´Can You Ever be Certain? Part II Cost Benefit Newsletter 86, 6 February 2006
Good business case analysis will not eliminate uncertainty about the results of decisions, but it can reduce risk to a minimum, measure what remains, and provide the means for keeping risk under control as the action goes forward.
Continued from Part I last week
Decisions to enter new markets, change strategy, or
launch alliances come with risks as well as potential rewards. That has always been the case, but in the current business climate, there is a new urgency to questions like these:
- "How do we know that we're going to see the projected results?"
- "Which is the better business decision? Can we be sure?"
- "How can I prove, later, that I'm acting responsibly now?"
Most people know that business case analysis is supposed to answer such questions, firmly and finally. Nevertheless, when we first hear from new clients or professionals coming to our business case seminars, some say they have been haunted by the questions even after completing a business case analysis. What kind of certainty should they expect from business case results?
In Part I (Newsletter 85) I discussed some pitfalls on the road to the "comfortable certainty" and accountability that decision makers are looking for. In Part II, below, we'll ask if anyone can really expect good answers to the questions above. Next week, in Part III, we'll decide whether or not to trust them.
Risk and Sensitivity Analysis: Think "Elementary"
Questions about certainty in business call for good risk analysis. "Good," by the way, does not have to mean "advanced" or "inaccessible to ordinary business people."
The kind of certainty claimed here comes from the world of elementary statistics." To learn and use what follows (and Part III next week) you will need a few probability terms from the basic introductory statistics course, the one for "non-statistical people". You will not need to go beyond that. Some of the leading risk analysis software tools come with excellent user guides that do not even assume that much background.
The purpose here is not to teach risk analysis, but rather to give some sense of what it can do. The business people and other professionals we see in our business case seminars often ask why so few business case builders follow through with good risk analysis. They ask, that is, once they see, how approachable it is and how useful the results are in building comfortable certainty and accountability.
Question 1: How do we know we're going to see the projected results?
The business case for a entering a new product market projects a net gain of $590,000 over the next five years. Everyone knows, however, that the real result will not be $590 thousand, exactly: it will be something more or something less. But can the business case builder say anything more about the likelihood of other results? Here is one kind of result to aim for:
This graph shows the probability of reaching or exceeding different net gain figures. It is based on a simulation exercise with the same financial model that produced the initial $590,000 estimate (for more on simulation, see Part III next week, or the white paper, "Business Case Essentials," or the Business Case Guide). Instead of showing just the most likely outcome, however, it says that the probability of realizing at least $329,000 is around 90%, while the probability of seeing $750,000 in gains, or more, is around 20%.
Moreover, the 80% confidence interval (dark blue area under the curve) says they can be 80% certain that the actual results will be between $329 and $789 thousand. This kind of answer may provide the "comfortable certainty" decision makers need, If they trust these results (Part III next week).
If the new product venture must bring gains of at least $300,000 or more in order to be worthwhile, decision makers might be quite ready to act on a 90% probability. If they must have $750,000 or more, this proposal does not look like a wise decision.
Question 2: Which is the better business decision? Can we be sure?
Management has two competing proposals on the table, each for a different product launch. One comes with a business case projecting a net gain of $590,000 across five years. The other looks forward to a projected five-year gain of $800 thousand. The company can only afford to invest in one of these initiatives. Which one should they choose?
Decision makers will weigh the proposals against each other in several ways, considering strategic fit, the competition, economic trends, market trends, and other factors no doubt. When the overriding concern is return on investment, however, decision makers may approach "comfortably certainty" with another kind of statistical guidance based on the same simulation exercise:
| Proposal | Expected Value | 80% Confidence Interval |
| Product launch A | $590,000 | $329,300 - $789,500,000 |
| Product launch B | $800,000 | $251,000 - $1,390,000 |
Proposal A has a lower expected value (most likely result), but it comes with a much narrower confidence interval. If management chooses proposal B, they have an 80% level of confidence that actual result will be somewhere between $329 and $789 thousand. The difference between these numbers is the range of "uncertainty," about $462 thousand.
By contrast, the proposal B comes with a higher expected value but a much wider range of uncertainty. Here, the 80% level of confidence stretches across $1,139 thousand of possible results (that is, $251 through $1,139 thousand).
Assuming they believe these results decision makers may take the narrower confidence interval as the comfortable certainty they need to act.
Question 3. How can I prove, later, that I'm acting responsibly now?
Accountability is becoming the watchword for decisions in project management, capital spending, policy changes, and other commitments of all kinds. Indeed, accountability angst may be the only way to explain why so many people start a financial justification business case, even though the decision is already made and the money already spent. Many ask "Can the business case really prove that I'm making a solid, responsible decision? Where does the proof come from?"
Accountability in the future comes from the same steps that establish trust and belief in case results today. We have seen above the kind of "certainty" that good business case results can claim. Results like those in Questions 2 and 3 above are useful--to those who believe them. But can anyone believe the claims? How far can you trust statistical results?
Next week the Cost/Benefit Newsletter takes on the hard questions about trusting statistics and believing the business case, final part of "Can You Ever Be Certain?"
Take action! Learn more about business case design from the Business Case Guide. Learn and practice proven methods for building your cases at a "Building the Business Case" Seminar.
Marty Schmidt
6 February 2006
mschmidt@solutionmatrix.com
www.solutionmatrix.com
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