Tag Archives: net present value

What Is the Cost of Doing Nothing?

An associate professor at Harvard Business School recently gave the world an inadvertent lesson on opportunity cost when he spent several days taking a family-owned Chinese restaurant to task, to the point of threatening legal action, for an apparent overcharge of $4. (Happily, he has since offered a sincere apology.)

Opportunity cost is the loss of benefit associated with an option that is not chosen, given a set of mutually exclusive alternatives. In our restaurant example, the professor gave up not only the refund that was immediately offered to him but also the benefit of the myriad other things he could have done instead of composing those emails – from advancing his research to enjoying a nice glass of pinot noir.  In the heat of the moment, it’s easy to overlook the possibility that what we’re doing right now isn’t, in fact, the most beneficial thing to be doing right now.

In my Value Consulting organization, we spend a lot of time with insurers exploring the value of transforming their business with a modern software platform. But recently, we’ve had some really interesting conversations focused on the converse of that: What is the opportunity cost of not moving forward? What is the cost of doing nothing? What is the cost of delaying a decision?

Let’s imagine that you’ve built a case for change in your organization. You’ve estimated that your company could realize a benefit of $12 million a year, beginning at the conclusion of a two-year project that will cost $25 million. But, with limited budgets and scarce human resources, approval for that $25 million could be a long way off.

Overcoming the big-ticket anxiety is difficult, but the math is pretty straightforward. In this simplified example, the investment pays back in year five, with a 10-year net present value of $31 million. So a choice in favor of the status quo will hurt your company by a net of $31 million over the next 10 years. Allocated evenly, that’s a loss of $8,500 per day – every day, including weekends and holidays – for the next 10 years. A six-month delay in moving forward will cost you $1.5 million. In the time you’ve spent reading this blog post, you’ve already lost 20 or 30 bucks.

Of course, an opportunity cost calculation is no guarantee that you’ll actually realize that benefit. The business case must be strong and realistic to begin with. The right software must be chosen, and the right decisions must be made during implementation to ensure success. The hard work of implementing the project must be done. But sometimes a simple, potentially cheeky data point is enough to start a much bigger, more serious conversation.

3-Point Plan for an Innovation Portfolio

One lament I often hear when I advise large company executives on the need to “Think Big” is that their biggest innovation challenge is not thinking big—it is thinking too much. Purportedly great ideas come from the front lines where the organization interacts with products and customers. They come from technology or marketing wizards keeping a sharp eye on disruptive market trends. They come from executives and board members grappling with questions at the organization’s strategic horizon. The challenge is that organizations are overwhelmed with more ideas than they can sort out, much less pursue. Perhaps the best advice on how to deal with the challenge of too many ideas comes from Peter Drucker, who offered this general principle:

Innovation begins with the analysis of opportunities. The search has to be organized, and must be done on a regular, systematic basis.” Don’t subscribe to romantic theories of innovation that depend on “flashes of genius.”

Rather than relying on randomness or organizational influence to dictate which ideas find a receptive ear, here is a three-point plan for initiating a systematic process for uncovering, assessing and scaling the best ideas. 1. Inventory Opportunities Start by casting a wide net. For example, sponsor a series of innovation contests and workshops to educate, build alignment and uncover potentially good ideas. Hold scenario planning sessions with senior executives and board members to explore both incremental and disruptive future business scenarios. Questions to ask might include:

  • Can you augment your customer interfaces to reveal customer preferences and to customize the customer experience, as Amazon and Netflix do?
  • Are there opportunities to better utilize the big data being generated by your business processes, including customer, operational or performance data, for innovation?
  • How might you reimagine key business, customer, and competitive issues if you could start with a clean sheet of paper?
  • How do the six disruptive technologies affecting other information intensive companies apply to you?
  • What extreme competitive threats, i.e., doomsday scenarios, might new entrants wielding these disruptive technologies pose to your organization?

Opportunities should include both continuous and discontinuous innovations. Continuous innovations offer incremental or faster, better, cheaper-type optimizations, such as shedding costs, reducing cycle times and generating incremental revenue. Discontinuous innovations are those that rise to the level of game-changing potential. 2. Develop a Holistic View Using an Innovation Portfolio Next, assess each opportunity based on competitive impact and investment type using the portfolio analysis framework as shown in Figure 1. Figure 1 Figure 1: Portfolio Analysis Framework Competitive impact measures differentiation against what competitors might deploy by the time an idea is launched. Remember Wayne Gretzky (who famously said he skates to where the puck is going, not to where it is)! A key mistake is evaluating an idea against one’s current internal capabilities, as opposed to where the competition is going. This dimension forces an explicit calculation of an idea’s future potential competitive impact. Investments can be one of three types:

  • Stay in Business investments (SIB) are for basic infrastructure or non-discretionary government mandates. SIB investments should be assessed on how adequately they meet regulatory or technical requirements while minimizing risk and cost.
  • Return on Investment opportunities (ROI) are pursued for predictable, near-term financial returns. Standard measures, such as net present value (NPV), return on equity (ROE) or other well-understood metrics are applicable here.
  • Option-Creating Investments (OCI) are pursued to create business options that might yield killer-app-type opportunities in the future. OCI investments do not yield financial returns directly.  Instead, they build capabilities and learnings that can be translated into future ROI opportunities. Like financial options, OCIs should exhibit high risk and offer tremendously high returns.

After arraying opportunities in the framework, eliminate those that fall outside of acceptable boundaries. For example, companies should not pursue opportunities that, once completed, are already at a disadvantage against the competition. For the remaining opportunities, develop an initial sizing of investment levels and potential benefits according to each investment category. Filter as appropriate. For example, eliminate ROI opportunities that do not meet standard corporate hurdles rates. Eliminate OCI opportunities that do not exhibit extraordinary option value. Eliminate SIB ideas that do not adequately minimize cost and risk—be very skeptical of SIB opportunities aimed at providing ROI or OCI benefits. Such opportunities should be judged directly as those investments types.  Figure 2 illustrates how the analysis might look at the end of this stage. Figure 2 Figure 2: Portfolio Analysis Results 3. Balance the Innovation Portfolio In personal investment portfolios, it is important to not place all hopes in one or two investments. The same is true for corporate innovation portfolios. To ensure competitiveness in the near term and in the future, they should include a mix of incremental and disruptive innovations. The right balance and prioritization depends on a company’s investment capabilities and competitive circumstances. For example, as shown in Figure 3, a market leader might field a portfolio geared toward aggressive growth by enhancing its infrastructure, investing heavily in near-term profitable opportunities and developing a small number of killer app options for sustaining its competitive advantage.  (My experience is that the right number of such options is on the low end of the magic 7, plus or minus two. That is because the limiting factor is senior executive attention, which is very limited, not investment dollars. Market leaders have lots of money to waste, but no project with true killer app potential can succeed without significant senior executive attention.) Figure 3 Figure 3: A Market Leader’s Balanced Portfolio Other illustrative portfolio profiles are shown in Figure 4. Commodity businesses tend to minimize SIB and OCI investments. Companies that are retooling might emphasize infrastructure and near-term investments and make only minimal investments in future options. Underperforming companies tend to invest in programs that barely achieve competitive parity, or worse, and do little to prepare for the future in any of the three investment categories. Figure 4 Figure 4: Illustrative Portfolio Profiles

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By adopting appropriate financial and competitive metrics and measures for each type of investment, companies avoid planning theatrics where guesses are disguised as rigorous forecasts. This can happen, for example, when infrastructure and other SIB investments are required to demonstrate explicit returns on investment. Or, it can happen when advocates of OCI efforts are required to calculate net present value of very uncertain long-term initiatives. Such forecasts can, of course, be made by  savvy proponents. But the analyses are better testaments to rhetorical and spreadsheet skills than certainties about the future. At the end of this three-step process, companies should have a prioritized and staged investment plan that represents a coordinated enterprise innovation strategy and follows the think big, start small and learn fast innovation road map. Achieving an adequate understanding of the entire landscape of possibilities facilitates and encourages thinking big. Continuing management of the innovation portfolio provides clear criteria for evaluating other big ideas as they come up. It also demands the discipline of starting small and learning fast in the pursuit of disruptive innovations that will shape the company’s future strategic prospects.

Should You Quantify IT’s ROI? (Part 1)

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, 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, quantifying helps with understanding the return on investment for any individual undertaking. Second, and perhaps more important, when many initiatives vie for scarce capital, quantitative cases can allow for comparisons. And in most organizations, one of the most important responsibilities of an executive team is to allocate capital to the most beneficial initiatives.

All this sounds quite straightforward. What, then, is the problem with the quantitative case, especially for initiatives that require big capital expenditures? The problem is not with the mechanics of quantifying. 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) sorts of 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 one can precisely establish the required investments and expected returns over a period. If I know that I have to travel 300 miles and know that I will drive 75 mph, 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.

Because the 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 the attempts at calculations – 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 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 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.