davenport webinar predictive analytics
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HBR webinar with Tom Davenport discussing Analytics, SAP involvement as well.TRANSCRIPT
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Predictive Analytics: Gaining Advantage by Using Analytics to Predict the Future
October 3, 2011 Brought to you by
Tom DavenportPresident’s Distinguished Professor of Management and Information TechnologyBabson College
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Copyright © 2011, SAS Institute Inc. All rights reserved.
Predictive Predictive Analytics at WorkAnalytics at Work
Tom DavenportTom DavenportBabson CollegeBabson College
Harvard Business Review WebcastHarvard Business Review WebcastOctober 3, 2011October 3, 2011
Thomas H. Davenport – Predictive Analytics4 | 2011 © All Rights Reserved.
What Are Analytics?What Are Analytics?
Optimization
Predictive Modeling/ForecastingRandomized Testing
Statistical analysis
Alerts
Query/drill down
Ad hoc reports
Standard Reports
“What’s the best that can happen?”
“What will happen next?”
“What happens if we try this?”
“Why is this happening?”
“What actions are needed?”
“What exactly is the problem?”
“How many, how often, where?”
“What happened?”
Descriptive Analytics(the “what”)
Predictive and Prescriptive Analytics(the “so what”)Degree
of Intelligence
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Thomas H. Davenport – Predictive Analytics5 | 2011 © All Rights Reserved.
Types of AnalyticsTypes of Analytics
What happened?(Reporting)
What is happening now?
(Alerts)
How and why did It happen?
(Modeling, testing)
What’s the next best action?
(Recommendation)
Cont
ent T
ype
Info
rmat
ion
Insig
htFuturePast
What will happen?(Prediction)
What’s the best that can happen?
(Optimization/simulation)
PresentTimeframe
Thomas H. Davenport – Predictive Analytics6 | 2011 © All Rights Reserved.
Applications of Predictive Applications of Predictive AnalyticsAnalytics
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?
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Thomas H. Davenport – Predictive Analytics7
Stage 5Analytical
Competitors
Stage 4Analytical Companies
Stage 3Analytical Aspirations
Stage 2Localized Analytics
Stage 1Analytically Impaired
Levels of Analytical Capability
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Masters of PredictionMasters of Prediction
Marriott — optimal pricingNextel—customer attritionCisco—forecastingTesco—offerseBay—web site testingNetflix—movies you’ll likeZappos—shoes you’ll likeGoogle—page rank, advertising, HR
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Thomas H. Davenport – Predictive Analytics9 | 2011 © All Rights Reserved.
The Analytical DELTAThe Analytical DELTA
Data . . . . . . . . . . breadth, integration, quality, technologyEnterprise . . . . . . . . . .approach to managing analyticsLeadership . . . . . . . . . . . . . . . passion and commitmentTargets . . . . . . . . . . . . . first deep, then broadAnalysts . . . . . professionals and amateurs
Thomas H. Davenport – Predictive Analytics10 | 2011 © All Rights Reserved.
DataData
The prerequisite for everything analyticalClean, common, integrated Accessible in a warehouseMeasuring something new and important
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Thomas H. Davenport – Predictive Analytics11 | 2011 © All Rights Reserved.
New Metrics / DataNew Metrics / Data
Wine Chemistry Smile FrequencyDefensive moves
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Some Current Data and Some Current Data and Technology DilemmasTechnology 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?
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Thomas H. Davenport – Predictive Analytics13 | 2011 © All Rights Reserved.
The Changing World of Analytics
Old BIOld BIAnalyst
Sandbox
EmbeddedAnalytics
AnalyticalApps
ProfessionalAnalysts
BusinessUsers
Multi-Purpose
Single-Purpose
Application Breadth
Primary Users
Thomas H. Davenport – Predictive Analytics14 | 2011 © All Rights Reserved.
Some Actual Analytical Apps
Spend analysis in life sciencesAftermarket services revenue growth for equipment manufacturersAnalyzing mortgage portfoliosFinancial planning and modeling in the public sectorEnterprise risk and solvency management for insuranceContract compliance in transportationNursing productivity in health careField sales hiring analysis in pharmaEmployee attrition analysis in telecomEmployee satisfaction and store performance analysis in retail
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Thomas H. Davenport – Predictive Analytics
Linking Data and DecisionsLinking Data and Decisions
Thomas H. Davenport – Predictive Analytics
Embedding Analytics in ProcessesEmbedding Analytics in Processes
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Source: SAP AG 2006
Receives ASN
Releases ASN
DeliveryExecution
UpdateInventory
AccountingUpdate
Inventory
Delivery PerformanceDelivery Performance“How effective is our fulfillment
process?”
CLTVCLTV“Does this order justify extra
efforts?”
Inventory ForecastInventory Forecast“Will this be back in inventory?”
Defection RiskDefection Risk“What is the customer status?”
Global ATPCheck
RequestGlobal ATP
CreationSales Order
Fulfillment Request
CreationPurchase Order
Creation &Release Delivery
RequestReturns per CustomerReturns per Customer“What is the customer history?”
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Thomas H. Davenport – Predictive Analytics17 | 2011 © All Rights Reserved.
EnterpriseEnterprise
If you’re competing on analytics, it doesn’t make sense to manage them locally
No fiefdoms of data, technology, or organizationA centralized organization or CoE is increasingly common
P&G, Caesars, Walmart, etc.
Thomas H. Davenport – Predictive Analytics
Under Enterprise ManagementUnder Enterprise Management
Web analytics+ Marketing +
Actuarial +Predictive +
Supply chain/OR
HR analytics+=
EnterpriseAnalytics!
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Thomas H. Davenport – Predictive Analytics19 | 2011 © All Rights Reserved.
LeadershipLeadership
CEOs—Google, Netflix, Capital OneCFOs—Caesars, HumanaCIOs—P&G, SchneiderCOOs—Ebay, Chicos
Thomas H. Davenport – Predictive Analytics20 | 2011 © All Rights Reserved.
The Best TargetsThe Best Targets……
Support a key strategic capabilityEngage top management commitment Create momentum for analytics across the enterpriseHave ambitious, yet pragmatic scopeAre data rich — or have the potential to beDramatically improve effectiveness of asset and/or labor-intensive activitiesHave broad implications across functions, processes, geographies, or business units
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Copyright © 2011, SAS Institute Inc. All rights reserved.
Thomas H. Davenport – Predictive Analytics
Are You Ready for Prediction/Optimization?Are You Ready for Prediction/Optimization?
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Optimal response
embedded in real-time process
Predictions of response by
target/ segment
Key targets and segments defined
Prediction and differentiated
action embedded in
process
Different approaches for
different targets/
segments
Well-defined, common, clean, and integrated
data
Data in Order
Key Targets/Segments
Differentiated Action
Institutional Action
Real-Time Optimization
Predictive Action
Thomas H. Davenport – Predictive Analytics22 | 2011 © All Rights Reserved.
AnalystsAnalysts
5-10%“Data Scientists”—Own/RentCan create new algorithms
Analytical Semi-Professionals—Own/RentCan use visual and basic statistical tools, create simple models
Analytical Amateurs--OwnCan use spreadsheets, use analytical transactions
15-20%
70-80%
* percentages will vary based upon industry and strategy
1%Analytical Champions--OwnLead analytical initiatives
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Thomas H. Davenport – Predictive Analytics
Roles for IT and CIOs in All ThisRoles 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 MindKeep in Mind
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►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!
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Questions?
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Type your question and name, and additional information if you wish, and click on the send button.
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Thank you for participating
This presentation was made possible by the generous support of SAP.
Learn more at SAP.com/PredictiveAnalytics
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