Manufacturing Indicators Rise Sharply

April 20, 2010

The quarterly Manufacturers Alliance just released their survey of manufacturing indicators and the results are very encouraging. The composite index rose from 57% to 78% which is the highest reading registered since the June 2004 survey. New orders, backlog, and shipments are improved.

Read the full survey results


Wal-Mart Cutting Prices

April 9, 2010

I noticed this in a WSJ article today on Wal-Mart aggressively cutting prices on 3700 items.

“Chief Marketing Officer Stephen Quinn said Wal-Mart expects to expand the number of price cuts in coming months with help from suppliers. Wal-Mart is encouraging them to reduce what they charge the chain in exchange for having it spotlight their products as part of its price "rollback. It forces them to sharpen their pencils a little bit and see what they can do to be a part of this," Mr. Quinn said. "Obviously they are competing with each other to get space and visibility at Wal-Mart."

Our company counts many Wal-Mart suppliers as clients. We provide sales reporting and inventory analysis services for them and I can tell you many are already being preassured by Wal-Mart to cut their prices. It’s a tough spot for a vendor, don’t cut your price and risk loosing a huge platform for distribution, or cut your price and reduce the profit. We are workign with these vendors to create price elasiticy models to hopefully avoid price cuts but in the case they do agree to a price cut study the effect. Remember not all products sell more with a lower price, and certainly the margins are reduced. Carefully analyzing the data and presenting your business case to the buyer will be critical to avoid a “rollback” becoming a permanent price cut.

Retail Sales Increasing

April 7, 2010

Despite uncertain economic reports retailers are expected to report increased sales according to an article in the WSJ.  Of interest to this blog the article noted retailers have been doing a good job of managing inventories in a difficult environment.  As we work with our clients a great deal of emphasis has been placed on forecasting sales demand and identifying out of stocks.  We have blogged a lot about how to use EDI 852 and point of sale data to manage inventory effectively and now is a great time to get started if your organization is not fully using data to improve your business.  With instock rates in the 98% range a vendor still has the opportunity to increase sales significantly with better inventory management.  Don’t miss your opportunity to get that last 2 or 3% of sales.

Supply Chain Analytics: Challenges and Solutions

March 11, 2010

Retailers and vendors in today’s retail market face the unenviable challenge of reducing costs and maintaining margins despite falling overall sales and slow-to-recover consumer demand. One of the areas in which retailers are pushing back onto vendors to is inventory management, which for vendors too often translates into retail partners that reduce overall inventories and require tightened delivery deadlines.  Retailers view the supply chain as one of the key places in which costs can be reduced—or better yet, passed off onto someone else—as a means of keeping shareholders happy despite reduced POS sales.  Wal-Mart continues to set the pace in this area, reducing its overall inventories across the board, reducing its brand assortments[1], adjusting its purchasing methods[2], and imposing tough penalties on those that miss their Must Arrive By Date (MABD).[3]

Thus, the impetus has fallen to vendors to manage their supply chains more efficiently so that the cost-savings being realized by their retailers’ inventory adjustments might trickle down to them as well instead of becoming a proverbial albatross.  And while the “glass pipeline” may remain elusive, industry experts postulate that, “Visibility of supply chain costs have never been better.”[4] Since, then, there remains continued pressure on everyone in the industry to reduce costs, there exists an opportunity now to address supply chain optimization unlike any time before.

As in all such processes, the first step in addressing this optimization is identifying the major challenges, which while not simple by any means, can be boiled down to three major focal points:

  1. Reduce supply chain costs
  2. Improving the responsiveness of the supply chain
  3. Managing demand volatility and Variability[5]

From an IT perspective, there are things that can be done with the data already being generated or received by most companies (even small ones!) to address some significant portion of each of these.

Reducing Supply Chain costs

While the operating costs of a supply chain are often the easiest numbers to point to and the most difficult for IT to address, there are data sources that can be leveraged to reduce costs.  For example, purchase orders, shipping data, and RTV (return to vendor) data is either generated internally or is received from retail partners (sometimes in a very straightforward EDI 812 document).  Unfortunately for many companies, these data sources come from disparate business systems and are stored in multiple locations, so tracking a single PO from the time the order was received thru the supply chain to its delivery at a store or in a DC is an arduous task requiring proficiency in Excel and fraught with the potential for human error.  Further, when compounded by the volume of orders received that many vendors keep up with, the task of tracking becomes futile, since the actionable information it generates rarely is identified in time to take the given action, but rather is often merely a confirmation of what has already been made known by retail partner that fined the vendor the late delivery or shorted pallet.  Thus, the lost efficiency of the analysts and the fees assessed by the retailers become additional costs in too many cases, and analysis of this data is simply not conducted.  However, those vendors that are able to aggressively track this data and address issues that may arise in a timely manner can avoid fees and improve their relationships with their retailers.  Unfortunately, upper management often struggles to see beyond the concrete costs figures and consider these less concrete but no less important opportunity for increased revenues or avoided fees.

Improving Responsiveness and Managing Demand Volatility and Variability

The delayed turnaround inherent in the difficulties discussed above relate directly to improving the responsiveness of the supply chain.  That is, supply chain utilization must address two areas of responsiveness:

  1. Responding to existing issues
  2. Responding to potential issues

Existing issues, as already discussed, are difficult to ID due to the disparate sources of data and the corresponding amount of time it takes to collate the information and determine what issues actually exist, since addressing existing issues is time-sensitive.

Potential issues are no less difficult, since these are often identified by considering all the aforementioned data sources and then including additional data sources such as POS data (from which forecasts are derived).  Mike Griswold, VP Retail for AMR Research, says, supply chain optimization “involves better forecasting methods and moving away from looking at warehouse shipments and toward POS and online sales data.” He goes on: many vendors fail to utilize POS data effectively for addressing supply chain issues because “it’s easier to get your arms around warehouse shipments because you’re dealing with weekly or twice-weekly sources of data.  When you get to POS, you’re getting down to day-level granularity for items and stores, and creating a forecast for three or four weeks out requires a fair amount of processing power.”[6] Of course, Griswold qualifies his position—forecasting based on POS and other data sources isn’t the final step.  “Retail is not designed to be an inventory holding area,” he says. “You may [get] an order for 1,000 televisions to be deployed across 100 stores, but not every store can handle 10 of each item.”[7]

Thus, forecasts must be based on actual POS historical sales, current trends, other considered supply chain factors, and tempered by the limitations of the stores for which the forecasts are generated.  Retailers provide a shelf-space and assortment designation (called plan-o-grams, modulars, sets, etc.) for most vendors which allows vendors to consider these factors when filling orders, and combined with their own warehouse quantities and capacity, now a very comprehensive and useful picture emerges, from which one may then deduce those potential issues and act to address them, instead of reacting after they become a time-sensitive emergency.

How Accelerated Analytics® Can Help You Optimize Your Supply Chain

Unfortunately, University of Pennsylvania professor of Operations and Information Management Marshall Fisher says the industry trend for vendors faced with the decision to have too little inventory and lose sales or have too much and be forced to liquidate leans toward the former. “Most companies are just moving along with less inventory. They are downsizing to meet less demand and accepting higher stockouts. The risk of a lost sale is smaller than having lots of unsold inventory.”[8]

But what if you had an integrated database solution that tied all of the disparate sources of data together into a single source of truth, from which actionable decisions could be made on timely, comprehensive data? The Rainmaker Group™, creators of Accelerated Analytics®, was first a business intelligence (BI) company and its expertise in BI solutions can be leveraged to create such an integrated database behind the Accelerated Analytics® interface, creating a powerful yet user-friendly tool that business users need and which management can understand.

Advantages offered by Accelerated Analytics®:

  • Integrated database to tie together all your data sources (P.O. files, Shipping documents, POS data, Plan-o-gram files, and more!) in a single location from which may be derived a single source of truth.
  • User-friendly reporting solution which provides rapid access to any of the data in the system and reduces the overhead normally associated with the collation and calculation of data
  • Exceptions reporting to identify shipping delays, stockouts, etc. automatically as often as required.
  • Proven forecasting methodology to generate proactive forecasts based on actual sales and inventory information


[1] Reda, Susan. “With SKU Reductions Under Way, Which Will Survive?” Stores March 4, 2010.

[2] Birchall, Jonathan. “Walmart Aims to Cut Supply Chain Cost,” Financial Times. 3 Jan 2010.

[3] Cassidy, William. “Wal-Mart Tightens Delivery Deadlines.”  The Journal of Commerce. 8 Feb 2009. 

[4] Lewis, Len.  “Delivering the World: Navigating obstacles in pursuit of global supply chain optimization.” STORES Magazine. February 2010.

[5] Based on the results of a Supply Chain Leaders’ survey conducted by IGD, a London-based consultancy.  Lewis, Len.

[6] Lewis, Len

[7] Lewis, Len

[8] Lewis, Len

You’re not the only one

March 7, 2010

I sat down with an analyst at a consumer products company the other day and had an in depth conversation with her about the process she goes through to export data from Retail Link and transform the data into reports for her management. I’ve been working with Wal-Mart vendors for a long time so I have a good awareness of the effort that it takes to go from raw data downloads to finished reports but this detailed conversation was an eye opener. There were 17 unique steps to get from point A to point B and they consume about 13 hours per week. The process starts on Monday morning and reports are distributed to management before lunch on Tuesday morning. Management reviews the reports and then typically sends follow questions and requests for detailed drill down as the week progresses. One weeks cycle runs into the next week’s and on and on it goes. If you’re shaking your head and saying “yep that sounds just like my job” maybe you can take some satisfaction in knowing you’re not alone. Keep up the good work, knowing what’s’ happening at the point of sale is critical and your efforts are making it happen.

Calculating Weeks of Supply

February 25, 2010

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. 

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.  Consider for example the sales for two vendors as seen in this chart.  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 sum mer 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.

Getting buyers to agree to a test

February 24, 2010

Getting your buyer to agree to push order recommendations, modular changes, SKU assortment changes, etc can be a challenge.  Here is some practical experience on how to make it happen.

Running a test with your buyer can be a very effective way to ‘sell them’ on new ideas.  Many times our clients want to use our forecasting tools to push recommended orders to replenishment managers but the replenishment manager is not receptive to adding extra work to their day and they certainly don’t want to risk overloading stores with too much inventory.   Many times our clients want to change the modular assigned to a store or SKU assortment within an existing modular but again the buyer is reluctant to make a change that could have negative results.  Proposing a test is a good way to limit their risk and overcome their concerns.  If the test is properly designed and the control group is selected to provide a proper comparison your idea should receive a fair vetting.

I spent considerable time today helping a client build a list of stores for a modular test at Wal-Mart.  My client has modular’s at Wal-Mart in the following widths: 40’, 36’, 32’ 20’ 12’.  The SKU assortment grows based on the width of the modular so a 20’ modular has all the SKUs of a 12’ modular plus some extras.  They have gained the agreement of their buyer to test 25 stores with a larger modular than the store would otherwise qualify for to see if the demand for their products is deserving of more square feet.   The test stores were identified by the buyer and are in close proximity to my client’s office so they can easily visit the stores.  The test stores have all been promoted to 36’ modular’s which is larger than they had in 2009 and larger than they would otherwise be traited for based on their profile.  The task today was to identify 25 control stores so we can test the sales lift over a 18 week period.  To identify the control stores the following information was pulled out of Retail Link: 2009 total units sold by store for all stores in my client’s home state.  The first thing we did was calculate the minimum, maximum, average, and median 2009 unit sales for the test stores.  We then eliminated all potential control stores which were not within the min/max, and then further narrowed our list by looking for stores that were +/- 20% of the median 2009 test store group unit sales.  All stores in the test group are Supercenters so we then eliminated all stores under consideration for the control group that were not Supercenters.   The next consideration was the demographics of the test store group compared to the potential control stores.  We pulled a list of demographics for test store group using the store zip code for each of the 25 test stores and looked at the following traits:  population density, median income, dominate race, and median age.   We created a profile using the averages for these traits.  We then cross referenced the possible control stores demographics along the same traits to identify the closest matches. 

The key is that by using UPC/store level EDI 852 or Retail Link data the vendor is often in a better position to analyze the demand of individual stores and make recommendations to a buyer on things like orders, modular’s, and SKU assortment.  Store level planning is the holy grail of maximizing sales but I’ve not met a buyer yet that has the time or resources to do that.   So the responsibility falls on the vendor to make it happen and proposing a test is often the way to get the ball rolling.  more information on retail analysis.

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Retail Replenishment – How tuned in are you?

February 23, 2010

I spent about 9 hours yesterday analyzing sales, order, and forecast data for Wal-Mart, Home Depot, and Lowe’s vendors and I am somewhat surprised by my observations.  It’s pretty clear there are some min/max rules in place as I can see patters to the order quantities based on the OH inventory and the order case pack quantities.  However what surprises me is that I also see a large number of what I would guess are “manual overrides.” That is UPC/stores which clearly need inventory and fall under the minimum OH of other stores but which do not have open order, and UPC/stores that are clearly overstocked (e.g. high WOS) and yet have an open order.  It makes sense there would be automated replenishment rules in place and then some lead-way for the buyer/replenishment manager to make judgment calls so that leads me to my question….

What do you know about your key retail customers replenishment rules?

  • Simple min/max ordering?
  • Based on OTB dollars?
  • WOS trigger?
  • At what level is demand calculated?  e.g. Category/Region, Category/State, Sub-category/State
  • Under what situations will the buyer do a manual override?

Positive Signs In Retail

February 23, 2010

Nordstrom and Lowe’s both reported big increase in profits and their CEO’s believe the economy is improving and their sales will continue to improve.

Nordstrom’s Profit More Than Doubles

Upscale department-store chain Nordstrom Inc. reported a 152 percent increase in profits during the quarter ended Jan. 30, underscoring how its strategy of expanding price points and carrying more exclusive merchandise is leading to more full-priced selling. The 108-year-old Seattle retailer missed Wall Street’s profit expectations by two cents a share on higher expenses and credit card delinquencies. The company’s shares fell 3.8% in after-hours trading, to $34.75.Nordstrom maintained a cautious outlook for 2010, noting that it expects same-store sales to increase between 2% and 4%,

Lowe’s Profits Up 27%

Lowe’s Cos. reported a 27% jump in fiscal fourth-quarter earnings amid signs that U.S. consumers are at least starting to consider home-renovation projects again after more than three years of hesitation. Chief Executive Robert A. Niblock said the home-improvement retailer’s first year-over-year quarterly earnings increase in seven quarters suggests "the worst of the economic cycle is likely behind us." Lowe’s expects to see a monthly same-store sales increase during the second quarter—the retailer’s peak selling season.

Making the most of Retail Link Data

February 18, 2010
Making the most of Retail Link Data
Wal-Mart vendors have access to a wealth of sales and inventory data through Wal-Mart’s Retail Link portal. The challenge for many vendors is that Retail Link can provide access to extremely detailed data which increases the quantity and difficulty of analyzing the data and making fast business decisions. Without the right tools the process can be very time consuming and difficult.

If you are a Wal-Mart vendor invest in a set of tools that will allow you to store and quickly analyze Retail Link data. The tool should allow storage of multiple years of store and item level detail and it should provide filtering and sorting to narrow the focus of your decision making. The focus your fist analysis efforts should be sales velocity and inventory in-stock. The tool should automatically filter the top 50 and bottom 50 stores by unit sales volume. This allows the vendor to quickly identify which stores are driving the most volume, as well as the stores that need immediate attention. Next it is critical to identify on a daily or weekly basis the stores that are out of stock. Fixing the inventory out of stock in these stores will directly increase your sales.

Become proactive in dealing with out of stock at a store level by reviewing the unit sales volume for all of your out of stock stores for the 8 periods prior to the out of stock. Determine an average period units sold and then identify for each store how many periods it takes to get new inventory to the store. So for example, if a store is averaging 6 units per week and it takes 14 days to get inventory to the store then the minimum inventory level that store should maintain at all times is 12 units. This provides two weeks of inventory on-hand and will allow for proactive replenishment to avoid stock-out exposure. As a Wal-Mart vendor you may be selling into over 3,500 Wal-Mart stores but if you complete this analysis for the top 70 or 80% of your stores based on units sold velocity, you will have gone a long way toward reducing out of stock situations and increasing sales.