Developing a new product or business is a risky endeavor with a lot of uncertainty and there are a lot of ways you might go about perusing the opportunity you envision. Which one is best? How big might the opportunity be? Where are the biggest potential risks and how might you avoid or mitigate them? These are just some of the many questions that you or your investors probably want some insight into before taking the plunge. Strategy modeling can help answer some of these questions and provide some guidance or boundaries for others. New product or business innovators will typically do some level of ‘financial’ modeling and some level or a business plan that describes the tactics of a strategy. Modeling multiple strategy options to characterize the differences in potential value and risks between them can help you explore multiple options and improve your odds of success.
What is Strategy Modeling?
“Strategy” - A conscious and coherent set of chosen actions to achieve a goal or objective
“Model” - a system of postulates, data, and inferences presented as a mathematical description of an entity or state of affairs. also: a computer simulation based on such a system
Product or business strategies exist in the context of highly complex and uncertain ecosystems or environments with competing actors and alternatives, diverse and shifting customer needs as well as all the other political, economic, social, technological, environmental, and regulatory dynamics. A good strategy will be based on beliefs and assumptions about how those dynamics will play out, but often without any conscious recognition of those assumptions, or much consideration of their potential impact on the probability of the success of the strategy.
Modeling & simulation are common means of evaluating uncertainty and risk in engineering and financial domains but are usually applied to product or business strategies. That’s probably because there’s not a broadly accepted, canonical, or precise definition of the elements and structure of product and business strategy. However, there’s tremendous potential value to be gained by modeling strategies.
Benefits of modeling strategies:
- Modeling forces a clear definition of Strategy as a hypothesis in a comprehensive and consistent way.
- Testing and evaluating a strategy via modeling and simulation is much faster and cheaper than just executing the strategy in full, avoiding the high cost of strategic failures.
- When testing strategies is fast and cheap, it opens the opportunity to do comparative analysis of several strategy options in parallel and after preliminary analysis, select one or two for more detailed analysis and execution, improving the odds of success.
- Modeling, simulation and evaluate can expose critical assumptions or beliefs that have material impact on the viability of the strategy. These can be characterized as key risks or hinge factors that can be tested or preemptively mitigated.
The Elements of a Strategy Model
As described above, a strategy must be precisely defined in a consistent way to be modeled, simulated and compared. There are many academic frameworks and schools of thought that delve into strategy or common aspects of product or business strategy at a conceptual level, but they don’t all frame or bound their definition of strategy the same way and are not described in ways that allow them to fit together seamlessly. Through our many years of studying and applying many of these frameworks, we’ve developed a consistent and canonical framework for describing strategies (learn more about BRI’s Strategy Hypothesis Framework here), as well as a structured approach for modeling and evaluating them. Some of the key concepts of that approach are as follows:
Modeling Uncertainty
One of the most challenging aspects of modeling strategies is the highly uncertain nature of the environment that they operate within. Leveraging concepts from the science of Decision Analysis, we describe elements of a strategy as Choices, Uncertainties, and Data.
- Choices are decisions or outcomes within your control. They are the main elements of your strategy (i.e. which segment of the market you choose to serve with your solution).
- Uncertainties are a range of potential qualitative or quantitative outcomes that are outside of your control (i.e. what share of the market chooses your solution over alternatives).
- Data are factual data that help inform your strategy model and anchor it in reality (I.e. the total number of potential customers that exist today in your target market segment).
- Logic that defines the mathematical relationship between the choices, assumptions, and data (I.e. projected annual sales is a function of the total potential sales that year times the market share assumption).
Scalable Model Fidelity
Strategy models need to scale from low to high levels of fidelity based on the maturity of the strategy and the scale of the investment being made. If you’re just trying to decide if a new product or business strategy is worth exploring at all, you might start with a very low fidelity model that you can develop in a day. If you’re betting your company on a new transformational strategy, you probably have both the insight and the resources to develop a much higher fidelity model and perform statistical analysis that will reveal more useful insights and understanding. The higher the fidelity, the more assumptions, potential risks, and opportunities can be exposed, but they also require much greater time and effort to develop and maintain. So, the fidelity should be matched with the scale of the risk of the investment decision behind the strategy.
Supporting Evidence
While it’s extremely helpful to capture and model the uncertainty of key assumptions as ranges and perform statistical analysis, the basis of assumptions may vary wildly between models. To help calibrate the confidence in the input assumptions, we recommend that modeled assumptions also include a reference to the level of supporting evidence that the assumption is based on. A simple guess is better than nothing, but a range based on a quantitative primary research study is better and we can ascribe much higher confidence to those results than the guess. The combination of statistical impact of the uncertainty range & level of supporting evidence it’s based on can highlight the most important assumptions in your model and focus your activities and resources on reducing those as you scale investment behind the strategy. Don’t waste resources on assumptions with little impact, or high impact but based on very high confidence evidence. Focus on the assumptions that have big impact, but little evidence behind them.
Tools for Strategy Modeling
If you see the value in strategy modeling, you may be wondering how to put strategy modeling into practice. Of the “tools” that we’ve seen and tried to apply in various ways over the years, they generally fall into two categories:
- Strategy specific thought frameworks - These are academic frameworks that help guide thinking about strategies or specific dimensions of strategy such as SWOT, PESTL, Porter’s 5-forces, the Business Model Canvas or Lean Canvas, etc.
- Technology tools for modeling - The most common of these is the simple spreadsheet but there are also market research and data gathering tools, specialized financial calculator tools, engineering modeling and analysis software, etc.
However, we found a dearth of options that were specific to product and business strategy, that connected all the elements of strategy in a common framework and could also simplify the process of modeling and performing qualitative and quantitative statistical analysis on the models. While spreadsheets are tremendously versatile, they require users to create their own strategy framework and model from scratch, typically don’t include representation of the inherent uncertainty of assumptions in the model and are not easy to scale between different levels of model fidelity. After spending decades building strategy models in spreadsheets and trying other tools, we decided there’s a better way and started developing our Growth Forge® software.
Growth Forge is software for product or business Strategy Modeling (as well as managing strategies through a structured innovation process and portfolios of multiple strategies). These are problems we’re working to solve and continuously improve with Growth Forge:
- Support any strategy for any type of product or business model
- Cover all key dimensions of product or business Strategy with BRI’s Strategy Framework.
- Automatically expose assumption types, uncertainty & capture the level of supporting evidence behind them.
- Provide immediate simulation and statistical analysis at every step as you build your strategy hypothesis model.
- Scale seamlessly from low to higher fidelity strategy hypothesis models.
If you want help putting Strategy Modeling into practice in your own company or want to learn more about our Growth Forge software, schedule time with us here.
