Academic journal article The McKinsey Quarterly

Being Intelligent about 'Intelligent' Technology

Academic journal article The McKinsey Quarterly

Being Intelligent about 'Intelligent' Technology

Article excerpt

How rebalancing the mix of human and machine skills processes can create competitive advantage

The failure of computer technology to deliver on ambitious promises of bottom-line value, together with a number of conspicuous systems disasters, has led many top managers to question the notion that IT can be used to gain competitive advantage. They are not alone. A recent MIT study found little evidence for any direct link between investment in IT and improved bottom-line performance.(*) Thus, with something close to a sigh of relief, many senior executives have returned to the familiar, low-tech world of quality management, front-line empowerment, and even business process reengineering to drive necessary organizational change.

Their timing is unfortunate. In the past, IT's troubling lack of business value has stemmed as much from a failure to reconfigure skills and organization around the intelligence inherent in the technology as from hands-on problems in implementation. New applications, however, now make such reconfiguration feasible. It works - and the benefits are huge.

Rebalancing human and machine intelligence can, for example, more than double clerical productivity, as well as liberate front-line employees to serve customers, rather than perform administrative tasks. And it can cut employee learning cycles from months to weeks and even sometimes days, enabling the rapid reshaping of established businesses. Indeed, some recently introduced direct financial services have actually been set up from scratch in nine months or less. Such capabilities offer significant first-mover advantages. But they also make traditional markets vulnerable to unexpected competition from new, greenfield entrants. As opportunity and as threat, they deserve a closer look.

The skill imbalance

In many companies, even routine operational processes have become too unwieldy for the human skills that struggle daily to cope with them. In one insurance company, for example, internal processes have become so complex that training cycles now extend beyond 12 months, and a large, expensive supervisory structure is needed to check that every transaction is correct. An important source of such excessive complexity has been the inability of many companies to replace their "legacy" systems - the old software and hardware portfolios built laboriously over the past three decades - with new and more flexible systems. For years, the seeming intractability of this legacy problem has pushed the cost, timing, and inflexibility of new IT investments to unacceptable levels.

As recent developments have shown, however, there are ways to tackle this problem by effectively leaving the legacy systems alone, bolting on new application packages, and then linking the two sets of software with interconnect technology.(*) But removing this kind of bottleneck has brought another - perhaps even more harmful - by-product of past complexity to light: a skill overload that breeds disenchanted front-line workers and cumbersome management structures.

When process complexity escalates rapidly, the demands on the skills of workers escalate more rapidly still. This usually provokes a counter-reaction - a visceral reluctance to move away from the "devil we know" in organizational form or operational procedure. And this reluctance, in turn, stiffens the resistance of already nervous top managers to the idea of reconfiguring their businesses in innovative - and value-creating - ways. This vicious cycle of reactions is perfectly understandable. But it is unnecessary.

Today, managers can leverage machine intelligence in a manner that allows a fundamental rebalancing of the demands on human and machine skills. This is because so-called "intelligent" software makes it possible to shorten the learning curves associated with new business processes. In the insurance company mentioned above, for example, the redesigned systems had, by intent, a user interface that could be learned in four weeks or less. …

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