Let’s say you’re a freelance writer. You’re trying to grow out your list of clients and get some more work, but you don’t want to commit to doing more work than you can actually handle. So, you sit down to analyze your previous work habits. How many words did you write per hour on average? Did the number of words vary by project type or industry? How many hours are you willing to work each week? How much overtime can you work before you become burned out? With these considerations, you’re able to figure out roughly how much demand you can meet. In this way, you optimize your earning potential and utilize your work hours in the most efficient way.
Though the example above presents a much simpler vision, manufacturing outfits have to engage in exactly the same sort of calculations in order to effectively align their production and shipping capacity with unfolding demand. For the freelancer, this process is probably just a few minutes of back-of-the-envelope math, but for production planners this process (known as demand capacity planning) can become a delicate high-wire act involving many variables and complications.
So, as a production planner, how do you go about optimizing your demand capacity planning? To begin with, you’ll need to figure out what the maximum production capacity of your plant is. In order to do so, you’ll need to break down the entire journey taken by each product into individual steps, from order creation to each machine or station it has to visit on the production floor. Your total throughput will be based on which of these stages can handle the fewest products per day. Calculate how many products this stage can handle per hour, and then multiply that by the number of operational hours per day in order to arrive at your maximum capacity. By gaining a sense of this number, you can figure out roughly how much demand your operation can accommodate, meaning that you have both a level of demand to aspire and a sense of how far you can go without overextending yourself.
Reading the suggestion above, you may have been thinking that you could calculate these values with a quick pen and paper or Excel session. While you probably could, you almost certainly shouldn’t. Why? Because effective demand capacity planning relies on a high degree of intra-operational visibility, which is almost impossible to achieve when you use programs like Excel whose files are often not centrally located or easily accessible for those who didn't create the file in the first place. Instead, you should make sure that you’re doing your planning and calculations with as much visibility and accessibility as possible, to avoid the issues that go along with information and planning silos (e.g. planners being forced to use outdated information, reduced communication and collaboration, etc.).
In the suggestions above, we’ve mostly spoken about capacity, but what about the “demand” side of the equation? Often, when businesses have difficulty effectively aligning capacity and demand expectations, it’s because their demand forecasts are outdated or based on obsolete information. A demand forecast that over or underestimates your customers’ future needs can leave you in a position of either overproducing stock (which then has to be warehoused, potentially at great cost) or scrambling to meet unexpected demand, potentially missing delivery deadlines or overusing your machines to the point of increasing your risk of a breakdown. By implementing predictive analytics workflows, manufacturers can avoid these issues with forecasts that more accurately predicts future demand levels in advance. Implementing workflows like this will require exactly the high degree of visibility described above, but the resultant increase in forecast accuracy can be a huge value driver, helping to prevent the disruptions that result from disconnect between reality and expectations in your production plans (e.g. shortages, overages, bottlenecks, etc.).
Another important tool you can use to ensure that your picture of future (and current) demand lines up with reality is the implementation of real-time data into your supply chain workflows. By monitoring demand changes as they occur and creating an up-to-the-minute picture of demand that’s available to planners across the entire value chain, you can create a more responsive production environment in which the relationship between your existing production capacity and your real demand levels is always clear and apparent. This has the advantage of giving you the ability to adjust your production volumes in real time in order to better maximize your capacity usage. If, for example, one of your products saw a sudden surge in demand levels, you would be able to adjust your production flows in real-time to produce more of that product. Likewise, you would be able to assess just how much of that product you could feasibly produce and mark it as “sold out” on your website and/or notify your customers at the very instant that on-time production and shipping became impossible.
Okay, let’s say you’ve taken all of the advice above to heart and you’ve been successfully aligning your production capacity with your demand levels. That means your job is done, right? Not quite. We’ve seen the ways that demand fluctuates over time (and the effects that that fluctuation can have on your value chain), but what about the ways in which capacity changes? As your machines age or get replaced, as you update your order creation process, and as you make other changes, your maximum capacity levels will shift. Frankly, even if you don’t consciously make any changes, your throughput is unlikely to stay exactly the same over time. This is why it’s so critical to pick a set of KPIs for measuring your performance and monitor them closely over time, tracking any changes and taking steps to mitigate any negative trends. In this way, you can keep your demand capacity planning on track for the long haul, gaining a level of operational control that will help keep your business running smoothly over the years.
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