A Flaw in Business Cases
September 19, 2009
A software business case compares the total cost of software with the benefits to be gained from implementing the software. If the IRR of the investment is adequate, relative to the company’s policies on capital investment, and if the simple-minded powers that be have a good gut feel about the case itself, it is approved.
Clearly, a business case isn’t perfect. Implementing software is an uncertain business. The costs are complex and hard to fix precisely. Implementation projects do have a way of going over; maintenance costs can vary widely; the benefits are not necessarily always realizable.
That’s where the gut feel comes in. If an executive thinks the benefits might not be there, the implementation team might have a steeper learning curve than estimated, the user acceptance might be problematic, he or she will blow the project off, even if the IRR sounds good.
Business cases of this kind are intended to reduce the risk of a software purchase, but I think they’ve actually been responsible for a lot of failures, because they fail to characterize the risk in an appropriate way.
There’s an assumption that is built into business cases, which turns out to be wrong. The fact that this assumption is wrong means that there’s a flaw in the business case. If you ignore this flaw (which everybody does), you take on a lot of risk. A lot.
The flaw is this. Business cases assume that benefits are roughly linear. So, the assumption runs, if you do a little better than expected on the implementation and maintenance, you’ll get a little more benefit, and if you do a little worse, you’ll get a little less.
Unfortunately, that’s just not the case. Benefits from software systems aren’t linear. They are step functions. So if you do a little worse on an implementation, you won’t get somewhat less benefit; you’ll get a lot less benefit or even zero benefit.
The reason for this is that large software systems tend to be “brittle” systems. (See the recent post on “Brittle Applications.”) With brittle systems, there are a lot of prerequisites that must be met, and if you don’t meet them, the systems work very, very poorly, yielding benefit at a rate far, far below what was expected of them.
This problem is probably easier to understand if we look at how business cases work in an analogous situation. Imagine, for instance, the business case for an apartment building. The expected IRR is based on the rents available at a reasonable occupancy rate. There is, of course, uncertainty, revolving around occupancy rates, rentals, maintenance costs, quality of management, etc. But all of this uncertainty is roughly linear. If occupancy goes up, return goes up, maintenance goes up, return goes down, etc. The business case deals with those kinds of risks very effectively, by identifying them and insuring that adequate cushions are built in.
But what if there were other risks, which the business case ignored? These risks would be associated with things that were absolutely required if the building was to get any return at all. Would a traditional business case work?
Imagine, for instance, that virtually every component of the building that you were going to construct–the foundation, the wiring, the roof, the elevators, the permits, the ventilation, etc.,–was highly engineered and relatively unreliable, required highly skilled people who were not readily available to install, fit so precisely with every other part of the system that anything out of tolerance caused the component to shut down, etc., etc. The building would be a brittle system. (There are buildings like this, and they have in fact proven to be enormously challenging.)
In such a case, it is not only misguided to use a traditional business case, it is very risky. If one of these risky systems doesn’t work–if there’s no roof or no electricity or no elevator or no permit–you don’t just generate somewhat less revenue. You generate none. Cushions and gut feel and figuring that an overrun or two might happen simply lead you to a totally false sense of security. With this kind of risk, it’s entirely possible that no matter how much you spend, you won’t get any benefit.
Now, businessmen are resourceful, and it is possible to develop a business case that correctly assesses the operational risk (the risk that the whole thing won’t work AT ALL). I’ve just never seen one in enterprise applications. (Comments welcome at this point.)
The business cases and business case methodologies that I’ve seen tend to derive from the software vendors themselves or from the large consulting companies. Neither of these are going to want to bring the risk of failure to the front and center. But even those that were developed by the companies themselves (I’ve seen a couple from GE) run into a similar problem: executives don’t want to acknowledge that there might be failure, either.
But the fact that the risk makes people uncomfortable doesn’t mean that it’s a risk that should be ignored. That’s like ignoring the risk that a piton will come out when you’re mountain climbing.
Is the risk real? Next post.