Business Intelligence vs. Business Analytics – How to Tell the Difference

1. Business Intelligence vs. Business Analytics – How to Tell the Difference Kate Schwarz, SAS systems engineer

2. Agenda What are BI and BA’s characteristics? What BA offers and why it’s critical for your business Illustrations & success stories

3. Business Intelligence or Business Analytics? What’s the difference? Business Intelligence • Rear-view mirror • Answers what happened? • Tactical/departmental/siloed • Pre-defined and canned • Comparative and hunch-based • Status quo Business Analytics • Windshield and beyond • Answers what’s next? • Strategic/enterprise/holistic • Discovery and ad hoc • Scientific and research-based • Market leading

4. Do your reports look like this?

5. Remember this?

6. Do grade school mathematics run your business?

7. This is BI

8. How many organizations define and deploy BI Business Value Reporting / OLAP Data Management How Much? How Many? What Happened? Data Access Information Data Knowledge

9. Simple yet useful questions… • How many new customers did we gain & lose (by time or geography)? • How much [product/service] did we sell during [timeframe]? • What are most and least active sales channels? • When are peak and valley transaction timeframes? Subcategory Week Month Time Year Product Company SKU Brand Country Category All Merchandise Location Region Zone Store

10. This is business analytics

11. Data Information Knowledge Intelligence Beyond Traditional Intelligence to Business Analytics Optimization Predictive Modeling What are likely outcomes? What are root causes? What’s the best that can happen? Forecasting Business Value Reporting / OLAP Data Management How Much? How Many? What Happened? Data Access

12. BA asks more compelling questions • How many new customers will we gain during the next [timeframe] by product, channel, location)? • Why were more new customers gained/lost this month? • How do we optimally communicate with customers? • Which customers are likely to respond to a promotion and of those who respond, how much will they spend? • Who are our most & least profitable customers? • How do we attract and retain profitable customers? • How to allocate marketing dollars to maximize profits? • What factors affect staffing levels to meet swelling & shrinking customer service demands?

13. FormulateQuestions MonitorResults Accumulate& Integrate Deploy& Evaluate DataQualityAnalysis Prediction & Analytics Transformand Select Query & Reporting The BA Cycle Team, Technologies, Techniques

14. BA requires: • Diverse data access & integration • Comprehensive data assessment and cleansing • Scalability

15. BI Frequency Distribution

16. BA Pattern Frequency Distribution

17. BI Frequency Distribution

18. BA Column/Variable Clustering

19. BA requires: • Going beyond query and reporting • Combining operational data with unstructured data

20. BI – query, reporting, graphing, charting

21. BA – regression, multivariate, process control, forecasting

22. BI – report & measure customers’ activities

23. BI - Unifying Customer Interaction + Demographics

24. BA - Unifying Customer Interaction + Demographics + Psychographics + Technographics

25. BA – Social Analytics • Identify roles within social groups: • Influencers • Followers • Social Group Value • Benefits • Improve marketing effectiveness • Increase retention • Improve new services

26. BA – Sentiment Analysis

27. BA requires predictive analytics: • Forecasting • Segmentation • Optimization

28. Forecasting

29. BI Line Plot

30. BA Forecast

31. Acquisition Provide appropriate benefits/loyalty programs, understand profile, look for similar fans Retention & churnprevention Loworno effortforretention Up-Selling Campaigns to increasespend & makesurefans are profitable BA – Segmentation IlustratedIdentifying high & low value customers, who’s likely to churn? High 5 2 7 Customer LTV 3 6 1 4 Low High Low Probability to Churn

32. Business Analytics - Optimization • Linear programming with constraints • Simulation • Often used to determine • maximum profit, performance, or yield • minimum loss, risk, or cost

33. BI – report & measure customers’ purchases

34. BA – optimization via price elasticity

35. Deliver BA via BI • Streamlined access to insightful reports • Dashboards that tell the whole story • Self service and fact-based decision empowerment

36. This is BI

37. This is business analytics

38. Smiles designed and delivered. • When we see a rose or a peony or a Peruvian lily, we don’t just see a gorgeous flower—we see an opportunity to help someone express a feeling: appreciation, condolences, gratitude, love. • When someone gets our flowers, it puts a smile on their face. Benefits Challenges How? • Reducing time and effort to make sure relevant offers are sent to the right customers. • Limited analytics staff & skills. • Achieve consistency across 15 different brands. predictive analytics, segmentation, sequencing Holistic view of customer’s attributes and behaviors Reduced operating expenses More innovations

39. BA for your enterprise Supply & Demand Customers Demand Forecasting Satisfaction & Retention Inventory Optimization Cross-Sell/Up-Sell Capacity Planning and Prediction Price Optimization Spend Analysis Marketing Optimization Segmentation & Profiling Utilization Analysis & Reporting Service Operations Giving Program Analysis Performance Measurement & Reporting Service Provider Profitability Advocacy Mobilization Contact Center Analysis Workforce Planning & Management Fraud Analysis Regulatory Reporting & Compliance Green Initiatives/Sustainability Predictive Asset Maintenance