We live in a world with great uncertainty and thus the common methods of forecasting often times fail to predict the future. During business school I had the opportunity to learn about scenario planning from one of the early practitioners, Jay Ogilvy who I credit with many of the concepts in this series of posts. I have used this method in a few instances to frame up a market opportunity and stress test how resilient our strategy will be.
Why scenario planning?
Scenario planning is a useful tool when you operate in an uncertain market and there are many potential futures. This is in contrast to a forecast that is best for a market with little uncertainty. Even some of the smartest individuals have made poor forecasts, including this quote from Steve Ballmer during his time as CEO of Microsoft and Ken Olsen the founder of a microchip company. Everyday financial analysts are building models to predict the future of a company that are fraught with failed logic like these quotes. The reason for scenarios is to diverge thinking around potential outcomes. What action would you take if you were Microsoft and you believed the opposite of what Ballmer said?
1977: “There is no reason for any individual to have a computer in his home.” — Ken Olsen, founder of Digital Equipment Corp.
2007: “There’s no chance that the iPhone is going to get any significant market share.” — Steve Ballmer, Microsoft CEO.
Source is Free Code Camp Medium Blog
The image below from my course at UC-Berkeley does a great job showing these two differences and how scenario planning allows for a more expansive view of the future.
Over the course of a series of posts I’ll walk through developing scenarios. Before we do that wanted to share some principles around scenarios:
- Scenarios are hypotheses of the future, not predictions
- Scenarios encourage divergent thinking by design
- Scenario set the stage to plan for multiple futures
- Scenarios are rich, data-driven, stories about tomorrow that can help you make better decisions today
The framework I’ll use for the series of post is based on the one I was taught during my time at UC-Berkeley by Jay Ogilvy.
Over the course of the next month I’ll break down the above framework into 4 posts, including this one:
- Define your focal issue
- Key Factors, Environmental Forces and Critical Uncertainties
- Scenario Logics and Scenarios
- Implications, Options and Early Indicators
Define your focal issue
Why spend time on defining the issue? I have found in my career that asking the right question is the most important step in getting to the answer that will most likely solve your customer’s need. In addition, this sets the ground work for the analysis.
I will use the home improvement industry as the example for this analysis. Despite many companies attacking the industry over the years, there are a number of challenges that face homeowners.
Here are a few pointers to defining the focal issue:
- The focal issue should cover a time horizon that is far enough out where there is significant uncertainty.
- The focal issue should be backed by research and discovery
- The focal issue should be specific enough. I like to use a model like a job story that has these elements: Situation + Motivation + Outcome + Time Horizon
For this example my focal issue is:
How will homeowners complete simple maintenance and repair projects on their home over the next 10 years?
I have selected this as there is a large emphasis currently on new business models (e.g. Uber of X), new technology (e.g. AI / Robotics) and demographics are changing (e.g. people do not have the skills or time to do this work themselves).
In the next article I’ll go deeper on the Key Factors, Environmental Forces and Critical Uncertainties that we could face. This is the most research intensive step of the process to help frame up which scenarios are most relevant.
Please feel free to post questions or comments.