Colin Thompson is back to tell us about the myths and potential pit falls surrounding return on investment. We all know it makes good sense to compare expected returns with intended investment but is it safe or wise to plan business ventures on assumption, this blog discusses just that.
There are a few English words you can use almost anywhere in the world, anytime, and be understood: Hotel, Okay, and Taxi belong to this class. Among business people, so does the word ROI.
For several years now, cautious managers everywhere treated 'Return on Investment' and its acronym "ROI" as words to live by. When a major proposal is on the table--such as an infrastructure upgrade, marketing program, changes to the product line, or anything else that calls for significant spending and therefore a business case--the normal response from the top has been something like this:
We'll invest only if we're sure that it comes with a good ROI. Show us the ROI first, then we'll talk about funding.
Somewhere between 60 and 80% of all major IT project proposals in the US and Europe, for example, now require a return on investment (ROI) analysis before funding. The figure varies, depending on which analyst study you read, but there's no question that the "ROI Required" rate is high.
From such reports, you might think that the ROI is winning the trust of decision makers everywhere. In fact, however, ROI's reputation as a reliable basis for decision making may have peaked and now be on the slide. The same analysts who tell us how many funding decision require ROI also tell us that more than half of such projects never deliver the expected ROI.
Several years ago, for instance, Nucleus Research published a now-famous study after interviewing SAP reference customers. Nucleus found that 57% of them did not receive a positive ROI. A majority of the participants in our 'Building the Business Case seminars' report that they no do not trust vendor produced ROI figures. Even worse, ROI predictions from their own project and product managers have not proven accurate. In some places, we find that ROI is little better than a four letter word.
"Why then," you might ask, "do decision makers put so much emphasis on ROI when so many ROI figures don't predict what actually happens?" If ROI can't do any better than that, don't we cause more bad decisions than we prevent by trusting ROI?
ROI in fact is a legitimate concept: It makes very good sense to compare expected returns to expected investment costs. The problem, however, is that ROI figures are insufficient and even dangerous to use--if they stand alone. An ROI estimate tells us only what we gain if things go as planned. It may be that gamblers, more often than business people, understand why ROI by itself is not enough and what else the decision maker also needs to know.
Two Kinds of Odds
The term "Odds" means two different things to gamblers. Serious gamblers know that one kind of odds has to be weighed against the other kind, in order to maximize the chances of coming out ahead. At the racetrack, "Odds" can mean
1. The ratio of the winning pay out to the cost of the bet, just like simple ROI ! A winning 2 pound bet on a 20-to-1 long shot puts 40 pounds in your pocket. The skill in betting lies in knowing how the payout odds compare to the other kind of odds:
2. The actual probability of winning. One glance at the tote board shows you the current pay out odds.
One glance at the bottom line of your ROI spreadsheet shows the predicted results of your business investment, if everything goes as planned. However, if you do go to the races, just watch the serious gamblers working, furiously, down to the last minute before the betting windows close, trying to estimate the probability odds. They visit the paddock and have a look at the horses. They pour over racing forms and tip sheets, and they work and re-work their racing calculators. Otherwise, they will tell you, it would all be "luck" and nothing more.
I believe that ROI estimates in business are often unlucky because managers give too much attention to the payout odds and too little attention to the probability odds. Very few know how to how to maximize ROI by measuring and managing uncertainty.
The Devil is in the Assumptions
Every forward-looking ROI estimate and business case stands on a foundation of assumptions. It can be no other way, after all, because the case predicts the future. Everything about the future is an assumption. A detailed case for a major business investment may require dozens or hundreds of assumptions about such things as future:
• Business volume
• Competitor's actions
• Market share
• Fuel prices
• Government regulation
• Software development time • Salary increases
• Productivity improvements
• Implementation costs
• Ramp up time
• Labour requirements
• Raw materials prices
Some assumptions come with high certainty, others come with high uncertainty. But every assumption adds some uncertainty to the bottom line cash flow or ROI estimate. It's tempting to lump all these factors together into a single risk figure. The key to managing your investment so as to minimize risk and maximize returns, is not treat risk as a single factor, but instead carefully weigh individual risk factors to determine:
• Which assumptions carry the most weight in driving results? What happens to results if we don't manage critical success factors to target levels? Sensitivity analysis addresses questions like these.
• What is the likelihood of other results besides the most likely predicted outcome? Which risk factors have to be watched carefully, as indicators that predictions need revising? Risk analysis answers questions like these.
One of our clients, for instance, had a proposal to begin a major ERP system implementation. This bottom line prediction was an incremental cash flow gain of nineteen million dollars over five years. That was a good looking "R" on an "I" of about three million dollars. Sensitivity analysis with the business case financial model, however, revealed a high correlation between projected financial results and two of the ROI analyst's assumptions, (1) the assumed reduction in product development time, and (2) the assumed implementation completion date. (See 'Business Case Essentials' for more explanation of sensitivity analysis.) Sensitivity analysis were some messages here that made management sit up and take notice.
• The ROI model assumed the ERP system would help lower new product development time by 30%. The high correlation between this assumption and financial results shows how the attractive ROI depends on reaching that target. In this case, a reduction of only 15% in development time (instead of 30%) brought the predicted gains down to $5M.
• The ROI model also assumed the ERP system would be fully implemented in 2 years (50% implementation per year). Clearly, missing the 2 year target would adversely impact the overall return on this investment. Stretching the implementation out to 4 years would raise costs and lower benefits to bring a zero net gain.
It's one thing to know generally that factors like implementation time and reduced development time are important. It's another thing entirely to bring home the importance of those factors in concrete terms. If you know ahead of time where the risks are, you can manage them (or at least watch them) and avoid unpleasant surprises down the road.
Take action!
Learn and practice proven 6D Business Case Framework at a ' Building the Business Case Seminar'. Learn more about business case design from one of our books, the 'Business Case Guide', 'Getting Your Budget Approved' , or the most frequently cited business case authority in print,' Business Case Essentials'.
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