James Mike Jay, MSE, MBA

About

Mike has more than 40 years' experience in executing studies in consumer insights, pricing, sales force planning, and customer relationship management.  Recent achievements include developing a dynamic pricing engine for a musical instrument eCommerce site using scraped data from over 20 websites and 50,000 products.  Utilizing advanced analytics based on syndicated data was used to cull five models from a legacy motorcycle company product offering.  He has developed product automotive demand models based on click stream data and dealer transaction data. He has directed the statistics department for a leading marketing research firm with responsibilities for firm wide statistical analysis of all surveys and ad-hoc marketing science projects in segmentation, analytic CRM and customer loyalty modeling. Decision technologies he is comfortable with include SQL, SAS, R, Tableau, Alteryx and Looker on a variety of platforms including SQL Server and BigQuery.

Education

Master of Business Administration, Rutgers University, Newark, NJ, completed course work requirements for a PhD in Marketing (ABD), Beta Gamma Sigma recognition.

Master of Science in Engineering, Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, DeVleig Foundation Fellow. Graduate coursework in operations research, simulation methods, information systems and statistics.

Master of Science, Engineering, Oakland University, Rochester, MI. Graduate coursework in control theory, discrete math and operations research.

Bachelor of Science, General Engineering, Oakland University, Rochester, MI, graduated with departmental honors.

Expertise

Analytics should be the heart of any strategy or tactical plan.  Data used ideally starts with internal sources and calibrated against experimental or external data.  Forge ahead into the grey and use analytics to make your plan.

Publications

Zetu, D. and Cheng, J. and Jay, J.M. and Lo, B. (2003) When will a consumer consider buying another car? , International Conference on Information Technology: Research and Education, 2003, Proceedings ITRE2003, pp. 530-53

Powers, K.I. and Jay, J.M. and Gao, T. (2003) Application of the LOESS Procedure for Monitoring and Detecting Critical Movements in the US Automobile Market, Proceedings of the 28th SAS^® Users Group International Conference, volume 267

Jay, J.M., Van Zandt, R.N. and Hanson, P.G. (1984) Fourth Generation Computer Language Bridges Gap for Production and Inventory Data in Business Cycle, Industrial Engineering, Vol. 16(9)

Richards, J.H. and Jay, J.M. (1983) Production Capability Analysis and Its Use In Chemical Plant Design, Proceedings of the 1983 Annual Industrial Engineering Conference, pp. 656-661