Every strategy analysis or decision contains some mechanism to assess outcomes; that is, some way to determine whether one strategy is better or worse than another. The assessment model may be in a computer (a spreadsheet or simulation model), or it may be in someone’s head (based on experience and/or expert knowledge, and known as “mental models”).
The quality of the assessment model you use is vital to the quality of your strategy decision (and its outcomes). To many people, “the computer” calculates a number, and that’s that. They may agree with the number or they may disagree with the number, but they don’t know that the number itself depends on the kind of model they used. Models can be based on accounting principles, trend analysis, rules of thumb, customer purchase decisions, and so on, and they can easily produce different numbers.
Just as different tools are not equally valid for every construction task, different models are not equally valid for all decisions. The model for your strategy decisions will serve as a strategy calculator, so it ought to work with strategy concepts. For instance, if customer preferences may change, if advances in technology may enhance products, or if new competitors may enter, then it’s essential to use a model that explicitly takes customers, quality, and competitors into account. (Accounting-based models don’t.) Because extrapolations implicitly assume that the past will persist, it’s critical also to make sure that the model doesn’t extrapolate historical trends. In effect, extrapolations lock in the past and make it hard for managers to discover threats, opportunities, and discontinuities.
Because we humans always use models (in our heads or in our computers) to predict outcomes, there’s no alternative to working with models in strategy analysis. It’s good to be skeptical of models (in our heads or in our computers), because skepticism begets rigor and insight. It’s good also to remember that mental models are not inherently superior to computer-based quantitative models. Yes, computers have limitations: for example, they calculate whether they’re given good or bad data. But so do people. The relevant question is not whether a quantitative model is perfect. The relevant question is whether managers can make better decisions — and one way or another, they will make decisions — by combining a quantitative model with their insight, or by using their in-sight alone. It’s tough to beat Garry Kasparov at chess, and it’s tough to beat the Deep Blue computer at chess, and it would probably be impossible to beat a Blue-Kasparov team.
We at ACS have decades of experience creating innovative, customized strategy-simulation models and simulation software. Companies use our strategy simulators to make much better business decisions, to test what-if questions, and to teach competitive strategy skills to their managers. Our simulation solutions don’t fall into the common traps of conventional analytic models, such as extrapolating the past into the future, looking only at financial information, or ignoring competition by focusing only on the client company.
We can run your strategy simulation for you, or we can turn the model over to you. You can run the strategy simulator yourself as often as you like, and update it as new data become available.