Author: Helen Thomas

Calculating Sell-Thru

Retail Sell-Thru

Sell through (or sell-thru) is a very useful metric for vendors to use in evaluating item performance, because it provides a composite measure of sales and inventory. But like many business measures, there is more than one method of calculating sell through.

The most common calculation is: Sell Thru % = Units Sold / (Units On-Hand + Units Sold). Sell thru is typically evaluated on a daily basis for fast moving products or weekly for slower moving or replenishment based products.  A higher value is better, indicating your sales velocity is good and your inventory is appropriately forecasted. If sell thru is low, this indicates either poor sales or too much inventory. In most cases, sell-thru for an item is compared in recent periods like current week and last week, as well as in aggregate across several months or even a year.

When evaluating sell-thru, it is also useful to group together products which have been selling for a similar period of time and/or which are sold into the similar store types. For example, comparing sell-thru for a product with 5 weeks of selling activity against a product with 20 weeks of selling activity most likely will not produce a useful comparison. In the same way, comparing sell-thru for a product in a group of stores in a highly affluent area is not likely to compare favorably to a group of stores with a low income level.

Most retail buyers have a set sell-thru percentage they use to judge vendors based on product category or department.  It is important for vendors to discuss the sell-thru expectations with the buyer in order to align with those objectives.

For reference, we’ve compiled sell-thru percentage data that you can use as a benchmark.



Create The Perfect Store Walk Report for Your Merchant

The strategic importance of walking a store with your retail merchant has been growing dramatically in the last several months.  Retailers like Home Depot and Wal-Mart are putting a strong emphasis on merchants spending more time in stores, so they can see firsthand the product presentation and get the pulse of what is happening at stores.  We have been told some retailers require merchants to spend a minimum of three days per week out of the office walking stores.

This creates a great opportunity for smart suppliers using point of sale analytics and reporting to drive high quality store walks and get the merchants to focus valuable minutes on their products on store walks.  The purpose of this article is to explain how you can grab as many of those minutes as possible.

First you need to create a store walk report.  The Accelerated Analytics store walk template includes the following elements:

·  Total store sales performance in dollars including rolling 52 week sales and prior 52 week comp, YTD sales and prior year comp, MTD sales and prior year comp.

· Store ranking based on total sales performance compared to stores in close geographic proximity.  If the retailer has BYO’s or Markets, like Home Depot, use those, if not, then use state and city.   We find it is best to present the ranking in terms of X out of Y.

·  8 week sales trend

·  Top 5 SKU’s and bottom 5 SKU’s based on unit sales.

For each of the top and bottom SKU’s, we include an image of the product along with the SKU and description, so the merchant can easily identify the product without having to go and read tags.  For each SKU, we also provide all the key metrics about that item including: rolling 52 week sales, YTD sales, last 8 week sales and comp year performance for each.  We include current on hand, weeks of supply and sell-thru.  Finally we rank that SKU based on sales performance among all the suppliers SKU’s sold in the store.

After you have created a store walk report, the next task is to get with the merchant so you can review and enhance the report based on additional metrics they want to see when walking the store.  By doing that, you not only end up with a report that is customized to their needs, but you also get their buy-in to use the report.  Essentially, you have created an indispensible tool for them and they will want to use it.  After the report is created, touch base with them frequently to find out what stores they will be visiting and when,  and then either send them the report for those stores or offer to tag along and bring the reports with you.

Our Accelerated Analytics customers have even taken the store walk to the next level using our iPad mobile access.  They are walking stores with the merchant, iPad in hand, and viewing the report in real time as they walk the aisle.

Many suppliers have become familiar with using point of sales reporting and analytics that is based on EDI 852 or retailer portal data, but taking it to the next level and creating targeted reports like a store walk report is where the value is really seen.  With a great store walk report, you can provide your merchant with the critical information they need and differentiate your company.  It’s a power tool that you need to add to your arsenal.

Even Simple Forecasting Can be High Value

Forecasting is part mathematics and part art, and due to this,  it can be extremely complex, but even simple forecasting can be very valuable.  Many vendors get too tied in a knot over the complexity of item and store level forecasting and then nothing gets done.  We encourage all vendors to start with the basics and increase the sophistication of your model over time.  Forecasting will provide you with critical information necessary to avoid stock outs and maximize your retail sales.  And if you do it right, you can gain a critical advantage over your competition and demonstrate to your buyers that your company is working hardest to be a good partner.

There is a simple process for forecasting.

1.   Sum the units sold for the most recent 5 weeks.

2.   Sum the units sold for the same period last year.

3.   Calculate the percentage change in units sold.

4.   Sum the units sold from the current week forward 16 weeks last year.

5.   Adjust the 16 week total to current year demand by multiplying times the calculated percentage change.

6.   Divide the adjusted 16 week units sold by 16 to get an average weekly forecasted units sold.

7.   Calculate a weeks of supply on hand by dividing the current on hand by the weekly forecasted units sold.

The forecast can be customized to your business by adjusting the base for the foundation (5 weeks above) to be longer or shorter depending on how heavily seasonality or promotional activity affects your sales.  E.g. shorten the period if your business is highly seasonal and lengthen the period if your business is primarily replenishment with little variability.  You can also adjust the current on hand value by adding any in transit inventory so you don’t overstock. 

Now that you have a good idea of the forecasted weeks of supply, you can use this value to make inventory production decisions.  Each vendor’s lead time to produce and land product at a store will vary, so you will need to determine your target weeks of supply and take appropriate action.

Vendor Managed Inventory (VMI): the Holiday Season

September 2 articles in the Wall Street Journal and the Chicago Tribune warn of potentially mild holiday buying driving inventory trends in major retailers across the country.  The chief concern cited in both: fear of too much inventory when the season ends and the resulting “frantic price slashing” (Tribune) and “discounting bloodbath” (WSJ). The Journal article cites slow back-to-school shopping as a harbinger of slow holiday sales and the Tribune goes on to quote a supply chain management expert as characterizing many retail locations as “zombie stores” regarding their dropping inventories.  “At best,” he says, “a store like that looks boring. At worst, it’s a struggle to get people to come in and buy product.”  This fear of clearance selling due to slow sales projections has retailers reducing the “breadth and depth of their assortments” going into the holiday season. 

For retailers, this trend is actually helping their numbers, keeping investors happy.  The Tribune reports that mainstream department stores and large discount chains actually improved their gross margin bottom line in the second quarter over last year (the notable exception being Macy’s).  But this trend can be bad for retailers, and the Tribune correctly notes that fickle, unhappy shoppers will just as soon go to another store to get what they want than buy the next best thing on the shelf. Further, Perry Ellis CEO George Feldenkreis says, “Inventories have been very depleted at retail and retailers are going to find themselves in a situation where some of them, if sales just improve a little bit, are really going to be out of inventory and they are going to be chasing inventory.”

What this means for vendors is that, among other things, it underscores the need for vendor managed inventory (VMI).  Given the current retail inventory trends and the projected trends for the holiday season, it is absurd for any vendor to think that they will be able to sit passively and wait for an order to be placed by their retail partners.  Rather, the vendor that supplies the most similar product to the need and can provide it most rapidly will be filling the voids this season, because the last thing that a retailer wants in this environment is to have an order need to be filled the next day and arrive three weeks later, too late to sell most of it, so that the lion’s share of the order ends up on a clearance rack.

So how does a vendor manage their inventory so that they can meet inventory needs at their retailers without too much cost for themselves?  Rainmaker has identified four key indicators that should be tracked:

  • Out of Stock Stores

    Stores with no items on the shelf cannot sell those items, and the longer they sit without sales, the less likely the retailer will be to re-order them in light of the industry trends.  However, take care not to overstock those stores by checking the sales trends for the last several weeks that the store did have inventory and the same period sales the previous year.  It stands to reason that sales will be down slightly over the previous year for most items, so reconcile that against the preceding several weeks and resolve stock outs immediately. 

  • Under Stocked Stores

    Current sales trends and same period sales the previous year combine to provide a valuable barometer for sales in the near future.  Consider these and identify those stores with too little inventory to meet anticipated demand, and bring them back up to minimum required amounts of inventory to meet the short term demand, lest they end up in the out of stock category.

  • Warehouse and DC Inventories

    Not all retailers distribute their products the same way, so knowing how the distribution of products works, and considering the general or store-specific inventories sitting in warehouses and distribution centers for retailers, will help prevent overstocking or overproducing products that may not be on a retail shelf, but might well be on a warehouse shelf or already on their way to a retail outlet.  Sum up item-level needs to resolve out of stock and under stocked stores to their associated warehouse or DC to prevent over-producing or over-shipping. 

  • Gross Margin Return on Investment (GMROI)

    MSRP is a fine concept, but more often than not, it isn’t a true gauge of what an item is selling for.  Additionally, shipping items to one retailer or store has different associated costs than to ship to a different retailer or store.  Calculating an average selling price for an item for each retail partner, and combining that with cost and inventory levels, allows one to identify which retailers are generating the highest gross margin return on investment. Further, as retailers reduce their assortments, key in on the items with the highest GMROI and allow the others to fade out.

To track these indicators, it is essential that it be done at an item/store level if buyers are going to take the vendor seriously and relinquish any control over the ordering process.  Managing inventory at this level can be difficult, especially for smaller vendors whose budget and resources are limited but whose retail partners are many.  Simply receiving, storing, and analyzing the vast amount of information required to track these indicators often requires whole departments, which are even then most often understaffed and overworked, degrading the quality of the answers they provide. Accelerated Analytics offers a comprehensive solution to these needs that culminates in a set of intuitive, business user-friendly reports that allow a vendor to begin analyzing data within hours of the arrival of data from a given retailer, rather than burning the lion’s share of time collating and formatting the information and only briefly analyzing it before it becomes stale. For a fraction of the cost of the overworked and understaffed department that attempts to handle these needs now, Accelerated Analytics’ solution can automate and improve this process dramatically. To see how Accelerated Analytics can assist in the resolution of your stock out and under stock troubles, request a free stock out exposure analysis or contact us today!

Lowe’s Integrating Planning and Execution (IPE)

Back in 2011, Lowe’s announced Q2 financial results with anemic growth and flat same store sales.   To improve performance, CEO Robert Niblock and EVP merchandising Bob Gfeller are implementing Integrating Planning and Execution (IPE), which places an emphasis on putting the right product in the right store at the right quantity.

This new focus got our attention since we provide EDI 852 data analysis and reporting to Lowe’s vendors.  Putting the right product in the right store at the right quantity is exactly what vendors use EDI 852 to accomplish.  Localized merchandising is the right strategy for Lowe’s, but they may run into some challenges executing the strategy with vendor’s assistance.

Many vendors we work with have Lowe’s as a customer, as well as other ‘big box’ retailers.  Across the board, these vendors get EDI 852 from their big box retail customers and we help them analyze the data at a SKU/store level.  But many of these vendors choose not to use Lowe’s EDI 852.

Instead,  they opt to pull reports from LowesLink®.  LowesLink® is a fine system for pulling reports.  The problem is the reports offer a snapshot of performance, not an analysis system.  If the vendor does not have a database to store weekly SKU/store data, it is nearly impossible for them to analyze weekly sales effectively and efficiently enough to participate in localized merchandising strategies.  Lowe’s does have Vendor DART which offers analysis tools, but the most powerful tools are reserved for large vendors.

Weekly analysis of EDI 852 at a SKU/store level is the foundation of a successful program like Lowe’s IPE.  Vendors know their products best and there are simply too many products for Lowe’s staff to conduct weekly SKU/store level analysis.  For Lowe’s Integrating Planning and Execution (IPE) to be successful long term, they must get vendors actively using the EDI 852.

LowesLink® is a registered trademark of LF, LLC.

Using Retail data for Forecasting Demand and Merchandising Planning

Many vendors have started to using EDI 852 data or retailer portal data for sales and retail merchandising, but so far, only a few are using EDI 852 data for forecasting of demand.  But the reality is, vendor inventory at stores is often too low to meet demand and the rates of out of stocks have been increasing. It’s not a big surprise that retailers are maintaining less inventory in stores in this retail environment; the cost of excess inventory is simply too high and open to buy dollars are at an all time low. But with proper forecasting of demand, a vendor can help the retailer to better manage inventory and avoid out of stocks. The great benefit of EDI 852 for merchandising planning is that it is store/SKU level data. Since a typical retailer is forecasting demand at a category and market level, the variability in the rate of sales among stores in a market can be large.

A more accurate model for forecasting of demand is to start at the store/SKU level, calculating an average rate of sale for the store/SKU and then based on the inventory on hand at that store, a weeks of supply. When the weeks of supply for a store/SKU has been calculated, the vendor can compare against the lead time to replenish the store and work to put a true demand driven supply chain in place. This model, while more intensive for the vendor to manage, usually creates a far different picture of inventory needs than simply market level min/max replenishment.

Improving Walmart Retail Link Data Analysis

Wal-Mart’s Retail Link* web site is a rich tool, providing vendors with a well of data for analyzing sales and inventory. The problem for many vendors is that Retail Link provides data, but storing the data, calculating metrics and providing users with analytics and reports can be a time consuming chore. Just this week I have spoken to three Wal-Mart vendors, who have dedicated staff to the task of running Retail Link reports and turning them into reports for other users. From our research working with many Wal-Mart vendors, we have calculated data manipulation and reporting averages 18 hours per week for most Wal-Mart vendors. On an annual basis, that is nearly 1,000 hours of administrative time spent just preparing data for analysis and reporting. In addition to the administrative time, there is a data storage issue most vendors encounter. Since the data is UPC/store level data, most vendors do not have the ability to store each weekly data file at the store detail level. As a result, they lose critical detail, as well as the ability to calculate key metrics like inventory weeks of supply on hand, or comp year performance comparisons. If your organization is spending administrative time preparing Retail Link data for analysis, consider for a moment how much more efficient it would be to eliminate that work and instead focus your staff on data analysis. What stores are performing poorly, what stores are performing above average, do you have the correct amount of inventory at each store? These are all questions your analysts should be analyzing, but instead they are spending half of their week preparing data. It’s a simple matter of efficiency and resource assignment.

*Retail Link is a Wal-Mart software application and is not affiliated with Accelerated Analytics.

Home Depot EDI 852

Home Depot vendors gain a critical advantage using Accelerated Analytics for point of sale data analysis. Home Depot vendors have the opportunity to use EDI 852 data to analyze their business and be very proactive in working with their merchants. A standard Home Depot EDI 852 document contains units sold, units on hand and dollars sold for each SKU and store. By storing this data each week and cross referencing the Home Depot store list, a vendor has the opportunity to understand store and SKU level selling trends and inventory consumption. The Home Depot EDI 852 data provides all the necessary ingredients to calculate key metrics like: inventory weeks of supply on hand, average rate of sale by store and SKU, and if you add your cost information you can arrive at GMROI as well. It has been our experience that Home Depot merchants expect a high degree of data analysis from their vendors, and it has also been our experience that they are very supportive of vendors who use the data to make recommendations on how to improve the business. The key to success is selecting a service provider like Accelerated Analytics that can help you store the data each week, calculate key metrics, and make the analysis and reports available to your sales teams in a timely fashion. Accelerated Analytics also provides advanced analysis like GMROI by plan-o-gram, which is critically important in working with your merchant. Armed with this data, we have seen vendors dramatically increase sales and optimize inventory levels.

Calculating Weeks of Supply Inventory

How to Calculate Weeks of Supply

A metric fundamental to managing the retail supply chain is weeks of supply (WOS). Weeks of supply tells the inventory manager how long the current on hand will last based on current sales demand.  By keeping your eye on weeks of supply, you can avoid inventory stock outs and lost sales.  The basic calculation for weeks of supply is pretty simple: on hand inventory / average weekly units sold.  However, our work with vendors demonstrates calculating an accurate and useful weeks of supply can be anything but simple.  Let me explain.  An EDI 852 document will provide units sold and on hand.   Very few EDI 852 documents provide data for inventory on order, inventory in transit, or inventory in the warehouse.  More sophisticated systems, like Wal-Mart’s Retail Link, will provide the additional inventory data.  So, the first issue an analyst working only with EDI 852 must overcome is to gain a complete picture of the inventory in the supply chain – all the inventory.  If you are working with a Home Depot 852 or a Lowe’s 852 you must also gather your purchase order and shipping data so that you have the ability to understand on order and in transit inventory.  You must also decide how to apply inventory in the supply chain.  That is, will you sum on hand + on order + in transit  to use as the numerator in your calculation?  Or perhaps you would prefer to ignore the on order due to long shipping lead times and use on hand + in transit.

Weeks of Supply

The next consideration is how to calculate the average weekly units sold which is the denominator in the weeks of supply calculation.  This requires some careful consideration.   If the number of weeks used to calculate the average is not selected correctly you will arrive at a misleading result.

One vendor has products which are non seasonal and tend to have very steady and consistent sales.  The other vendor has products which are seasonal and sell much higher in the warm spring and summer months.  When choosing the number of weeks for calculating the weeks of supply, you want to consider the rate at which your demand changes.  If your demand is fairly steady,  like the non seasonal vendor, a larger number of weeks can be used.  If, however,  your demand tends to change rapidly due to seasonality or based on some event like selling licensed apparel during football season, then you should choose a smaller number of weeks.  Our experience shows that a seasonal vendor should consider a four week window of sales demand and a non seasonal vendor should choose 8 to 10 weeks.

The final point to make about calculating weeks of supply is to consult with your retail buyer on the period of demand they are using.  If you are using four weeks and they are using six weeks, you will arrive at different order quantities.  By discussing the calculation, you may find your method is more accurate or you may find the retailer has good reasons for their method.  If you still feel your method is more accurate, then calculate weeks of supply using both methods and track the accuracy over time.  This will provide you with the factual data to either change your calculation method to align with the buyer’s, or demonstrate to them why your calculation is more accurate.

Frequently Asked Questions about Accelerated Analytics

What is EDI 852?   EDI 852 is a standard data format used to transmit product activity data. Files are typically sent daily or weekly and will include sales activity by product, and for some retailers, inventory on-hand.  Activity is typically summarized at a distribution center level, unless store level data is deliberately selected. Some EDI 852 forms will also include pricing information, inventory on-hand but unavailable for sale, order point, order quantity, and order status. EDI 852 is provided as a text data file using special character sets to describe the coded data to the decoding software.

My organization is a manufacturer and our retail customers are offering to send us point of sale data.  Can we use Accelerated Analytics® to analyze POS data? 
Absolutely! Accelerated Analytics® was designed to provide business users with a simple and effective means to analyze POS data from both a buyer and manufacturer/supplier perspective. Our engineers can work with your team as well as the retailer to load the data into Accelerated Analytics® and format your custom reports.
Can we use Accelerated Analytics® to analyze EDI 852 data?
Yes.  As a part of our service we accept EDI 852 data and provide the translation into a useable format for reporting and analysis.
What’s the difference between point of sale data and EDI 852?
First, the format of the data is very different.  EDI 852 is provided as a text data file using special character sets to describe the coded data to the decoding software.  If you open an un-translated EDI 852 file, you will have a very hard time understanding what you are looking at.  POS data, on the other hand, is typically provided in a text file with descriptive column headers, which can be easily opened and used in Excel.  Second, EDI 852 contains a basic set of product activity data, while a POS file is usually much more rich.  POS often will include cost and price information, and more detail inventory.
What retailers are you working with today?
A list of our currently covered retailers can be found here.
What industries do your vendor customers work in?
Our customers include apparel, footwear, consumer products, specialty hardlines, health and beauty, pharmaceuticals, and grocery.
Do we have to setup our own reports?
Not unless you want to.  Our service includes many pre-configure template reports that we customize during the on-boarding process to meet our customers precise needs.  Templates are included for sell-thru, stock-out exposure, inventory on-hand, period over period sale and inventory comparisons, top selling items, and much more.  All reports can be viewed by product, product category, store, geography, time, etc.  The reports are saved and available to end users with one click of the mouse.
What is collaborative forecasting, planning and replenishment (CPFR)?
(CPFR) Collaborative Planning, Forecasting, and Replenishment is a business practices that combines the intelligence of multiple trading partners in the demand planning and fulfillment of customer demand. CPFR was pioneered by Wal-Mart as a next step to efficient consumer response (ECR) and vendor managed inventory (VMI) and is now promoted by the Voluntary Interindustry Commerce Standards Association (VICS). CPR is a proven retail supply chain improvement process.
What is the bullwhip effect and why is it important?
The bullwhip effect among supply chain partners is a situation in which the supplier has a clearer view of demand than the retailer, but a less accurate forecast. Traditional supply chains are extremely prone to this bullwhip effect; typical order fluctuations of +/-5% on the customer end can easily balloon to +/-40% on the manufacturer end, thus showing an increasing demand variation of 2:1 at each level of the supply chain. Accurate forecasting can help to eliminate the bullwhip effect and increase overall profitability by 5%. The most effective way of smoothing out bullwhip effect oscillations is for suppliers to understand what drives demand and supply patterns. Understanding demand and supply patterns is best accomplished through a detailed look at POS data.
What makes Accelerated Analytics® unique?
Accelerated Analytics® connects buyers and suppliers in a collaborative environment, where point-of-sale data is used to improve forecast accuracy, demand planning, and decrease stock-outs. The Accelerated Analytics® environment is a hosted service including pre-configured reports, world-class analysis tools, and color coded exception dashboards. These tools quickly turn data into actionable information and promote data based decision making.  With Accelerated Analytics®, there is no software to buy or install and Rainmaker Group does all the data processing.
Who are some companies that have implemented collaborative planning forecasting and replenishment (CPFR)?
Over 150 companies have implemented collaborative planning forecasting and replenishment (CPFR) including: Sara Lee, Wal-Mart, Schering-Plough, Walgreens, Kmart, Target, Eckerd, Safeway, Ace Hardware, Manco, Canadian Tire, Johnson & Johnson, Carrefour, Henkel, Kimberly-Clark, Marks & Spencer, Metro, Proctor & Gamble, Sainsbury’s, Nestle, Best Buy, Scan Disk, and Federated. In all likelihood, there are many more unpublished implementations as well.
How is my retail supply chain improved by demand planning using EDI, DDSN, or CPFR?
Studies of retailers by Harvard Business, Grocery Manufacturers Association, National Retail Federation, and AMR Research show results of 15% less inventory, 17% better perfect order performance, and 35% shorter cash-to-cash cycles. The close collaboration between buyers and suppliers makes these improvements possible. Accelerated Analytics® provides the technology in a hosted service so there is no hardware or software to purchase.
If our suppliers are not asking for POS data, why should I consider Accelerated Analytics®?  
It’s not a surprise your suppliers are not asking for data. Most suppliers are intimidated by the prospect of asking for POS data and they do not have the tools to manage and analyze that volume of data. Successful business transformation does not begin as a reaction, but rather because business leaders have the vision to proactively invest in tools which drive their business forward faster than their competition. Research shows that when retailers proactively engage suppliers to collaborate on demand forecasting, 57% report improved relationships. Demand planning in the retail supply chain and collaboration between buyers and sellers, leads to more accurate forecasts and higher sales.
Why can’t we just use our electronic data interchange (EDI) system to send suppliers demand planning data?  
Many retailers have tried using EDI 852 to take advantage of collaboration and demand planning opportunities with suppliers. This is a natural first step; the infrastructure for EDI 852 is already in place, serving as the communication medium between retailers and suppliers. But most retailers are finding that sending out an EDI 852 document with summarized POS and inventory replenishment does not provide much benefit. Why? EDI does not add any new information; EDI is summarized at such a high level, it provides about the same detail as the purchase orders already in the system. The best a supplier can do with EDI 852 is load it into excel, because they do not have an analysis tool. In addition, parsing out a separate EDI 852 file every week for each supplier is time intensive. Most importantly, the supplier rarely has the tools necessary to accept the data and conduct effective analysis.