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 a pride of ownership. While we don’t think the process should be completely devoid of emotion, it should be based on unbiased 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.

1.      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.

2.      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.

3.      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).

4.      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.

5.      Generate a category analysis: The category analysis is a roll-up 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.

6.      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 the 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.

Black Friday and Cyber Monday have come and gone but the holiday selling season is far from over. The commentators have put their musings and predictions out there. Consumers will have the final word. The (so-called) impeding death of malls and stodgy chains will be further discussed. So, what’s a retailer to do? Was their holiday fate set several months ago when they planned it? Maybe, but it’s all about execution. Retail is hard work but built on the simplest of principles that are so often forgotten. That’s why I want to focus on the 2 most important- customer service and making sure inventory is turned quickly and appropriately.

It’s a war out there and there is no room for anything but exceptional service. This applies both in-store and on-line. The customer has so many choices and few tolerate mediocre experiences for the sake of getting the perfect item. A recent experience at Walmart.com proves poor customer service isn’t limited to brick and mortar. A holiday gift for our kids ordered 2 weeks ago still hasn’t arrived even though we’ve been given 2 specific delivery windows. They wasted our time- 2 days of “must be home to sign” and 7 calls to Walmart customer care. Our experience was that they could care less. Poorly trained call centers, lack of communication/visibility and too many cooks in the kitchen highlighted how Amazon will continue to beat them with their effective distribution formula. And this wasn’t the first time we had a problem with Walmart drop ship fulfillment (Walmart, please call us to see our Drop Ship Tracker software!). In fairness to Walmart, other items in the order that they had in their DC’s arrived very quickly.

On the other side of the spectrum, a truly wonderful experience can remind us why making a physical visit to a store can provide entertainment and be more fulfilling than just clicking a few buttons. At a recent trip to the mall- this one alive and well- I found associates in just about every store I walked into upbeat, eager to help and caring. I could tell some coaching had taken place. I got the shoes I needed and other items that I didn’t.

Now to inventory. Making the sale requires having what the customer wants when they want it and where they want it. During my store management days, I learned first hand how foot traffic and the velocity of sales changes so dramatically during the holiday. I think a good analogy is the ERS Star Loop- which is based on a concept created by USAF Colonel John Boyd. According to Boyd, decision making occurs in a recurring cycle of observe-orient-decide-act. An entity that can process this cycle quickly, observing and reacting to unfolding events more rapidly than an opponent, can thereby “get inside” the opponent’s decision cycle and gain the advantage. I know it’s an extreme example, but it holds true for retail. The holiday season is a microcosm of inventory flow at the lowest level. We work months in advance to plan our receipt flow just right. But during the holiday season, every day and in many cases every hour equals a week or month. Whoever can react to the consumer’s needs the quickest wins. A key is constantly replenishing stock through the day and monitoring what’s happening on the other side of the mall.

Suppliers play a key role as well. They should be studying sales and inventory at a greater frequency and seeing if they can provide support to quicken the pace of the decision loop. Those suppliers who are willing to put in the extra effort usually are rewarded with additional sales and become a more trusted advisor of the buyer. VMI (vendor managed inventory) can be a major advantage for retailers, especially at holiday. With the supplier constantly monitoring sales and using smart systems to check stock positions they can write orders every day. Depending on how fast they can move inventory through their fulfillment process the more benefit it brings.

So, the next few weeks will reveal the winners and losers and the commentators will come back with their post season “I told you so’s”. As for me, I’ll be stuck in a loop of constantly thinking about new analogy’s to compare retail to. 

 

Like most people in the retail industry, merchandising is built into my DNA. It means I can’t walk through a store without straightening a shelf, wondering how well something is doing or chatting with a sales associate like they were my best friend. Unfortunately, it never switches off. Not even on vacation. I recently took a weekend cruise with some of my family. We were on a shiny new Carnival ship (Horizon) that just launched in April. There were lots of fun and thrills as most of these floating cities now must keep you and 5,000 of your closest friends busy. The ship had many things I have not seen on a cruise ship before including an IMAX theater, a sky bike (terrifying but fun), smart elevators (more on that later), and a significant amount of space devoted to retail. With limited physical space, the designers of the ship obviously had to think through how to optimize the selling area. There were several small stores- liquor, jewelry, logo merchandise, island apparel, and our favorite- the “Cherry on Top” candy store. Most of these stores had both an enclosed area and open “sidewalk” space. The enclosed part was very small- maybe 10’ X 8’. But outside the door, in the aisle were tables with products at promotional prices. With constant commentary of retail revolutions, the impending death of brick and mortar and the like, it was nice to see good, old-fashioned merchandising and promotion at work. I’m talking about the basic fundamentals that so many companies have lost sight of. Attracting customers with great displays, offering round the clock advertisements for specific items and holding experiential events to draw customers into the store to keep them there. Granted on a cruise ship your audience can’t escape you, but with so many choices of things to do, capturing their attention is no easy task. There was plenty of business in the duty-free shops. The souvenir shops had plenty of traffic, but the selection was very limited compared to the amount of space devoted to it. What really seemed to be doing the best was the candy store. Besides a fresh ice cream parlor in the back where you can pick your own toppings, they have the traditional bins with assorted chocolates, gummies, and hard candies. They also had several boxed gift sets and old-fashioned favorites targeted to my age group (remember pop rocks and bottle caps?). The point is that retail venues come in so many shapes and sizes these days but the simple formula of engaging and compelling the consumer still works regardless of format. Playing to the consumer’s imagination is still a dopamine rush that translates into more sales.

Now on to those smart elevators. I’ve seen them before in some buildings in NYC- you enter the floor number you want to reach, and you are assigned an elevator. There are no buttons inside the elevator. Generally, they work well because fancy algorithms are optimizing the most efficient way to move everyone to where they want to go. Sounds like a great idea for a cruise ship with 5,000 passengers. Not so much. At peak times, they were utterly useless. Waiting for an elevator, you have no idea when your door will open because you don’t see what floor it’s currently on. Am I waiting for a minute or 10 minutes? If there are 5 people in my party do I select the floor I want to go to 5 times, so the elevator can anticipate capacity? One fellow vacationer made the comment that he liked it because kids can’t go inside the elevator and push the button for every floor. About 10 minutes later I watched a kid hit the button for every floor- waiting for the elevator. Talk about killing the algorithm! When there were not large crowds, they worked great. When there were large crowds they caused more frustration than conventional elevators. At ERS we are in the inventory optimization business, so we know a thing or 2 about bias. It’s all about the model and making adjustments.

I commend Carnival for optimizing the retail space and creating something experiential and fun. But please, bring back the dumb elevators!

A lot of retailers and manufacturers are turning to data scientists in the hope that they can make heads or tails of data. That’s a great thing- but a carefully crafted strategy and goal on exactly how data can be used to improve business is a necessity. Furthermore, data scientists may have great technical skills but lack the necessary retail knowledge and experience to make use of those skills. It’s not about coding or using one of the many visualization tools on the market that matters. It’s the domain expertise that makes the difference. Not knowing what to look for is putting a lot of dollars to waste. Luckily, learning the fundamentals of retail is not hard. I offer the following five recommendations when putting your data scientist and strategy to work.

1. Know what questions need to be asked. Learn the fundamentals of retail. Determine benchmarks for performance- what is good, bad, relative to the business you are studying. When I introduce our interns to retail analysis for the first time I focus on two simple statistics. The number of stores that have inventory and no sales, and the number of stores with sales and no inventory. One implies there is an execution (presentation) problem and the other indicates a stock out. Fixing both have an immediate positive impact on business. There are many scenarios like this for both brick & mortar and e-commerce POS (point of sale) data. Our retail primer can help.
2. Don’t lose sight of the end consumer. The POS data we analyze exists because somebody bought something, somewhere, for some reason. The more we can explain each of those, the more we can improve our assortment, allocation, and timing. Studying POS by itself is introspective. It does help improve basic decision making but we have long integrated 3^rd party data with POS to reveal more game-changing insights. Understanding where to place tests, target products to the right demographics, improve inventory flow of seasonal products are just a few examples. What else affects shopping habits? Weather? Demographics? The price of a gallon of gas? This is essentially applying “Big Data” principles on a smaller, yet more usable level. A lot of 3^rd party data is free or cheap if you look hard enough.
3. Focus on inventory productivity. On both the wholesale and retail side of the business, the largest capital investment is inventory. The delicate balance of not having too much or too little is what every company strives for. Mistakes can be extremely costly, so improving inventory productivity by even a small percentage could mean millions of dollars added to the bottom line. Having the ability to analyze every SKU-store combination can bring to light many opportunities and liabilities that would otherwise go unnoticed.
4. Provide the required data to take action. Many analysts get caught up in the trap of thinking their role is to just uncover information. But what yields the most value is providing the supplementary data needed to take action. For example, if a particular SKU-store is determined to be under-inventoried, the action would be calculating a replenishment order. Then communicating what action is required with simple instructions and in a format that is easily implemented provides the greatest chance for that action to be taken. Creating a process for that should be part of the data strategy.
5. Evaluate the role of Artificial Intelligence. It comes in many forms and flavors from the use of simple algorithms to deep machine learning. We are just now reaching the point where AI can provide valuable insights depending on how large your business is and the tools you choose to use. The next generation of data tools will utilize it (like our RetailNarrative) so you need to understand what it can do for you. There are some encouraging developments in AI that I think will speed up our ability to catch and predict trends more accurately. Like humans, it must develop the knowledge and experience to know what to look for (We call it “Augmented Intelligence”).

The abundance and availability of data doesn’t necessarily relate to better decision making. You must know how to use the data. I have focused primarily on POS data here, but there are many other facets and data points at retail where similar data strategies can be used to yield positive results.