AFS Actionable Consumer Goods Analytics
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AFS Actionable Consumer Goods Analytics
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AFS Actionable Consumer Goods Analytics
- 1. Actionable CG Analytics: Leveraging Industry Trends and Data Availability 2016 AFS User Conference
- 2. ©2016 AFSTechnologies, Inc., Proprietary and Confidential • Emerging data sources • Industry analytical trends • Consumer Goods challenges • How to leverage these trends • AFS Product sessions Actionable CG Analytics
- 3. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Traditional CG Perspective on Data PROMOTION PLANNING PROMOTION MANAGEMENT FIELD MANAGEMENT FIELD REPS CUSTOMERS Actionable Insights IN-FIELD EXECUTION DISTRIBUTION DSD & VAN SALES POS ORDERS ACCOUNT MANAGEMENT FIELD METRICS ACTIONABLE INSIGHTS displays
- 4. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Smart Appliances Electronic Shelf tags Amazon Dash Button Smart Cars Groupon Live Weather Apps Social Media Google Analytics Smart Phones Credit Cards Growing Digital CG Ecosystem GPOs GS1 Raw Material Traceability Currency Market Commodity Exchanges POS Data 3rd Party PortalsSpin Data DSD Ticket Detail Digital Product Libraries Consumer Manufacturer Broker Retailer Operator Distributor Wholesaler Shopper Cards High-tech shopping carts Video Mining
- 5. ©2016 AFSTechnologies, Inc., Proprietary and Confidential All this data. Why can’t I find insights? Data must be: • Interpretable • Relevant • Novel.
- 6. ©2016 AFSTechnologies, Inc., Proprietary and Confidential TPM vs. TPO Industry buzz: TPO is where all the payback is. Why do I need TPM?
- 7. ©2016 AFSTechnologies, Inc., Proprietary and Confidential TPM vs TPO Industry buzz: TPO is where all the payback is. Why do I need TPM? TPM creates the data, processes and controls to create the big data.
- 8. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Descriptive Analytics Descriptive statistics summarizes the data. Is this sufficient to drive action and outcomes?
- 9. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Time Trade spending is over budget! Forecast based on “guestimates” 1. Real-Time Visibility Sense & Respond • Something happens in the past, and we respond to prevent it in the future. • Actual off-invoice • Bill-backs paid YTD • Fixed budget or live accrual • Net bill-back liability • Compare Actual YTD to Budget YTD 2. Issue Identification Resolution: Cancel or change events
- 10. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Accessible data (data you have) Model f(x) Inaccessible data (data you don’t have) Predictive Analytics • Build a statistical model using existing data to predict data that we don’t have. • Requires a validated model in addition to your data. • Examples include: forecasts, base lines, lift factors
- 11. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Time Resolution: Cancel or change events Trade spending if forecasted to be over budget! Forecast based on “guestimates” 1. Real-Time Visibility Advanced Sense & Respond Predictive and exception-based workflows and processes • Sense latest change in sales, promotion lift, etc. to anticipate and Respond to problems before they happen • Actual off-invoice • Bill-backs paid YTD • Fixed budget or live accruals • Net bill-back liability • Compare Actual YTD to Budget YTD • Add predictive analytics: Lift factors & baselines • Actual + Forecast = Latest Estimate 2. Issue Identification 3. Proactive Resolution & Execution
- 12. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Prescriptive Analytics: Actionable Analytics! Existing Data with Alerts Specific Actions & Workflow Payback! $$$$
- 13. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Time Resolution: Cancel or change events Forecast based on “guestimates” 1. Real-Time Visibility Super Advanced Sense & Respond Prescriptive and exception based workflows and processes. • Sense latest changes in demand, supply or capacity and rapidly Respond to provide precise, optimized execution to avoid projected problems • Actual off-invoice • Bill-backs paid to date • Fixed budget or live accruals • Net bill-back liability • Compare Actual YTD to Budget YTD • Add predictive analytics: Lift factors & baselines • Actual + Forecast = Latest Estimate Scenario Planning: Manually compare different options Optimization: what combination of events to meet the goal? 3. Proactive Resolution & Execution Trade spending if forecasted to be over budget! 2. Issue Identification
- 14. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Challenges and Solutions Challenge Solution I don’t have time to do this Review your current analytics… Automate your descriptive analytics, use management-by-exception to save time
- 15. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Challenges and Solutions Challenge Solution I don’t have time to do this Review your current analytics… Automate your descriptive analytics, use management-by-exception to save time Data and analytics are expensive! Do a cost-benefit analysis Prioritize highest ROI projects Seek out underutilized data Concept: Just enough data to generate a return and competitive advantage
- 16. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Challenges and Solutions Challenge Solution I don’t have time to do this Review your current analytics… Automate your descriptive analytics, use management-by-exception to save time Data and analytics are expensive! Do a cost-benefit analysis Prioritize highest ROI projects Seek out underutilized data Concept: Just enough data to generate a return and competitive advantage Reacting too quickly can be disruptive Use ‘time boxes’ For each problem, consider what ‘bucket’ is the minimum you need to generate a payback; Daily? Weekly? Monthly?
- 17. ©2016 AFSTechnologies, Inc., Proprietary and Confidential • #1: What is the opportunity payback of fixing the problem? • Law of diminishing returns; solving 80% may be good enough • Is the solution too disruptive? • Consider negative side effects and limitations • #2: How expensive is the solution to your problem? • Cost of data? Include software to mange it, labor to analyze it • #3: Find your Smart Data and do an ROI analysis • Look for your under-utilized data assets • Find challenges where the payback is X times the cost of the solution • How to go about filtering the data to make it actionable • Strive for prescriptive analytics Where to start?
- 18. ©2016 AFSTechnologies, Inc., Proprietary and Confidential • Data you already own • Seek out data silos within your organization • Trading partners! • Integrate with other data sources to add value • Data you can access for free • Industry portals, governmental databases, trade associations • Data you can purchase • Start with small initial scope to prove ROI • Remember: just enough data, and 80/20 rule • How to filter available data to what’s important? What data?
- 19. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Big Data Visibility • Representation - data • Accessibility – process and permission “Single version of the truth” • Intelligence – • Data mapping and cleaning • Heuristics • Predictive analytics • Decision management – prescriptive analytics • Outcome-based metrics and performance…to generate a payback!
- 20. ©2016 AFSTechnologies, Inc., Proprietary and Confidential Learn More! Blog articles that may interest you: • Eliminating Trade Promotion Surprises for Finance • 5 Foodservice Insights For Your Trade Promotion Management • Helping Your Field Force Achieve the Perfect Store Visit us at afsi.com
Editor's Notes
- Star Trek Convention – Gene Rodenbury (1980s) – mankind’s knowledge doubles every 18 months)
- Uses existing data, but also the action and feedback data to guide the decision maker to a desired outcome.