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  • Slide 1
  • Copyright 2010 SAS Institute Inc. All rights reserved.Copyright 2009, SAS Institute Inc. All rights reserved. Business Intelligence vs. Business Analytics How to Tell the Difference Kate Schwarz, SAS systems engineer
  • Slide 2
  • 2 Copyright 2010, SAS Institute Inc. All rights reserved. What are BI and BAs characteristics? What BA offers and why its critical for your business Illustrations & success stories Agenda
  • Slide 3
  • 3 Copyright 2010, SAS Institute Inc. All rights reserved. Business Intelligence or Business Analytics? Whats 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 whats next? Strategic/enterprise/holistic Discovery and ad hoc Scientific and research-based Market leading
  • Slide 4
  • 4 Copyright 2010, SAS Institute Inc. All rights reserved. Business Intelligence is business as usual. Business as usual is not good enough.
  • Slide 5
  • 5 Copyright 2010, SAS Institute Inc. All rights reserved. Do your reports look like this?
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  • 6 Copyright 2010, SAS Institute Inc. All rights reserved. Remember this?
  • Slide 7
  • 7 Copyright 2010, SAS Institute Inc. All rights reserved. Do grade school mathematics run your business?
  • Slide 8
  • 8 Copyright 2010, SAS Institute Inc. All rights reserved. This is BI
  • Slide 9
  • 9 Copyright 2010, SAS Institute Inc. All rights reserved. Business Value How many organizations define and deploy BI Reporting / OLAP Data Management Data Access How Much? How Many? What Happened? Data Information Knowledge
  • Slide 10
  • 10 Copyright 2010, SAS Institute Inc. All rights reserved. Simple yet useful questions Product Time Location Year Month Week Store SKU Brand Region Subcategory All Merchandise Country Company Zone Category 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?
  • Slide 11
  • 11 Copyright 2010, SAS Institute Inc. All rights reserved. This is business analytics
  • Slide 12
  • 12 Copyright 2010, SAS Institute Inc. All rights reserved. Optimization Predictive Modeling Forecasting Reporting / OLAP Data Management Data Access What are likely outcomes? What are root causes? Whats the best that can happen? How Much? How Many? What Happened? Beyond Traditional Intelligence to Business Analytics Business Value DataInformationKnowledgeIntelligence
  • Slide 13
  • 13 Copyright 2010, SAS Institute Inc. All rights reserved. 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?
  • Slide 14
  • 14 Copyright 2010, SAS Institute Inc. All rights reserved. The BA Cycle Team, Technologies, Techniques Formulate Questions Accumulate & Integrate Data Quality Analysis Transform and Select Query & Reporting Prediction & Analytics Deploy & Evaluate Monitor Results
  • Slide 15
  • 15 Copyright 2010, SAS Institute Inc. All rights reserved. BA requires: Diverse data access & integration Comprehensive data assessment and cleansing Scalability
  • Slide 16
  • 16 Copyright 2010, SAS Institute Inc. All rights reserved. BI Frequency Distribution
  • Slide 17
  • 17 Copyright 2010, SAS Institute Inc. All rights reserved. BA Pattern Frequency Distribution
  • Slide 18
  • 18 Copyright 2010, SAS Institute Inc. All rights reserved. BI Frequency Distribution
  • Slide 19
  • 19 Copyright 2010, SAS Institute Inc. All rights reserved. BA Column/Variable Clustering
  • Slide 20
  • 20 Copyright 2010, SAS Institute Inc. All rights reserved. BA requires: Going beyond query and reporting Combining operational data with unstructured data
  • Slide 21
  • 21 Copyright 2010, SAS Institute Inc. All rights reserved. BI query, reporting, graphing, charting
  • Slide 22
  • 22 Copyright 2010, SAS Institute Inc. All rights reserved. BA regression, multivariate, process control, forecasting
  • Slide 23
  • 23 Copyright 2010, SAS Institute Inc. All rights reserved. BI report & measure customers activities
  • Slide 24
  • 24 Copyright 2010, SAS Institute Inc. All rights reserved. BI - Unifying Customer Interaction + Demographics NameJohn Smith Address10 Main Street Anytown, CA 90210 Gendermale Purchases this month10 Census block14 Tenure5 years Visits to website5 Web site spending$250 Merchandise spending$100
  • Slide 25
  • 25 Copyright 2010, SAS Institute Inc. All rights reserved. BA - Unifying Customer Interaction + Demographics + Psychographics + Technographics NameJohn Smith Address10 Main Street Anytown, CA 90210 Gendermale Purchases this month10 Forecasted purchases next month12 Census block14 Tenure5 years Visits to website5 Web site spending$250 Merchandise spending$100 Intersts & activitiesFantasy leagues, local high school sports Segmentlow profit potential, low attrition risk Social Media Ladder RungJoiner Net Promoter ScorePromoter
  • Slide 26
  • 26 Copyright 2010, SAS Institute Inc. All rights reserved. Identify roles within social groups: Influencers Followers Social Group Value Benefits Improve marketing effectiveness Increase retention Improve new services BA Social Analytics
  • Slide 27
  • 27 Copyright 2010, SAS Institute Inc. All rights reserved. BA Sentiment Analysis
  • Slide 28
  • 28 Copyright 2010, SAS Institute Inc. All rights reserved. BA requires predictive analytics: Forecasting Segmentation Optimization
  • Slide 29
  • 29 Copyright 2010, SAS Institute Inc. All rights reserved. Forecasting
  • Slide 30
  • 30 Copyright 2010, SAS Institute Inc. All rights reserved. BI Line Plot
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  • 31 Copyright 2010, SAS Institute Inc. All rights reserved. BA Forecast
  • Slide 32
  • 32 Copyright 2010, SAS Institute Inc. All rights reserved. High Low High Low Probability to Churn Customer LTV Acquisition Provide appropriate benefits/loyalty programs, understand profile, look for similar fans BA Segmentation Ilustrated Identifying high & low value customers, whos likely to churn? Retention & churn prevention Up-Selling Campaigns to increase spend & make sure fans are profitable Low or no effort for retention5 3 1 2 4 6 7
  • Slide 33
  • 33 Copyright 2010, SAS Institute Inc. All rights reserved. Business Analytics - Optimization Linear programming with constraints Simulation Often used to determine maximum profit, performance, or yield minimum loss, risk, or cost
  • Slide 34
  • 34 Copyright 2010, SAS Institute Inc. All rights reserved. BI report & measure customers purchases
  • Slide 35
  • 35 Copyright 2010, SAS Institute Inc. All rights reserved. BA optimization via price elasticity
  • Slide 36
  • 36 Copyright 2010, SAS Institute Inc. All rights reserved. Deliver BA via BI Streamlined access to insightful reports Dashboards that tell the whole story Self service and fact-based decision empowerment
  • Slide 37
  • 37 Copyright 2010, SAS Institute Inc. All rights reserved. This is BI
  • Slide 38
  • 38 Copyright 2010, SAS Institute Inc. All rights reserved. This is business analytics
  • Slide 39
  • 39 Copyright 2010, SAS Institute Inc. All rights reserved. ChallengesHow?Benefits spent more time preparing and moving data than making decisions & taking action. unable to optimize gift size and response rates while maintaining a low per-dollar cost for donations. Leading conservation organization working around the world to protect ecologically important lands and waters for nature and people Achieves a fund-raising efficiency of 89 percent, according to Forbes magazine's annual survey of the largest U.S. charities. data integration, data mining, and customer intelligence Increased in revenue per item mailed More money is available for conservation with less spent on fund raising
  • Slide 40
  • 40 Copyright 2010, SAS Institute Inc. All rights reserved. ChallengesHow?Benefits Accelerating lab results Increasing the number of beds available for intensive care patients Sending patients home sooner once theyre healthy enough to leave A world-class academic and health care system Strives to transform medicine and health locally and globally through innovative scientific research, rapid translation of breakthrough discoveries, educating future clinical and scientific leaders, advocating and practicing evidence-based medicine to improve community health, and leading efforts to eliminate health inequalities. data visualization & performance management Scorecards quickly reveal what is working well and what requires improvement. Decision makers understand why * how key performance indicators have changed.
  • Slide 41
  • 41 Copyright 2010, SAS Institute Inc. All rights reserved. ChallengesHow?Benefits reduce back orders save staff time optimize inventory levels Enhance, preserve and restore vision worldwide. Discover and develop innovative eye care products that improve the quality of life by helping people see better. For more than 60 years, Alcon has focused on helping people worldwide see better through our core competencies research and development, manufacturing and sales. Forecasting Improved customer service levels alongside increased volumes without raising inventory or staffing. Reduced investments in inventory.
  • Slide 42
  • 42 Copyright 2010, SAS Institute Inc. All rights reserved. ChallengesHow? Benefits 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. Smiles designed and delivered. When we see a rose or a peony or a Peruvian lily, we dont just see a gorgeous flowerwe 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. predictive analytics, segmentation, sequencing Holistic view of customers attributes and behaviors Reduced operating expenses More innovations
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  • 43 Copyright 2010, SAS Institute Inc. All rights reserved. ChallengesHow? Benefits offer customers low-cost deals while simultaneously increasing overall company revenue. determine how to display & flag best deals after customers search. Expedia delivers consumers everything they need for researching, planning, and purchasing a whole trip. Provide direct access to one of the broadest selections of travel products and services through its North American Web site, localized versions throughout Europe, and extensive partnerships in Asia. operations research simulations, design of experiments Clearer views of the millions of customers. Web site designs that make customers linger & buy. Reduced fraud.
  • Slide 44
  • 44 Copyright 2010, SAS Institute Inc. All rights reserved. BA101 An Introduction to Business Analytics
  • Slide 45
  • 45 Copyright 2010, SAS Institute Inc. All rights reserved. Supply & DemandCustomers Service Provider Profitability Giving Program Analysis Contact Center Analysis Fraud Analysis Green Initiatives/Sustainability Advocacy Mobilization Performance Measurement & Reporting Workforce Planning & Management Regulatory Reporting & Compliance Predictive Asset Maintenance Segmentation & Profiling Marketing Optimization Price Optimization Cross-Sell/Up-Sell Satisfaction & Retention Utilization Analysis & Reporting Spend Analysis Capacity Planning and Prediction Inventory Optimization Demand Forecasting Operations Service BA for your enterprise