POS analysis for strategic value

Several recent meetings with vendors has highlighted a growing trend - POS data analysis has been and continues to be an operations imperative, but vendors are increasingly finding strategic value in POS analysis. EDI 852 forms the foundation of the analysis with UPC and store level sales and on hand.  But looking beyond sell thru and tradition metrics, a savvy vendor can use the data to present to a buyer planogram compliance and even sales plans based on localized assortments. How many of your competitors do you think have that level of sophistication to present to a buyer? This is a great time to look beyond the regular use of EDI 852 / POS data and become a strategic resource to your buyer.

Walmart Point of Sale Data Reporting

If you are a Walmart vendor, you have access to a wealth of data via Retail Link. As a service provider, we work with a lot of Wal-Mart vendors, helping them to analyze the point of sale data made available by Walmart through Retail Link. Sometimes a vendor will ask us “If I have Retail Link, why do I need to hire someone to help me analyze POS data?”

Retail Link provides a method for getting POS data, but as the vendor, you will be responsible for transforming the data and you will need a database to store the data. Both of these are critical to provide for comp week and comp year comparisons which are the basis for accurate and insightful POS analysis. The complexity of building a database to store Retail Link data is more than most vendors want to bite off since it requires hardware, software, and IT skills to accomplish.

What can you do with Retail Link data if you have it stored in a database?
· Analyze SKU/store level sales
· Analyze SKU/store level on hand
· Analyze average unit selling price by SKU/store
· Analyze planogram compliance by verifying on hand and selling at traited and valid stores
· Identify out of stock stores, and even forecast demand based on prior sales
· Create SCRIPT forecasts for your buyer indicating where inventory is needed to maximize sales and avoid out of stocks.
· Group stores into A, B, C categories based on SKU level sales volume.

Walmart buyers expect vendors to use Retail Link data to analyze and manage their SKU activity. If you are not already using the data, of if you are not using it as well as you could be, then you are missing sales opportunities. Don’t wait for your buyer to call you and ask a question you can’t address – start working with the data today.

Retail Point of Sale Analysis How To Guides

Analyzing point of sale data can be a daunting task for an analyst, especially when there is very little real world training available. That is why the Accelerated Analytics team has written four “how to” guides that share the secrets we use to analyze over 69,000,000 unit sales per week. Now you can get real world insight, available for download right to your desktop!

The retail data analysis “how to” guides provide category management and business analysts with a practical easy to follow approach for narrowing down large volumes of EDI 852 and retail point of sale data into manageable, actionable reports. Many vendors to Wal-Mart with Retail Link or vendors receiving EDI 852 are have a wealth of data available to them, but analyzing the data on a weekly basis can be challenging. These guides provide insights the Accelerated Analytics team uses to turn the data into improved sales and in-stocks.

If you are a vendor to Home Depot, Wal-Mart, Lowe’s, or any other major retailer, these guides can help you be more successful.

The series contains four “how to” guides with simple step-by-step processes for completing a:
· SKU Analysis
· Store Analysis
· Out of Stock Analysis
· SKU Forecast

Learn more and get your copy here:
http://www.acceleratedanalytics.com/download-whitepapers/

Making the most of POS data analysis

The Accelerated Analytics team is hosting an event in New York City on Feb 21.   If you are responsible for using POS data from your retail customers this is a must attend event.

NRF Show 2007

The Accelerated Analytics team had the opportunity to attend "The Big Show" today in New York City.  If  you are not familiar with the show, this is the annual trade exposition sponsored by the National Retail Federation.  Overall, the show is a good source of industry news and provides an opportunity to spend time learning about new technologies and vendors in the market.  The show floor can be a bit overwhelming, with thousands of vendors.  This year, we were struck by the number of empty booth spaces as compared to prior years.  It would seem the declining attendee rate has impacted the NRF like most organizations, although this is still a very big show.   It is very hard to gauge who is attending, but we had the opportunity to talk with representatives from Gap, Jo-Ann Stores, The Andersons, Wal-Mart, and saw many other retailers, so it seems the usual suspects are in attendance.  It does seem most of the attendees are part of the IT, store operations, or supply chain teams.  One conversation we had with a fairly good sized retailer regarding their supply chain vendor collaboration was a bit surprising.  This vendor told us they make weekly product activity data available to their suppliers, but only a handful really use the information.  This was a surprise because, as we work with vendors, most tell us the opposite is true - they request the data, but their retail partners are not filling that request.  In fact, something in between is probably true.  Our experience tells us retailers are generally making the data available, but in many cases, not in the format the vendor would like to receive, so they are challenged to do much with it.  This is unfortunate since there is much that can be done with the data.  Hopefully, more productive programs will be put in place in 2007.

If you are in NYC and have the opportunity to attend the show, make time to visit the Microsoft booth. (full disclosure, we are a MSFT partner)  Their booth is huge and filled with solutions for every aspect of a retail operation.  The representatives working the booth are overly technical, but if you ask questions about their client work, they can provide some very interesting tid-bits of information.  We especially enjoyed our conversation with the Project Real team.  If you want to learn about how a huge data warehouse is deployed at a real customer, you need to check that out.

 We dropped our cards into most of the fishbowls we found, so maybe we will win something:)

Dashboards Make POS Data Analysis Easy

If you are selling products through a retail channel and your retail customers are willing to share POS data, you have a great opportunity to increase your sales and optimize inventory - if you can create an effective solution to manage a large amount of data and distill it into smart business decisions.  This is where a dashboard can be a very effective tool. 

In a recent article, Steve Pugh of Howard Products discusses how he is using dashboards to monitor sales at several thousand retail stores so he can direct buyers on the most effective purchasing strategies. 

Here is an exerpt from the article...

Dashboards can be home-grown, using the graphing and charting capabilities of Excel spreadsheets, for example. There also are specialized software applications. Howard Products, a manufacturer of wood care products, recently contracted with Accelerated Analytics to install Accelerated Analytics, a Web-based dashboard application to monitor purchase order and sales data, in addition to inventories.

The process "allows us to quickly come up with exceptions reports showing when our customers' inventory levels are too low," said Steve Pugh, VP at Howard Products. Pugh said he can immediately identify quick-selling stores or regions, or even individual products.

"I did that just yesterday with a customer we rolled out nationwide," Pugh said. "I can just hit a button and dump sales figures to a spreadsheet with colors, then direct it to the buyer saying we can do one blanket order to bring him up to speed."

At Howard Products, there are different dashboards for different folks; generalized big-picture versions for top executives, team-oriented ones for regions, and job-specific ones for individual sales reps.

You can read the entire article here

Newsletter launch

The Accelerated Analytics team is launching a newsletter for POS data analysis best practices and vendor compliance news.  Take a moment and sign-up here.  Our first issue will be sent out in a few short weeks with the lead article summarizing our research on the "POS Data Analysis Maturity Model."

Trade Promotion Dollar ROI

If there is one problem common to vendors selling products through a retail channel, it is getting a handle on the ROI of trade promotion dollars.  Unless you are responsible for spending and managing these funds, it's hard to appreciate the complexity of this problem.  But the reality is, as much as 30% of sales are spent on trade promotion.  That is a lot of money to pour into a program without the ability to track effectiveness.

So what's a vendor to do?  Unfortunalty, there is not a simple solution, but one tool that seems to work is carefully monitoring POS data available from your retail customers.  By looking at weekly unit sales for promoted items, it is possible to calculate the lift associated with your expenditures.  As we have chronicled on this blog, that brings many challenges also.

As you develop the capability to work with POS data, remember these best practices:

1) Working the data should be the smallest portion of your effort.  If you find yourself spending 80% of your time building reports, you've got a problem.  Seek a better solution.

2)  Define your business objectives first, then build exception based reports to isolate top performers and laggards.  If you expect a program to create a 15% increase in sales, then use software to compare week over week unit sales and automatically color in red those SKU's that are below expectations.

3)  Measure and manage.  Much of the decision making on how trade promotion dollars are spent is done based on gut feel and buyer feedback.  Instead, learn to track the unit sales and then trust your numbers and make impartial decisions.

Reporting vs. Planning

Several times in the last few days, our team has been involved in discussions with vendors regarding the difference between reporting and planning.  Surprisingly, many vendors see these two as synonymous functions, when in fact the are distinctly different. 

Reporting involves looking at what happened in a past period.  The period could be five minutes ago or 5 weeks ago, it does not matter.  The basic concept is that you are studying what happened in the past.

Planning is what happens after the report is analyzed.   It involves looking in the future and creating a series of actions based on what was reported to have happened.  e.g. a merchandising plan provides a specific open-to-buy (OTB) plan typically on a category level. 

Why is this important?  Because many vendors see the process of gathering EDI 852 sales and inventory data as a planning function, when it is actually a reporting function that serves as an input into the planning function.   Management needs to understand the difference and adjust their expectations accordingly.  Otherwise you run the risk of throwing out the baby with the bathwater when the EDI 852 data program fails to meet the needs of the business from a planning perspective. 

Is Supplier Collaboration Such a Risk?

This is the headline story in the October 2006 Integrated Solutions for Retailers magazine.  The story details the efforts Dillard's is making to share store level sales and inventory data with suppliers.  On the one hand, we are pleased to see another large $7.7 billion dollar retailer that "get's it", on the other hand we are surprised by the question in the headline.  Is vendor collaboration really a new and untested business model as the article suggests?  Just the opposite, the model has been shown to produce higher in-stock percentages and better assortment planning.

The obvious conclusion one reaches when reading the article is that vendors need a set of tools to better turn raw EDI 852 data into actionable decisions.  This is accomplished using a tool like our Accelerated Analytics service.  By using a comprehensive service, the vendor can get out of the data management business and go straight to making smart decisions.  Reports can be quickly created that highlight stores with too little inventory or declining sell-thru.  

Working with POS data

As we speak with manufacturers about how they are handling POS data from their retail customers, we find they are having trouble with the "noise" inherent in the data.  One of our clients get a very typical EDI 852 file each week with units sold and units on hand for each UPC for each store.  This is great data, but it takes up about 40 pages in a standard row and column format.  The issue of course is that it takes a long time to sort through and arrive at actionable information.  There is simply too much noise in the data.  And the problem is magnified when dealing with several retail customers at once.

We find it is much better to approach the analysis in a top down rather than bottom up fashion.  Top down analysis involves calculating sell-thru and weeks supply for each item.  Based on viewing these metrics, one can much more easily spot the trouble areas than by attempting to review line after line of sales and inventory with no context or relative performance information.  

When working with your POS data, start by identifying leading indicators for your data like weeks supply.  Leading metrics are actionable and add needed context to your decision making.  In this way, you can be much more efficient when dealing with lots of POS data.

Next, talk to your customer about how they analyze performance.  Some retailers look at sales by item and style, especially in apparel.  In soft goods, this is less important because they have longer lasting SKU's and more rigid replenishment guidelines.  By understanding what your customer is measuring and how often, you can align your metrics so you are both scoring performance in the same way.

Trade Promotion Management

The Accelerated Analytics team had the pleasure of attending the TPMA show in Chicago last week, as well as presenting a keynote presentation on POS data analysis.

Some interesting facts about trade promotion:

53% of companies do not know if their promotions make money

50% of companies do not know if the promotions they run add incremental value to the brand

51% of companies have not implemented changes to their trade promotion programs in light of new Sarbanes-Oxley and FASB regulations

It was clear as we spoke to manufactures at the show that they are struggling with POS data. Most of the manufacturers we spoke to are still using Excel as their primary tool. This creates a number of issues as the volume of data grows and the source data files come in various formats. It is abundantly clear a more robust POS data analysis tool like Accelerated Analytics is needed by a majority of manufacturers. It was interesting, this is true of both large and small manufacturers we spoke to. This is because in most cases, POS data analysis is a line of business issue and is not supported by the IT function. Most manufacturers we spoke to are looking for an outsourced service to handle the data. They don't want to invest into hardware and software that will become a growing expense over time. They also do not want to mess with the data integration issues.

Effective Key Performance Indicators

The Accelerated Analytics team spent a majority of the day to day reviewing retail point of sale data provided by a manufacturer client of ours.  These are large reports with thousands of rows of data organized by UPC, reporting units sold, units on hand, forecast units, etc.  This particular client sells to a 'big box' retailer, so each UPC is duplicated for over 2,000 stores.  Not an easy task to review and draw out meaningful and actionable intelligence.  It was clear as we reviewed the data that we needed to create a few top line key performance indicators to summarize what was happening. The natural choices were sell-thru, weeks supply on hand, and in-stock percentage.  By calculating these metrics and then eliminating all the columns of units sold and units on hand, we were able to more quickly identify which products were performing well and which were not.  This caused us to write up for this client a short summary on how to define effective key performance indicators to manage their business.

Effective key performance indicators are:

Context driven. Reporting units sold by UPC does not by itself yeild much information.  On the other hand, units sold compared to forecast provides very useful context to the user because you can immediately judge the relative performance.

Actionable.  If a report tells you UPC 384730384738 sold 374 units, what action can you take based on that knowledge?  Not much.  However if the report tells you the sell-thru percentage is 9% you immediately know action is required. 

Gather together your top 3 reports and review them to see if the data summarized provides KPI's or just data. Then work on creating KPI's that provide context and actionable information.  You will be surprised by how much more effective your analysis can be.

Betting your business on a spreadsheet?

A surprisingly large number of organizations are still using spreadsheets as the backbone of core business processes like POS data analysis, category management, and vendor collaboration.  There are many reasons for this, and even for a business intelligence professional like myself, I cannot simply dismiss their use altogether.  Although, it would be good for business ;-)  Spreadsheets are an incredibly useful tool in many situations.  However, they are also terribly overextended and misapplied.

I cannot tell you how many times in the past month I've heard some form of this statement; "Our spreadsheets work just fine, I don't see any reason for us to change."

I am going to take a few deep breaths and be as diplomatic as possible in answering that statement.  So here are a few reasons not to use spreadsheets for POS data analysis, category management, or vendor collaboration. 

Spreadsheets are inefficient for most complex data analysis.  Spreadsheets were designed to be a presentation layer for data and allow a user to perform some limited high level math.  Unfortunately, in many offices, spreadsheets have become complex programming environments where power users spend hour after hour manipulating data.   Because they are on the very edge of what a spreadsheet was designed to do, they spend 80% of their time fetching and manipulating data and only 20% performing analysis.

No single version of the truth.  Each spreadsheet has its own business logic, calculations, and definitions, so each user must spend time simply familiarizing themselves with the information.  In some cases they will have a different definition, so then the spreadsheet must be recreated to suit their needs.  One client of mine comes to each meeting, distributes his spreadsheet, and then leaves to refill his coffee cup and use the restroom while all the other attendees just figure out his math. 15 minutes on the front of every meeting multiplied times a dozen senior managers!

Lack of data quality and consistency.  Any time data is manually inserted into a spreadsheet, an opportunity exists to make a mistake.  The mistake could be inserting the wrong set of data or not applying the correct unit of measure.

Spreadsheets create a single point of failure.  Almost every office I have ever visited has a power user with an Access database and an Excel spreadsheet.  The rest of the office lives in fear of the day this power user might choke on a chicken bone at lunch, or decide they would rather live in Tahiti.

No auditability or verification.  In the post-SOX business world, this is a key concern for any public company or large private company with ambitions of an IPO.

Making Data Come Alive

A picture truly is worth a thousand words...especially when you are analyzing data.  Which would you rather have? A spreadsheet with a thousand SKU's showing sales and gross margins or a picture that instantly tells the story?  If you have spent hours analyzing data in Excel, you probably have a strong preference.  When we work with business users, they are amazed at the way our Accelerated Analytics software can show them a picture of what is happening in their business.  We are always amazed they don't already have this technology.  The next time you have to conduct a complex analysis, consider how a picture like this would make your life a hundred times easier.

 

Which came first, the chicken or the egg?

Many times, when I talk to retailers about sharing data with vendors, I hear some version of "Well they are not asking for it," or "only if they can show me how they will use it."

It reminds me of the classic quandary...Which came first, the chicken or the egg?

Or in this context... which comes first... the retailer offering to share data, or the vendor requesting data?

Innovative leaders in any industry are always optimists.  They are the ones that don't wonder if a vendor will use the data or how, they wonder how big of an improvement in sales can happen by even one good decision.  They wonder if they can get another couple percentage points closer to the perfect order by sharing data.  What would happen if vendors were empowered to be category captains and proactively helped to manage in-stock performance?  What if they really analyzed POS data in the way your internal team does?  They don't know the answers.  But they are optimistic about the opportunity.  They do some research, learn others have had success, determine the risk is low, and take a step forward.

Notice I said leaders are optimists, not fools.  I own a business.  I understand the realities of limited resources and prioritizing a portfolio of possible projects.  But given the abundance of research on the benefits of sharing data with vendors, this project falls solidly in that coveted upper right quadrant.  If you don't belive me, google ECR, DDSN, or CPFR and read the case studies.

So how does one insipre a VP of Merchandising, or Supply Chain, or Purchasing to take that first step?  How do you position the WIFM?