As the holiday season comes to an end it’s a good time to reflect on what worked- and didn’t in your 2018 assortment. Studying the business by item- the productivity versus the investment made in each- cost, space, resources to manage, etc. can help determine what earns another year in the assortment. This process is commonly referred to as SKU Rationalization or Optimization. It has even more relevance today for retailers extending their assortments to compete online. It can be a gut-wrenching experience, especially if there is pride of ownership. While we don’t think the process should be completely devoid of emotion, it should be based on un-biased results. Those results should be taken with a grain of salt. I learned a hard lesson in my buying days of cutting too much out of the assortment. Your assortment must serve several purposes- tell your story, entertain, fill your customer’s needs and make money. Finding that balance between optimal inventory and not missing sales is a key goal.
Most people think rationalization applies only to replenishment or continuing items, but there is value in studying the entire assortment- including fashion- to uncover trends which can aid design and category planning. And it’s not just for retailers. We recommend manufacturers conduct an analysis on their lines as well. They need to understand the relationship between costs- design, production, warehousing and shipping- and profit generated. In the case of drop shipping it can be very risky, especially without a firm commitment from the retailer.
There are a variety of methodologies and formats that can be used to conduct SKU rationalization. For more complex rationalization with large assortments or extremely high or low velocities we use a multitude of factors and more advanced algorithms. However, even a simple analysis can yield great insights. Most of our simple rationalizations are based on sell through for a fixed period of time- usually launch of an item, that enables us to compare apples to apples.
The following 6 steps can be used to conduct a simple SKU rationalization analysis. To view the full example with additional content and images click here.
- Determine which statistics to include: The KPI’s chosen for the analysis should be based on the retail philosophy. For example, if the goal is to sell as many units as possible without regard to profit, then sell through % and units sold are key. If selling less but making more profit is the goal then profit dollars and gross margin return on inventory should be included. In most cases a combination of the variables will be used. Make a chart of the key statistics for determining performance and then weight the importance of each. This will be helpful when determining a composite ranking of performance that weights the statistics based on your retail philosophy.
- Establish a baseline: The baseline could be a specific level of performance you deem as acceptable, and compare actuals against that, or use the actuals to derive average performance for each category. Because some items may have shipped at different times, we generally like to look at the first 6-8 full weeks of selling (Sell through %) for items planned to sell for at least 6 months. For fast fashion first 4 weeks of selling may be more appropriate.
- Create quartiles based on the average performance: Quartiles are helpful because they provide a simple way to group similar performing items together and provide a sliding scale of how good or bad an item is. Determine performance for each item for the first 4-8 weeks of its life, then determine the average against all the items. Create the quartiles from that (Excel can do it for you).
- Assign items to a quartile: Now sort each item into its respective quartile. The top quartile represents the best performance. Be mindful of the overall performance- it is possible that even the top quartile was not acceptable, or that the bottom quartile was still excellent.
- Generate a category analysis: The category analysis is a rollup of the items into their respective categories. It shows how many items fall into each quartile and helps determine the percentage of the assortment that worked well and did not. We may assume that any performance except for the 4th quartile is acceptable. That would mean 4th quartile items do not continue. Of course, you can make your own assumptions based on your business.
- Visualize and Interpret the results: Now it’s time to clean up the analysis and make it presentable. Depending on how many items you have in each category this can get tricky. Try to create a simple template with 4 big boxes in it- one for each quartile. Then put the name and/or an image of each item into the respective quartile. This might draw out what items have in common- and that may have driven (or not driven) business. For example, maybe everything in the 4th quartile was a certain color or silhouette. Design teams can find this very useful. The count of items that were acceptable is important- and helps you define that relationship between number of items and the productivity you are trying to achieve.
To view a full example with images and more detailed explanation please click here. If you have questions about SKU Rationalization or would like templates please visit our website and contact us at www.enhancedretailsolutions.com.