Information Impact

This special series explains how to measure and quantify the value of your company's critical information.

By Erik Thomsen

Executive Summary

Erik Thomsen Information is a critical asset to an organization. But how do you value it? Without proper methods of valuation, you cannot rationally decide among alternative IT (and other information affecting) investment strategies. Traditional attempts to quantify the value of information have focused on correlating what is most readily observable: IT spending and organizational performance. This first in a series of articles will help you understand how information creates organizational value, and how to quantify that value, by showing you how to measure key aspects of the utilization of information at key junctures along the causal links defined by decisions.

The boom in data warehousing and decision support coincided with the technology-driven bull market of the last half of the 1990s. During those high-flying times, it was almost impossible not to make money. Information - and the technology for collecting, storing, and managing it - was a source of competitive advantage. Although many companies conducted studies in an attempt to measure the ROI of data warehousing or decision-support systems (DW-DSS) projects, the major force driving the market was the fear of being left behind. I use the terms DW and DSS interchangeably because these days, there is enough overlap in their meanings.

For now, the heady boom times are over. You can no longer buy a new server, mumble a few incantations, and expect to receive a flood of new orders, customers, or investments. In these bearish days, it is increasingly necessary to justify all initiatives, IT or other, in terms of their quantified impact on your organization's key performance indicators.

So, how do you quantify the impact of IT investments on organizational performance to a skeptical and rational boss? Can it even be done? Traditional attempts have focused on linking the two things that are most readily observable: IT spending and organizational performance. While it is certainly necessary to measure IT spending and organizational performance, that isn't the whole story.

Crossing Hume's Chasm

The reason why performance isn't the whole story might be called "Hume's Chasm" (see Figure 1). As the empirical philosopher David Hume would have pointed out, although you may prove that $2 million were spent on a DW-DSS project and $6 million in additional revenues were recorded, these numbers do not prove that the spending on the DW-DSS project caused the increase in revenues. For example, sales may have increased because of a rapidly expanding market and would have still done so without the spending on the DW-DSS.

The only way to cross Hume's Chasm without falling in is to trace the utilization paths of information from IT systems on one end to organizational performance on the other. Decisions make up the causal links along these paths (see Figure 2). Thus, the only way to prove that changes to your information systems caused some measurable change to your organization's critical metrics is through a twofold approach: Link changes in measurable attributes of the information supplied with changes in decisions made, and link changes in decisions made with changes in your organization's metrics.

You can represent the relationship between IT investment and organizational value with linked ratios, where the D symbol represents a change. (See Figure 3.)

To link IT with organizational value, CIOs and CFOs should be shaking hands over decisions. CIOs should be asking, "What decisions will managers or executives make with the information generated by IT?" CFOs should be asking, "What were the decisions whose consequences are measured by our performance metrics?"

In an attempt to build a linked causal chain across Hume's value chasm, the purpose of this series is to outline an approach that enables you to measure or infer the following information value metrics:

• Source information quality
• Decisionoriented information quality
• Decision quality per decision
• Organizational value per quality of decision
• Changes in decision quality per changes in information quality
• Changes in organizational value per changes in decision quality
• Changes in information quality per changes in IT investment.

• Identify your most important decisions
• Look at the information quality for your most important decisions
• Determine which decisions rely the most on which information systems
• Determine which decisions rely the most on noncomputer information
• Assign a monetary value to the improvement of information quality
• Evaluate the relative merits of investing in different information systems.

The approach complements any management metric program currently in place, whether based on the balanced scorecard, value imperative, value code, activity-based management, or any other approach. You can also use the approach with any method for propagating estimated costs and benefits such as net present value, risk-adjusted return on capital, decision analysis, and real options (see Resources).