This blog is the first in a series.
What is a quantitative business case for an IT investment? It is a quantifiable measure of benefit, in dollars, that can be realized by making a quantified investment of resources. While resources can be capital, human, intellectual property, etc., in the end it can all be reduced to money. What money is one putting in and what return is one getting out as a result?
Making the quantitative case is a long- practiced ritual in many insurance organizations. I may be committing heresy by asserting that the quantitative case is much overrated, doesn’t serve the purpose it was intended for very well, and may in fact be an exercise in futility. I’m not making a general statement: I’m speaking about various IT modernization or transformation initiatives in the insurance industry, which I work in and serve.
I took enough corporate accounting and finance courses to qualify as a finance major and as a result am familiar with the mechanics of discounted cash flow analysis, valuation of initiatives, calculations of NPV, IRR, payback, etc. etc. While the theory of the quantitative approach has always seemed compelling a mathematical measurement of the benefit yield of a particular resource investment, 20 years of practice has taught me the reality and informed my views very differently.
Why then is the quantitative case typically so favored? There are two primary reasons. First, it helps with understanding the return on investment for any individual undertaking. Second, and perhaps more important, when there are many candidate initiatives that vie for scarce capital, the quantitative case for each initiative can allow the people who allocate scarce capital to make comparative decisions about which initiatives to pursue. And in most organizations, one of the most important responsibilities of an executive team is to allocate capital to the kinds of initiatives that will most benefit the organization, allowing it to realize the business goals and objectives.
All this sounds quite straightforward, logical, and rational. So, what then is the problem with the quantitative case, especially for the initiatives that require big capital expenditures? The problem is not with the mechanics of developing it. Once the investment and income streams over a reasonably desired time horizon are identified, weighted average cost of capital (WACC), discounted cash Flow (DCF), net present value (NPV), and internal rate of return (IRR) type metrics are quite mechanical to calculate. The real problem with so-called insurance modernization or transformation initiatives is with establishing the variables of investment stream, income stream, and time.
There are two ways to try to establish these three variables. First, if for an initiative, one can precisely establish the required investments and expected returns over a period of time. As an analogy, if I know that I have to travel 300 miles, and know that I will drive 75 miles per hour, then I can mathematically say that I will complete my travel in four hours. Second, if a vast body of empirical evidence exists, then one can at least probabilistically try to establish the three variables with associated confidence levels. But I would argue that with initiatives in the insurance industry that require large capital-expenditures, neither approach works.
With insurance industry initiatives, quantifying income returns, investments, and time period with precision is extremely difficult, if not impossible. On the investments front, projecting increase in premiums and profits, cost savings through headcount reductions and other items, and cost avoidance are all an exercise in sheer guesswork. Estimating the costs and timelines of large technology projects also remains elusive. No matter how diligently and hard people work to identify these, the estimates end up being wrong--often, not by some tolerable deviation, but rather by orders-of-magnitude in overruns in costs and time.
Since that vast body of insurance initiatives suffers the same fate, there isn’t reliable empirical evidence to probabilistically establish income, investments and time period with any degree of confidence. And there are other variables that further undermine this differential in resources and execution approaches from one initiative to the other, culture of organizations, market changes, technology changes, and much more.
Despite the problems associated with the quantitative business case, most organizations still diligently pursue it. Internal teams work on project portfolios and appropriation of funding exercises. Vendors are always at hand to help the teams develop the business case to sell it to the C-Suite and the board. Within the organization, committees and councils are established to review the “case”, “wisely adjudicate” and pick “winners” and “losers” among candidate initiatives. All these various constituents are well intentioned and are following the rules of the game. The problem is with the current “rules of the game” and not with those who play.
Are there alternative approaches then, both to decide whether or not to fund a given initiative and, once funded, to determine how best to use the funding to ensure that an initiative is yielding benefits? In several instances, I have been fortunate to witness bold leaders abandon the traditional method and take a more pragmatic approach. I’ll discuss this in Part II of this blog.
Ram Sundaram is a principal of X by 2, a technology consulting firm that specializes in IT transformation projects for the insurance industry.
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