## Decision Data

Don't make a decision in the dark - Get the light of data

When you want to make an important decision, your decision data can make or break the decision making process. It is about the old adage "Garbage in, garbage out1." What you want is "Good data in, good decisions out."

The first kind of data that you want is data that will define the problem or decision to be made. Let's consider an example:

## Example

Your company ABC Corp has received a request from one of its divisions to purchase a backhoe. The backhoe requested will cost \$75,000. You, a new business analyst, decide to gather some decision data. Upon investigation, you find that the requesting division only used a backhoe 4 times for 12 days total in the current year. In the previous 2 years, it was 10 days and 15 days. Rental on backhoes is \$250. / day for an average cost of \$4,000. / year. Using just a rough and dirty payback method of economic analysis without even considering time value of money, you find that the payback time is about 19 years. Hardly a capital project that gets a CEO excited. With the data that you have collected so far, you would probably make a no decision.

You decide to dig a little deeper. You find that because that division is in a small town they have also have to rent a flat bed truck to transport the backhoe from a rental yard that is 50 miles away. That adds a cost of about \$3,000 per year. In addition there are 2 other companies in the same town that use backhoes. They must rent and transport also. Their average combined usage is about 40 days per year. An inquiry finds that they would be willing to rent your backhoe to save transportation cost. Now you economics look like this:

```Backhoe cost     \$75,000
Annual savings     7,000
Annual revenue    10,000
```

The payback of about 4 years is much more attractive. It is well worth doing a more accurate analysis. Doing a thorough job of researching the data turned a bad capital project into a good one.

## Summary

Good research to gather decision data is important in 2 major areas of the decision process. First you gather enough data to really determine what the problem is. If you don't really understand the problem or the decision to be made then you are just wasting time. Second, you can't make good decisions if you don't consider all options. You should gather an exhaustive list of the feasible alternatives to solving the problem or making the decision.

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