Intelligent Enterprise

Better Insight for Business Decisions

RSS
Webcasts
Whitepapers
Subscribe
Home

June 13, 2001

Information Impact

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

By Erik Thomsen

Continued from Page 1

ORGANIZATIONAL METRIC QUESTIONS

1. What primary metrics does your organization - and its eternal analysts - use to measure its overall performance? Typical examples include sales, sales per employee, earnings before interest and taxes (EBIT), gross profit, gross margins, and earnings per share.

2. What are your key secondary metrics or key performance indicators? Secondary metrics aren't tied directly to an organization's financial performance. Instead, they reflect specific operational areas. Typical examples include customer satisfaction, product quality, and employee satisfaction.

3. Over what range of operational dimensions can you evaluate your organization's primary metrics? Can you evaluate earnings for each customer or per average customer; earnings per product or earnings per employee?

4. How would you compare the value of actions that have direct impact on the organization's primary metrics, such as sales-to-lead ratios, with actions that have direct impact on the organization's secondary metrics, such as improved manufacturing quality or upgraded retail space?

5. How would you compare the value of actions that affect only the organization's secondary metrics? For example, how would you compare the relative merits of improving customer satisfaction vs. product quality?

6. How would you rank your organization's metrics by degree of certainty? For example, cash on hand typically has a high degree of certainty, while customer lifetime value is composed of a variety of predictions and has a much lower degree of certainty.

Dss Self-Diagnostic Capabilities Quiz

Before you can improve the value of your DSS-DW systems, you need to be able to measure their current value. In order to measure their current value, you need to have the appropriate self-diagnostic capabilities.

The questions break down into organizational metric questions, IT questions, and decision questions (see the sidebars, "Organizational Metric Questions," "IT Questions," and "Decision Questions,"). By trying to answer the questions, you will discover your organization's DSS self-diagnostic capabilities. Note how all of the DSS value questions are in the decision category.

Congratulations if you can answer all of the questions! However, if you are like most readers, you would have a hard time answering most of the decision questions and even the more common organizational metric and IT questions. But if you can't answer all these questions, you do not have the ability to diagnose the state of your decision-support systems; you can't value the information that you are spending money to create, and you can't rationally choose between alternative information investments. Your organization's CIO and CFO are flying blind.

The DEER cycle Approach

The decision execution environment representation (DEER) cycle approach focuses on:

Decisions as the key information utilizing events

Decision consequences as what are (or should be) measurable by the organization's value metrics

The linkages between changes to:

Source-oriented information attributes (such as timeliness)
Decision-oriented information attributes (such as understood correlations between information values and optimal decisions)
Decision quality
Organizational values that could be financial or any other type of indicator.

The DEER cycle approach provides for varying levels of precision. It works just as well for information that resides in people. And it doesn't assume that decisions are the only source of value creation for the organization, but rather that decisions are the only source of value creation for factual information (such as sales data), as opposed to skill-enhancing information (such as online tutorials). Finally, the DEER cycle approach introduces a framework for looking at decisions and highlights the fundamental importance of good dimensional analysis in order to evaluate organizational metrics over the greatest location range possible.

The approach works by defining causal connections between changes, which affect measurable attributes of the information and changes to the measurable values of key organizational metrics. As shown in Figure 4, the DEER cycle connects measurable organizational metrics with the outcomes of key, activity-based, decisions within the framework of decision graphs that define the incremental organizational value of incremental changes in decision quality. Such changes in decision quality connect with incremental changes to the measurable attributes of information.

I will describe the DEER cycle approach in the remainder of this series along with the following three supporting topics, which you will also need to understand:

The phases of a decision cycle
How you can evaluate causal linkages through multiple passes of increasing precision
The interplay of dimensional modeling and organizational metrics.

As I would like you to get a quick feel for looking at decisions as the causal link between information and organizational value, I will end this first installment with a small example of how to use rough weighting, which is the coarsest form of valuation, to get a fast thumbnail estimate of the value of certain decisions, the value of the underlying information, and the quality of the information upon which you base your decisions.