Each of our service offerings is built on a platform of sound research and proven practices, and shaped by the following three principles:
- KIS – Keep it Simple
- People First
- Efficiency, scalability and cost-effectiveness
Simple does not mean simplistic. As you will see below there is a lot of research, conducted over several decades and validated by numerous researchers, supporting the methods we use. What the research tells us is that the methods themselves do not have to be complicated to be effective.
Our forecasting method of role-play simulation – Essential Business War Games – has repeatedly been shown to provide as much as 2x the accuracy of expert opinion and complex game theory-based modeling in conflict situations. Such situations occur any time you make a strategic move in the marketplace.
Modern society has evolved into a very expert-centric culture, and the use of experts can have great benefit. But there is one area where experts have proven to be of little value – in forecasting the outcome of future events. Here the research is unequivocal. Non-experts, working off publicly-available information, outperform the experts every time.
Our COMPETE Management Process enables and encourages the people already working in your company – front-line sales and service people, line managers and middle management – to make meaningful contributions to your accuracy in forecasting the likely outcome of business events such as new product launches, new market entries, and other new initiatives.
Efficiency, scalability and cost-effectiveness
Building on the two principles above, our approach is to add practical, useful skills to the toolkit of existing personnel, deploy processes and techniques that require a minimum of new technology, and can be used in departments, business units, or across an entire enterprise.
Sample Peer-reviewed and Scholarly Research
Green, K. C. & Armstrong, J. S. (2011), “Role thinking: Standing in other people’s shoes to forecast decisions in conflicts”. International Journal of Forecasting, 27, 69-80.
Schwarz, Jan Oliver. (2009), “Business wargaming: developing foresight within a strategic simulation”. Technology Analysis and Strategic Management, Volume 21, Number 3, pp. 291-305.
Tressler, David M. (2007), “Negotiation in the new strategic environment: Lessons from Iraq. Strategic Studies Institute, U.S. Army.
Pinker, Edieal J. (2007), “An Analysis of Short-Term Responses to Threats of Terrorism” Management Science, Vol 5, No. 6. pp. 865-880.
Green, K. C. & Armstrong, J. S. (2007), “Value of expertise for forecasting decisions in conflicts”, Interfaces, 37, 287-299.
Green, K. C. (2005), “Game theory, simulated interaction, and unaided judgment for forecasting decisions in conflicts,” International Journal of Forecasting, 21, 463-472.
Trotman, Ken T. (2005), “Auditor negotiations: An examination of the efficacy of intervention methods”.The Accounting Review, Vol. 80, No. 1. pp. 349-367.
Green, K. C. & Armstrong, J. S. (2005), ”The war in Iraq: Should we have expected better forecasts?” Foresight, 2, 50-52.
Miller, Ken & Don Brown. (2003), “Risk Assessment War Game (RAW)”. US Army & University of Virgina.
Green, K. C. (2002), “Forecasting decisions in conflict situations: A comparison of game theory, role-playing, and unaided judgment”. International Journal of Forecasting, 18, 321-344.
Armstrong, J. S. (2002), “Assessing game theory, role playing, and unaided judg-ment,” International Journal of Forecasting, 18 (3), 345-242.
Armstrong, J. S. (2001), “Role playing: A method to forecast decisions.” In Armstrong, J. S. (Ed.), Principles of Forecasting: A Handbook for Researchers and Practitioners. Norwell, MA: Kluwer Academic Publishers, 15-30.
Armstrong, J. S. (2001), “Combining forecasts.” In Armstrong, J. S. (Ed.), Principles of Forecasting: A Handbook for Researchers and Practitioners. Norwell, MA: Kluwer Academic Publishers, 417-439.
Singer, Alan E. (1990), “Forecasting Competitor’s Actions: An evaluation of alternative ways of analyzing business competition”. International Journal of Forecasting, 75-88.
Armstrong, J.S. (1987), “Forecasting Methods For Conflict Situations”, in G. Wright and P. Ayton (eds.), Judgmental Forecasting, 157-176.
Armstrong, J.S. (1980), “The Seer-Sucker Theory: The Value of Experts in Forecast-ing,” Technology Review, June/July, 16-24.
Cocozza, Joseph J. and Steadman, Henry J. (1978), “Prediction in psychiatry: An Example of misplaced confidence in experts,” Social Problems, 25: 265-276.
Chamberlin, T.C., (1965), “The method of multiple working hypotheses.” Science, 148: 754-759. Reprinted from Science, 1980.
Cowles, Alfred, (1933), “Can stock market forecasters forecast?” Econometrica, 1: 309-324.
Gilad, Benjamin (2008), ”Business War Games” Career Press.
Hoch, J. Stephen (2004), “Wharton on Making Decisions” Wiley.
Yates, Frank J. (2003), “Decision Management: How to assure better decisions in your company”. Jossey-Bass.
Armstrong, J. S. (2001), “Principles of forecasting – A handbook for researchers and practitioners” (International series in operational research & management science). Springer.
Sample General Publication Articles
Role Playing as a Forecasting Tool from Knowledge@Wharton
Managing the Strategy Journey from McKinsey