When we have capacity constraints, it is not always easy to make the right decisions to remove these constraints, increase capacity, or decide which products to prioritize within the available capacity.
To help make the right decisions, relevant visualization can be helpful. An easy-to-read graph can be understood at a glance and facilitates informed and rapid decision-making.
Without clear visualization, we will spend most of our energy debating the relevance of the figures—and since our projections are based on forecasts, there is bound to be debate.
The way in which load/capacity is typically visualized is by projecting a load with infinite capacity and comparing it to the installed capacity. (We are comparing it to the demonstrated capacity, not the theoretical capacity, right?)
Let's take an example. Here is our projection for the coming months:
Well, it's clear that we don't have enough capacity for this resource. We would need to more than double or triple capacity to be in a good position: increase opening hours, outsource, acquire new resources, qualify the products concerned with alternative resources, etc.
On top of that, the immediate workload is enormous, a sign that we have fallen behind. We are therefore already in crisis mode, and crisis situations do not always facilitate informed decisions... Any resemblance to the "backlog bubble" that some of you may continue to push back to next month would be entirely coincidental...
This view is useful for assessing the lack of capacity. It is understandable for the production manager. But is it understandable for the CEO, the CFO, or the sales director? Not necessarily.
The measures to be taken will be costly. You will undoubtedly need the agreement of all S&OP stakeholders.
This resource is clearly overloaded. But is it really that serious? What is the real impact?
Our infinite capacity S&OP projection for all products that go through this constrained channel is shown below, based on a simulation of the coming months. In the short term, we do not have enough stock and supplies in progress, but then the replenishment mechanism should allow us to maintain stock within reasonable ranges and meet demand. Your infinite capacity MRP shows something similar.
To try to visualize what the capacity constraint on this resource implies, let's switch it to finite capacity.
Now, the load-capacity graph is no longer very clear: the finite capacity planning algorithm ensures that the resource is used to 100% of its capacity, but what is the impact?
Let's project our inventory with this constraint enforced—ah, yes, now it's clearer: if we do nothing, in one year we will lose $1.3 million in sales.
This capacity assumption leads to delays of more than one month, depending on the period.
Rather than projecting backorders value, we can also project a loss of earnings in terms of contribution margin.
This visualization will facilitate decision-making. The CEO, CFO, and sales director will fully understand the implications, much better than "resource X is saturated, we won't be able to do everything."
Of course, it is advisable to project several scenarios—demand, capacity—to evaluate the alternatives.
If, in order to assess the impact of the constraint, you have to extract infinite capacity workload data from your favorite ERP system, load it into Excel, and run it through every possible scenario to show the impact, not only will it take a lot of time and energy, but data it will also likely be questioned by your stakeholders.
When everything is accessible online and visually clear, you can finally focus the decision-making process on the real risks and impacts!
To summarize: