The preparations made for Y2K were likely the most forward-looking events in the collective history of information technology. Whether the great non-event represented acute foresight and preparation or simply false hype is debatable. The consensus, however ­ which is backed by data ­ is that IT's track record for planning is notoriously poor. Stories of capacity shortfalls, long lead times and failure to anticipate business needs abound. Unfortunately, IT planning is still held hostage in every budget battle, plagued by poor communication and victimized by endless internal transfer pricing debates.

In this environment, what can you do to generate better predictive information that can guide planning and provisioning? Rather than trying to understand or even consider all the internal and external information that is now available, leading companies are creating predictive models that rely on only a few key financial and operating factors. By limiting the criteria and capitalizing on the speed of measurement offered by technology, better predictions, faster forecasts and quicker plans are had.

Their tool is "driver-based forecasting." It predicts future business performance and the requirements of IT by pinpointing those factors that drive demand for services. By focusing on the drivers of demand for IT services, it is possible to move the function from a reactive to proactive mode. The transition not only enhances service levels, but also allows for significant cost benefits through better purchase planning and improved resource allocation.

The first step in selecting meaningful drivers is focusing on factors that are both material and volatile. "Materiality" is defined as any factor that has a significant impact on demand for IT services such as head count, new product development and promotion scheduling. It is determined by comparing the relative proportion of a material factor to the total demand for IT resources. "Volatility" is how much the factor varies from period to period. You must understand the relationship between these two characteristics to determine the variable's impact on your planning. Put simply, big things that change a lot are more important to watch than small things that don't.

You can then create a predictive model by evaluating each cause-and-effect relationship and estimating the impact on your IT plans. Is the relationship material? Is it volatile? If the answers are "yes" to both, then some measurement of the activity is needed and an understanding of the impact for IT services appropriate. Examples that typically apply to IT services include new product launch schedules, scheduled plant maintenance and new technology releases.

For years, senior executives have talked about using technology for strategic advantage, yet few have realized the promise. Increasingly, best- practices companies are able to directly link measures from their IT metrics to those that track overall corporate performance. For a telecommunications company, one of the critical elements to new product launches is the ability to account for and invoice new customers. Programs such as "Fridays Free" and "5¢ Sundays" sound great. However, such seemingly simple promotions can cause near heart failure to those who support the billing systems.

For instance, I once worked with a major telecommunications company whose IT staff first learned of its new pricing program ­ which its systems were expected to support ­ from an advertisement on television. Apparently someone dropped the ball when planning the promotion, and IT was left out of the loop. However, if IT and marketing had agreed up front that one of the drivers of the marketing campaign's effectiveness would be the ability to implement new pricing and that IT had a critical role in ensuring system readiness, a process of advance communication could have given IT advance warning that a major new requirement for systems support would be needed.

Best-practices companies typically anticipate needs faster and more accurately by focusing on two dimensions. First, they use operational driver-based analysis, which correlates driver data with the typical decisions an IT manager must make to improve planning accuracy. Second, they measure goal attainment and build a knowledge base that improves predictive accuracy over time.

The combination of understanding cause-and-effect relationships of internal company functions and the compromising of predictive accuracy over time provides IT with what it needs most ­ which is more time to prepare. While not flawless, driver-based forecasting provides IT managers with significant insight into likely future demands.

By linking IT to business drivers and overall corporate strategy, the function moves from the role of mere support to that of a true strategic enabler. In forward-thinking companies, the CIO is increasingly viewed as a business partner. Unfortunately, only 65 percent of companies in answerthink's best-practices benchmark studies have a CIO. And of that total, less than 10 percent report directly to the CEO.

Driver-based forecasting is a valuable tool for shaping IT into a more responsive business partner. With it, IT can simultaneously drive down costs while improving both functional and corporate effectiveness. Without it, CIOs and senior IT managers are forced to play the reactive role to most corporate initiatives ­ reinforcing the traditional image of IT as always late, over budget and disconnected from the needs of the business.

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