Creating a Business Case for Big Data
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The document outlines a business case for implementing big data solutions, emphasizing the importance of aligning big data initiatives with corporate strategy and quantifying benefits. It presents a comprehensive agenda, identifies challenges, and provides keys for building effective use cases, showing how big data analytics can enhance customer experiences, optimize operations, and ultimately improve profitability. The document also notes critical considerations such as staffing requirements for data scientists and recommends best practices for developing a strong business case.
Creating a Business Case for Big Data
- 1. Big Data Architectural Series: Creating a Business Case for Big Data facebook.com/perficient linkedin.com/company/perficient twitter.com/Perficient
- 2. About Perficient Perficient is a leading information technology consulting firm serving clients throughout North America. We help clients implement business-driven technology solutions that integrate business processes, improve worker productivity, increase customer loyalty and create a more agile enterprise to better respond to new business opportunities.
- 3. • Founded in 1997 • Public, NASDAQ: PRFT • 2013 revenue ~$373 million Perficient Profile • Major market locations throughout North America • Allentown, Atlanta, Boston, Charlotte, Chicago, Cincinnati, Columbus, Dallas, Denver, Detroit, Fairfax, Houston, Indianapolis, Minneapolis, New York City, Northern California, Oxford (UK), Philadelphia, Southern California, St. Louis, Toronto, Washington, D.C. • Global delivery centers in China, Europe and India • >2,200 colleagues • Dedicated solution practices • ~85% repeat business rate • Alliance partnerships with major technology vendors • Multiple vendor/industry technology and growth awards
- 4. BUSINESS SOLUTIONS Business Intelligence Business Process Management Customer Experience and CRM Enterprise Performance Management Enterprise Resource Planning Experience Design (XD) Management Consulting Our Solutions Expertise TECHNOLOGY SOLUTIONS Business Integration/SOA Cloud Services Commerce Content Management Custom Application Development Education Information Management Mobile Platforms Platform Integration Portal & Social
- 5. Our Speaker Bill Busch Sr. Solutions Architect, Enterprise Information Solutions, Perficient • Leads Perficient's enterprise data practice • Specializes in business-enabling BI solutions that enable the agile enterprise • Responsible for executive data strategy, roadmap development, and the delivery of high-impact solutions that enable organizations to leverage enterprise data • Bill has over 15 years of experience in executive leadership, business intelligence, data warehousing, data governance, master data management, information/data architecture and analytics 5
- 6. Agenda Two Perspectives Big Data Business Case Challenges Four Keys To Big Data Business Case Building Do’s and Don’ts 6
- 7. Big Data Business Case Two Perspectives 7 Big Data Information Technology Infrastructure Data Integration Data Hub Data Lake Appliances Clusters Data Warehouse Cost Out Business Stakeholders Analytics New Product Design Customer Experience Operations Optimization Reduce Fraud Data Monetization Increased Profitability
- 8. 8 Optimizing Single Process Traditional Analytics Business Big Data Focus Business Case Challenge Optimizing Business Outcomes Big Data Analytics
- 9. Which business process should I use for the business case? 9 Business Big Data Focus Business Case Challenge Customer Experience Cycle
- 10. 10 Big Data Analytics Business Big Data Focus Business Case Challenge Decision Making Brand Management New Products & Services Customer Experience Reducing Operating Costs Optimize Supply Operations Pricing Optimization
- 11. IT Big Data Focus Business Case Challenge 11 Infrastructure modernization projects can be expensive Re-platform legacy systems Adjunct systems add to Op-Ex Support an additional system
- 12. Address the Who Layer the Benefits Link to Strategy Determine the Approach 12 Four Keys Building a Data Business Case
- 13. Address the Who Layer the Benefits Link to Strategy Determine the Approach 13 Four Keys Determine the Approach
- 14. Business or IT Focus? 14 Executive Summary Introduction Background Business Drivers Scope Key Financial Metrics Analysis Assumptions Business Process Changes Costs Benefits Financial Non-Financial Cash Flow Statement (NPV) Risk Strategic Options Opportunity Costs Conclusion & Recommendation, and Next Steps Appendix – Supporting Information Business Focused -Quantify Benefits IT Focus -Quantify Costs and Compare Options
- 15. Determine Your Approach Direct Evidence Initiative Optimization Business Outcome Corporate Asset 15
- 16. Direct Evidence Positives Challenges Description Big Data Application 16 Proof from an experiment or actual implementation resulting in the claimed benefit Typically pilot or test & learn project With Big Data, direct evidence is the result of a business-focused proof-of-concept o Most convincing o Opportunity to become familiarly with Big Data Technologies o Can be used to “test” which business cases to pursue o May need a business case to get to a pilot o If the business case is not proven, program may be at risk
- 17. Positives Challenges Description Initiative Optimization Big Data Application 17 This business case type leverages a transformational program to fund optimization activities driven by analytics. Most common funding mechanism. Include description how the analytical capability supports the program’s goals. Consider presenting Big Data as an option compared to traditional solutions. o Easiest to create o Does not require a separate benefits analysis o Good way to fund architecture modernization o May require a business case if added to scope o Internal competition for funding o Corporate culture will determine the success of this approach
- 18. Positives Challenges Description Business Process Improvement Big Data Application 18 Leverages improvement in one or more business process without the benefit of piggy-backing on a transformational project Can require significant work since more than one business case will need to be analyzed o Best used to support the Big Data Analytics initiative o Information is readily available o May require a business case if added to scope after program commences o Funding may be put at risk if program goes over budget
- 19. Positives Challenges Description Corporate Asset Big Data Application 19 Approaches the business case that the company requires Big Data Analytics as a means to either remain competitive or lead its industry. Numerous industry benchmarks exist on the value of analytics. These can be used to build a financial business case for Big Data. o Best used to support the Big Data Analytics initiative o Information is readily available o Generally the hardest to defend o Can result in un-realistic numbers o Requires executive support or directive
- 20. Corporate Asset Bottom-Line Business Case 20 On average, 6 Data Scientists will generate $10M/year ROI from analyzing Big Data* *Intel Corporation
- 21. Address the Who Layer the Benefits Link to Strategy Determine the Approach 21 Four Keys Link to Strategy
- 22. 22 Big Data Analytics Decision Making Business Case Quick Review Brand Management New Products & Services Customer Experience Reducing Operating Costs Optimize Supply Operations Pricing Optimization
- 23. Linking to Corporate Strategy 23 Chose benefits that relate to the corporate strategy. Consider using combination of Financial and Non-Financial metrics. Strategic Imperatives
- 24. 24 Linking to Corporate Strategy Strategic Imperatives Actions Requiring Decisions Increase Gross Margin Reduce Fuel Expense Meet Website SLAs Improve Customer Satisfaction Resolve Customer Complaints more Quickly Run Maintenance cycle on Diesel Generators Frequency & Length of idle cycle Analytical Contribution Identify and prioritize actions Prescribe prioritized corrective actions Model asset optimization capability System-wide understanding of causal factors Performance / health within time period Assign a confidence factor to predictions Identify casual factors impacting equipment life Early detection of equipment failure Supply-chain optimization Better root-cause identification Minimize decision time
- 25. Tell the Story Data Scientists in the Network Operations Department will use the Big Data Analytics capability to analyze generator run logs, weather data, fuel costs to identify, prioritize actions to reduce diesel generator idle time. These actions will reduce fuel costs and increasing gross margin. Furthermore, this will reduce our carbon footprint and enhance our brand image as a socially responsible company. 25
- 26. Quantifying Benefits 26 Most challenging portion of developing business case Not all benefits are quantifiable Both financial and non-financial can be quantified PoC may be required to either quantify or validate benefits
- 27. 27 Current Value (CVal) Coefficient of Improvement (Cof) Quantifying Benefits Simplified Model Future State Benefit (FVal)
- 28. 28 Quantifying Benefits Sum of Decisions Current Value (CVal) Coefficient of Improvement (Cof) Future State Benefit (FVal) n(CVal)(Cof) = FVal (CValn)(Cofn) = FVal Same Coefficient Different Coefficients
- 29. Quantifying Benefits Determining Coefficients • What: Leveraging Industry research to establish coefficients required to calculate a financial benefit • Most common and easiest to understand Industry Research • What: Leveraging the opinion of subject matter experts with unique knowledge to provide the coefficients required to calculate a benefit • A Delphi method can be used to utilize the opinion of many experts for a more accurate/substantiated result 29 Expert Estimation • What: Evaluating a group of like decisions before and after a process change and identifying the standard error before the and after a process change. The reduction of the standard deviation is then quantified to arrive at a financial benefit. • Hardest to understand Decision Risk Valuation
- 30. Business Case Solving the “Which Business Case” Problem Which business process should I use for the business case? 30 Customer Experience Cycle
- 31. 31 Big Data Analytics Business Big Data Focus Business Case Challenge Decision Making Which Business Process How to Optimize
- 32. ) 32 Quantifying Benefits Average Benefits of Many Use Cases Current Value (CVal) Coefficient of Improvement (Cof) Future State Benefit (FVal) AVG ((CValn)(Cofn) = FVal
- 33. Address the Who Layer the Benefits Link to Strategy Determine the Approach 33 Four Keys Layer the Benefits
- 34. Layering Benefits Increasing Business Case Impact 34 Use Additional Approaches Evaluate Additional Use-Cases Include Additional Benefits
- 35. Different Approach Direct Evidence Initiative Optimization Business Outcome Corporate Asset 35
- 36. 36 Additional Use Cases Sum of Benefits Current Value (CVal) Coefficient of Improvement (Cof) Future State Benefit (FVal) (CValn)(Cofn) = FVal
- 37. Tell the Story Example Data Scientists in the Network Operations Department will use the Big Data Analytics capability to analyze generator run logs, weather data, fuel costs to identify, prioritize actions to reduce diesel generator idle time. These actions will reduce fuel costs and increasing gross margin. Furthermore, this will reduce our carbon footprint and enhance our brand image as a socially responsible company. 37
- 38. Four Keys Address the Who Address the Who Layer the Benefits Link to Strategy Determine the Approach 38
- 39. Bottom-Line Corporate Asset 39 On average, 6 Data Scientists will generate $10M/year ROI from analyzing Big Data* *Intel Corporation
- 40. Addressing the Who Leveraging Big Data Analytics requires Data Scientists to use the system Companies may not have enough Data Scientists on staff to obtain the purported benefits Include staffing and training Data Scientist in the business case Each Data Scientist can generate $1.6Million in annualized ROI. If a business case has a $20Million annual ROI this suggests that 12 Data Scientists are required. 40
- 41. Final Thoughts Do’s • Chose the appropriate approach(s) • Tell how solution supports the corporate strategy • Quantify benefits in dollars where possible • Use the business case to setup the PoC • Include Data Scientist staffing and training in business case costs Don’ts • Select an infrastructure only use case • Create a build it and they will approach • Single-use case business case • Use an inappropriate level of detail for the company culture 41
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