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Content
Predictive analytics: what is it?
SAP Predictive Analysis: solution overview
Demo: customer churn prediction in telecom
Use-case
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Predictive analytics: what are we looking at?
What are my typical shopping baskets?
What are the characteristics of thecustomers who are churning?
Which pieces of my equipments will fail, when, and where?
Which of my claims are likely to be frauds?
What kind of similar groups of customersdo I have?
Are there predictable patterns in thevariations of my customers’ demand?
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SAP Predictive Analysis: algorithms out of the box
association clustering classification outliers classification forecasting
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Elements of project methodology: CRiSP-DM model
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SAP Predictive Analysis: solution overview
Rich client, integrated with Lumira
Data sources: Excel, Hana, free-hand SQL
Integrated with R
Algorithms run locally or on Hana
Roadmap: merge with KXEN products
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Hana
SAP Predictive Analysis: architecture
PA client
PAL Data
PA client
DataData
PA + Hana standalone PA
model
run
model run
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SAP Predictive Analysis: demo
Scenario for the demo: prediction of customer churn in telecom area
Based on a simplified data set, from actual data from The Center for Customer Relationship
Management at Duke University, used in a Duke/Teradata tournament in 2003.
PA version used: 1.19.0, from SAP’s trial offer
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SAP Predictive Analysis: demo
A powerful and relatively easy-to-use tool
Strong vizualization capabilities
Not a magic bullet, data knowledge will be important:
• initiate patterns recognition
• understand & validate the proposed models
• integrate with business processes
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Use-case: Warranty POC
Results and Benefits
• Delivered an SAP Predictive Analysis HANA Proof of
Concept using client data within the Accenture Innovation
Center for SAP lab environment
• Completed concept to delivery within a rapid deployment
timeframe of 6 weeks
• Demonstrated SAP Predictive Analytics capabilities and
benefits of tool, and put forth a vision for a future roadmap
of SAP PA for the client
• Client Warranty Specialist to leverage capabilities
demonstrated in the POC to more effectively forecast
warranty costs and defect trends before, and to mitigate
financial impact
• Accelerated future delivery by leveraging POC solution to
rapidly launch Predictive Analysis implementation
Challenge
VELUX gives a long warranty on their products. Today they
forecast manually on how much they will need reserve for
warranty cost going forward. By improving the warranty
forecast the client hope to achieve the following:
• With a more accurate forecast, free up funds and resource
to be used elsewhere
• Get a deeper understanding of which defects drives the
warranty claims and identify how these can be reduced
• Move away from a manual and individual-dependent
solution
• By analyzing the data with Predictive Analysis, identify
trends in defects and mitigate those before they have a
larger impact.
• By analyzing production defects by plant, get a holistic
view of production quality across the company and identify
areas that need attentionty across VELUX and identify
areas that needs attention
Solution
• The PoC demonstrated the capabilities of the SAP
Predictive Analysis tool and the Warranty Analytics
expertise from IDC analytics team
• The PoC was conducted using VELUX data exported to
the Innovation Center environment into an SAP HANA
data model. The Analytics team in the IDC conducted the
analysis using SAP Predictive Analysis on top of HANA
• This was all completed within a six week period with a
team of Client and Accenture with technical support from
SAP resources, across Denmark, India and the United
States
• The solution tested hypotheses of the data, including:
• What products, product groups and components
contribute most to defects?
• What components are likely to fail together?
• What is forecasted defect frequency by product?
• What are the outliers by product, age, factory, etc?
ScenarioVELUX, a global company within building materials, have just migrated their entire BW solution to HANA. They were now looking how to leverage the new environment and
to harness the power that HANA brings, including the SAP Predictive Analysis. In order to gain momentum at the start of the Predictive Analysis project and to validate the
use case and benefits, a Proof of concept (PoC) was initiated leveraging the Accenture Innovation Center for SAP and the Accenture Warranty Analytics team.
