In two previous posts, I introduced a case which offers a practical, real world example of how risk analysis can enrich the strategic planning process. We learned of PrimeCorp (a disguised name), a large company with a national presence in the U.S., and met Jim and Curtis, PrimeCorp’s head of Strategic Planning and CEO, respectively. If you haven’t read Parts I and II of this series of posts, please do so now. It contains background needed to understand this and the following post.
Putting the Model to Work
The first revelation of PrimeCorp’s risk-adjusted forecast was that it was lower than the original forecast.
To illustrate how this happened, imagine forecasting your personal income for next year. Let’s say that your salary is X dollars per year, so that is your original forecast. But with a risk-adjusted view of your future earnings, you might also acknowledge a 15% chance of getting a bonus equal to 10% of your salary, and you might also acknowledge a 20% chance of losing your job and not finding another one for the rest of the year. So 15% of the time your expected income would be X / 2 (this reflects an assumption that you have an equal chance of losing your job on any day of the year, in which case your expected income would be the same as losing your job halfway through the year). 60% of the time your income would simply be X, and 25% of the time your income would be 1.1 * X.
By combining these possible outcomes with their odds of taking place, we get:
( .15 * 1.1 * X) + ( .65 * X) + (.20 * .5 * X) = .915 * X
In other words, the risk-adjusted forecast for your income is 91.5% of your salary.
In capturing the characteristics of ‘below plan’ and above plan years at PrimeCorp, we learned that given an equal chance of each, there was more downside potential in the ‘below plan’ years than upside potential in the ‘above plan’ years. As a result, their risk-adjusted forecast was below the original forecast. This was a bit of a revelation to PrimeCorp’s leadership team.
Changing the Odds
To then forecast the prospective impact of a strategy management program, we asked PrimeCorp’s leaders to adjust the odds of having a ‘below’ ‘above’, and ‘as planned’ year given successful execution of their strategy. The responses ranged from no or very modest impact from the skeptics, to a cautiously larger impact from those who supported the idea of implementing our proposed strategic management process.
After some discussion, their sense of the impact was consolidated into three scenarios:
- ‘Low’ impact, with a small avoidance of the ‘below plan’ outcome, the same odds of an ‘as planned’ outcome, and no improvement in the likelihood of the ‘above plan’ outcome, with respective odds of 20%, 55%, and 25%;
- ‘Moderate’ impact, shifting the curve, with respective odds of 20%, 49%, and 31%;
- ‘Improved’ impact, with respective odds of 15%, 55%, and 30%.
Running the model with PrimeCorp’s own expectations yielded definitive results. Even under the most conservative scenario, the investment in the strategic management system would be paid back in under three years. And the forecast was based entirely on inputs from PrimeCorp.
Next: Outcomes at PrimeCorp, and the case summary.