Crystal Reports Administration: Report Accuracy Issues

In other articles, we talk about data accuracy. That is an essential component of report accuracy. But, even if all of your data are accurate and current, your Crystal Reports might still fail to be accurate. How can that be?

Let's consider a case history. Dave was the National Sales Manager for a company that sold informational products. Dave's sales people were supposed to record the reason for losing any given sale. Dave noticed from his Crystal Reports that "too expensive" was the #1 reason. However, sales experts like Gitomer routinely say price is seldom the reason.

Dave decided to go on a few sales calls, and he soon learned the reasons included such things as:

• Sales rep not listening to customer's business needs.
• Sales rep not educating customer on value of the products.
• Sales rep wasting customer time and then trying to make the sale in the last few minutes of the appointment.

So, Dave redesigned the post-sale questions to include such things as:

• Customer business needs not clear.
• Customer didn't understand value of the products
• Sale not focus of the visit.

What Dave did was eliminate all excuses--external things the sales people couldn't control--and replace them with things the sales people could improve on. Now, the reports were accurate and truly useful.

If you can persuade managers in your situation to go after this kind of information--true business intelligence rather than political excuse-making--you will find the value of your job goes up exponentially.

Some other issues:

• The reports give a distorted view of the forest because they are lacking some key trees. It's easy to mischaracterize a situation by leaving out key data. This is similar to the situation Dave had, bit slightly different. In Dave's case, they were looking for the wrong information. In this case, they got the wrong information because they didn't ask for the right information.
  
  Example: Ron was the QA manager for a factory. He reviewed the customer returns, and found the most commonly identified problem was a cosmetic issue with Product X. However, the customer return cards did not have a choice for "Other" or for "battery-related." The most common problem actually was deformed battery clips. But, the database had no such problem in it, because customers were choosing other items from a list. So, the reports gave an incorrect picture of what problems needed addressing.
  
• The reports are laid out wrong. Such things as graphs not scaled properly, heading emphasizing minor issues, and important information being buried can all skew the perceptions of what's being reported--and thus lead to false conclusions.
  
• The reports fall into strictly Newtonian or Einstienian thinking. That is, they provide information in absolute terms only or in relative terms only. Some things need to be known as absolutes, and some things need to be known relative to other things.
  
  Example: Larry runs an electrical testing firm that uses databases heavily. Electrical equipment needs "baseline testing" to establish what's healthy for that particular piece of equipment. Two similar pieces of equipment may have very different measurements from each other. So, the concept of trending is important. Larry uses Crystal Reports to show trends of equipment condition. At the same time, he reports power quality events in absolute terms. It doesn't matter that events are more or less than they were last year--the fact they exist is significant.

Conclusion

Your Crystal Reports will be accurate only when three conditions exist:

• The underlying data are the correct data for the goals of the report (this is often not the case, as in Dave's example above).
• The underlying data are accurate.
• The report structure and layout are correct for the goals of the report.

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