strategic business leadership executive education seminar analytics in strategic decision making...

Strategic Business LeadershipExecutive Education Seminar

Analytics in Strategic Decision Making Brazil Executive Seminar, April 2014

PRESENTED BYDR. FAIZUL HUQOHIO UNIVERSITY

AGENDA

2

• Introduction to Business Analytics.

• Example of Analytical Tool Implementation for Supply Chain Sustainability

• How to make Analytics work for Strategic Success

• Practice Quiz

Introduction to Analytics

What is Analytics?The extensive use of data, statistical and quantitative analysis, explanatory and predictive models and fact-based 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• 1950’s

Decision Support Systems• 1970’s

Enterprise Resource Planning• 1990’s

Related MethodologiesBusiness Intelligence

Competitive Intelligence

Business Process Management

Business Analytics

Information-based Strategy

Hierarchy of Analytics Sophistication

Analytically Impaired

Localized Analytics

Analytical Aspirations

Analytical Companies

Analytics Competitors

Com

petit

ive

Adv

anta

ge

Sophistication

Consumer Products

• Anheuser Busch• E & J Gallo• Mars• Proctor & Gamble

Financial Services

• Barclay Bank• Capital One• Royal Bank of Canada• Progressive Casualty• WellPoint

Hospitality & Entertainment

• Boston Red Sox• Harrah Entertainment• Marriott International• New England Patriots

Industrial Products

• CEMEX• John Deere & Company

Pharmaceuticals

• AstraZeneca• Solvay• Vertex Pharmaceuticals

Retail

• Amazon• JC Penny• Tesco• Wal-Mart

Telecommunications

• Sprint• O2• Bouygues Telecom

Transport

• FedEx• Schneider National• United Parcel Service

eCommerce

• Google• Netflix• Yahoo!

Who Uses Analytics (continued)

NetflixStarted in 1997 by an angry Blockbuster customerLooked like another dot.com flop

Online orderingSnail mail deliveryCompeting 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 AnalyticsSpreadsheets

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

Subjective probability assessments

Interactions among decisions

Objective probability measurements

Restrictions on decisions

Factors in Decision MakingTime pressures:

• Potential deferment of some decisions

• Possibility of obtaining additional information

One-time versus repetitive decisions

Attitudes regarding risk

ExampleYou 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?

ExampleYou 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?

Gamble

Take Sure Thing$1,500

Heads: P=0.5 $2,000

Tails: P=0.5$1,000EV = .5($2000)+.5($1000)=$1500

Decision Tree Analysis

Decision AnalysisAn 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 OutcomeIn 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 ModelsAssist 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 learning-adaptive processes of management more nearly like those of science.

Problem Recognition

ImplementModel

Termination

EvaluateModel

Effectiveness

Simplify Model

Correct Model

Enrich Model

Model Solution And

Validation

ProblemDefinition

ModelFormulation

Data Gathering and

Processing

Modeling and Decision Making

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, 2011Please 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

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

Make Analytics a Common Practice in the Company by Expending Effort to Always Apply Analytical Tools for Decision Making

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.

Get Buy In from Top to Bottom of the Company That Will Help Build an Operational Infrastructure for the Application of

Analytics

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.

Employ the Workforce Necessary to Effectively and Successfully Implement Analytics for Business Decision Making

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


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


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


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


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


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



• 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


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


Perceived Positive Impact


Analytics Capability Enabled Talent


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 OnesEstablish Clear Lines of Communication Thus Creating Transparency in The Decision Making 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.

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