What is scenario planning?
While an environmental analysis seeks to understand how the direction of identifiable trends may affect a company’s ability to profit in the future, there are, unavoidably, some “uncertainties” that no one can predict with accuracy.
For example, things like the results of a presidential election, the content of new legislation, or the standards that an industry will adopt.
There’s no way to predict the future, but as executives we still have to make decisions even if important factors are not well known.
To deal with these uncertainties and make
This technique is called Scenario Planning and is used to create alternative probable “futures” which you can use to test your strategy.
The technique has been around since the mid-1960s and is very popular in companies like Royal Dutch Shell and Microsoft among others.
Creating your scenarios
In its simplest version, you would start by coming up with a pair of uncertainties, and define two potential outcomes for each that could happen by the end of the period of evaluation, usually five, ten or fifteen years.
When you cross the two variables against each other (each with two possible outcomes), it results in four different combinations.
These four combinations, along with the trends that you identified in your environmental analysis, each form a potential scenario, which is just a probable version of the future.
For example, let’s say that as part of an environmental analysis you have some doubts about whether or not electric vehicles would get national approval to operate in self-driving mode within the next five years.
The penetration of electric vehicles (EV) in the US is advancing increasingly fast, and there’s no doubt that these will become more and more popular over time. That makes EV penetration a trend, because you can accurately predict where it is going: up.
However, getting national approval for driverless circulation in the next five years is an uncertainty, since no one can provide a definitive answer for it.
To complete the analysis, let’s pick oil prices (whether they will be high or low) as your second uncertainty.
By crossing your two uncertainties against each other, you get four combinations of things that could happen by the end of the fifth year:
- National approval with high oil prices,
- National approval with low oil prices,
- No national approval with high oil prices, and
- No national approval with low oil prices.
The final step is to think about the implications of each of the combinations above and complement those with the future state of the known trends.
For example, if the EV industry gets national approval for driverless cars, AND oil prices are high (case 1 above), then you could assume that under that scenario the penetration of EV charging stations across the US will be extremely high, and that leading vendors of enabling technologies such as Lidar sensors and other vision equipment used in driverless navigation will become powerful.
Next, you follow the same process for each of the remaining combinations, and document each scenario based on the known information and the implications of the particular intersection of uncertainties.
You can now use these scenarios to test your strategy against each and adjust your plans accordingly if needed.
For example, from scenario 1 above, an EV manufacturer may conclude that they need to invest in a promising Lidar startup now to mitigate the negotiation power that vendors may have if that case materializes.
Scenario planning exercises can be highly complex and take months to complete, even years for companies in the oil and power industries. Because of this labor intensity, there are industries where the benefits don’t justify the effort.
But in cases where an uncertainty could make or break the business, it can be a powerful tool to help you make good strategic decisions.