Let’s keep return-on-investment (ROI) and total-cost-of-ownership (TCO) in perspective. You cannot build a business with these hammers. Are they important? Yes. Insightful? Usually. But obsessive-compulsive TCO/ROI behavior is as unhealthy as obsessive-compulsive quality, learning or re-engineering behavior. Remember these?
The ultimate argument for a technology initiative is made in the business case. But key to good business cases is qualitative and quantitative data about the cost of a technology project’s entire life cycle and the strategic impact it will have on meaningful business processes. TCO is about cost and ROI is about benefit.
Let’s start with costs. There are acquisition costs, operational costs and softer costs that are by nature more difficult to quantify. Total-cost-of-ownership calculations should also include costs over the entire life cycle of a hardware or software product. Softer costs include the cost of downtime, internal consulting that comes from indirect sources, and costs connected with your degree of standardization.
TCO data is an essential part of any business case which should ultimately be driven by the strategic and/or tactical return you expect to get from your investment. In other words, TCO data drives return-on-investment (ROI) data — which, like TCO data — is both hard and soft.
Is it important to ask meaningful questions about why a business technology initiative exists — and what impact it will have on the business (if it goes well)? Of course. So why is there so much disagreement about ROI? Research suggests that while lots of ROI methods are used, by far the most popular are ones that calculate cost reduction, customer satisfaction, productivity improvement and contributions to profits and earnings. Two years is also considered by the majority of business technology executives as a reasonable time over which to measure ROI.
So what are the methods?
One of the easiest is based on a simple calculation that starts with the amount of money you’re spending on a business technology initiative (that includes TCO and other data) and then calculates the increased revenue or reduced costs that the investment actually generates. If a project costs a million bucks but saves two million then the ROI is healthy.
Another simple method is based on payback data — the time it takes to offset the investment of the business technology initiative through increased revenues or reduced costs. If the payback period is short — and the offsets are great — then the project is “successful.”
There are also methods based on economic value analysis or value added (EVA), internal rates of return (IRR), net present value (NPV), total economic impact (TEI), rapid economic justification (REJ), information economics (IE) and real options valuation (ROV), among too many others. Do we really need this much precision? (No.)
What about soft ROI? In the mid- to late-1990s, companies developed Web sites for a variety of reasons. First generation sites were essentially brochureware, where very few transactions took place. What was the ROI on these sites? They did not reduce costs: in fact, they increased them. Nor did they generate revenue. They were built to convince customers, Wall Street analysts, investors and even their own employees that they “got it,” that they understood that the Web was important. An significant intangible benefit? Absolutely.
While I think that anyone who launches a business technology project without any TCO and ROI data is insane, I also appreciate the need for balance and reasonableness. This is why there’s so much controversy about TCO/ROI. Lots of people think that too rigorous an application of TCO and ROI methodology will distort projects and perhaps even undermine business results. Others think that companies should know what to do instinctively and therefore shouldn’t need a whole lot of data to make sound business decisions. Some think that the last thing they need to do is launch a training program to get their people up to speed on the latest and greatest approaches to TCO and ROI, that the time would be better spent just working the projects; and there are those who think that the effort to collect and analyze TCO and ROI data is disproportionate to the returns.
What to do?
Simplicity — as usual — is our friend.
Adopt a flexible approach to TCO and ROI. TCO data should feed ROI data which should feed the overall business cases for business technology decisions. Hard data is always better than soft data, but soft data — if it can be monetized (like generating a premium for your stock price or enhancing your brand) — should also be analyzed.
The simplest approach to TCO data collection and assessment is a template that requires the collection of specific hard and soft data, and the simplest approach to ROI data collection and assessment is based on simple metrics that measure payback over a reasonable period of time. Payback should be defined around internal metrics — like cost reduction — and external ones, like improved customer service and profitability. Not too complex — but meaningful. Some projects will pay themselves back in a year, while others may take three. Beyond three, things get too fuzzy, so I’d re-think projects with anything longer than three-tier ROI tails.
TCO and ROI should not be used as clubs to bludgeon people: they should be used to inform decisions and monitor progress. (They should also play a role in the death of projects gone berserk) In other words, TCO and ROI questions should always be asked, but the answers don’t always need to be perfect.
Steve Andriole is the Thomas G. Labrecque Professor of Business at Villanova University where he conducts applied research in business/technology convergence. He is also the founder and CTO of TechVestCo, a new-economy consortium that focuses on optimizing investments in information technology. He can be reached at firstname.lastname@example.org.