How do you know if you have the right tools? Anything that helps you identify potential disruptions far enough in advance to take corrective action, or makes it possible for you to reach the right decision faster and more consistently, or increases planning visibility across touchpoints, is potentially the right tool. On the other hand, anything that pushes users towards Shadow IT or makes plans more volatile and susceptible to disruption (e.g. because the production chain has become too lean) is almost certainly the wrong tool. Of course, it’s not always easy to tell which is which from the outside—which is why you need to consider the specific features of any given solution before making a decision.
One of the most powerful features that your APS can offer is real-time planning and data visibility. Why? Because this forms the foundation of all the other improvements that modern APS solutions can offer to production planners. Let’s imagine a scenario: You’re a production planner at a large automotive plant. You’ve optimized your production sequences for different orders and order ratios, and you’re able to quickly schedule runs based on the real demand that emerges. Unfortunately, the sales team is operating in a silo, and you usually don’t know about the orders that are coming until hours after they’ve materialized. As such, your machines—though perfectly capable of powering an efficient production run—sometimes wind up sitting idle even though there are actually production runs to be done. This eats into your efficiency, and thus your bottom line.
How do you avoid this? Real-time integration: in this way, you can avoid costly idle, unexpected parts outages, and other pitfalls by making each touchpoint on the value chain visible to every related touchpoint.
In the above paragraph, the underlying theme was the importance of speed. In order to take advantage of the time and resources at your disposal, you need to get information as quickly as possible. Once you’ve got that information, you need to turn it into completed sequences and schedules just as quickly—otherwise you run the same risks of downtime or inefficiencies that we saw above. What’s the best way to make sure that happens? To adopt an APS that offers AI-powered workflows for rapid planning and replanning based on your specified scenarios. This is an area where something like explainable AI (i.e. algorithms that “show their work” and help planners to visualize the reasoning behind particular decisions, rather than simply spitting out an answer from a black box) can be particularly valuable. As conditions change, the order slotting and scheduling modules within your APS create automatic adjustments to your planning in order to find the optimal schedule for meeting demand in a timely and cost effective way. This helps boost your operational efficiency in a way that enables you to stay lean without giving up flexibility.
Speaking of flexibility: just as you want to keep your capital commitments as low as possible without increasing risk to an unacceptable level, you only want to pay for the software functionality you’ll actually use, without making it impossible to grow your capabilities in the future. Your APS might seem like less of a risk in that department than your ERP (which can often be the site of monolithic deployments that wreak unintended business havoc), but a similar balancing act applies. You need to find a solution that’s flexible enough to handle your needs even as they change and evolve. As such, it’s important to look for APS suites that support modular deployments and implementations. This might look like a cloud APS solution that lets you manage your computing capacity in a dynamic way, or it might mean a central solution that’s designed to interwork easily with a number of different add-ons. Whatever the exact specifications, you want to avoid putting yourself in a situation where you can’t make adjustments to your production network or change your forecasting workflows because your IT doesn’t support it.
This feature relates to real-time functionality, but it bears its own mention: When you’re trying to balance and smooth your production flows on an ongoing basis, you need to know what’s happening on your shop floor when it’s happening. This means that you need to be able to get alerts (whether that's from IoT devices deployed throughout your production lines or through some other method) directly in your planning platform such that you can perform instantaneous replannings when the unexpected crops up. In this way, you’ll be able to take advantage of the visibility and speed that we’ve been discussing to improve your throughput and reduce disruptions through proactive scheduling.
Last but not least, we get to user experience. It’s perhaps not perfectly accurate to describe UX as a “feature” in the same sense as the other items on this list, but it’s an important consideration nonetheless. Like we saw with the mention of explainable AI above, there’s real value to be gained when planners understand why a planning solution is making the suggestions that it’s making. In general, the more effectively a particular APS solution can reduce barriers and cut down complexity for the user, the more effectively that user will be able to gain value from the tool. In other words, a clean UX is the best way to operationalize the potential scheduling improvement that the right APS can bring. No one wants to invest in powerful and sophisticated technology only to find that planners are still using Excel spreadsheets because the solution itself is too difficult to use. Much better to have a solution that’s designed around the needs of the users whose jobs are supposed to be made easier.