Archive for September, 2006

Effective Key Performance Indicators

September 22, 2006

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 2000 stores.  Not an easy task to review and draw out meaningful and actionable intelligence.  It was clear as we reviewed the data 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.


Understanding EDI 852 Product Activity Data

September 20, 2006

We have been receiving allot of phone calls lately from manufacturers trying to understand the EDI 852 data files their retail customers are sending.

We posted a new page on our web site for understanding EDI 852 product activity data that you might find helpful if you are dealing with this issue. The Accelerated Analytics team would be happy to answer questions if you need help. contact us

Collaboration comming of age?

September 20, 2006

A recent shared strategy study titled “The State of Collaboration 2005”by Consumer Goods Technology, RIS, and Forrester sited some encouraging results our team felt needed to be shared.  read the study

Finding #1: almost two-thirds of rretailers and manufacturers feel they suffer adverse business effects when they do not collaborate.

Finding #2: EDI 852 is still the primary tool most firms use to collaborate.

Our conversations with manufacturers indicates they are having a hard time dealing with the EDI 852 data provided by retailers.  Plus many retailers have developed web portals which provide data files in even different formats.  There is simply too many different formats, and too much data to wade through on a weekly basis.  This points to the need for a tool to make the most of the opportunity.

Still, this is good news to see momentum continues to grow.

McDonald’s WiFi

September 14, 2006

As a marathon runner McDonald’s is not typically on my list of places to eat.  I have a tough time finding anything there that fits my preferred diet and still tastes good.  But I’ve been reading about their WiFi deployment and I needed to do a few things on the Internet the other day so I thought I’d give it a try.  It was a pretty typical WiFi experience on WayPort infrastructure.  I’ve logged-on to their network many times in the past at airports, and other locations.  The service is fairly reliable, and the speed is acceptable.

What I was disappointed with was the $2.95 for two hours price tag.  McDonald’s is smart to get into WiFi.  But I tend to align myself with concept that WiFi used as a differentiation strategy should be free. (one of the only gripes I have against Starbucks is they charge outrageous fees for WiFi) Especially when McDonald’s has so prominently promoted their new network as the backbone for corporate e-biz including eLearning, POS transactions, franchisee communications, and appliance status monitoring.  As I sat there and clicked through my email I could not help but smirk at the irony I was helping to subsidize McDonald’s business communications.

Here’s an idea… print a code on a customers receipt that is good for 30 minutes of free WiFi.  That way for the windshield warriors you create an incentive to visit the store and get lunch while you also discouraging people that would come and just hang out all day and not make a purchase.  Or create a frequent visitor club where you can earn free WiFi minutes for some number of burgers purchased.  Just a thought…. they are on the right track but I think McDonald’s could improve upon their strategy just a bit.

What a difference a year makes…?

September 13, 2006

When you spend as much time as we do involved in ‘missionary’ conversations educating senior retail and consumer goods executives it is a breath of fresh air when a research report is published which directly supports your business case.  That is why we were celebrating in November 2005 when the “2005 Shared Strategy Study: The State of Collaboration was released as a joint project by Forrester Research, Consumer Goods Technology and RIS News.

One of the important findings of the report – 70% of retailers, and 82% of manufacturers agree they suffer adverse business effects when they do not collaborate.  Based on this finding alone one would expect a ground-swell of interest in collaborative technologies.  Right?

As we approach the one year anniversary we can report the following based on our many, many conversations.  Only a handful of retailers are making a serious investment into collaborative technologies.  Instead most retailers are taking a wait and see approach, or they are simply using existing EDI or worse yet, spreadsheets as a stop-gap.  Most manufacturers we talk to are suffering through the expense and difficulty of dealing with what retailers are sending to them.  Imagine getting a dozen different files each week from your customers.  And these are not small files.

The technology to collaborate effectively is pretty straight forward.  It can even be implemented in a managed service model so you don’t have to spend allot of money up front, or hire a bunch of IT guys.  Hopefully another 12 months will see big changes.

The BullWhip Effect

September 11, 2006

The Accelerated Analytics team published a white-paper recently titled “The Business Case for Supply Chain Collaboration.”  This white-paper included a discussion on the bullwhip effect which has received a great deal of positive feedback so we thought we would include an expert….

The basic premise of the demand driven collaborative supply chain model is that in order to achieve the highest possible in-stock and simultaneously minimize waste, all parties within the supply chain must have timely access to actual dales demand data and all parties must have a means by which they can work together to coordinate promotions and business planning.

A forecast by definition is an estimate made in advance of an event occurring and is therefore an educated guess.  Unfortunately, even sophisticated forecasting software can have an error rate of 50% on promoted items.  Most troubling of all, forecast accuracy decreases moving backward into the supply chain.

The reason forecast accuracy decreases moving backward in the supply chain can be illustrated by plotting sales over time for supply chain participants as depicted in chart 1.   Notice the actual sales demand recorded at the retail point of saleshad moderate variation.  This is because the retailer builds their forecast model using actual demand as tracked through their point of sales systems.  But notice how much more chaotic and unpredictable the demand curve becomes as you move away from the actual point of sale.  Demand as viewed by the supplier, wholesaler, and manufacturer is based on estimated sales which combined with latency and manually adjusted “safety stock” causes increasingly inaccurate and chaotic forecasts.  Research indicates fluctuation in actual customer demand of +/- 5% can be interpreted by supply chain participants as a change in demand of up to +/- 40%.  As depicted in chart 1, although actual demand has only changed +/-5% the reaction of supply chain participants is dramatically exaggerated and is known as the bullwhip effect.   Much like cracking a whip the user only needs a small motion in their wrist (point of sale) to cause a huge motion in the end of the whip (manufacturer).

The bullwhip effect causes inaccurate forecasts, inefficiency, and waste within the supply chain.  Anytime the forecast line of a supply chain participant (e.g. chart 1, wholesaler, manufacturer, or supplier) is above or below the actual demand line (e.g. chart 1; retail sales) inventory levels are not optimized and out of stocks or inventory build-up will occur.  The U.S. Department of Commerce estimates $3 trillion in excess inventory is locked in the U.S. and European supply chains.   The bullwhip effect is exacerbated by the parties in the supply chain who do not have an accurate understanding of actual demand.  In other words, they are forecasting but the inputs upon which their forecast model is built are inaccurate.

Accurate forecasting and close coordination between supply chain partners can help to eliminate the bullwhip effect and dramatically increase overall profitability.  The most effective way to improve forecast accuracy at each step in the supply chain is to base the forecast on actual sales demand data.  In this way, each point in the supply chain can be demand driven and the parties can collaborate on the same forecast inputs.  In addition, promotions can be coordinated and managed to maximize sell-thru without causing supply disruptions.  As information quality improves, cycle times are compressed through the entire supply chain process.

Applying Sun Tzu to Supply Chain Strategy

September 5, 2006

I have been reading Sun Tzu over the holiday weekend.  Very interesting reading.  It’s the type of reading where you cover a few lines and then take an hour to reflect on what it means to your business.

One passage stuck me:

“Therefore, determine the enemy’s plans and you will know which strategy will be successful and which will not.”

I often find myself in conversations with senior executives debating the merits of expanding their vendor collaboration program.  Typically they already have a program in place but I am advocating an expansion of that program and the application of new technology.  In these conversations there is tremendous inertia to maintain the status quo.  After all, why fix a program that’s not broken.  At their level in the organization they don’t hear the day to day challenges of the EDI manager who is fielding vendor support calls. In fact most of the time they hear just the opposite from the middle level manager, “oh everything is fine Mr. Executive, no need to come and visit me just keep on moving.”

But if one critically evaluates where the most successful retailers (e.g. enemies) are making investments one cannot espace the conclusion they are moving to more and more sophisticated vendor collaboration programs.  They are making investments before a problem occurs because they want to enjoy the corresponding lift of competitive advantage.

So here is what I encourage all executives to do:  create two columns on a piece of paper and write your top five competitors down the left column.  Then on the other side for each competitor write down everything you know about their supply chain initiatives at this moment.  If you are coming up blank that is your first clue there is a problem.  Now consider what your organization is doing.  What threats or opportunities are evident?  Every time I have gone through this exercise with an executive we have both been surprised at the results.

Gross Margin Return on Investment (GMROI)

September 1, 2006

GMROI is one of the most important metrics in the retail/supplier world because it allows you to understand both the velocity with which your inventory is turning and  the return you are getting on your investment.  GMROI is a measure of inventory productivity that shows the relationship between total sales and the gross profit you earn on those sales in conjunction with the amount of dollars invested in inventory.

GMROI can be expressed as either a percentage or dollar multiple.  Many retailers calculate GMROI at a product family or department level but it can also be calculated at an individual item level.

GMROI (%) = gross margin (%) x [sales / average inventory at cost]

where gross margin (%) = (sales – cost of goods sold) / sales

average inventories at cost for one year = add ending inventory at cost for every month of the year plus the ending inventory at cost for the previous year and then divide by 13.

Analysis software which automates the calculation of GMROI at an item level and then allows the user to input exception monitoring based on business logic is ideal.  This setup provides significant time savings and proactively alerts a user to problems.