Learn More About Predictive Analytics and SAPAdditional information    SAP.com/PredictiveAnalytics    Or email us @ Predic...
Predictive Analytics: Gaining Advantage                                            by Using Analytics to Predict the Futur...
Predictive                                                                                              Analytics at Work ...
Types of Analytics                                                                                                     Tim...
Levels of Analytical Capability                                                                                   Stage 5 ...
The Analytical DELTA                                                     Data . . . . . . . . . . breadth, integration, qu...
New Metrics / Data                                               Wine Chemistry                 Defensive moves          S...
The Changing World of Analytics                                                                                           ...
Linking Data and Decisions                                                                                                ...
Enterprise                                                                           If you’re competing on analytics, it ...
Leadership                                                                          CEOs—Google, Netflix, Capital One     ...
Are You Ready for Prediction/Optimization?                                                                                ...
Roles for IT and CIOs in All This                                                                            Restructure t...
Questions?                                              To ask a question … click on the “question icon” in               ...
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Davenport Webinar Predictive Analytics

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HBR webinar with Tom Davenport discussing Analytics, SAP involvement as well.

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Davenport Webinar Predictive Analytics

  1. 1. Learn More About Predictive Analytics and SAPAdditional information SAP.com/PredictiveAnalytics Or email us @ PredictiveAnalytics@sap.comOnline community & discussion board “SAP Predictive Analytics”Upcoming webinars Run Better with Predict Analytics & In-Memory Technology Dr. David Ginsberg – December 6th, 2011 SAP Webcast Series: Unwire Your Enterprise Discuss the importance and growth of mobile technology and to explore how your organization can leverage powerful mobility solutions to capitalize on the immense rewards offered by developing and executing against a comprehensive mobility strategy.© 2011 SAP AG. All rights reserved. 1
  2. 2. Predictive Analytics: Gaining Advantage by Using Analytics to Predict the Future Tom Davenport President’s Distinguished Professor of Management and Information Technology Babson College October 3, 2011 Brought to you by Questions? To ask a question … click on the “question icon” in the upper-left corner of your screen. Type your question and name, and additional information if you wish, and click on the send button. Brought to you by 1Copyright © 2011, SAS Institute Inc. All rights reserved.
  3. 3. Predictive Analytics at Work Tom Davenport Babson College Harvard Business Review Webcast October 3, 2011 What Are Analytics? Optimization “What’s the best that can happen?” Predictive Modeling/ “What will happen next?” Predictive and Forecasting Prescriptive Randomized Testing “What happens if we try this?” Analytics Degree Statistical analysis “Why is this happening?” (the “so what”) of Intelligence Alerts “What actions are needed?” Query/drill down “What exactly is the problem?” Descriptive Analytics Ad hoc reports “How many, how often, where?” (the “what”) Standard Reports “What happened?” 4 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics 2Copyright © 2011, SAS Institute Inc. All rights reserved.
  4. 4. Types of Analytics Timeframe Past Present Future Information What is happening What happened? What will happen? now? (Reporting) (Prediction) Content Type (Alerts) What’s the best How and why did It What’s the next best that can happen? Insight happen? action? (Optimization/simulatio (Modeling, testing) (Recommendation) n) 5 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics Applications of Predictive Analytics What offers will customers accept? What price will they pay? Which recruit will become a high performer? How likely is it that this customer will leave? Which supplier is most likely to fail to deliver? 6 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics 3Copyright © 2011, SAS Institute Inc. All rights reserved.
  5. 5. Levels of Analytical Capability Stage 5 Analytical Competitors Stage 4 Analytical Companies Stage 3 Analytical Aspirations Stage 2 Localized Analytics Stage 1 Analytically Impaired Thomas H. Davenport – Predictive Analytics 7 Masters of Prediction Marriott — optimal pricing Nextel—customer attrition Cisco—forecasting Tesco—offers eBay—web site testing Netflix—movies you’ll like Zappos—shoes you’ll like Google—page rank, advertising, HR 8 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics 4Copyright © 2011, SAS Institute Inc. All rights reserved.
  6. 6. The Analytical DELTA Data . . . . . . . . . . breadth, integration, quality, technology Enterprise . . . . . . . . . .approach to managing analytics Leadership . . . . . . . . . . . . . . . passion and commitment Targets . . . . . . . . . . . . . first deep, then broad Analysts . . . . . professionals and amateurs 9 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics Data The prerequisite for everything analytical Clean, common, integrated Accessible in a warehouse Measuring something new and important 10 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics 5Copyright © 2011, SAS Institute Inc. All rights reserved.
  7. 7. New Metrics / Data Wine Chemistry Defensive moves Smile Frequency 11 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics Some Current Data and Technology Dilemmas Analytics on premise, private cloud, public cloud? Different tools for “big data”? Is a data warehouse still necessary? Will “analytical apps” take off? How can analytics be embedded? 12 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics 6Copyright © 2011, SAS Institute Inc. All rights reserved.
  8. 8. The Changing World of Analytics Analyst Multi- Old BI Sandbox Purpose Application Breadth Single- Analytical Embedded Purpose Apps Analytics Business Professional Users Analysts Primary Users 13 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics Some Actual Analytical Apps Spend analysis in life sciences Aftermarket services revenue growth for equipment manufacturers Analyzing mortgage portfolios Financial planning and modeling in the public sector Enterprise risk and solvency management for insurance Contract compliance in transportation Nursing productivity in health care Field sales hiring analysis in pharma Employee attrition analysis in telecom Employee satisfaction and store performance analysis in retail 14 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics 7Copyright © 2011, SAS Institute Inc. All rights reserved.
  9. 9. Linking Data and Decisions Thomas H. Davenport – Predictive Analytics Embedding Analytics in Processes Defection Risk Creation Purchase Order “What is the customer status?” Creation Request Global ATP Inventory Forecast Sales Order “Will this be back in inventory?” Global ATP Check Fulfillment Request Creation & Release Delivery Request Returns per Customer “What is the customer history?” CLTV “Does this order justify extra Delivery Execution efforts?” Update Update Releases ASN Inventory Inventory Accounting Delivery Performance Receives ASN “How effective is our fulfillment process?” Source: SAP AG 2006 16 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics 8Copyright © 2011, SAS Institute Inc. All rights reserved.
  10. 10. Enterprise If you’re competing on analytics, it doesn’t make sense to manage them locally No fiefdoms of data, technology, or organization A centralized organization or CoE is increasingly common P&G, Caesars, Walmart, etc. 17 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics Under Enterprise Management = Predictive + + HR analytics Actuarial + Enterprise Analytics! Web analytics + Marketing + Supply chain/OR Thomas H. Davenport – Predictive Analytics 9Copyright © 2011, SAS Institute Inc. All rights reserved.
  11. 11. Leadership CEOs—Google, Netflix, Capital One CFOs—Caesars, Humana CIOs—P&G, Schneider COOs—Ebay, Chicos 19 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics The Best Targets… Support a key strategic capability Engage top management commitment Create momentum for analytics across the enterprise Have ambitious, yet pragmatic scope Are data rich — or have the potential to be Dramatically improve effectiveness of asset and/or labor-intensive activities Have broad implications across functions, processes, geographies, or business units 20 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics 10Copyright © 2011, SAS Institute Inc. All rights reserved.
  12. 12. Are You Ready for Prediction/Optimization? Real-Time Optimization Optimal response embedded in real-time process Institutional Action Prediction and differentiated action Predictive Action embedded in process Predictions of response by target/ segment Differentiated Action Different approaches for different targets/ Key Targets/Segments segments Key targets and segments defined Data in Order Well-defined, common, clean, and integrated data 21 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics Analysts Analytical Champions--Own 1% Lead analytical initiatives “Data Scientists”—Own/Rent 5-10% Can create new algorithms Analytical Semi-Professionals—Own/Rent 15-20% Can use visual and basic statistical tools, create simple models Analytical Amateurs--Own Can use spreadsheets, use 70-80% analytical transactions * percentages will vary based upon industry and strategy 22 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics 11Copyright © 2011, SAS Institute Inc. All rights reserved.
  13. 13. Roles for IT and CIOs in All This Restructure the entire IT organization to emphasize decision-making e.g., P&G’s “Information and Decision Solutions” Establish a COE, competency center, or consulting group around analysis and decisions e.g, Kimberly-Clark’s BICC Include analytics and decision processes in the broader information provision process E.g., Cisco Advanced Services “Production Analytics” Thomas H. Davenport – Predictive Analytics Keep in Mind ► Five levels, five factors for building predictive analytical capability ► Data and leadership are the most important prerequisites ► Make sure your targets are strategic ► Tie all your predictive analytics work to specific decisions ► This is not business as usual—there is a historic opportunity to transform your industry! 24 | 2011 © All Rights Reserved. Thomas H. Davenport – Predictive Analytics 12Copyright © 2011, SAS Institute Inc. All rights reserved.
  14. 14. Questions? To ask a question … click on the “question icon” in the upper-left corner of your screen. Type your question and name, and additional information if you wish, and click on the send button. Brought to you by Thank you for participating This presentation was made possible by the generous support of SAP. Learn more at SAP.com/PredictiveAnalytics Brought to you by 13Copyright © 2011, SAS Institute Inc. All rights reserved.

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