What is it?
A statistical snap shot audit is an objective method to rank certain operational aspects of a store’s performance. It compares the store’s activities to company averages and scores the store based on being above, at, or below other store’s performance levels. So for example, a store with a $100 refund average would be ranked (and scored lower) than a store with a $50 refund average.
Why is it important?
Truly objective data can provide greater insight and be a better predictor of future and potential losses.
Long Story Short
A statistical snapshot is a form of Forced Ranking applied to stores. Although it is a true and important measure of a store’s performance compared to other locations, it doesn’t take into account important differences that occur due to store size, revenue, location, or staffing.
Forced Ranking has been a controversial topic in employee evaluations although many large organizations continue to use it with positive results. In auditing, a statistical snapshot provides the same advantages with the same controversy.
The process starts by drawing on data we already collect and measure. Measurements like mark-out-of stock dollars, damages as a percent to sales, average items per transaction, average refund dollars, void count, dollars per transaction, etc. We combine each data category to discover the average across the company for each activity and then rank each store’s performance from best to worst. Future changes in averages tell us if overall performance is moving up, down, or staying the same.
During the audit process, each store would be graded on these defined categories in accordance with where they fell in the ranking or may be graded by whether they were above, below or at the average. The methodology provides a very objective analysis of performance. In addition, over time, we can determine which categories provide real predictors of certain problems e.g. Not meeting sales plans, high loss or shrink, poor customer service.
A statistical snap shot has the advantage of removing subjectivity from the audit process. It allows a company to see performance metrics very clearly and to determine the weak-points that require greater effort and additional resources. Much of the data will also help determine operational issues that will ultimately lead to bigger problems in lost profitability and sales.
The downfall, of course, is that the process does not take several important things into consideration.
For example, certain stores may be very well operated, may always achieve sales goals, and may be profitable, but because of traffic or shopper attitudes, the store experiences a high number of refunds or damages. By ranking these stores as under-performers we are not only missing the point, but may be punishing the operators instead of rewarding their successes.
Additionally, a statistical snap shot doesn’t contemplate the very fact that the law of averages insists that someone always be above and someone always be below that average. And even below average may be excellent performance. In this type of dynamic and the first example, there may be no action the store can take to improve the category. Worse, in trying to improve, the store personnel may create bigger issues—such as refusing a refund to hit their refund dollar goal.
The Balance Sheet
- Objective data
- Measures performance based on overall averages
- Identifies short-falls in performance metrics
- Focuses on Key Performance Indicators
- Creates a clear strategy for additional resources/improvements
- Results aren’t dependent on reviewer’s knowledge/expertise
- Does not contemplate differences in traffic, volume or demographics
- Does not consider that “below” average may still qualify as “excellent”
- Regardless of performance, by design, some stores will always be “below” the average
- In certain categories, there may be no efforts that can improve the performance
- Below “average” may not correlate to future problems
- A strictly number-driven resource allocation may result in missed problems
The Big Question
What’s the best way to leverage the snapshot’s benefits and avoid the pitfalls?
A statistical snap-shot has a number of advantage and can provide insightful information about the “state” of a store. However, the potential pitfalls warn against it as a single tool for determining performance. One method of use is to apply it as one score in a category of audit scores and work it into the final score. Through a weighted method, we can enjoy the benefits of this form of auditing without it skewing the important point that facts often require context to provide meaning.
Statistical snap-shots can be the best first step in discovering the correlations between store operational performance and shrink (loss) performance because the numbers provide consistent and objective criteria.
Authored by: Ray Esposito