Wiki

Managing and Using Information Systems: A Strategic Approach – Sixth Edition

Keri Pearlson, Carol Saunders, and Dennis Galletta

© Copyright 2016 John Wiley & Sons, Inc.

Chapter 12 Knowledge Management, Business

Intelligence, and Analytics

Opening Case: Netflix

• What gave Netflix assurance that House of Cards would be a success?

• What gives Netflix a competitive advantage?

© 2016 John Wiley & Sons, Inc. 3

More Real World Examples

• Caesar’s and Capital One both collect and analyze customer data.

• Result: They can determine who are the most profitable customers and then follow up with them. • Caesar’s: frequent gamblers • Capital One: charge a lot and pay off slowly

• They provide products that would appeal to the profitable customers.

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A Real World Example from Sports

• Oakland As and Boston Red Sox baseball teams • Crunched the numbers on the potential players, such

as on-base percentage • Others who did not do the analysis failed to recognize

the talent

© 2016 John Wiley & Sons, Inc. 5

Five Ways Data Analytics can Help an Organization (McKinsey and Co.)

• Making data more transparent and usable more quickly

• Exposing variability and boosting performance • Tailoring products and services • Improving decision-making • Improving products

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Terminology

• Knowledge management: The processes needed to generate, capture, codify and transfer knowledge across the organization to achieve competitive advantage

• Business intelligence: The set of technologies and processes that use data to understand and analyze business performance

• Business analytics: The use of quantitative and predictive models, algorithms, and evidence-based management to drive decisions

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Data, Information, and Knowledge (reprise)

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The Value of Managing Knowledge Value Sources of Value

Sharing best practices • Avoid reinventing the wheel • Build on valuable work and expertise

Sustainable competitive advantage • Shorten innovation life cycle • Promote long term results and returns

Managing overload • Filter data to find relevant knowledge • Organize and store for easy retrieval

Rapid change • Build on/customize previous work for agility • Streamline and build dynamic processes • Quick response to changes

Embedded knowledge from products

• Smart products can gather information • Blur distinction between manufacturing/service • Add value to products

Globalization • Decrease cycle times by sharing knowledge globally • Manage global competitive pressures • Adapt to local conditions

Insurance for downsizing • Protect against loss of knowledge when departures occur • Provide portability for workers who change roles • Reduce time to acquire knowledge © 2016 John Wiley & Sons, Inc. 9

Dimensions of Knowledge

Explicit  Teachable  Articulable  Observable in use  Scripted  Simple  Documented

Tacit  Not teachable  Not articulable  Not observable  Rich  Complex  Undocumented

Examples: • Estimating work • Deciding best action

Examples: • Explicit steps • Procedure manuals

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Four Modes of Knowledge Conversion (and examples)

Transferring by mentoring, apprenticeship

Transferring by models, metaphors

Learning by doing; studying manuals

Obtaining and following manuals

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Knowledge Management – Four Processes

• Generate – discover “new” knowledge • Capture – scan, organize, and package it • Codify – represent it for easy access and transfer

(even as simple as using hash tags to create a folksonomy)

• Transfer – transmit it from one person to another to absorb it

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Measures of KM Project Success

• Example of specific benefits of a KM project: • Enhanced effectiveness • Revenue generated from extant knowledge assets • Increased value of extant products and services • Increased organizational adaptability • More efficient re-use of knowledge assets • Reduced costs • Reduced cycle time

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Components of Business Analytics

Component Definition Example Data Sources Data streams and repositories Data warehouses; weather data Software Tools Applications and processes for

statistical analysis, forecasting, predictive modeling, and optimization

Data mining process; forecasting software package

Data-Driven Environment

Organizational environment that creates and sustains the use of analytics tools

Reward system that encourages the use of the analytics tools; willingness to test or experiment

Skilled Workforce Workforce that has the training, experience, and capability to use the analytics tools

Data scientists, chief data officers, chief analytics officers, analysts, etc. Netflix, Caesars and Capital One have these skills

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Data Sources for Analytics

• Structured (customers, weather patterns) or unstructured (Tweets, YouTube videos)

• Internal or external • Data warehouses full of a variety of information • Real-time information such as stock market prices

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Data Mining • Combing through massive amounts of customer data,

usually focused on: • Buying patterns/habits (for cross-selling) • Preferences (to help identify new products/

features/enhancements to products) • Unusual purchases (spotting theft)

• It also identifies previously unknown relationships among data.

• Complex statistics can uncover clusters on many dimensions not known previously • (e.g., People who like movie x also like movie y)

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Four Categories of Data Mining Tools

• Statistical analysis: Answers questions such as “Why is this happening?”

• Forecasting/Extrapolation: Answers questions such as “What if these trends continue?”

• Predictive modeling: Answers questions such as “What will happen next?”

• Optimization: Answers questions such as “What is the best that can happen?”

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How to be Successful

• Achieve a data driven culture • Develop skills for data mining • Use a Chief Analytics Officer (CAO) or Chief Data

Officer (CDO) • Shoot for high maturity level (see next slide)

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Level Description Source of Business Value

1 – Reporting What happened?

Reduce costs of summarizing, printing

2 – Analyzing Why did it happen?

Understanding root causes

3 – Describing What is happening now

Real-time understanding & corrective action

4 – Predicting What will happen?

Can take best action

5 – Prescribing How should we respond?

Dynamic correction

Five Maturity Levels of Analytical Capabilities

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BI and Competitive Advantage

• There is a very large amount of data in databases. • Big data: techniques and technologies that make it

economical to deal with very large datasets at the extreme end of the scale: e.g., 1021 data items • Large datasets can uncover potential trends and causal

issues • Specialized computers and tools are needed to mine

the data. • Big data emerged because of the rich, unstructured

data streams that are created by social IT.

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Practical Example • Asthma outbreaks can be predicted by U. of Arizona

researchers with 70% accuracy • They examine tweets and Google searches for words

and phrases like • “wheezing” “sneezing” “inhaler” “can’t breathe” • Relatively rare words (1% of tweets) but 15,000/day

• They examine the context of the words: • “It was so romantic I couldn’t catch my breath” vs • “After a run I couldn’t catch my breath”

• Helps hospitals make work scheduling decisions

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Sentiment Analysis

• Can analyze tweets and Facebook likes for • Real-time customer reactions to products • Spotting trends in reactions

• Useful for politicians, advertisers, software versions, sales opportunities

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Google Analytics and Salesforce.com • Listening to the community: Identifying and monitoring all

conversations in the social Web on a particular topic or brand. • Learning who is in the community: Identifying demographics such

as age, gender, location, and other trends to foster closer relationships.

• Engaging people in the community: Communicating directly with customers on social platforms such as Facebook, YouTube, LinkedIn, and Twitter using a single app.

• Tracking what is being said: Measuring and tracking demographics, conversations, sentiment, status, and customer voice using a dashboard and other reporting tools.

• Building an audience: Using algorithms to analyze data from internal and external sources to understand customer attributes, behaviors, and profiles, then to find new similar customers

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Google Analytics

• Web site testing and optimizing: Understanding traffic to Web sites and optimizing a site’s content and design for increasing traffic.

• Search optimization: Understanding how Google sees an organization’s Web site, how other sites link to it, and how specific search queries drive traffic to it.

• Search term interest and insights: Understanding interests in particular search terms globally, as well as regionally, top searches for similar terms, and popularity over time.

• Advertising support and management: Identifying the best ways to spend advertising resources for online media.

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Internet of Things (IoT)

• Much big data comes from IoT • Sensor data in products can allow the products to:

• Call for service (elevators, heart monitors) • Parallel park, identify location/speed (cars) • Alert you to the age of food (refrigerator) • Waters the lawn when soil is dry (sprinklers) • Self-driving cars find best route (Google)

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Intellectual Capital vs Intellectual Property

• Intellectual Capital: the process for managing knowledge

• Intellectual Property: the outputs; the desired product for the process

• Intellectual Property rights differ remarkably by country

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Closing Caveats

• These are emerging concepts and disciplines • Sometimes knowledge should remain hidden

(tacit) for protection • We should remain focused on future events,

not just look over the past • A supportive culture is needed in a firm to

enable effective KM and BI

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Chapter 13 Privacy and Ethical Considerations

in Managing Information

Three Breaches: TJX, Target, Home Depot

• TJX Co: largest security breach of its computer system in the history of retailing: 90 million customer records were stolen

• Target: 40 million; Home Depot: 56 million • All had to decide between notifying their customers

immediately, or waiting the 45 days allowed by the jurisdictions.

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Outcomes

• Target: • Stock fell 9% a few days after disclosure • Profits fell 46% in the following quarter

• TJX: • Stock fell 8%

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Cybersecurity Bill, 18 Dec, 2014

• Supports R&D to develop best practices • Supports education in the area • Prepares the workforce • Federal agencies need a cybersecurity plan:

• Guarantee individual privacy, verify software and hardware, address insider threats

• Determine the origin of messages • Protect cloud information and data transmission

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Normative Theories of Business Ethics

• Managers must assess initiatives from an ethical point of view

• Most managers are not trained in ethics, philosophy, and moral reasoning • Difficult to determine or discuss social norms

• Three theories of business ethics are useful for assessing an initiative

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Figure 12.1 Three normative theories of business ethics.

Theory Definition Metrics Stockholder Maximize stockholder

wealth in legal and non- fraudulent manners.

Will this action maximize stockholder value? Can goals be accomplished without compromising company standards and without breaking laws?

Stakeholder Maximize benefits to all stakeholders while weighing costs to competing interests.

Does the proposed action maximize collective benefits to the company? Does this action treat one of the corporate stakeholders unfairly?

Social contract Create value for society in a manner that is just and nondiscriminatory.

Does this action create a “net” benefit for society? Does the proposed action discriminate against any group in particular, and is its implementation socially just?

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Stockholder Theory

• Stockholders advance capital to corporate managers who act as agents in advancing their ends.

• Managers are bound to the interests of the shareholders (maximize shareholder value).

• Manager’s duties: • Bound to employ legal, non-fraudulent means. • Must take long view of shareholder interest.

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Stakeholder Theory

• Stakeholders are: • Any group that vitally affects corporate survival and

success. • Any group whose interests the corporation vitally

affects. • Management must balance the rights of all

stakeholders without impinging upon the rights of any one particular stakeholder

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Social Contract Theory

• Corporations are expected to create more value to society that it consumes.

• Social contract: • 1. Social welfare – corporations must produce greater

benefits than their associated costs. • 2. Justice – corporations must pursue profits legally,

without fraud or deception, and avoid actions that harm society.

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The Three Normative Theories

• How do they apply to TJX, Target, Home Depot? • What are the advantages of notifying customers

early? • What are the advantages of waiting as long as

legally permitted? • What are the advantages of finding a way to avoid

notifying customers?

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Big Data

• Can guess income from zip code • Therefore, can identify targets from zip codes • Should you pass up the opportunity to alert

potential customers of your products? • If not, your competitors will get there first!

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Interesting Outcomes

• Pregnant daughter – Target knew and accidentally alerted her dad. How?

• Buying habits were shared by other pregnant women: • Unscented soap • Cotton balls • Vitamins

• How did Target reveal this to the dad? • Target sent her some ads for diapers and

maternity clothes

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New Study in Science

• Take a file from a credit card agency, with disguised credit card numbers: 1.1 million records

• 90% of the identities can be found by connecting three things

• Information easily found on Instagram, Facebook, FourSquare

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Ethical Tensions with Governments

• UAE tried to require RIM to disclose confidential information for national security

• Sony Pictures had a project ruined by North Korean threats

• Google’s features are restricted in China

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Mason’s areas of managerial concern “PAPA”

Area Critical Questions

Privacy What information must a person reveal about one’s self to others? What information should others be able to access about you – with or without your permission? What safeguards exist for your protection?

Accuracy Who is responsible for the reliability and accuracy of information? Who will be accountable for errors?

Property Who owns information? Who owns the channels of distribution, and how should they be regulated?

Accessibility What information does a person or an organization have a right to obtain, under what conditions, and with what safeguards?

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Privacy

• The right to be left alone • Possessing and using the “best” information helps

an organization win • High priority: Keeping it safe and secure • Regulations cover the authorized collection,

disclosure and use of personal information • But is it clear enough?

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Privacy Paradox

• Convenience vs privacy • Make it harder for criminals to steal information, it

will be less convenient for genuine users • 15,000 customers in 15 countries:

• Overall, 51% said they wouldn’t trade off privacy for convenience; 27% said they would.

• India: 40% wouldn’t; 48% would • Germany: 70% wouldn’t; 12% would

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What about Actual Behavior? • Teens repeatedly demonstrate a lack of concern about

privacy • Often they regret their decisions • 70% of recruiters have rejected candidates for postings

they found online • But only 20% strengthened their privacy settings when

Facebook began allowing it • Privacy is valued more in Europe than in the US

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Software or Site Terms of Service

• Ignored widely, often due to length and legal language

• Pen Pal’s Terms of Service are longer than Hamlet • Fewer than 2% read the terms • A UK site included selling a person’s immortal soul

and thousands accepted it.

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Cookies

• Can access only the cookie it created! • So what’s the concern? • Easy. Have a third party place content on your

page • Widespread practice: DoubleClick has content on

thousands of sites • But back to convenience: Without cookies, you

could not have a “shopping cart”

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Accuracy

• Controls are needed to ensure accuracy • Data entry errors must be controlled and managed

carefully • Data must also be kept up to date • Removing data after needed or when legally

mandated is not easy

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Bank of America Example

• What did Bank of America do to the couple near Christmas?

• Just from checking out refinancing rates, appearance of risk rose

• B of A admitted error but neglected to report this to credit agencies

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Property

• Mass quantities of data are stored • Who owns the data? • Who has rights to it? • Who owns the images that are posted in cyberspace?

Photographer? Subject? Facebook? • Proper ownership implies legal rights but duties too

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Accessibility

• Access to systems and their data is paramount • Users must be able to access this data from any

location (if legal and it can be properly secured) • Major issue – how to create and maintain access to

information for society at large • This access needs to be limited to those who have a

right to see and use it (to limit identity theft). • Also, adequate security measures must be in place on

their business partners’ end.

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What Should a Manager Do?

• Create a culture of responsibility • Post policies

• Implement governance processes for information control

• Avoid decoupling responsibility • i.e., make Managers responsible for their decisions

that lead to privacy problems

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Green Computing

• The digital economy uses 10% of the world’s energy

• In 2007, the 5 largest search companies used 2.4 gigawatts. • Hoover Dam only generates 2.0

• Since then it has reduced thanks to “green” efforts in data centers • Virtualization • Relocation for more natural cooling

• e.g., Google in Finland

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Triple Bottom Line Impact

• TBL (3BL) • People: Being socially responsible • Planet: Saving the environment • Profit: Saving money

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That’s a wrap!

Dr. Les Stovall [email protected]

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