Analytics in Strategic Decision Making Brazil Executive Seminar, April 2014 PRESENTED BY DR. FAIZUL HUQ OHIO UNIVERSITY Strategic Business Leadership Executive Education Seminar AGENDA • Introduction to Business Analytics. • Example of Analytical Tool Implementation for Supply Chain Sustainability • How to make Analytics work for Strategic Success • Practice Quiz 2 Introduction to Analytics What is Analytics? The extensive use of data, statistical and quantitative analysis, explanatory and predictive models and factbased management to drive decisions and actions. The most recent step in increasingly sophisticated and effective approaches to providing technical assistance to decision-making. Analytics Chronology Scientific Management • 1890’s – 1920’s Operational Research • World War II Operations Research/ Management Science Enterprise Resource Planning • 1950’s • 1990’s Decision Support Systems • 1970’s Related Methodologies Business Intelligence Competitive Intelligence Business Process Management Business Analytics Information-based Strategy Competitive Advantage Hierarchy of Analytics Sophistication Analytics Competitors Analytical Companies Analytical Aspirations Localized Analytics Analytically Impaired Sophistication Consumer Products • Anheuser Busch • E & J Gallo • Mars • Proctor & Gamble Industrial Products • CEMEX • John Deere & Company Financial Services • Barclay Bank • Capital One • Royal Bank of Canada • Progressive Casualty • WellPoint Pharmaceuticals • AstraZeneca • Solvay • Vertex Pharmaceuticals Hospitality & Entertainment • Boston Red Sox • Harrah Entertainment • Marriott International • New England Patriots Retail • Amazon • JC Penny • Tesco • Wal-Mart Who Uses Analytics (continued) Telecommunications • Sprint • O2 • Bouygues Telecom Transport • FedEx • Schneider National • United Parcel Service eCommerce • Google • Netflix • Yahoo! Netflix Started in 1997 by an angry Blockbuster customer Looked like another dot.com flop Online ordering Snail mail delivery Competing against giant with $3 Billion in Revenues Grew from $5 Million 1999 revenue to $1 Billion 2006 revenue Netflix- Competing Through Analytics •Deliver a personalized web page for each customer •Cinematch Movie Recommendation Engine •Developed by a mathematician •$1 Million prize for 10% improvement by an outsider •Discovering and focusing on most profitable customers Harrah’s Entertainment – Competing Through Analytics • No override of revenue management system • Measuring customer loyalty and targeting service levels accordingly • Optimize range and configuration of games • Provide options at bottlenecks Characteristics of Analytical Executives Passionate believers in analytical and fact-based decision making In God we trust; All others bring data. Barry Beracha, CEO of Earthgrains Do we think this is true? Or do we know? Gary Loveman, CEO of Caesar’s Entertainment Characteristics of Analytical Executives Passionate believers in analytical and fact-based decision making Appreciate analytical tools and methods Willing to act on the results of analyses Willing to manage a meritocracy Tools and Techniques in Analytics Spreadsheets Optimization Models Explanatory & Prediction Models Decision Analysis Models Data warehousing and data mining Online Analytical Processing (OLAP) Digital Dashboards Factors in Decision Making Multiple (antagonistic) goals and/or objectives Individual versus group decisions Restrictions on decisions Interactions among decisions Objective probability measurements Subjective probability assessments Factors in Decision Making Time pressures: • Potential deferment of some decisions • Possibility of obtaining additional information One-time versus repetitive decisions Attitudes regarding risk Example You meet a stranger who gives you $1000 in cash and then offers you an opportunity to: • Receive an additional $500, or • Watch him flip a coin and receive an additional $1000 if heads but receive nothing additional if it is tails. Do you choose to... • Take the sure thing? • Gamble? Example You meet a stranger who gives you $2000 in cash but requires that you: • Return $500 immediately, or • Watch him flip a coin and return nothing if heads but return $1000 if it is tails. Do you choose to... • Take the sure thing? • Gamble? Decision Tree Analysis $1,500 $2,000 EV = .5($2000)+.5($1000)=$1500 $1,000 Decision Analysis An attempt to make decision making explicit by structuring the decision process Permits the analysis of the consistency of decision making Assists supervision in evaluating the decision making of subordinates Neither necessary nor sufficient to produce good results but may increase the frequency of obtaining good results Allows for consistent and unbiased comparisons of options Good Decision – Bad Outcome In 1965, Andre-Francois Raffray (age 47) agreed to pay $500 a month • To Jeanne Calment (age 90) until her death • To buy her apartment in Arles “for life” In December 1995, Raffray died at age 77 having paid more than $180,000 for the apartment • And Jeanne celebrated her 120th birthday • Raffray’s widow and children are obligated to continue payments Decision Models Assist decision makers by providing information helpful in resolving a pending decision Always involve a degree of abstraction and simplification of the actual decision environment Do not create information, but rather concentrate and focus information The Basic Proposal of Decision Analysis Improvements in the decision making process will occur if the methods of science are applied to the decisions which managers must make. Something is to be gained from making the learningadaptive processes of management more nearly like those of science. Modeling and Decision Making Problem Recognition Enrich Model Simplify Model Problem Definition Correct Model Model Formulation Model Solution And Validation Data Gathering and Processing Implement Model Evaluate Model Effectiveness Termination DHL Application of Analytics for Sustainability The degradation of the environment has led many governments and customers to pressure businesses to make their operations more environmentally friendly. The case illustrates an effective example of corporate social responsibility. Specifically, it demonstrates how a small increase in a supply chain budget can drastically reduce carbon dioxide emissions in the transportation of LCD TVs from their manufacturing bases to a distribution centre. source: Ivey/NUS Cases DHL Sustainability Case Cont… Issues: • Environmental Sustainability; Linear Programming; Logistics; Optimization Analysis; Spreadsheet Modeling; Corporate Social Responsibility; China Disciplines: • Management Science, Operations Management, International Industries: • Transportation and Warehousing Setting: • China, Large, 2011 Please look at the Excel Spreadsheet Handout with the Data Making Analytics Help in Strategic Advantage Make Analytics a Common Practice in the Company by Expending Effort to Always Apply Analytical Tools for Decision Making Get Buy In from Top to Bottom of the Company That Will Help Build an Operational Infrastructure for the Application of Analytics Employ the Workforce Necessary to Effectively and Successfully Implement Analytics for Business Decision Making Make Analytics a Common Practice in the Company by Expending Effort to Always Apply Analytical Tools for Decision Making In order for a company to be successful in their use of Business Analytics(BA) it must expend the most effort to truly implement BA in their organizational decision making Get Buy In from Top to Bottom of the Company That Will Help Build an Operational Infrastructure for the Application of Analytics The successful use of BA requires building Operational Infrastructures within its Supply chain and Intra-organizational entities that can continuously support the most effective use of BA. Employ the Workforce Necessary to Effectively and Successfully Implement Analytics for Business Decision Making For successful use of BA in organizational decision making the personnel must be in place who are dedicated to and capable of effectively employ BA for making decisions. Make Analytics a Common Practice in the Company Permeate the Company’s Decision Making Process With the Use of Business Analytics Make Decision Making an Integrated Process Across The Company Make the Use of Analytics Strategically and Mission Focused Be More Aggressive in Acquiring/Learning Sophisticated and Specific analytical Tools Permeate the Company’s Decision Making Process With the Use of Business Analytics • Expand BA practices where feasible • Companies with reliance on BA are more successful • Low reliance on BA for Decision making leads to less effective implementation of BA • Make BA second nature within the company • Shift BA use from occasional to routine leading to greater effectiveness Reliance on BA and Effectiveness Source: SAS Institute/Bloomberg Research Services Reliance on Analytics Source: SAS Institute/Bloomberg Research Services Make Decision Making an Integrated Process Across The Company • Integrate Analytics organization wide • Do not isolate BA to a single department function • Avoid siloing of data and functionalities • Breakdown Silos • Create cross-divisional data teams • Create transparency through data sharing and process cooperation across the company Cross Divisional Integration Source: SAS Institute/Bloomberg Research Services Make the Use of Analytics Strategically and Mission Focused • By bringing Analytics to task a company is twice as likely to be successful then not • Majority of companies using BA employ Analytics heavily in Finance • Majority of the successful companies use Analytics in Marketing and Sales, SCM, and Product Development • Start with one or two BA initiatives because employing Analytics can be complex. Summary Data of Analytics use in Functional areas Source: SAS Institute/Bloomberg Research Services Be More Aggressive in Acquiring/Learning Sophisticated and Specific analytical Tools • • • • • Use Business reporting, KPI, and Dashboards Employ sophisticated Forecasting tool Undertake Data and Text Mining Use Simulations and Scenario development Employ Web Analytics Use of Analytics Tools by Companies Source: SAS Institute/Bloomberg Research Services Build Operational Infrastructure Articulate a Strategy for Managing and Accessing Data Acquire and Implement the Appropriate Technology Needed for Data Driven Analytics Activities Formalize the Data Management Process Data Access Summary Source: SAS Institute/Bloomberg Research Services Articulate a Strategy for Managing and Accessing Data • Improve the Quality, Integrity, and Consistency of Data • Increase Accessibility of Data that leads to Positive and Effective BA efforts • Make Business Information Readily Available to those who need it • Make the Source of Information and Data Central • Facilitate Data and Information Sharing across the Company Acquire and Implement the Appropriate Technology needed for Data Driven Analytics Activities • Much of BA is fairly low-tech. Such as Standard Electronic Spreadsheets • Additionally acquire Software and other Technology that is more Complex and Capable than Standard Spreadsheets • Integrate Software for Data Mining, Forecasting, and Predictive Analysis into Business Processes • Make the Technology for Accessing the Data needed for Analysis • Standardize the Technology for Accessing, Integrating, and Analyzing information from all functional areas. Use of Technology for Analytics in Firms Source: SAS Institute/Bloomberg Research Services Formalize the Data Management Process • Put in place Appropriate Data Management Processes • Put in place general Data-Governance Rules and Policies • Articulate Defined Data Stewardship • Identify Master Data Definitions Survey Information of Data Management Process Source: SAS Institute/Bloomberg Research Services Employ the Workforce Necessary Get Buy In From The Company Hierarchy For Acquisition of the right Personnel Establish Clear Lines of Communication Thus Creating Transparency in The Decision Making Process Hire Talented Analysts and Also Develop Home Grown Ones Get Buy In From The Company Hierarchy For Acquisition of the right Personnel • The Three Key areas to focus on are: Senior Executive Buy in Everyday Reliance on Analytics Required Analytics Capability Enabled Talent Senior Leadership Buy in Data Summary Source: SAS Institute/Bloomberg Research Services Perceived Positive Impact Source: SAS Institute/Bloomberg Research Services Analytics Capability Enabled Talent Source: SAS Institute/Bloomberg Research Services Summary of the Steps Needed • Permeate the Company’s Decision Making Process With the Use of Business Analytics • Make Decision Making an Integrated Process Across The Company • Make the Use of Analytics Strategically and Mission Focused • Be More Aggressive in Acquiring/Learning Sophisticated and Specific analytical Tools • Articulate a Strategy for Managing and Accessing Data • Acquire and Implement the Appropriate Technology Needed For Data Driven Analytics Activities • Formalize the Data Management Process • Get Buy In From The Company Hierarchy For Acquisition of the right Personnel • Establish Clear Lines of Communication s Thus Creating Transparency in the Decision Making Process • Hire Talented Analyst and Develop Home Grown Ones Establish Clear Lines of Communication Thus Creating Transparency in The Decision Making Process Formalize the Data Management Process Striking a Balance • Data versus Judgment The Optimal Balance depends on the Number of Factors, the Tools, the People, and the Decision at hand • Modeling for Decision Making The Modeling tool is Context Dependent. • Analysis versus Intuition There is no fixed balance between the reliance on Intuition and Experience and reliance on Quantitative Data and Analysis Thank you ? ?QUESTION? ? Sample Quiz for CAP • • • • A sample Quiz to Test Your Analytics Acumen CAP stands for Certified Analytics Professional The Certification is Given by INFORMS I will Grade These and Return them to you at the Banquet. Thank You.