Do
you know how minimum orders, minimum production releases, and transfer
batches affect your distribution network? As a supply chain
professional, it’s essential to understand the impact of lot sizes on
your inventory, lead times, and ability to deliver to your customers.
In this article, we’ll explore how to visualize the impact and adapt to
minimize the minimums. Who in your organization is the owner and
accountable for this technical data?
What is the impact of lot sizes on your inventory, on your lead times, and on your ability to deliver to your customers?
A historical approach focused on total costs
The
EOQ formula has imprinted in our practices a notion of economic
quantity. If we buy, manufacture, or transport less than Q, it costs
“too much”. It has been demonstrated over and over again that
this formula makes no sense,
and that it makes even less sense in the modern world, but the damage
has been done, and this notion has remained imprinted in our
subconscious. Your ERP system probably offers an economic quantity
calculation based on this logic.
If you’re a buyer in industry or trading, chances are that minimum
orders and the discounts they will allow are part of your negotiating
arsenal.
Visualize the impact, and adapt
The
Demand Driven approach,
especially for inventory replenishment, facilitates visualization of
the impact of minimums batches on inventory. The green zones of the
replenishment loops allow you to judge the impact of minimum batches on
inventory. By identifying green zones that represent a significant
value and a significant number of days, you can begin to make
adjustments to your flexible model to minimize the minimums.
We rarely see what impact minimum orders have on our inventory and flows.
Of course, we know that if the minimum is high, we will carry more
inventory. We also know that if we are busy manufacturing a large
quantity of something, the other products to be manufactured will wait…
since we are busy. We also know that if we receive a container once a
month, we will have more stock and less agility than if we receive
goods every week.
We know all this. But how can we show the impact of this to induce
decisions? How can we influence purchasing strategy if we can’t show
the consequences? How can we convince production to increase the number
of changeovers?
The Demand Driven approach, especially for inventory replenishment,
facilitates this visualization. The green zones of the replenishment
loops allow you to judge the impact of minimums batches on inventory.
Let’s look at some examples from real cases.
The green zone in the article below is based on a minimum order of
70,000 units, for an average consumption of less than 10 per day. The
minimum order represents a value of €23k – and over 7000 days of
consumption! These situations are obvious in the DDMRP model and
alert to the need for adaptation.
The example below concerns an item with shelf life: the minimum order
implies a maximum stock level that exceeds shelf life, which implies
that we will destroy part of what we buy…
Inventory modeling also makes it easy to measure the impact of minimum orders on inventory investment.
The graph below shows the structure of the replenishment model, all
items included, of an end-to-end supply chain. All the replenishments
of the supply chain of the company concerned are cadenced by green
zones which represent a total of €39M. The average impact on stocks
will be half, approximately 19.5M.
If we measure this in days
(below), the green zones represent 41 calendar days. This means that
beyond the stock impact, on average it will take 41 days to sell a
batch. More globally, between the safeties (red zone), the
work-in-progress (yellow zone), and the batches (green zone), it takes
on average more than 66 days for this supply chain, and up to more than
90 days, to adapt to the changes in demand.
Note: this is not bad, given the industry this company is in – let’s compare it with your own supply chain…
Visualizing minimum order levels,
the risks they entail, and their impact on inventory costs and lead
times enables a different kind of dialog with stakeholders – e.g.
purchasing, production, suppliers, and customers. It is now a question
of defining a flow model – a model to respond to market requirements –
that is adapted to support business needs.
A minimum should be minimum!
Reducing lot sizes is one of the main levers to develop
the agility of a supply chain. The first step is to visualize and
correct the outliers: the lot sizes that represent a significant value
and a significant number of days. This should be part of your monthly
ritual of monitoring and adjusting your model.
In your supply chain model adaptation rituals, measure the impact of
your green zones in value and number of days, and persevere to reduce
them.
Of course, a pragmatic approach is required in order not to go too far
– the lead time factor in the DDMRP model leads to the inclusion of a
“reasonable” lot size threshold according to the flow of an item.
In short? Visualize and minimize your minimums!
Get in touch.
For more information, contact KenTitmuss.