management: Leveraging Invisible Assets, Knowledge and Process
Management Volume 8 Number 3 pp 137–154.
12 Sharda R, Frankwick GL, Turetken O (1999), Group knowledge networks: a framework and an
implementation. Information System Frontiers 1, No. 3, 221–239.

7

Typically, as Davenport and Prusak have explained13:

Data is: simple observation of states of the world
Information is: data endowed with relevance and purpose
Knowledge is: Valuable information from the human mind.

Knowledge builds upon information that is extracted from data. In contrast to data that
can be characterized as a property of things, knowledge is a property of agents
predisposing them to act in particular circumstances. Information is that subset of the
data residing in things that activates an agent through the perceptual or cognitive filters.
In contrast to information, knowledge cannot be directly observed. Its existence can only
be inferred from actions of agents.

The relationship between these three concepts is actually very well presented by
Skyrme and Amidon, with the addition of wisdom, in the diagram of what they called
“The Pyramid of Knowledge Hierarchy”14:

Figure 1: The Pyramid of Knowledge Hierarchy

Besides that, Bellinger et al. has also developed a hierarchy diagram comprising data,
information, knowledge and wisdom, with the addition of different levels of understanding
achieved during the transition through these four categories.

13 Davenport, T. and Prusak, T (1998), Working Knowledge: How organisations manage what
they know, Harvard Business School Press: Boston
14 Skyrme and Amidon (1997), reported in Knight, T and Howes, T, 2003, Knowledge
Management: A Blueprint for Delivery, Butterworth Heinemann: Oxford p.13

8

Figure 2: The Data, Information, Knowledge and Wisdom Hierarchy15

The key to Bellinger’s hierarchy diagram is the different levels of achieved
understanding. In common with the earlier approaches, data may be viewed as some
disconnected collection of facts about a domain that have little intrinsic interest.
Information emerges from the domain when relationships between the facts are
established and understood; this is somewhat richer than simply establishing a context
for the facts. Knowledge emerges when the patterns of relationships are identified and
understood; a quite different perspective from size and longevity. Finally wisdom (the
pinnacle of understanding) uncovers the principles that describe the patterns of
relationships. Along with the increasing of hierarchy from data to wisdom, correctedness
and understanding also increase during this transition process.

15 Bellinger G., D. Castro, and A. Mills (2004), Data, Information, Knowledge, and Wisdom.
Retrieved from: http://www.systems-thinking.org/dikw/dikw.htm

9

For example: The differences between data, information and knowledge
as well as the different types of knowledge can be more vividly explained
using the analogy of cake-making. An analysis of a cake’s constituents
provides data. For most purposes this is not very useful, just by the
looking at it one might not even tell it is a cake. A list of ingredients
(information) is more useful as it gives the data context, so that an
experienced cooker could probably make the cake. However, if
everything is written down with the form of a recipe, then this becomes
knowledge, it could tell everyone how to make the cake. The recipe is
knowledge, but it is only the explicit knowledge. If the process of making
the cake is very complicated, or even some of the process is hard to be
expressed on paper, then the final taste of the cake would really depend
on the mastery of tacit knowledge, even with the recipe on hand, not
everyone could make a very good cake.

What is Knowledge Management?

Definition

From the individual’s perspective knowledge would be meaningless useless it can be
transferred to and acquired by an actual person and from the organization’s perspective
knowledge would be worthless if it could not be put into application when it is needed for
organization’s business. Thus it would be of great importance for an organization to
provide strategies to get the right knowledge to the right people at the right time and in
the right format. As the complexity of organizations increases, together with the growing
scale and scope of information activities due to the development of Information and
Communication Technologies (ICTs), effectively and efficiently managing knowledge
becomes a pressing necessity of strategic importance for modern organizations.

Bassi defines knowledge management as16:

a process of knowledge creation, capturing and application through its
documenting and codifying, storage and dissemination them through data banks
and communication channels with the purpose of increasing the organizational
effectiveness.

The online Media Access Group called Knowledge Praxis (www.media-
access.com/main.html) defines knowledge management as a business activity with two
primary aspects:

• Treating the knowledge component of business activities as an explicit
concern of business reflected in strategy, policy, and practice at all levels of
the organization.

• Making a direct connection between an organization’s intellectual assets —
both explicit [recorded] and tacit [personal know-how] — and positive
business results.

16 Bassi, L.J. (1997), Harnessing the power of intellectual capital, Training & Development,
December, 51(12):25-30.

10

Based on interviews with the Chief Knowledge Officers from various organizations,
Skyrme define knowledge management as17:

the explicit and systematic management of vital knowledge and its associated
processes of creating, gathering, organizing, diffusion, use and exploitation, in
pursuit of organizational objectives.

Notwithstanding the difficulty of establishing a consensus definition for knowledge
management, at least the following range of key considerations in relation to knowledge
management should be identified:

• It is fundamental that knowledge should be utilized and shared within the
organization; and if possible, should be stored in its most explicit forms.

• Knowledge management does not just stop on the purpose of sharing;
knowledge management should also be regarded as the enabler of
innovation and learning.

• The purpose of knowledge management is to make organizations more
efficient and effective, and to be aligned with organizational strategy for
the support of achieving organizational objectives.

The Evolution of Knowledge Management

Knowledge management has a long and distinguished history. It was initiated arguably
as long ago as in the 1960s, when Peter Drucker first coined the term “knowledge
worker”18. Debra Amidon has composed a detailed timeline of knowledge management
and has traced many of the early roots going back to the early 1980s, some of the
significant events were:19

• 1986 – publication by Swedish knowledge management pioneer Karl-Erik Sveiby
of The Know-How Company (with Tom Lloyd).

• 1987 – ‘Managing the Knowledge Assets into the 21st Century’ round table
(between US academia, business and government) – one of the first nationwide
efforts to harness intellectual capital.

• 1991 – appointment of Leif Edvinsson as Vice President of intellectual capital for
Skandia, arguably the first formal board level appointment related to knowledge
management

• 1991 – publication of seminal Harvard Business Review article by Ikujiro Nonaka
on the ‘knowledge-creating company’, later expanded and published as a book
with Hirotaka Takeuchi (1995)

• 1993 – ‘Intellectual capital: your company’s most valuable asset’ – article by Tom
Stewart in Fortune that helped raise awareness of knowledge management in the
world of business

17 David J. Skyrme (2002), Knowledge Management: Approaches and Policies
18 As quoted in Panchak, “The Future of Manufacturing”, Peter Drucker has observed:
“Increasingly, the human being does not work in mass production, but in what might be called
“team production.” And that means that increasingly the producing human being is a knowledge
worker. Workers as they did before the Industrial Revolution, own the means of production. The
means is between their ears.”
19 Knowledge Innovation® Timeline – http://www.entovation.com/timeline/ Knowledge
Innovation® is a registerd tradmark of ENTOVATION International

11

• 1995 – first business seminars and conferences in the USA e.g. Knowledge For
Strategic Advantage – co-sponsored by Arthur Andersen and the American
Productivity and Quality Center, held in Houston.

• 1996 – first business conferences in Europe
• 1998 – The World Bank chooses the theme Knowledge for Development as the

topic for its annual world development report.

There has been a rapid spread of the influence and uptake of knowledge management
following its wider promotion since late 1990s. There are now more than a dozen
periodicals and magazines with knowledge management in their title, such as
Knowledge Management, Knowledge Management Magazine, Knowledge Management
Review and the Journal of Knowledge Management. All provide a valuable ongoing
resource for knowledge managers and include helpful case studies and guidance from
experts.

Although first seen in the private sector knowledge-intensive large companies in the oil,
pharmaceutical, high technology and financial services industries, it has spread into
most other industries as well as the public sector. In the last couple of years, especially
after the publishing of the United Nations Millennium Declaration (General Assembly
resolution 55/2) and the report of the U.N. Secretary-General on a road map toward its
implementation (A/56/326), which …

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Why Big Data is the new competitive advantage

by: Tim McGuire, James Manyika, Michael Chui, James Manyika, Michael Chui
Issues: July / August 2012. Tags: Strategy and Technology/Social Media.
Categories: Featured and Strategy.

Many observers, including the authors of this article, believe that
Big Data is the new, new thing that will see some companies
leapfrog others to become best in class. There are a few skeptics,
but readers will find a compelling case and a toolkit for the smart
use of Big Data in this article.

Data are now woven into every sector and function in the global economy, and, like other essential factors
of production such as hard assets and human capital, much of modern economic activity simply could not
take place without them. The use of Big Data — large pools of data that can be brought together and

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analyzed to discern patterns and make better decisions — will become the basis of competition and growth
for individual firms, enhancing productivity and creating significant value for the world economy by reducing
waste and increasing the quality of products and services.

Until now, the torrent of data flooding our world has been a phenomenon that probably only excited a few
data geeks. But we are now at an inflection point. According to research from the McKinsey Global Institute
(MGI) and McKinsey & Company’s Business Technology Office, the sheer volume of data generated,
stored, and mined for insights has become economically relevant to businesses, government, and
consumers.

The history of previous trends in IT investment and innovation and its impact on competitiveness and
productivity strongly suggest that Big Data can have a similar power, namely the ability to transform our
lives. The same preconditions that allowed previous waves of IT-enabled innovation to power productivity,
i.e., technology innovations followed by the adoption of complementary management innovations, are in
place for Big Data, and we expect suppliers of Big Data technology and advanced analytic capabilities to
have at least as much ongoing impact on productivity as suppliers of other kinds of technology.

All companies need to take Big Data and its potential to create value seriously if they want to compete. For
example, some retailers embracing big data see the potential to increase their operating margins by 60 per
cent.

Big Data: A new competitive advantage
The use of Big Data is becoming a crucial way for leading companies to outperform their peers. In most
industries, established competitors and new entrants alike will leverage data-driven strategies to innovate,
compete, and capture value. Indeed, we found early examples of such use of data in every sector we
examined. In healthcare, data pioneers are analyzing the health outcomes of pharmaceuticals when they
were widely prescribed, and discovering benefits and risks that were not evident during necessarily more
limited clinical trials. Other early adopters of Big Data are using data from sensors embedded in products
from children’s toys to industrial goods to determine how these products are actually used in the real world.
Such knoiwledge then informs the creation of new service offerings and the design of future products

Big Data will help to create new growth opportunities and entirely new categories of companies, such as
those that aggregate and analyse industry data. Many of these will be companies that sit in the middle of
large information flows where data about products and services, buyers and suppliers, consumer
preferences and intent can be captured and analysed. Forward-thinking leaders across sectors should
begin aggressively to build their organisations’ Big Data capabilities.

In addition to the sheer scale of Big Data, the real-time and high-frequency nature of the data are also
important. For example, ‘nowcasting,’ the ability to estimate metrics such as consumer confidence,
immediately, something which previously could only be done retrospectively, is becoming more extensively
used, adding considerable power to prediction. Similarly, the high frequency of data allows users to test
theories in near real-time and to a level never before possible.

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We studied five domains in depth—healthcare and retail in the United States, the public sector in Europe,
and manufacturing and personal location data (the location data generated by the smart mobile devices
many of us now carry) globally—and some broadly applicable ways of leveraging big data emerged.

Five ways to leverage Big Data
1. Big Data can unlock significant value by making information transparent. There is still a significant
amount of information that is not yet captured in digital form, e.g., data that are on paper, or not made easily
accessible and searchable through networks. We found that up to 25 percent of the effort in some
knowledge worker workgroups consists of searching for data and then transferring them to another
(sometimes virtual) location. This effort represents a significant source of inefficiency.

2. As organisations create and store more transactional data in digital form, they can collect more
accurate and detailed performance information on everything from product inventories to sick days and
therefore expose variability and boost performance. In fact, some leading companies are using their ability
to collect and analyse big data to conduct controlled experiments to make better management decisions.

3. Big Data allows ever-narrower segmentation of customers and therefore much more precisely
tailored products or services.

4. Sophisticated analytics can substantially improve decision-making, minimise risks, and unearth
valuable insights that would otherwise remain hidden.

5. Big Data can be used to develop the next generation of products and services. For instance,
manufacturers are using data obtained from sensors embedded in products to create innovative after-sales
service offerings such as proactive maintenance to avoid failures in new products.

Value created by the use of Big Data
If the U.S. healthcare system were to use big data creatively and effectively to drive efficiency and quality,
the sector could create more than $300bn in value every year. Two-thirds of that would be an 8 percent
reduction in U.S. healthcare expenditure. In the developed economies of Europe, government
administrators could create more than €100bn ($123bn) in operational efficiency improvements alone by
using Big Data – and that’s not including employing advanced analytic tools to reduce fraud and errors and
boost the collection of tax revenues.

But it’s not just companies and organisations that stand to gain from the value that Big Data can create.
Consumers can also reap highly significant benefits. For instance, users of services enabled by personal-
location data can capture $600bn in consumer surplus.

Take smart routing using real-time traffic information, which is one of the most heavily-used applications of
personal-location data. As the penetration of smart phones increases, and free navigation applications are
included in these devices, the use of smart routing is likely to grow. By 2020, more than 70 percent of

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mobile phones are expected to have a GPS capability, up from 20 percent in 2010. All told, we estimate that
the potential global value of smart routing in the form of time and fuel savings will be about $500bn by
2020. This is equivalent to saving drivers 20bn hours on the road, or 10 to 15 hours every year for each
traveller, and about $150bn on fuel consumption.

Some of the most significant potential to generate value from Big Data will come from combining separate
pools of data. The U.S. healthcare system, for instance, has four major pools of data – clinical; activity
(claims) and cost; pharmaceutical and medical products R&D; and data about patient behaviour and
sentiment – each of which is primarily captured and managed by a different constituency. MGI estimates
that if U.S. healthcare fully used all the available techniques that can be enabled by Big Data, such as
analyzing records of real-world medical treatments, their costs and health outcomes to guide physicians on
which treatments provide the best outcomes at the best cost, the annual productivity of the sector could
grow by an additional 0.7 per cent. But achieving this boost in productivity will require the combination of
data from different sources – often from organizations that have no history of sharing data at scale. Sets of
data such as patient records and clinical claims would have to be integrated.

Doing so would create benefits not just for the various industry players but for patients, who would have
broader, clearer access to a wider variety of healthcare information, making them more informed. Patients
would be able to compare not only the prices of drugs, treatments, and physicians, but also their relative
effectiveness, enabling them to choose more effective, better-targeted medicines, potentially even
customised to their personal genetic and molecular make-up. To obtain those broad benefits, healthcare
consumers may have to accept a slightly different trade-off between their privacy and the benefits that wider
pooling of data would bring.

Sensitivities around privacy and data security are just one hurdle that companies and governments need to
overcome if the economic benefits of big data are to be realised. One of the most pressing challenges is a
significant shortage of people with the skills to analyse big data. By 2018, the United States alone could
face a shortage of 140,000 to 190,000 people with deep analytical training (in statistics or machine
learning) and another 1.5m people with the managerial and quantitative skills to be able to frame and
interpret analyses effectively enough to base decisions on them.

There are also many technological issues that need to be resolved to make the most of big data. Legacy
systems and incompatible standards and formats often prevent the integration of data and the application of
the more sophisticated analytics that create value. Ultimately, making use of large digital datasets will
require the assembly of a technology stack from storage and computing through analytical and visualisation
software applications.

Above all, access to data needs to broaden. Increasingly, companies will need to access data from third
parties, e.g., business partners or customers, and integrate them with their own. A vital competency for
data-driven organizations in the future will be the ability to create compelling value propositions for others,
including consumers, suppliers and potentially even competitors, to share data. If it looks unlikely that data
sharing will occur despite the potential for societal benefits (a market failure), legislators may then have to
step in.

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As long as companies and governments understand the power of Big Data to deliver higher productivity,
better value for consumers, and the next wave of growth in the global economy, there should be a strong
enough incentive for them to act robustly to overcome the barriers to its use. By doing so they will unleash
avenues to new competitiveness among companies, higher efficiency in the public sector that will enable
better services, even in constrained fiscal times, and enable firms and even whole economies to be more
productive.

Big data is a big deal
The era of Big Data could yield new management principles. In the early days of professionalized corporate
management, leaders discovered that minimum efficient scale was a key determinant of competitive
success. Likewise, future competitive benefits are likely to accrue to companies that can not only capture
more and better data but also use that data effectively at scale. We hope that by reflecting on such issues
and the five questions that follow, executives will be better able to recognize how big data could upend
assumptions behind their strategies, as well as the speed and scope of the change that’s now under way.

1. What happens in a world of radical transparency, with
data widely available?
As information becomes more readily accessible across sectors, it can threaten companies that have relied
on proprietary data as a competitive asset. The real-estate industry, for example, trades on information
asymmetries such as privileged access to transaction data and tightly held knowledge of the bid and ask
behaviour of buyers. Acquiring both requires a significant expense and effort. In recent years, however,
online specialists in real-estate data and analytics have started to bypass agents, permitting buyers and
sellers to exchange perspectives on the value of properties and creating parallel sources for real-estate
data.

Cost and pricing data are becoming more accessible across a spectrum of industries. Another swipe at
proprietary information is the assembly by some companies of readily available satellite imagery that, when
processed and analyzed, contains clues about competitors’ physical facilities. These satellite sleuths glean
insights into expansion plans or business constraints as revealed by facility capacity, shipping movements,
and the like.

One big challenge is the fact that the mountains of data many companies are amassing often lurk in
departmental “silos,” such as R&D, engineering, manufacturing, or service operations—impeding timely
exploitation. Information hoarding within business units also can be a problem: many financial institutions,
for example, suffer from their own failure to share data among diverse lines of business, such as financial
markets, money management, and lending. Often, this prevents these companies from forming a coherent
view of individual customers or understanding links among financial markets.

Some manufacturers are attempting to pry open these departmental enclaves: they are integrating data
from multiple systems, inviting collaboration among formerly walled-off functional units, and even seeking
information from external suppliers and customers to co-create products. In advanced-manufacturing

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sectors such as automotive, for example, suppliers from around the world make thousands of components.
More integrated data platforms now allow companies and their supply chain partners to collaborate during
the design phase—a crucial determinant of final manufacturing costs.

2. If you could test all of your decisions, how would that
change the way you compete?
Big Data ushers in the possibility of a fundamentally different type of decision making. Using controlled
experiments, companies can test hypotheses and analyze results to guide investment decisions and
operational changes. In effect, experimentation can help managers distinguish causation from mere
correlation, thus reducing the variability of outcomes while improving financial and product performance.

Robust experimentation can take many forms. Leading online companies, for example, are continuous
testers. In some cases, they allocate a set portion of their Web page views to conduct experiments that
reveal the factors that drive higher user engagement or sales gains. Companies selling physical goods also
use experiments to aid decisions, but Big Data can push this approach to a new level. McDonald’s, for
example, has equipped some stores with devices that gather operational data as they track customer
interactions, traffic in stores, and ordering patterns. Researchers can model the impact of variations in
menus, restaurant designs, and training, among other things, on productivity and sales.

Where such controlled experiments aren’t feasible, companies can use “natural” experiments to identify the
sources of variability in performance. One government organization, for instance, collected data on multiple
groups of employees doing similar work at different sites. Simply making the data available spurred lagging
workers to improve their performance.

3. How would your business change if you used Big Data
for widespread, real-time customization?
Customer-facing companies have long used data to segment and target customers. Big Data permits a
major step beyond what until recently was considered state of the art, by making real-time personalization
possible. A next-generation retailer will be able to track the behavior of individual customers from Internet
click streams, update their preferences, and model their likely behavior in real time. They will then be able
to recognize when customers are nearing a purchase decision and nudge the transaction to completion by
bundling preferred products, offered with reward program benefits. This real-time targeting, which would
also leverage data from the retailer’s rewards program, will increase purchases of higher-margin products
by its most valuable customers.

Retailing is an obvious industry for data-driven customization because the volume and quality of data
available from Internet purchases, social-network conversations, and, more recently, location-specific smart
phone interactions have mushroomed. But other sectors, too, can benefit from new applications of data,
along with the growing sophistication of analytical tools for dividing customers into more revealing
microsegments.

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4. How can Big Data augment or even replace
management?
Big data expands the possible domains of application for algorithms and machine-mediated analysis. At
some manufacturers, for example, algorithms analyze sensor data from production lines, creating self-
regulating processes that cut waste, avoid costly (and sometimes dangerous) human interventions, and
ultimately lift output. In advanced, “digital” oil fields, instruments constantly read data on wellhead
conditions, pipelines, and mechanical systems. That information is analyzed by clusters of computers,
which feed their results to real-time operations centers that adjust oil flows to optimize production and
minimize downtimes. One major oil company has cut operating and staffing costs by 10 to 25 percent, while
increasing production by 5 percent.

Products ranging from copiers to jet engines can now generate data streams that track their usage.
Manufacturers can analyze the incoming data and, in some cases, automatically remedy software glitches
or dispatch service representatives for repairs. Some enterprise computer hardware vendors are gathering
and analyzing such data to schedule preemptive repairs before failures disrupt customers’ operations. The
data can also be used to implement product changes that prevent future problems or to provide customer-
use inputs that inform next-generation offerings.

The bottom line is improved performance, better risk management, and the ability to unearth insights that
would otherwise remain hidden. As the price of sensors, communications devices, and analytic software
continues to fall, more and more companies will be joining this managerial revolution.

5. Could you create a new business model based on
data?
Big Data is spawning new categories of companies that embrace information-driven business models.
Many of these businesses play intermediary roles in value chains where they find themselves generating
valuable “exhaust data” produced by business transactions. One transport company, for example,
recognized that in the course of doing business, it was collecting vast amounts of information on global
product shipments. Sensing opportunity, it created a unit that sells the data to supplement business and
economic forecasts.

Another global company learned so much from analyzing its own data as part of a manufacturing
turnaround that it decided to create a business to do similar work for other firms. Now the company
aggregates shop-floor and supply-chain data for a number of manufacturing customers and sells software
tools to improve their performance. This service business now outperforms the company’s manufacturing
business.

11/10/21, 1:52 PM Data Mining: Purpose, Characteristics, Benefits & Limitations – WiseStep

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Data Mining: Purpose, Characteristics, Benefits &
Limitations

To make the meaning of data mining easy, one can separate the words and try to

understand the meaning better.

Here data mining can be taken as data and mining, data is something that

holds some records of information and mining can be considered as digging deep

information about using materials. So in terms of defining,

What is Data Mining?

Data mining is a process that is useful for the discovery of informative and

analyzing the understanding of the aspects of different elements.

We can always find a large amount of data on the internet which are relevant to

various industries. The term data is referred here as raw collection of stats and

details, which is not sorted.

By Chitra Reddy

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The same data if is organized and sorted then it turns out to be information,

which can be used by us in various ways. This extraction of information from the

raw data is another form of data mining.

Few other processes which include in data mining are,

Data Integration

Data Cleaning

Data Transformation

Pattern Evaluation

Data Presentation

The knowledge or information which is acquired through the data mining process

can be made used in any of the following applications −

1. Market Analysis

2. Production Control

3. Customer Retention

4. Science Exploration

5. Fraud Detection

6. Sports

7. Astrology

8. Internet Web Surf-Aid

What Can Data Mining Do:

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Data mining helps in analyzing and summarizing different elements of

information. A mining process is a form wherein which all the data and

information can be extracted for the purpose of future benefit.

1. It helps to identify the shopping patterns:

Most of the time while designing some shopping patters one might experience

some sort of unexpected issues.

And to overcome and find out the actual reason behind that data mining can be

helpful. Mining methods discover all the information about these shopping

patterns.

Moreover, this data mining process creates a space that determines all the

unexpected shopping patterns. Therefore, this data mining can be beneficial while

identifying shopping patterns.

2. Increases website optimization:

As per the meaning and definition of data mining, it helps to discover all sorts

of information about the unknown elements. And adding to that data mining

helps to increase the website optimization.

As most of the key factors of website optimization deal with information and

analyzation, similarly, this mining provides such information which can utilize

data mining techniques to increase website optimization.

3. It is beneficial for marketing campaigns:

Most importantly, all the elements of data mining is dealt with information

discovery and also in its summarization way.

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Moreover, it is also beneficial for marketing campaigns because it helps to identify

the customer response over certain products available in the market.

Therefore, all the working format of these data mining processes identifies

the customer response through the marketing campaign, which can

implement profit for the growth of the business.

4. Determining customer groups:

As it is explained earlier, data mining models help to provide customer responses

from marketing campaigns. And it also provides informational help while

determining customer groups.

These new customer groups can be initiated through some sort of surveys and

these surveys are one of the forms of mining where different types of information

about unknown products and services are gathered with the help of data mining.

5. It helps to measure profitability factors:

The data mining system provides all sorts of information about customer

response and determining customer groups. Therefore, it can be helpful while

measuring all the factors of the profitable business.

As these types of working factors of data mining, one can clearly understand

the actual measurement of the profitability of the business.

Moreover, these data mining processes differentiate key factors between profit

and loss elements of the business.

6. Increases brand loyalty:

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These marketing campaigns use these mining techniques to understand the

behaviour and habits of their own customers. And it also allows their customers to

choose their brand of clothes which makes them comfortable.

Therefore, with the help of the data mining technique, one can definitely bemore

self-reliant when it comes to decision making as it provides most of the possible

information about different types of brands available.

Purpose of Data Mining:

The main purpose of data mining process is to discover those records of

information and summarize it in a simpler format for the purpose of others.

Therefore, understanding the purpose of the mining process is a matter of

information.

1. It increases customer loyalty:

As most of the information about data mining covers up all the detailing of the

discovery of information.

Similarly, when it comes to marketing campaign this data mining process handles

all customer satisfaction and customer loyalty regarding issues. Therefore, at the

end of the line these data mining process benefits those who are in a similar field

of work.

And finally, the marketing industry deals with data mining creating an increased

level of customer loyalty.

2. It identifies hidden profitability:

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At the starting level of this data mining process, one can understand the actual

nature of work, but eventually, the benefits and features of these data mining can

be identified in a beneficial manner.

One of the most important elements of these data mining is considered as that it

provides the determination of locked profitability.

Therefore, this data mining provides clear identification of hidden profitability so

that one can overcome the risk factor in their business.

3. Minimizes clients involvement:

Most of the time while gathering information about certain elements, products

and services, one used to depend on their clients for some additional information.

But these data mining processes change everything and that is because of the help

of such inclusion of technology in the data mining process.

Therefore, the end conclusion is that all the information discovered through this

data mining process is initiated through information technology.

4. Customer satisfaction:

One of the main nature of working which is involved in the mining techniques are

from their informational matters.

Most of people seek for others’ help while making some decisions. But it is not

always easy to follow anyone suggestion. And that is why with the help of data

mining one can be confident enough to make their own decision.

Moreover, it gains the trust of its customers with such kind of efforts.

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Characteristics of Data Mining:

Data mining service is an easy form of information gathering methodology

wherein which all the relevant information goes through some sort of

identification process.

And eventually at the end of this process, one can determine all the characteristics

of the data mining process.

1. Increased quantities of data:

In earlier days, the data mining system can be determined with the help of their

clients and customers, but in today’s date, one can acquire any number of

information without the help of those clients.

Moreover, after this kind of revolution in the mining system, it also added one

more problem and that is large quantities of work.

With the help of this information technology, one can acquire a large number

of information without any extra burden or trouble.

2. Provides incomplete data:

Most of the people provide incomplete information about themselves in some of

the survey conducted with the help of data mining systems.

Therefore, people ignore the value of their information and that is why they

provide incomplete information about themselves in those surveys conducted for

the benefit of the mining systems.

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Moreover, these mining systems changed the perspective of people and because of

that, people fear the exchange of their personal information.

3. Complicated data structure:

Data mining is a form wherein which all the information is gathered and

incorporated with the help of information collection techniques. These

information collecting techniques are more of manual and rest are technological.

Therefore, most of the understanding and determination of these mining can be a

bit complicated than other structures of information technology.

Data Mining Applications:

Data mining is mostly used by many of the big gaints in the information

technology sector and also some small industries by making use of their own

techniques. Some of the popular domains are,

1. Market Analysis and Management

2. Corporate Analysis & Risk Management

3. Fraud Detection

1. Market Analysis and Management:

The following mentioned are the various fields of the market where the data

mining process is effectively used,

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Customer Profiling

Finding customer requirements

Cross-market analysis

Target marketing

Determining customer purchasing pattern

Provides summary information

2. Corporate Analysis and Risk Management:

The following mentioned are the various fields of the corporate sector where the

data mining process is effectively used,

Finance Planning

Asset Evaluation

Resource Planning

Competition

3. Fraud Detection:

Frauds and malware is one of the most dangerous threats on the internet. It is

almost a kind of crime that is increasing day after day. The fraud detection

process can be mainly used through credit card services and telecommunication.

With the help of the services most of the important information like duration of

the call, location, the time and day etc can be acquired which helps in big time.

Benefits or Advantages of Data Mining Techniques:

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There are several types of benefits and advantages of data mining systems. One of

the essential matters of these mining creates a complete structure of analysis of

mining techniques.

1. It is helpful to predict future trends:

Most of the working nature of the data mining systems carries on all the

informational factors of the elements and their structure.

One of the common benefits that can be derived with these data mining systems is

that they can be helpful while predicting future trends. And that is quite possible

with the help of technology and behavioral changes adopted by the people.

2. It signifies customer habits:

For example, while working in the marketing industry one can understand all the

matters of customer behaviour and their habits. And that is possible with the help

of data mining systems.

As these data mining systems handle all the information acquiring techniques. It

is helpful in keeping track of customer habits and their behavior.

3. Helps in decision making:

There are some people who make use of these data mining techniques to help

them with some kind of decision making.

Nowadays, all the information about anything can be determined easily with the

help of technology and similarly, with the help of such technology one can make a

precise decision about something unknown and unexpected.

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4. Increase company revenue:

As it has been explained earlier that data mining is a process wherein which it

involves some sort of technology to acquire

some information about anything possible. And this type of technology makes

things easier for their profit earning ratio.

As people can collect information about the marketed products online, which

eventually reduces the cost of the product and their services.

5. It depends upon market-based analysis:

Data mining process is a system wherein which all the information has been

gathered on the basis of market information.

Nowadays, technology plays a crucial role in everything and that casualty can be

seen in these data mining systems. Therefore, all the information collected

through these data mining is basically from marketing analysis.

6. Quick fraud detection:

Most parts of the data mining process is basically from information gathered with

the help of marketing analysis. With the help of such marketing analysis, one can

also find out those fraudulent acts and products available in the market.

Moreover, with the help of it one can understand the importance of accurate

information.

Limitations or Disadvantages of Data Mining Techniques:

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Data mining technology is something that helps one person in their decision

making and that decision making is a process wherein which all the factors of

mining is involved precisely.

And while the involvement of these mining systems, one can come across several

disadvantages of data mining and they are as follows.

1. It violates user privacy:

It is a known fact that data mining collects information about people using some

market-based techniques and information technology. And these data mining

process involves several numbers of factors.

But while involving those factors, data mining system violates the privacy of its

user and that is why it lacks in the matters of safety and security of its users.

Eventually, it creates miscommunication between people.

2. Additional irrelevant information:

The main functions of the data mining systems create a relevant space for

beneficial information.

But the main problem with these information collections is that there is a

possibility that the collection of information processes can be a little

overwhelming for all.

Therefore, it is very much essential to maintain a minimum level of limit for all

the data mining techniques.

3. Misuse of information:

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As it has been explained earlier that in the data mining system the possibility of

safety and security measure are really minimal. And that is why some can misuse

this information to harm others in their own way.

Therefore, the data mining system needs to change its course of working so that it

can reduce the ratio of misuse of information through the mining process.

4. Accuracy of data:

Most of the time while collecting information about certain elements one used to

seek help from their clients, but nowadays everything has changed. And now the

process of information collection made things easy with the mining technology

and their methods.

One of the most possible limitations of this data mining system is that it can

provide accuracy of data with its own limits.

Conclusion:

Finally, the bottom line is that all the techniques, methods and data mining

systems help in the discovery of new creative things. And at the end of this

discussion about the data mining methodology, one can clearly understand the

feature, elements, purpose, characteristics, and benefits with its own limitations.

Therefore, after reading all the above-mentioned information about the data

mining techniques, one can determine its credibility and feasibility even better.

11/10/21, 1:50 PM Technology Will Erase 5 Million Jobs | Best Countries | US News

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A World Economic Forum report predicts a loss of more than 7 million jobs because of technological advances and a gain of slightly more than 2

million through specialization.

DAVOS, Switzerland — As if plummeting stock markets, fears of a new recession and a growing gulf between rich
and poor isn’t enough to deal with, world leaders have a new concern: a loss of more than 5 million jobs in 15
developed and emerging economies by 2020.
That is what world leaders were told on Wednesday as the World Economic Forum opened its meetings at Davos
with a stark picture about how technology will reshape society. Further, those job losses will come in the world’s
leading economies: the United States, China, Germany, the United Kingdom, Japan, France and Australia, as well as
in developing economies such as India.

In its report, “The Future of Jobs,” the WEF forecast a loss of more than 7 million jobs because of technological
advances and a gain of slightly more than 2 million through specialization. In the report, WEF founder and Executive

Technology Will Erase 5 Million Jobs

Leaders at World Economic Forum are urged to immediately train workforces for a changing future.

By Mina Al-Oraibi

Jan. 20, 2016

Save

( V I N C E N T YU / A P )

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Chairman Klaus Schwab urged governments to prepare their countries’ workforces for a changing future, otherwise
issues such as inequality and unemployment will only worsen.
The report’s message came on a day where discussion panels focused on technological disruption and changing
work environments, as well as daily headlines such as falling oil prices, slowing economic growth in China and

armed conflicts around the world. This year’s WEF gathering, the 46th such annual meeting, is entitled “Mastering the
Fourth Industrial Revolution.”
“The Fourth Industrial Revolution refers to the fusion of technologies across the physical, digital and biological
worlds which is creating entirely new capabilities and dramatic impacts on political, social and economic systems,”
says Schwab. “The speed, scale and systemic nature of this transformation has the potential to disrupt all sectors
and call into question the essence of human nature and identity.”
The “Fourth Industrial Revolution” is also the title of Schwab’s latest book. While he admits to writing it in three
months, Schwab has been discussing these ideas and their implication on the world for years. And he wants the
world to listen up.
The impact of automation is just one aspect of this new revolution. Cyber security is another. “We will see more
security issues with the Internet of things,” warned Eugene Kaspersky, chairman and CEO of Kaspersky Lab, at a
panel organized by Internet security company WiseKey. From the vulnerability of power plants to transit systems and
automated cars, Davos has been abuzz with these concerns. Jimmy Wales, the Founder of Wikipedia, urged
attendees to take security seriously, but not to allow government to use the pretense of ‘security’ to deprive users of
encryption.
For 46 years, leaders from the worlds of politics, business, culture and civil society have been descending on the
otherwise sleepy Swiss town of Davos snuggled in the Alps to join in discussions, deals and parties. And each year,
the World Economic Forum has been faced with the daunting task of providing an over-arching theme for the
meeting. This year, more than 2,500 participants are convening to discuss topics ranging from cyber security to
automation and changing work patterns, as well as broader issues that address technology and humanitarian crises.
In addition to its strong convening power – this year bringing everyone from the Queen of Belgium to Kevin Spacey
together – the World Economic Forum sees itself as a global think tank. Over the past 24 hours, they have published
reports to support the ideas behind the theme of the Fourth Industrial Revolution.

Tags: Best Countries, China, India, United States

11/10/21, 1:49 PM Leading disruptive innovation – Ivey Business Journal

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Leading disruptive innovation

by: Soren Kaplan
Issues: July / August 2012. Tags: Leadership. Categories: Innovation and Leadership.

While we may be able to appreciate a disruptive innovation in
retrospect, it is debatable whether we can convert our
understanding into a formal, repeatable process. In today’s
turbulent environment, leading disruptive innovation is likely more
about best principles than best practices, and requires a disruptive
approach to management itself. Down with convention, then, and
up with what this author terms LEAPS, an original but potentially
very effective way of leading and managing disruptive innovation.

In today’s complex, dynamic world, having a disruptive innovation capability is mandatory, both for growing
a business and protecting existing markets. But leading disruptive innovation requires new mindsets and
behaviours, for leaders themselves and for the organizations that develop them. This author describes the
qualities and competencies required for leading disruptive innovation

Disruptive innovation that transforms or creates new markets has become the Holy Grail for many
companies. Books like The Innovator’s Dilemma[i], along with Apple’s remarkable success and the high-
profile failures of Blockbuster, Borders, and Kodak, have created a heightened awareness and a desire for
game-changing innovation. More resources, models, and tools exist to help companies innovate than ever
before.

Leaders today, however, face a big challenge when it comes to disruptive innovation. Many executives rise
through the ranks of management, where predictability and control are valued and rewarded. Unlike
operations management, disruptive innovation – whether creating it or responding to it – involves extreme
uncertainty. Unexpected events, inevitable failures, and a fundamental lack of control are inherent to the
process. But few leaders are formally prepared to deal with the realities of leading or responding to
disruption.

mailto:?subject=Ivey%20Business%20Journal:%20Leading%20disruptive%20innovation&body=An%20article%20from%20the%20Ivey%20Business%20Journal%20is%20being%20shared%20with%20you:%0D%0A%0D%0ALeading%20disruptive%20innovation%0D%0A%0D%0AWhile%20we%20may%20be%20able%20to%20appreciate%20a%20disruptive%20innovation%20in%20retrospect,%20it%20is%20debatable%20whether%20we%20can%20convert%20our%20understanding%20into%20a%20formal,%20repeatable%20process.%C2%A0%20In%20today%E2%80%99s%20turbulent%20environment,%20leading%20disruptive%20innovation%20is%20likely%20more%20about%20best%20principles%20than%20best%20practices,%20and%20requires%20a%20disruptive%20approach%20to%20management%20itself.%20Down%20with%20convention,%20then,%20and:%20%0D%0A%0D%0ARead%20the%20article%20at%20https%3A%2F%2Fiveybusinessjournal.com%2Fpublication%2Fleading-disruptive-innovation%2F

11/10/21, 1:49 PM Leading disruptive innovation – Ivey Business Journal

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This article highlights the key dynamics involved in leading disruptive innovation. My goal is to outline the
core leadership experiences and practices involved in the process. A five-phase model, using the acronym
“LEAPS,” provides a structure for understanding the ways leaders create clarity during times of great
uncertainty. This model was developed during the research for my book, Leapfrogging[ii]. In addition to
specific company examples, empirical research from U.S. and European universities provides insight into
some of the more subtle social and psychological success factors that distinguish leaders who are best
suited to drive disruptive change.

Leaping into uncertainty
Perhaps the most defining characteristic of disruptive innovation is the great uncertainty that it creates for
leaders, organizations, and entire industries. The music, entertainment, computing, mobile phone, book
publishing, photography, and healthcare industries have all experienced dramatic change due to new
technologies, business models, distribution channels, government regulations, and market expectations.
Companies in these industries have been forced to experiment and introduce new technologies and
business models, not just to compete, but to survive.

While most organizations possess a general awareness of the importance and necessity of disruptive
innovation and change in general, there is a gap when it comes to understanding the deeper leadership
qualities necessary for driving them. Many leaders rely on research and data for decision-making to
manage daily operations, for example, but during times of disruption, waiting for hard data to make
decisions can quickly result in failure. Leaders must be comfortable using whatever information they have
on hand, integrating inputs from diverse sources around them, and then using their intuition to round out the
decision-making process.

The challenge for any business is that the competencies necessary for leading disruptive innovation are not
formulaic or quantifiable. As Gary Hamel says, “New problems demand new principles. Put bluntly, there’s
simply no way to build tomorrow’s essential organizational capabilities—resilience, innovation and
employee engagement—atop the scaffolding of 20th century management principles.” Hamel goes on to
say, “In an age of wrenching change and hyper-competition, the most valuable human capabilities are
precisely those that are least manage-able[iii].”

While a disruptive innovation can be seen and understood in retrospect, it is debatable whether it can be
transferred into a formal, repeatable process. In today’s turbulent environment, leading disruptive
innovation is likely more about best principles than best practices, and requires a disruptive approach to
management itself.

Using LEAPS to drive disruption
Whether going after disruptive innovations that leapfrog competitors and customer expectations, or
focusing on “blue oceans[iv]” that represent white-space opportunities to create entirely new markets, the
leadership issues are similar. Leaders must embrace ambiguity, live with uncertainty for long periods of
time, and confront the critiques of naysayers both inside and outside of their organizations. Jeff Bezos,

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CEO of Amazon, summarized the essence of the leadership challenge when he said, “Any time you do
something big, that’s disruptive, there will be critics… We are willing to be misunderstood for long periods of
time[v].” Few business schools, let alone companies, prepare their leaders to live with being
misunderstood or criticized, especially for extended periods of time. When it comes to leading for
disruption, recognizing that “the soft stuff is the hard stuff” can make the difference between success and
failure.

I have developed five strategies to address the inherent uncertainty of disruptive innovation and change.
Falling under the acronym LEAPS, each strategy contains specific principles that provide the basis by
which leaders harness uncertainty, ambiguity, and even surprises to reinvent their organizations and
industries.

Listen – Start with Yourself, Not the Market
Contrary to conventional wisdom, disruptive leadership is not about analyzing customer needs, creating
specifications to meet each need, and building great products and services to meet them. Bob Ulrich, the
former CEO of the retailer Target, was opposed to direct consumer market research, and focus groups
especially. During Target’s breakthrough growth years, the Target team used its own instincts to infuse
everything with leading edge design, from transforming store layouts to creating partnerships with
designers like Philippe Starck. Consumers didn’t know what they had been missing when going to Wal-
Mart or Sears until Target showed them how “Tar-zjay” could give them “cheap chic” in a way no other
retailer could.

Leaders like these don’t get bogged down in data, but rather find opportunities to deliver an entirely new
level of value. Research from the University of Amsterdam[vi] reveals the dyanmics behind how these
leaders rise above the complexity of today’s business environment. Researchers found that when subjects
were presented with large amounts of data, those that conducted the most analysis and spent the most
time reviewing options and choices were not the best decision-makers. In fact, those who were forced

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to ignoredetailed data through intentional distractions from the researchers used “unconscious thinking
time” in their thinking process. They not only made superior decisions but were better able to recognize
patterns in the complex data.

Steve Jobs and Apple never conducted market research as they developed the iPod, iPhone and iPad[vii].
Rather, Jobs and his team at Apple defined products and a user experience they, themselves, wanted.
Asking the market what it wanted would have been fruitless since consumers didn’t know what they were
missing until they were given it by the company. Leading through disruption involves determining what one
values and where we want to make a difference – both in what we do and how we do it. Disruptive
innovations come from people and organizations who “innovate for themselves” because they want to
make a difference for others.

Explore – Go outside to stretch the inside
Leading through disruption requires an agile mind that appreciates ambiguity. Disruptive innovators know
that uncertainty contains as much opportunity as it does risk. But to make this mindset practical, it is
essential to push personal, team, and organizational comfort zones. Borders, the recently bankrupt
bookseller, stuck to its retail knitting even while Amazon, Apple, and Barnes & Noble were introducing
eBook platforms to transform the industry. When leaders remain safely rooted in how things are done
today, they miss the kind of insight and market impact needed to protect themselves from, or create, a true
disruption.

A series of research studies from INSEAD and Northwestern University[viii] sheds light on how leaders can
overcome the paralysis that characterized Borders’ leadership. Researchers studied the problem-solving
skills and creativity levels of individuals who have lived in two or more cultures versus those who have
never lived abroad. The findings from the research demonstrates that when individuals are forced to
confront competing assumptions and norms through living abroad, the boundaries of their assumptions and
related defenses soften. The concepts of “the right way” versus “the wrong way” break down. Instead of
responding to a challenge like a deer in the headlights, they see connections and patterns that most others
don’t see and find the most creative opportunities.

Leaders who possess a track record of pushing their own personal boundaries are best equipped for
tackling the gray areas. These individuals stretch their comfort zones by taking on roles spanning different
functions, working across diverse industries or living in different cultures. As a result, they’re most
comfotable taking themselves, their teams, and their organizations out of the proverbial corporate comfort
zone and into uncharted territory.

Act – Take small simple steps, again and again and again
Paradoxically, leading disruptive innovation involves simultaneously focusing on your own intentions and
motivations to make a difference, like Target and Apple did, while at the same time gathering as much
external input as possible – from customers, employees, partners, or anyone else deemed relevant to the

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opportunity. Disruptive leadership involves putting a flexible stake in the ground around a specific
opportunity, and then taking a series of actions to intentionally challenge assumptions and rapidly change
direction as many times as necessary.

Researchers from the University of Virginia[ix] explored the differences in problem-solving styles and
thinking between serial entrepreneurs (individuals with at least 15 years experience and who had taken one
or more companies public in their careers) and professional managers from large corporations (including
leaders from Shell, Philip Morris, and Nestle). Each cohort was provided a hypothetical case of a start-up
and was asked how they would help it develop and grow.

The entrepreneurs first looked at the resources and information they had at their disposal, defined short-
term actions, and then improvised. They looked for ways to solicit input from anyone and everyone who
would listen. Their primary objective was to deliver something tangible to customers, even if it wasn’t fully
developed, in order to gain feedback, challenge their assumptions, learn, and iterate to better ideas.
Professional managers, on the other hand, began by listing concrete goals and plans. They too viewed
customer input as important, but saw it as a single up-front input to help them understand customer
requirements.

The researchers concluded that the greatest difference between entrepreneurs and corporate managers
lies in the difference of a single belief about the future. Professional managers assume the future can be
predicted; they create goals and plans and then attempt to control how things will unfold. The fundamental
assumption, therefore, is that personal assumptions and learning happens primarily in the beginning of the
process. Serial entrepreneurs, on the other hand, find ways to use external inputs of all types to challenge
their assumptions throughout the journey to their breakthroughs. They use a multitude of small steps and
activities to help them adapt and and modify their goals and strategies.

Leading disruptive innovation requires a mindset of continuous adaptation. Going after big opportunities
doesn’t mean we must bet the farm. Leading disruptive innovation involves determining which small steps
will have the greatest impact. While taking this approach can indeed help minimize risk, it requires leaders
to approach “planning” in a flexible way that allows for major shifts in goals, metrics, and timelines.

Persist – Take the surprise out of failure
When Sarah Robb O’Hagan, President of Gatorade, learned that many young football players pack
bananas in their sport bags but find them mashed between their cleats before practice, she asked her
product development team to develop a pre-workout drink pouch packed with carbohydrates. Gatorade
launched the pouch with the goal of tapping into a white-space opportunity.

“We knew drink bottles like the backs of our hands, but pouches were a completely new animal,” according
to O’Hagan. But while the pouches tested well in the lab, some of them leaked on store shelves. In many
companies, customer complaints would have halted the innovation in its tracks. Rather than run for cover,
O’Hagan helped Gatorade “reframe failure” by emphasizing the importance of trial and error. “We could
have waited another six months to ‘get it right, but we would have missed both the summer season and a
great learning opportunity. In fact, the leaky pouches caused everyone to revisit their assumptions about the

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packaging, which led to an even better ergonomic design and superior packaging materials,” she told her
team[x]. Leadership like O’Hagan’s characterizes the reframe required for disruptive innovation. While few
leaders want failure, setbacks are a natural part of the process when leading disruptive innovation.

Leaders who face the fear of failure head on – and who help their teams and organizations do the same –
are most prepared to use setbacks as springboards to success. A Harvard University study on the impact
of fear on decision-making, for example, found that fear creates pessimism, which leads to risk-averse
behavior. This same dynamic occurs on a widespread scale when the stock market falls and investors sell
at the bottom to “get out” in order to regain a sense of certainty.

Leading for disruptive innovation involves creating “optimistic persistence” in order to combat fear,
pessimism and the tendency to retrench back into the safety of the existing business model. Research
from Columbia and Harvard Universities[xi] found that when people were asked to act assertively, they
experienced a biological response consistent with feelings of being powerful. When compared to people
who were asked to act passively, those who felt more powerful took greater risks when given the
opportunity to gamble money.

Leading disruptive innovation involves taking action in the face of uncertainty, seeing results, learning from
them, and modifying assumptions and behaviors based on these results. Even when the results are
“negative,” the goal is to persist in using the insights gained from the experience. Such an approach
creates a sense of progress where positive results can be celebrated and setbacks can be seen as learning
opportunities. This mental model feeds optimism and inspires further action, which results in the type of
optimistic persistence required to weather the tough times.

Seize – Make the journey part of the (surprising)
destination
Canon recently launched the EOS 5D Mark II camera, targeting general photo enthusiasts. But something
surprising happened within months of the launch. Professional videographers started using the point-and-
shoot camera. With video quality equal to more specialized cameras used for television commercials, this
less expensive alternative packed a big punch. To Canon’s own surprise, the Mark II had unexpectedly
started disrupting the high-end professional video market. Canon is now developing cameras specifically
designed for this industry – and disrupting the market in the process.

A whole basket of examples shows how companies begin with one focus and end up succeeding with
another. Wrigley started out selling baking soda and soap. Giving away gum was a perk for customers
who responded with such surprising delight that the company shifted its entire focus to chewing gum.
YouTube began as a dating web site before becoming the de-facto standard for sharing videos on the web.
Hasbro initially sold pencils and school supplies before stumbling upon an independent inventor who sold
the company the rights to Mr. Potato Head.

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The path to disruptive innovation is not always predictable or linear. For example, Jim Collins and Morten
Hansen, authors of Great by Choice, discovered that “luck events” play a significant role in long-term
business success[xii]. Leaders who capitalize on good luck, and who are best prepared for bad luck,
achieve far superior results than their peers. Collins and Hansen’s research shows that leaders need to
find comfort in uncertainty, but also be well prepared to respond to unanticipated events.

Most companies view uncertainty, and especially surprises, as things to prevent and avoid. Even positive
surprises like Canon’s are simply seen as lucky happenstance, far from being connected to real strategy.
The underlying assumption is that predictability and control are the cornerstones of leadership. No wonder
every management book on Amazon with “surprise” in its title is about how to minimize the possibility of
experiencing the dreaded phenomenon.

Leading disruptive innovation, however, is a process fundamentally laden with surprise, the core essence of
uncertainty. Recognizing the potential power of surprise when we receive unexpected jolts to our
strategies, plans, and assumptions, allows us to respond with purposeful agility – versus dismiss surprises
as problems while concurrently disregarding the insights or messages they may contain.

Disruptive innovation requires Disrupting
Leadership
More and more leaders and companies recognize that they must proactively disrupt, or risk being
disrupted. But business-as-usual leadership, where big visions are followed by detailed roadmaps and
action plans, do more than stifle disruptive innovation. They represent liabilities to success. Leading
disruptive innovation involves adopting principles that fall outside the traditional training of managers and
leaders.

New leadership competencies are required to navigate disruption. This means uncovering one’s deeper
motivations to drive meaningful opportunities for others; pushing personal boundaries to challenge one’s
own assumptions; taking steps into the unknown with the view that failure isn’t failure at all but rather a
stepping stone to learning and progress; and tuning into surprises as a kind of portal for gaining new
insights and uncovering opportunities. To lead disruptive innovation successfully requires that we disrupt
the most fundamental mindsets and behaviors that have led us to our current success.

[i] Christensen, C. (2003), The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fall,
Harper Paperbacks, New York.

[ii] Kaplan, S. (2012), Leapfrogging: Harness the Power of Surprise for Business Breakthroughs, Berrett-
Koehler, San Francisco.

[iii] Hamel, Gary & Breen, Bill (2007). The Future of Management, Harvard Business School Press.

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About the Author
Soren Kaplan

Soren Kaplan is a Managing Principal at InnovationPoint LLC, San
Francisco, California. He previously led the innovation group at
Hewlett-Packard, and was a co-founder of iCohere, one of….Read
Soren Kaplan’s full bio

[iv] Kim, W. and Mauborgne, R. (2005), Blue Ocean Strategy, Harvard Business School Press, Boston.

[v] http://www.geekwire.com/2011/amazons-bezos-innovation (accessed June 20, 2012)

[vi] A. Dijksterhuis and L. F. Nordgren, “A Theory of Unconscious Thought,” Perspectives on Psychological
Science 1 (2006): 95–109.

[vii] http://money.cnn.com/galleries/2008/fortune/0803/gallery.jobsqna.fortune/3.html (accessed June 20,
2012)

[viii] Maddux, William & Galinsky, Adam (2009). Cultural Borders and Mental Barriers:

The Relationship Between Living Abroad and Creativity, Journal of Personality and Social Psychology,
Published by the American Psychological Association, Vol. 96, No. 5, 1047–1061

[ix] http://www.inc.com/magazine/20110201/how-great-entrepreneurs-think.html (accessed June 20, 2012)

[x] Kaplan, S. (2012), Leapfrogging: Harness the Power of Surprise for Business Breakthroughs, Berrett-
Koehler, San Francisco.

[xi] D. R. Carney, A. J. C. Cuddy, and A. J. Yap, “Power Posing: Brief Nonverbal Displays Affect
Neuroendocrine Levels and Risk Tolerance,” Psychological Science 21 (2010): 1–6.

[xii] Collins, J. and Hansen, M. (2011), Great by Choice: Uncertainty, Chaos, and Luck—Why Some Thrive
Despite Them All, HarperCollins Publishers, New York.

STOCKS

The Coca-Cola Company: A Short
SWOT Analysis
Kenneth J. DeFranco, Jr. | May 20, 2015

The Coca-Cola Company (KO – Free Coca-Cola Stock Report ) appears set to plod along during its 2015
campaign. In that vein, a stronger U.S. dollar has hindered overall profitability. This year, the company’s
pre-tax profits are likely to decline in the high-single-digit neighborhood, meaning share net may fail to
reach last year’s mark of $2.04. Further, recent volumes indicate the top line will probably remain largely
muted, especially in developed markets, as health-conscious consumers continue to shy away from
beverages containing elevated levels of sugar or artificial sweeteners. Thus, Coca-Cola has taken steps to
address these concerns. In an effort to right the ship, the beverage maker has ramped up its marketing,
advertising, and promotional activities. Although these actions ought to positively impact results, it may take
some time for recent measures to take root.

Investors evaluating a position in Coca-Cola will notice that the equity has mostly been stuck in neutral over
the last couple of years, displaying support around the $37.00 mark and hitting resistance around $44.00.
Despite lacking explosive growth potential for the foreseeable future, this issue maintains many solid
qualities. These shares offer accounts worthwhile risk-adjusted return. Indeed, the stock boasts a dividend
yield above the present Value Line median. In addition, conservative investors should note KO garners our
Highest rank (1) for Safety, which is primarily owed to the company’s strong Financial Strength rating (A++).

Therefore, these factors leave us asking a couple of questions. First, will the company be able to overcome
current top- and bottom-line obstacles? And, is this issue a good pick for the long term? We will address
these issues by performing an easy-to-follow SWOT analysis of the company, evaluating its Strengths,
Weaknesses, Opportunities, and Threats.

The Business

The Coca-Cola Company, founded in Georgia in 1892 and incorporated in 1919, is the world’s largest
beverage company. It owns/licenses and markets more than 500 nonalcoholic beverage brands, primarily
sparkling beverages but also a variety of still beverages such as waters, enhanced waters, juices and juice
drinks, ready-to-drink teas and coffees, and energy and sports drinks. In addition, the business owns and
markets four of the world’s top five nonalcoholic sparkling beverage brands: Coca-Cola, Diet Coke, Fanta
and Sprite. Finished beverage products bearing the company’s trademarks, sold in the United States since
1886, are now sold in more than 200 countries.

Coca-Cola makes its branded beverage products available to consumers throughout the world via a
network of company-owned or -controlled bottling and distribution operations as well as independent
bottling partners, distributors, wholesalers and retailers — the world’s largest beverage distribution system.
Beverages bearing trademarks owned by or licensed to KO account for 1.9 billion of the approximately 57
billion servings of all beverages consumed worldwide every day.

Strengths

Brand Awareness: The Coca-Cola Company is one of the most widely recognized brands across the globe.
Its signature logo, classic red & white colors, and world-famous jingle resonate with consumers of all ages.
There are two key players in this sector of the beverage business, one being Coca-Cola, while the other
remains PepsiCo, Inc. (PEP ). That said, Coca-Cola maintains its position in the top post as the clear-cut
winner. Although both businesses constantly jockey for increased market share, Coca-Cola has the edge
here. The beverage producer also garners a core following customers, as many consumers that deem
themselves fans of its products tend not to shift toward other brands. Going forward, the company’s vast
financial resources ought to fuel its sizable marketing efforts and increased product innovation, which
should propel market-share gains over the long haul.

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Robust Distribution Network: Coca-Cola makes its products available to individuals in more than 200
countries through the world’s largest distribution network. Its ability to utilize company-owned/-controlled
distributors, as well as independent bottlers, wholesalers, and retailers has no parallel. This system enables
KO to closely manage costs, rapidly introduce new items into the marketplace, and saturate various
geographic locations. Moreover, its meaningful network allows for an enhanced level of quality control and
safety for its goods. The stable distribution platform has been a boon for expansion in recent years, as the
company has sought to reach new customers in remote locations. These diverse operations have aided
market presence, volumes, deliveries, and product introductions during a crucial span.

Weaknesses

Water Management: Water is a main ingredient in substantially all of the company’s products. It is vital to
the production of the agricultural ingredients on which the business relies and is needed in KO’s core
manufacturing processes. Also, this resource is critical to the prosperity of the communities Coca-Cola
serves. Water is a limited resource in many parts of the world, facing unprecedented challenges from
overexploitation, as well as rising demand for food and other consumer and industrial products whose
manufacturing processes require water. These events increase the risk of pollution, poor management, and
effects stemming from climate change. As the demand for water continues to climb around the world, and
water becomes scarcer, the overall quality of available water sources may very well deteriorate markedly,
leaving the Coca-Cola system to incur higher costs or face capacity constraints that could adversely affect
its profitability or net operating revenues in the long run.

Foreign Currency Fluctuation: The company earns revenues, pays expenses, owns assets, and incurs
liabilities in countries using currencies other than the U.S. dollar, including the euro, the Japanese yen, the
Brazilian real, and the Mexican peso. In 2014, it used 70 functional currencies in addition to the U.S. dollar
and derived $26.2 billion of net operating revenues from operations outside the United States. Because its
consolidated financial statements are presented in U.S. dollars, Coca-Cola must translate revenues, income
and expenses, as well as assets and liabilities, into U.S. dollars at exchange rates in effect during or at the
end of each reporting period. Therefore, increases or decreases in the value of the U.S. dollar against other
major currencies affect its net operating revenues, operating income, and the value of balance sheet items
denominated in foreign currencies. In addition, unexpected and dramatic devaluations of currencies in
developing or emerging markets could negatively affect the value of the beverage provider’s earnings from,
and of the assets located in, those markets. Weaknesses in some currencies might be offset by strengths in
others over time due to the geographic diversity of the company’s operations. Moreover, KO also employs
derivative financial instruments to further reduce its net exposure to foreign currency exchange rate
fluctuations. However, it cannot fully hedge the impact from fluctuations in foreign currency exchange rates,
particularly the strengthening of the U.S. dollar against major currencies or the currencies of large
developing countries.

Opportunities

Diversification: The company has been hard at work utilizing its ample war chest to build a presence in
rapidly-growing beverage categories. Currently, it owns 16% of Keurig Green Mountain and is developing a
fresh Keurig Kold device that is set to debut this fall. Keurig, famous for pod-based, hot drinks intends to
feature Coke-branded products for its upcoming platform. In addition, Coca-Cola recently finalized its
purchase of a 17% stake in Monster Beverage. The deal provides the company with access to a popular
energy drink growth segment. All told, we anticipate these transactions will bolster the top and bottom lines
immediately. These joint ventures also deliver Coca-Cola with established inroads to a younger customer
base. Looking ahead, KO will probably aim to forge increased relationships with coffee, energy, and health
drink businesses.

Extended Reach: The population continues to increase at a steady clip. In order to capitalize on this fact
and consumers’ shift toward healthier living Coca-Cola has focused on bolstering a variety of its business
lines. Areas such as India and China have ramped up demand for the company’s latest juice and coffee
offerings. Too, developing countries face hefty clean water shortages, which ought to result in surging
demand for the company’s bottled water goods. These business segments have increased at double-digit
rates in the past year, highlighting an elevated need for beverages other than Coca-Cola’s traditional drinks.
We believe Coca-Cola remains dedicated to differentiating its portfolio and delivering emerging markets
with various beverage staples over the long term.

Threats

Nutritious Selections: It’s been no secret that soft drink providers have suffered some of late. A cultural shift
toward natural and organic products has led many to opt for nutritional waters, smoothies, and various
healthy beverage options. Thus, core soda offerings that include high amounts of sugar, or diet items with
artificial sweeteners, have fallen out of favor with buyers. What’s more, this trend does not seem likely to
abate, as consumers continue to boost their knowledge of proper dietary requirements and exercise
programs. Further, many health professionals have called for the elimination of foods and beverages
containing lofty amounts of sugar, since these products place individuals at an elevated risk of becoming
obese, developing diabetes, and suffering from heart disease. Also, a negative perception of these
beverages has surged due to federal regulators’ desire to place excess taxes on sodas and sugary soft
drinks.

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Indirect Competition: Although companies such as Starbucks (SBUX ) and Dunkin’ Brands Group
(DNKN ) do not compete directly with Coca-Cola, these businesses do place a dent in the company’s
market share. The chains offer customers healthier alternatives, unique choices, and customer loyalty
rewards that are not easily matched by Coca-Cola. In addition, smaller franchises and retail chains provide
patrons with private-label substitutes for traditional Coke products, which allows these businesses to deliver
beverages at a lower price. Industry data suggest potential customers will continue to be pulled away from
basic drink selections in favor of customizable options that carry a greater nutritional benefit.

Conclusion

While the number of challenges facing Coca-Cola are abundant, this company does possess a good deal of
promise for the future. Its overall size, leverage, and financial resources have it well positioned to take
advantage of worthwhile acquisition targets. Too, the company’s brand appeal and cult-like following insure
that it will probably remain a top-tier beverage provider going forward. Coca-Cola’s vast distribution network
should enable better volumes ahead and success in burgeoning markets. All told, conservative investors
wanting a reliable source of income and a bit of capital gains exposure might want to give The Coca-Cola
Company a glance.

At the time of this article’s writing, the author did not have positions in any of the companies mentioned.

© 2021 Value Line, Inc. All Rights Reserved

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Making Decisions n a Constantly Innovative Environment

Technology and Decisions

Innovation

Knowledge Management

Big Data and Data-Driven Decisions

SWOT Analysis

References

Week 4: Decision Making and Problem Solving

Lesson 1 of 6

Technology and Decisions

Innovation distinguishes between a leader and a follower

Steve Jobs

Skill #4: Collect knowledge and information about current events,
technology, the business environment, the client’s business, your company
and consider these when making decisions.

Technology has brought and will bring enormous amounts of information for the manager to

consider when making business decisions. This has two main challenges for managers:

1. The �rst is maintaining sustainability in a technologically disruptive
environment.

2. The second is managing knowledge for better decision making. 

Managers today must look ahead and stay informed of new innovation to be sure that their

business can stay competitive. They must know what is important to the stakeholders in

every decision they make and the problem they solve now and �ve years from now.

Developing expertise or hiring people whose expertise you can rely upon is crucial to staying

alive.  Innovation, the true core leadership challenge for staying competitive, will have at its

heart the need for technology.  In a recent Forbes article, Liz Ryan pointed out ten skills every

manager must know. She makes the point that every manager must understand how their

role �ts into the company and how their business competes in its marketplace. Thee ten

skills are as follows:

Every manager needs to be able to ask for and take in feedback from their

employees — without becoming defensive.
1

Every manager must develop the ability to take an employee’s perspective and see

things from the employee’s point of view. 
2

Every manager needs to understand how his or her function �ts into the overall

organization and how their business competes in its marketplace. 
3

Every manager needs to learn self-re�ection. They need to notice their own fear

reactions — for example, when their boss is upset with them or when they are

upset with one of their employees.

4

Every manager needs to know how to acknowledge and reinforce employees –

and how to avoid bashing and criticizing them when they make a mistake.
5

Every manager needs to learn to stand up for their teammates when a higher-up

manager gives an order that isn’t feasible or achievable.
6

Every manager needs to learn to manage his or her own career, completely apart

from managing their department.
7

Every manager needs to learn to communicate with people of di�erent ages,

ethnic backgrounds, religions, political stripes and personality types and must

learn to be open to a wide range of perspectives.

8

Every leader must learn how to build trust and community at work. Without trust,

a department can’t function the way it should.
9

Finally, every manager must learn to be human at work, especially when

conditions are ripe for fear-based management tactics to creep in.
10

All too often a manager knows their department but not how it works with others in the

company, customers and industry. Managers too often fail to look at current events or new

technology until it is too late!  Making decisions requires the perspective of the present and

knowledgeable guess at the future. Understanding the consequences an alternative may have

on the future can only be had if many factors about the decision are looked at by the

decision-maker. In fact, as was pointed out in week two our survey on managers points out

that 77.8% of the respondents felt that considering many factors in decision making through

the use of a structured process was one of the most important skills a manager can have

(Moss, 2018).

Lesson 2 of 6

Innovation

Innovation is moving at a scarily fast pace.

Bill Gates

According to Investopedia.com, “Disruptive Innovation refers to a technology whose

application signi�cantly a�ects the way a market or industry functions. An example of

modern disruptive innovation is the Internet, which signi�cantly altered the way companies

did business and which negatively impacted companies that were unwilling to adapt to it.”

Read Kaplan’s (2012) article where he discussed the LEAPS method for driving disruption in

business, which includes the following process:

Listen – Start with yourself, not the market

Explore – Go outside to stretch the inside

Act – Take small simple steps over and over

Persist – Take the surprise out of failure

Seize – Make the journey part of the destination

In 2016, a World Economic Forum report predicted that more than

7 million jobs would be lost due to technological advances  – more

than �ve million of those by 2020. Read about this prediction here.

Did this actually happen? Do some research and �nd out!

According to Merriam Webster, Arti�cial Intelligence is,
“a branch of computer science dealing with the
simulation of intelligent behavior in computers, or the
capability of a machine to imitate intelligent human
behavior.”

In 2018, the Society for Human Resources Managers predicted how AI may
change how leaders inspire, manage, and engage a new workforce. Click
below for more on these predictions.

Focus on Value through Experimentation –

Value will emerge through experimentation

Many projects will fail, but lessons learned will be valuable

Managers should allow teams to be creative, curious, and innovative

Diversity to Create Collaboration and Broader Perspective –

Teams need to be diverse in background, gender, race, and nationality

Academic and disciplinary diversity is also important

Avoid homogenous project teams

Change to Align and Engage –

Become data driven as a culture change in the organization

Change the way people interact and communicate

Engage all employees

Reskilling Talent –

Understand employees’ skills and where gaps may be

Facility skills training 

transform jobs and rede�ne work and create a team concept to create e�ciencies

Empower Decision-making –

Empower teams to make decisions

Give authority at lower levels

AI as your Coach and Advisor –

Create a new approach to leadership development

Jared Lindzon (2017) talked about the way that AI is also changing the way that companies are

organized. Take a few minutes to read through his article. How does this article relate to the

article above? Did you see any similarities?

Lesson 3 of 6

Knowledge Management

Skill #5: Know the basics of knowledge management and use this knowledge
when considering collecting information when making a decision. 

How do you manage all the data that technology brings to a company?  Think about your own

life.  Like many people, you may have several e-mail accounts, two or three devices that

clutter your wall sockets; computers on your desk or in your pocketbook; and a growing

number of social media accounts, apps or chats. You have information coming at you from all

directions and you are just one person.  So, what must it be like leading a business?  Aside

from individual data management issues, a business has multiple uses for data collection not

the least of which is decision making.   Hence, a business must �nd ways to collect data,

store it, and evaluate it for e�cacy in decision making. This skill set is commonly known as

knowledge management and it is a skill set with which managers should have a working

familiarity. 

Click here to learn a bit more about the Basics of Knowledge Management.

An organization’s strategy and its knowledge management need to be in alignment. It is

important that there is a strong �t between the two in order to have success. Watch the video

below to learn more about how knowledge management can drive enterprise strategy.

How knowledge management drives enterprise strategy

How knowledge management drives enterprise strategy

In this article, the authors discuss several facets of Knowledge Management, including four

kinds of process that are closely related, including:

Knowledge Representation – the process of identifying, preparing, documenting

and actualizing knowledge

Knowledge Communication – combining processes that concern the distribution

of information and knowledge, mediation of knowledge, knowledge sharing, co-

construction of knowledge, and knowledge-based cooperation

Use of Knowledge – Transformation of knowledge to goods and services

Development of Knowledge – external knowledge procurement, creating

knowledge resources, like research and development, and forming knowledge

networks.

the article also discusses critical success factors for implementing knowledge management

within the organization, including:

Corporate Culture

Employee Quali�cations

Learning Culture

Management Support

Integration of Knowledge Processes to Organization’s Processes

New Information and Communication Technologies

Lesson 4 of 6

Big Data and Data-Driven Decisions

According to Merriam-Webster, Big Data is “an accumulation of

data that is too large and complex for processing by traditional

database management tools. Did you know that the �rst known

use of “Big Data” was in 1996?

Big Data and Competitive Advantage

According to a 2012 article from McGuire et al, there are �ve ways to leverage big data in an

organization:

Big Data can unlock signi�cant value by making information transparent. 1

As organizations create and store more transactional data in digital form, they can

collect more accurate and detailed performance information on everything from

product inventories to sick days and therefore expose variability and boost

performance.

2

Big Data allows ever-narrower segmentation of customers and therefore much

more precisely tailored products or services. 
3

Sophisticated analytics can substantially improve decision-making, minimize

risks, and unearth valuable insights that would otherwise remain hidden. 
4

Big Data can be used to develop the next generation of products and services.5

In that same article, the author provided �ve questions that executives can re�ect on to help

recognize how big data could upend assumptions behind their strategies and speed up the

scope of change underway.

What happens in a world of radical transparency, with data widely available?1

If you could test all of your decisions, how would that change the way you

compete?
2

How would your business change if you used Big Data for widespread, real-time

customization?
3

How can Big Data augment or even replace management?4

Could you create a new business model based on data?5

Make sure that you read the complete article for the rest of the important information

concerning Big Data and competitive advantage, as there is a great deal of excellent

information.

Marr (2016) came up with 10 steps for data-driving decision making in business. Click on the

numbers below to review each of the steps, and review the entire article as well for more

information on each of these items.

         

Start with Strategy

Hone in on the business area

Identify your unanswered business questions

Find the data to answer your questions

Identify what data you already have

Work out if the costs and effort are justi�ed

Collect the data

Analyze the data

Present and distribute the insights

Incorporate the learning into the business

According to one article, there are many purposes, characteristics, bene�ts, and limitations to

data mining. Review the information below, and then read the entire article for more in-depth

information.

Processes which Include Data Mining –

Data Integration

Data Cleaning

Data Transformation

Pattern Evaluation

Data Presentation

Uses for Information Acquired in Data Mining –

1. Market Analysis

2. Production Control

3. Customer Retention

4. Science Exploration

5. Fraud Detection

6. Sports

7. Astrology

8. Internet Web Surf-Aid

What can Data Mining Do? –

Help to identify shopping patterns

Increase website optimization

Bene�cial for marketing campaigns

Determine customer groups

Help measure pro�tability factors

Increase brand loyalty

Purpose of Data Mining –

Increase customer loyalty

Identify hidden pro�tability

Minimize client involvement

Customer satisfaction

Characteristics of Data Mining –

1. Increased quantities of data

2. Provide incomplete data

3. Complicated data structure

Data Mining Applications –

1. Market Analysis and Management

a. Customer Pro�ling

b. Finding customer requirements

c. Cross-market analysis

d. Target marketing

e. Determining customer purchasing pattern

f. Provides summary information

2. Corporate Analysis and Risk Management

a. Finance Planning

b. Asset Evaluation

c. Resource Planning

d. Competition

3. Fraud Detection

Bene�ts of Data Mining Techniques –

It is helpful to predict future trends

It signi�es customer habits

Helps in decision making

Increase company revenue

It depends upon market-based analysis

Quick fraud detection

Limitations of Data Mining Techniques –

1. It violates user privacy

2. Additional irrelevant information

3. Misuse of information

4. Accuracy of data

Lesson 5 of 6

SWOT Analysis

It is important in a business setting that you fully understand what a SWOT analysis is and

how to apply one e�ectively. SWOT stands for Strengths, Weaknesses, Opportunities, and

Threats. Strengths and Weaknesses are factors that are internal to the organization whereas

Opportunities and Threats are external factors. Let’s take a look below in more detail about

SWOT and how it is applied in business.

This article discusses how to do a SWOT analysis, so please read through it carefully. It also

provides a video (below) and a matrix that allows you to create a SWOT on your own. You may

want to keep the matrix for future use.

YO U TU B E

How to Use SWOT Analysis

How to Use SWOT Analysis

To learn more about SWOT and download the free worksheet, see our article

at: https://www.mindtools.com/swot?

utm_source=youtube&utm_medium=video&utm_campaign…

V I E W O N YO U TU B E 

Please review this Coca Cola Case Study of a SWOT Analysis

so you can see an example of a SWOT analysis applied. Did

you understand the internal Strengths and Weaknesses as

well as the external Opportunities and Threats?

Lesson 6 of 6

References

Anonymous (2014).  How knowledge management drives enterprise strategy.

https://www.youtube.com/watch?v=SvEcTEB9ajQ
1

Anonymous (n.d). Knowledge management.

https://education.stateuniversity.com/pages/2149/Knowledge-Management.html
2

Lindzon, J. (2017). How AI is changing the way companies are organized.

https://www.fastcompany.com/3068492/how-ai-is-changing-the-way-

companies-are-organized

3

Loyola, R. Leading in the age of AI and automation.

https://blog.hrps.org/blogpost/Leading-in-the-Age-of-AI-and-Automation
4

Marr, B. (2016). Data-driven decision making: 10 simple steps for any business.

https://www.forbes.com/sites/bernardmarr/2016/06/14/data-driven-decision-

making-10-simple-steps-for-any-business/?sh=1811cd4d5e1e

5

McGuire et al (2012). Why big data is the new competitive advantage.

https://iveybusinessjournal.com/publication/why-big-data-is-the-new-

competitive-advantage/

6

Mina, A. (2016). Technology will erase 5 million jobs.

https://www.usnews.com/news/best-countries/articles/2016-01-20/technology-

will-erase-5-million-jobs

7

Module 1 readings: Knowledge management basics: Concepts, objects, principles

and expectations. https://learn.umgc.edu/content/enforced/524378-001146-01-

2208-OL3-7382/Knowledge%20Management%20Basics.pdf

8

Reddy, C. (n.d.) Data mining: purpose, characteristics, bene�ts & limitations.

https://content.wisestep.com/data-mining-purpose-characteristics-bene�ts-

limitations/

9

Soren, K. (2012). Leading disruptive Innovation.

https://iveybusinessjournal.com/publication/leading-disruptive-innovation/
10

SWOT Analysis (n.d.).

https://www.mindtools.com/pages/article/newTMC_05.htm
11