Feedback of the Week: On Data Quality:
I worked in retail and manufacturing for many years and bad product data was always a problem that, even today, people just accept and deal with as part of their day job.
For most of my career I worked in Space and Category management departments where accurate data was critical to optimizing the shelf space, yet daily, errors in the data were identified and more time was spent on trying to correct the information, then spent on actually analyzing the data to make the most of the space.
We never got the data 100% accurate and so used gut feel on many occasions to make decisions on whether to extend or reduce the distribution of a product into the stores or give it more facings on the shelf. At that time, (and it probably still is!) it was more about getting a planogram out to stores by a certain deadline so they could merchandise the shelf. My decisions to put a product into 50 stores as opposed to 500 stores based on the, not wholly accurate, information I had at the time, will have undoubtedly had a massive impact on sales, not only for my employer, but for the Brand owner!
That’s why I get frustrated, even today, when suppliers tell me that only the retailer benefits from good quality data and the retailer tells me its not their problem, this the supplier who should be giving them accurate data……………stalemate!
We talk about collaboration and sharing information to make the supply chain more efficient, but nobody seems to want to tackle the issue of bad data head on. It’s easier for individual departments to do their own thing and let someone else worry about the bigger picture, unless of course, you are on the board, in which case, the subject of product data is just a dull distraction that is best left alone.
It’s about time that individuals in these organisations got together as virtual teams or, as some companies are doing, formed data quality teams and tackled the problem. There are product data quality solutions providers out there that have been around for many years, have a massive amount of experience, that are eager to help and have built and developed data quality services that many companies could see immediate benefit from.
I leave you with this thought……If I had more accurate product dimensions I wonder how many more products would have got stocked in more stores and if that product I mentioned, was listed in 500 stores instead of 50, as the Brand Manager and Buyer, how much more would you have sold? I reckon that alone would probably pay for the data quality service for many years!
GXS Product Data Quality (PDQ)
Bristol Packet Wharf
On Wal-Mart and RFID:
As a long time follower of your publication, and a 30 year veteran of the automated material handling industry, I am mostly in agreement with you, but....
It seems there is always a but. I need to start with the fact that I worked on my first RFID project in the late 80's, when the tags were to track heavy materials around the plants. Later, I spent some time in defense initiatives where the applications were high energy active tags and pretty effective too.
After the Wal*Mart mandate, I worked with a number of executives (Kraft and other firms) and asked their views. Since it was a case level RFID initiative when announced, most manufacturing folks said, "it is too expensive" and I agreed. The costs were $.50 plus and the read rates and speed were deplorable. The technology that was needed was still in development, and still is, which was a low-power passive tag. I previewed prototypes at RPI (under $.10) and was impressed by the concept but the facts were not so good. As I make my living consulting on technical and financial feasibility for automation, I'll follow with this set of thoughts.....
Technically, the potential to get to low-cost case level RFID tag is there today, but only as a technology that can be read at the checkout, which was the focus - store level usage in close proximity read environments. As a tool in distribution, the "cheap" tags can not be read under the variety of conditions prevailing in products and environments in DCs and at the rates need to maintain DC velocities. Hence, pallet RFID tracking will no doubt succeed, bringing some benefits, but far from the requested in the initiative.
Financially, a visionary friend of mine, Art St Onge, founde rof the St Onge and Company Consulting company, did an extensive review of the benefits of case level RFID and while I was a doubting Thomas, his presentation numbers and logic were impressive and I theoretically bought on. He showed retailer and supplier seeing returns on investment.
To close, I would challenge you on the improbability oflong term success,as ultimately, it will gain traction as technology keeps plugging along. Short term, I am right with you.
So...., there are my thoughts, for what they are worth.
Keep stirring the pot, PLEASE!
LW Consulting, LLC
On Peak Oil and Russia:
Yes, I think it [Russian Oil production slowdown) is a significant indicator, not of the end of oil, but of the increasing difficulty of harvesting any greater quantities of oil in coming years.
Prices? I think at some point as prices rise, demand will drop, and prices will then tend to fall off. Lower prices will enable more use that will push prices up again. This cycle will continue, I expect, interrupted by occasional large discoveries such as Alaska’s North Slope and the North Sea that resulted in cheaper gas in the 1980’s, until the remaining petroleum reserves are largely used up. I would sum up my prediction as up and down, and up over the long run.
The effects on our society will be devastating unless public opinion can be alerted to the overall situation, and plans can be made to anticipate social effects, city life, food production, land ownership and transportation, and especially services to vulnerable populations that are already overstressed.
Jim Newcomer, Ph.D.
On Optimization versus Simulation:
I read Supply chain Optimization Versus Simulation.
To add: In general, solutions derived from Simulation are not optimal. This generalizes the fact that the benefits realized from simulation solutions are lower than the optimal solution. Time required to find an optimal solution from simulation process is dependent on the number of input variables.
On Easiest Areas for Big Supply Chain Improvement:
This is really a great read. I would like to add more which will save the supply chain cost
1. Change in Mode of transport, i.e., Import of inputs through ocean freight rather than airfreight
2. Zero communication gap among supply chain stakeholders, which will help to make proper planning tosource, procurement of inputs that lead to reduce supply chain cost
3. Buy big fish rather than small fish: Buying decision of a bunch of inputs rather than small but take supply partially as you require which will lead to reduce supply chain cost (by reducing storage cost, purchase savings).
Mohammad Mosharraf Hossain