Implementation/The Future

1. Implementation/The Future • A Look Back • A Look Ahead • ME as Lifetime Learning

2. A Look Back . . . • Marketing Engineering is Marketing. • Marketing Engineering is a means to an end. • Models require judgement. • Whole > sum of parts. • Software Û rapid prototyping (personal modeling).

3. Implementation:A Five Step Process 1. Problem identification 2. Modeling 3. Calibration 4. Implementation 5. Control/Improvement

4. Implementation:Step 1—Problem Identification • Review symptoms Û diagnose disease. • Eliminate irrelevant issues; include all relevant issues. • Agree on problem with all relevant stake-holders (sources of funds, data, implementation responsibility): generate shared ownership up front.

5. Implementation:Step 2—Modeling • Variables • Relationships • Objectives

6. Implementation:Step 3—Calibration (Assign values to parameters) • Objective • Subjective (judgmental) • Combined (Bayesian)

7. Implementation:Step 4—Implementation • Be opportunistic • Start simple/keep it simple • Begin with an end in mind (Not “What data do I have?”)

8. Implementation:Step 5—Control/Improvement • Make it a program,not a project

9. What Can You Do NOW? • 1. Find a problem: • New Product entry?? • Dumb spreadsheet? • Resource allocation? • 2. Build a boxes and arrows diagram. • 3. Develop a model: • Yourself (off-the-shelf)/ME adaptation/Excel. • In-house expert (needs expertise to build/use model). • Expert consultant (new model/state-of-the-art methodology). • 4. Calibrate; Evaluate; Implement; Control.

10. Marketing Engineering:A Look Ahead • Data warehousing • Online analytic processing (OLAP) • Intelligent marketing systems • Simulations • Groupware • Improved user interfaces • ASP model/Lifetime learning

11. Share & Merchandising 1 2 40 1 0 30 8 Merchandising Index Volume Share 6 20 4 10 2 0 0 01-31-88 07-17-88 01-31-89 Volume Share Merchandising Index To: Sizzle Brand Manager From: CoverStory Date: 07/05/89 Subject: Sizzle Brand Summary for Twelve Weeks Ending May 21, 1989 Sizzle’s share of type in total United States was 8.3 in the C&B Juice/Drink category for the twelve weeks ending 5/21/98. This is an increase of 0.2 points from a year earlier, but down 0.3 from last period. This reflects volume sales of 8.2 million gallons. Category volume (currently 99.9 million gallons) declined 1.3% from a year earlier. Sizzle’s share of type is 8.3—up 0.2from the same period last year. Display activity and unsupported price cuts rose over the past year—unsupported price cuts from 38 points to 46. Featuring and price remained at about the same level as a year earlier. Components of Sizzle Share Among Sizzle’s major competitors, the principal gainers are: Shakey: up 2.5 points from last year to 32.6 Private Label: +0.5 to 19.9 (but down 0.3 since last period) and loser: Generic Seltzer: –0.7 to 3.5 Shakey’s share of type increase is . . . Components of Sizzle Share Among components of Sizzle, the principal gainer is: Sizzle 64oz: up 0.5 points from last year to 3.7 and losers: Sizzle 48 oz: down 0.2 to 1.9 Sizzle 32 oz: down 0.1 to 0.7 Sizzle 64 oz’s share of type increase is partly due to 11.3 points ride in % ACV with Display vs. year ago. Xerox 10-98 6 - 8

12. Modeling Technology Intelligent/automated decision models Groupware plus decision models OLAP plus decision models MarketingEngineeringtomorrow Stand-alone marketing decision models General purpose analysis tools (e.g., SPSS, LP packages) MarketingEngineeringtoday Model User Analyst Trainedmanager(in marketingengineering) Novicemanager Non-managerialemployee Forecasting Allocation and optimization Simulation An overview of the evolution of Marketing Engineering to support a wider range of users and decision tasks using emerging technologies Explanation Decision Tasks Xerox 10-98 6 - 9

13. The New Learning Model • We are all becoming knowledge workers • Learning and work are becoming contemporaneous. • The shelf life of information/knowledge is shrinking dramatically • Learning is becoming a perpetual process. • Information is becoming freely available to learners • Learning is becoming a democratic process. • New knowledge/information is being created at mind-numbing rates. • Learning is becoming a discernment process. • Knowledge is needed “just-in-time,” not “just-in-case” • Learning is becoming context-embedded. • Career moves and job changes are becoming more frequent. • Learning is becoming self-directed.

14. http: Request for a Model Web Server (Model Access Point) Browser Client (Model User) Java: A network-centric computer programming language. RMI: Remote Method Invocation A system that allows a Java object running on one machine to communicate with methods (e.g., models) of another Java object running on a different Java machine. http: Hypertext Transfer Protocol The protocol that defines communication between Web Servers and Clients. http: Response A Java Applet (user interface) Java RMI Java RMI Data Server (Data Store) Application Server (Model Store) Java RMI The Architecture of www.valueharvest.com

15. Our Future Plans forMarketing Engineering • Continue to test effects of Marketing Engineering under controlled experimental conditions • Further implement ideas/tools in companies • Professional versions on line • Continuous improvement of existing models • Develop new models (e.g., generalized resource allocator, sales territory alignment, enhanced choice modeling) • Marketing Engineering on the Net as ASP • ME/HCV Portals—stay connected---www,mktgeng.com/www.valueharvest.com