Testing Your Costing Data

Feb 10, 2016

When is the last time you took leftovers out of the fridge and conducted the ever so popular “smell test”? Believe it or not, we conduct the “smell test” on a daily basis. We may smell a baby to determine if a diaper change is necessary, or you may smell your child’s breath to see if they truly brushed their teeth like the said. While this is a method we use to determine if something “passes the test,” have you ever considered  areas of life where we conduct (not so literal) smell tests?

Data TestingFor example, when educating my 8-year-old on subtraction, I explain the answer cannot be bigger than the number from which you are subtracting. The number can be the same, if subtracting zero, or smaller. However, if the end result is larger than the number subtracted, there is an error. To me, this is a great example of applying the “smell test” to a given scenario.

Are there areas of your personal or professional life where you knowingly applied such a test? What are they?

I am working with a client who would like to update their cost system. Several years ago, when we established the system, we did not have a lot of actual data to build from or support the model. Over time we have produced more and more extremely valuable real-time data. However, we have never linked our cost model with this data for validation. Counter-intuitive processes have been occurring and as a result, management has asked us to determine the cause.

We have determined part of the issue involves assumptions being built upon years of assumptions. Actual data from the past year was not compared to see how close the model delivered. In addition, last year’s actual information was not utilized to develop the current model with the current year’s assumptions. The future was built upon years and years of assumptions, which most certainly resulted in numerous inaccuracies. Now irrelevant information has been developed and used.

Upon being hired, we recognized the current methods were not passing the “smell test.” We hired 24 additional employees and our sales were expected to increase by 10%, yet our model told us labor hours would be 30% less than the prior year! Management said they have become more efficient and plan to develop even greater efficiencies in the coming year, but wow!

It is critical to take the time to step back and evaluate your data. Does this make really sense? Is this the end result I anticipated? If not, then why not? You can build your own “smell tests” into your model which force you to consider key points for operational and financial growth.  Use formulas to help you recognize areas of concern.

Categories: Cost Accounting