Recently a wholesale distributor turned to me, anxious about one of his
competitors who is also using SAP solutions.
The competitor recently made a proposal to his customer to include shelf
life on the tag for each item delivered.
For his industry, it seems to be a competitive advantage as restaurants,
the final customers, are not computerized and could use the tags to find shelf
life information easily and insure final tracing and quality. They were, of course, also questioning how
the competitor could have done this. The response is very easy; they used
batches including the shelf life characteristic.
Still, some companies implementing SAP decide not to use batches and
therefore also do not use the shelf life characteristic that separates stock
into unique elements. They think this is not productive as you have to input
information when both receiving and sending the product, as the stock is in SKU-batch
and no longer globally on the SKU. Even
if you use voice picking, you could have items with two different shelf life
numbers in your rack and then you need to somehow read the one you are picking
to update the stock. This will make the
picking less productive.
So the first and easy response to the question about implementing
batches is “No!” - to try to keep processes easy and simple.
In the long run, this could turn out to be a mistake when considering
the need for auditing, tracing, and optimizing. Not having batches will prove
to be a serious drawback, as they are a key foundational element of the tool
needed. Even worse, it might trigger the need for a parallel system that is not
integrated and therefore much more work and, at the end, has a higher cost of
ownership with additional resources to run and maintain another system.
The first reason to consider batches is that the FDA in their pilot
project for improving product tracing along the food the supply chain has
clearly established the batch/lot number as a best practice. And the European Food Safety Authority (EFSA)
has issued directive 178-2002 imposing a requirement to trace the genealogy of
any potentially dangerous food bottom up and top down and provide the detail to
the administration on request. Here, batches or the shelf life are key to finding
the stock that is a potential danger.
The second point is that more and more customers, especially the
biggest ones, have specific contract requirements defining a minimum time
remaining before the shelf life expiration date has been reached. And, therefore, you will have multiple
contract types pending – some with very high requirements, some lighter and
some without any time contract.
How, then, are you going to meet the customer’s requirements if you do not
have shelf life stored in your database? Certainly not by FIFO (first in, first
out).
The third point is optimization when you run your material requirement
planning (MRP). Classic MRP is built on stock, sales order, forecast used by
sales order, and purchase orders in transit. You will need to launch such an
MRP or, even simpler, an MRP on order point when you do not have shelf life in
your system. And then when you run MRP, it
is possible to that you have stock in your system that is close to its expiration
date on the tag but not yet expired. Your system will suppose it is available
to deliver the customer. But the next
day when it is time to prepare the shipment, the operator will see the shelf
life on the tag, scrap it and take other stock. Then a part of your stock will have
vanished and you may have difficulty reconciling the weekly forecast as there
was a decrease in stock that was not anticipated. So you have not only the cost
of the scrap but even worse, you can also have the cost of out of stocks and
missing sales until the next MRP run recovers your scrap - so there is a double
penalty.
The stock here is living, so we cannot apply classical MRP.
So in food distribution, even for stock with a long shelf life, having
the shelf life stored in batch is a must.
With that data, a distributor can, at least, run a FEFO (first expired, first
out ) and not a FIFO, and will avoid surprises when their supplier does not
respect the FEFO process themselves.
Also it would give them the opportunity to run alert tables like this one: Let’s imagine 21 days is the minimum required
by most of your customers.
|
| 21 days freshness
| 22 days freshness
| 23 days freshness
| 24 days freshness
| 25 days freshness
| 26 days freshness
|
| Today
| 0
| 20
| 25
| 50
| 60
| 30
|
| Day +1
| 10 : alert
| 15
| 50
| 60
| 30
| 100
|
| Day +2
| ….
|
|
|
|
|
|
| Day +3
| …..
|
|
|
|
|
|
This report gives better visibility and allows you to anticipate
minimums with the effort of going through the listing. But the best solution is to run MRP taking shelf
life into account, and SAP APO has an algorithm that is able to do it. It considers stock with its shelf life, and
any stock that is not consumed in the right window is placed in alert and not
considered in the MRP run.
The algorithm will calculate a perfect match between the supply and the
timeframe window for deliveries. And if you have orders in your system, it will
also take into account the minimum shelf life requested by the customer as
mentioned earlier. It can also take into
account product maturity time, like with
meat where you need at least 15 days of stock before delivery.
And this capacity of avoiding both scrapping and out of stock in the
complex environment of timeframe windows has lots of value for your
customer.
SAP runs shelf life.
Frank Marguier has 15 years of
experience in the distribution and food industry. He was involved in the early projects of meat
transformers and traders running SAP.
