Academic journal article The McKinsey Quarterly

A Hard and Soft Look at IT Investments

Academic journal article The McKinsey Quarterly

A Hard and Soft Look at IT Investments

Article excerpt

It's getting tougher and tougher to calculate costs and estimate benefits

No methodology can substitute for judgment

A new approach: total value of ownership

Throwing good money after bad would make any manager uneasy. But then, uneasiness could be a good thing where IT investments are concerned. Few senior executives understand why their investments in IT have gone wrong or how to get them right in the future, according to recent interviews.(*)

One reason for their bewilderment may be that it's difficult to calculate the absolute value of information technology to an organization. IT is simply too integrated into most businesses to be isolatable as a variable. And rare is the senior executive who possesses the knowledge and experience to make IT decisions confidently. Many end up delegating fundamental decisions about their business to IT and financial staff. All too often, the result is complex legacy systems, proliferating distributed technologies, and lax development discipline.(*)

We believe IT decisions must be made like other business decisions: on the basis of value. This means that the "softer," more qualitative benefits that IT can bring must be evaluated and properly factored in. Costs are not the whole story, even when they are projected over the entire life of an investment. Rather, managers need to understand the total value of ownership that an IT investment may represent.

Such an understanding can be developed through a traditional cost/benefit methodology that is customized to address the issues unique to IT decisions. Another prerequisite is the active participation of line managers. No methodology can compensate for managers who shy away from making decisions. Fortunately, the key issues in IT aren't technical, but managerial. Making good IT decisions is something that all executives can do, provided they use a sound evaluation methodology and take the trouble to develop their business and IT judgment.

Decision-making challenges

Once, figuring out the cost of an IT investment was easy. The cost of a new application, for instance, was just the extra mainframe and disk capacity required, some developer time, and maybe some software licences. The price tag might be bigger than you would have liked, but at least you knew what it was.

Today, the hardware and software may cost you less, but they are just the beginning. Hard-to-predict support and maintenance costs, business costs associated with making the transition to the new system, and other hidden costs can more than double the initial investment.

Benefits are harder to measure too. Where once you could predict and control the number of data-entry clerk positions you would save by integrating your back-end systems, today your goal might be to gain market share or increase customer loyalty. Payoffs like these are not controllable and depend on other business functions beyond IT.

Today's technology is also much more complex, as simple integrated systems give way to proliferating layers of servers, operating systems, network protocols and routers, database software, middleware, and desktop hardware and software. Not surprisingly, it is getting harder and harder to ascertain the long-term impact of any technology choice. Moreover, the integration between business units and between functions means that a change in one system often affects dozens of others, some of them, perhaps, in other organizations. And the accelerating pace of technological change, with product life cycles now a matter of months, is a further barrier to good IT decision making.

The limitations of current practice

These challenges cast a harsh light on current practice in the evaluation of IT investments. Interviews show that companies do not always demand solid business cases for IT investments, that they have trouble handling decisions based on soft benefits, and that they often lack the maturity of judgment to make decisions where only scant quantitative data exists. …

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