Competing on Analytics The New Science of Winning

Competing on Analytics The New Science of Winning Tom Davenport University of Houston ISRC November 15, 2007

The Planets Are Aligned for Analytics 4 Powerful IT 4 Data critical mass 4 Skills sufficiency 4 Business need 2 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

What Are Analytics? Analytics Competitive Advantage Decision Optimization What’s the best that can happen? Predictive Analytics What will happen next? Forecasting What if these trends continue? Statistical models Why is this happening? Alerts What actions are needed? Query/drill down Where exactly is the problem? Ad hoc reports How many, how often, where? Standard reports What happened? Reporting Degree of Intelligence 3 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

What Should Organizations Do with Analytics? 4 Using analytics is good v Finding the best customers, and charging them the right price v Minimizing inventory in supply chains v Allocating costs accurately and understanding how financial performance is driven 4 Competing on analytics is better v Making analytics and fact-based 4 | 2007 © All Rights Reserved. decisions a key element of strategy and competition Thomas H. Davenport – Competing on Analytics

What Is Analytical Competition About? 4 Dispassionate analysis 4 Data and statistics 4 Computers 4 Discipline and rigor 5 | 2007 © All Rights Reserved. 4 Passionate advocacy 4 Intuition 4 People 4 Creativity and insight Thomas H. Davenport – Competing on Analytics

Analytical Competitors Old Hands Polishing Their Edge 4 4 4 6 | 2007 © All Rights Reserved. Marriott — Revenue management Wal-Mart — Supply chain analytics RBC — Cost and customer profitability P&G — Supply chain Progressive — Pricing risk Thomas H. Davenport – Competing on Analytics

Analytical Competitors Major Turnaround in Strategy or Culture 4 4 Harrah’s — Loyalty and service Tesco — Loyalty and Internet groceries MCI — Network pricing Rogers / Nextel / Verizon Wireless / Cablecom — Customer relationship processes 4 A’s / Red Sox / Patriots / Rockets — Players for price 7 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

Analytical Competitors Number-Crunchers from Birth 4 Capital One — “Information-based strategy” 4 Amazon — Supply chain, advertising, page changes 4 Yahoo — Pages as controlled experiments 4 Netflix — Movie preference algorithms 8 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

Analytical Competitors Cut Across Industries Consumer Products Industrial Products • Kraft • Deere • Mars • Cemex • E&J Gallo Retail Financial Services • J. C. Penney • Bank of America • Best Buy • Barclay’s Transport / Travel and Entertainment • Humana • Fed. Ex Government • New York Police Dept. • VA Hospitals • Schneider • Hilton • Army Recruiting 9 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

Analytics in Professional Sports 4 Identify undervalued attributes 4 Develop new performance metrics 4 Know when a player is ready to move up 4 Use your own selection criteria 4 Assess the ability to work as part of a team 4 Understand risk better than your competitors 4 Determine who gets hurt and who gets tired 4 Who inspires others to play better? 4 Who drags down the team? 10 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

MA OR PE RF ES C PIE NC E The Analytical Delta PROGRESS 11 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

STAGE 5: Analytical Competitors 11/32 firms STAGE 4: Analytical Companies PE R FO RM AN CE The Analytical Performance Delta 6/32 More analytical = higher performance STAGE 3: Analytical Aspirations 7/32 STAGE 2: Localized Analytics 6/32 STAGE 1: Analytically Impaired 2/32 12 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

The Analytical Performance Delta (cont. ) 15% of top performers versus 3% of low performers indicated that analytical capabilities are a key element of their strategy. 47% 33% 27% 19% 12% 9% 8% 10% 0% No analytical capability Minimal analytical capability Some analytical capability Above average analytical capability Analytic capability is a key element of strategy Source: Accenture Survey of 205/392 companies 13 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

High Performers Use Analytics Top performers have a greater analytical orientation than low performers. High Performers Low Performers 65 % have significant decision-support/analytical capabilities 23% 36 value analytical insights to a very large extent 77 77 8 have above average analytical capability within industry 33 62 ta and analysis 73 51 14 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

How Analytical Competitors Make Money 4 Optimize a distinctive capability or external relationship v Customer relationships, supply chain, HR, R&D, etc. v Harrah’s, Marriott, Amazon, etc. 4 Understand take action on the business better v MCI, Sara Lee Bakeries, RBC 4 Offer analytics to customers as the core offering v Apex Management Group in insurance risk management v Franklin Portfolio Associates in equity portfolio development 4 Offer analytics to customers to augment existing product or service v Smart. Swing in golf clubs v Nielsen/IRI in retail/consumer products 15 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

The Analytical Landscape Is Always Changing 4 Airlines—letting a business model become obsolete 4 Baseball teams—on-base percentage becomes overvalued 4 Capital One—other banks catch up, and they enter a new business 16 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

The Analytical DELTA — Pieces S CE PIE Data. . . . breadth, integration, quality Enterprise. . . . approach to managing analytics Leadership. . . passion and commitment Targets. . . first deep, then broad Analysts. . . professionals and amateurs 17 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

Data 4 The prerequisite for everything analytical 4 Clean, common, integrated 4 Accessible in a warehouse 4 Measuring something new and important 18 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

New Metrics / Data Wine Chemistry 19 | 2007 © All Rights Reserved. Driving Data Run Production Thomas H. Davenport – Competing on Analytics

Enterprise 4 If you’re competing on analytics, it doesn’t make sense to manage them locally v No fiefdoms of data v Avoiding the analytical equivalent of duct tape 4 Some level of centralized expertise for hardcore analytics 4 Firms may also need to upgrade hardware and infrastructure 20 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

Enterprise-Wide Customer View Types of Data Sales Processes in Which Data Used Marketing Logistics Service Internal Transaction Web Metrics External Geo-Demo External Attitudinal 21 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

Leadership 4 Gary Loveman at Harrah’s v “Do we think, or do we know? ” v “Three ways to get fired” 4 Barry Beracha at Sara Lee “Our CEO is a real data dog” Sara Lee executive v “In God we trust, all others bring data” 4 Jeff Bezos at Amazon v “We never throw away data” 22 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

The Great Divide Full steam ahead! Is your senior manageme nt team committed? 23 | 2007 © All Rights Reserved. • Hire the people • Build the systems • Create the processes Prove the value! • Run a pilot • Measure the benefit • Try to spread it Thomas H. Davenport – Competing on Analytics

Targets 4 With limited analytical resources, pick a major strategic target, with a minor or two v. Harrah’s = Loyalty + Service v. Patriots = Player selection + TFE v. Barclay’s = Asset analysis + Credit cards v. UPS = Operations + Customer data 4 Can also have two primary user group targets v. Wal-Mart = Category managers + Suppliers v. Owens & Minor = Logistics + Hospitals v. Progressive = Actuaries + Customers 24 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

Analysts 5 -10% Analytical Professionals — Can create algorithms 15 -20% Analytical Semi-Professionals — Can use visual tools, create simple models Analytical Amateurs — Can use spreadsheets 70 -80% 25 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

Taking Action 4 Analytics need to be embedded into the machinery of organizational action v Operational decision-making v Business processes v Manager and employee behavior v Customer expectations 26 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

The Analytical DELTA — Progress Moving to: Stage 1 Analytically Impaired Success Factor Stage 2 Localized Analytics Stage 3 Analytical Aspirations Stage 4 Analytical Companies Stage 5 Analytical Competitors Data Inconsistent, poor quality, poorly organized Data useable, but in functional or process silos Organization beginning to create centralized data repository Integrated, accurate, common data in central warehouse Relentless search for new data and metrics Enterprise n/a Islands of data, technology, and expertise Early stages of an enterprise-wide approach Key data, technology and analysts are central -ized or networked All key analytical resources centrally managed Leadership No awareness or interest Only at the function or process level Leaders beginning to recognize importance of analytics Leadership support for analytical competence Strong leadership passion for analytical competition Targets n/a Multiple disconnected targets that may not be strategically important Analytical efforts coalescing behind a small set of targets Analytical activity centered on a few key domains Analytics support the firm’s distinctive capability and strategy Analysts Few skills, and these attached to specific functions Isolated pockets of analysts with no communication Influx of analysts in key target areas Highly capable analysts in central or networked organization World-class professional analysts and attention to analytical amateurs PROGRESS 27 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

Next Steps for Analytics 4 Continual pursuit of new data types 4 Real-time action 4 Content mining, intangibles analytics 4 Engineering multi-modal decisionmaking 4 Model management / analytical resource management / knowledge management 28 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics

It Doesn’t Happen Overnight — Start Now! 4 Takes a while to put data and infrastructure foundation in place, and even longer to develop human capabilities, a fact-based culture, and “success stories” 4 Barclay’s five-year plan for “Information. Based Customer Management” 4 UPS — “We’ve been collecting data for six or seven years, but it’s only become usable in the last two or three, with enough time and experience to validate conclusions based on data. ” 29 | 2007 © All Rights Reserved. Thomas H. Davenport – Competing on Analytics