Discussion 13
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© 2016 John Wiley & Sons, Inc.
Chapter 12 Knowledge Management, Business Intelligence, and Analytics
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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.
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Data from 33 million people provided strong evidence that the British version was very popular and Kevin Spacey was also a popular actor
Again, data from millions of users, showing what they watch, when they pause, when they rewind, etc. Patterns emerge that speak volumes about preferences. Their analytics algorithms provide better data than focus groups (and in real time).
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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.
© 2016 John Wiley & Sons, Inc.
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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.
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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
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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Data, Information, and Knowledge (reprise)
© 2016 John Wiley & Sons, Inc.
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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.
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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
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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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 |
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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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)
© 2016 John Wiley & Sons, Inc.
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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?”
© 2016 John Wiley & Sons, Inc.
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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)
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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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.
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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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.
© 2016 John Wiley & Sons, Inc.
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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)
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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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
© 2016 John Wiley & Sons, Inc.
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Summary
After you have listened to this lecture and read Chapter 12 of your text
Go to Discussion Board 13 and answer the discussion prompt
Finally complete Quiz 12
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© 2016 John Wiley & Sons, Inc.
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