A good plan is a success half-done but not a crystal ball

These unknown planning variables can be broken down into three categories: lack of resource availability, an inaccurate capacity model and an impeded information flow. Still, there are valuable steps and actions to consider while managing these challenges.

Deviation that happens during, or close to, the planning execution

Preventative maintenance breaks can be simulated, and scheduled shutdowns and lack of staffing should be part of regular planning routines. However, unplanned shutdowns due to equipment failure may force the closure of a production line. This is a real-life example showing how force majeure can impact even the most advanced and optimized planning simulation. In this case, a lack of resource availability is forcing production to deviate from the original plan.

To recover, there are a couple of actions to consider:

• Operational systems, such as MES (Manufacturing Execution Systems), need to have the option to reroute work orders to a different line or workstation and in a different modified sequence than initially planned. With this flexibility, it is possible to use alternative resources or start producing products that do not require the nonfunctioning portion of the line.
• Re-plan as soon as possible. Production progress data should be updated automatically, but equally important is knowing the estimate of when the problem will be solved and the line up and running again. This will shift the problem from a failure into a planned, proactive action, allowing the generation of a new best scenario and giving all the essential stakeholders, customers, logistics, and possibly alternative factories a new plan to execute.

Industrial force majeures are typically related to resource availability, including sick leave, broken equipment or other logistics issues, and production shutdowns. Also, material availability can mean quality issues or missing raw material supplies. Force majeure can also be a performance issue, where production or shipment takes more time than planned. These matters are a common part of the everyday life of industrial companies. Deviating from the original plan is not an issue as long as there are operational-level flexibility and the capacity to quickly re-plan while testing what-if scenarios.

Capacity model is not accurate enough

If the planning simulation suggests beginning a painting process from dark objects moving into light colors, it is highly unlikely the operators would follow that directive. It would result in too many changeovers and line cleanings while hindering productivity. In that case, there would be a deviation from the plan because the unit process is not optimized correctly.

Another example would be setting the line capacity at 80t/hour, but realistically, only 50t/hour is achievable. In this case, certainly, production will not meet the planned schedule.

These two examples show the need for the near-100% accurate process modeling of an Advanced Planning Solution. For the virtual twin of capacity model, there are two crucial questions to answer:

• Is the plan feasible? Can you successfully execute according to the plan — on schedule and in the proposed sequence?
• Is the plan optimized? Describing an optimal strategy is a surprisingly complex task. Instead of focusing on operational metrics, such as productivity and so on, the best way to reach long-term business benefits is to follow the company business rules and strategic decisions. Turning these into the planning rules is an effective way to avoid partial optimization.

Do not follow an unrealistic plan; for example, when planned production is more than what can be feasibly produced. However, be mindful that any decision made on the shop floor not to follow a sub-optimal plan must be well-justified. For the operators, some choices — such as frequent changeovers due to shorter production runs — might seem irrational due to the extra effort it requires. Also, if only looking at unit operations, it may seem that the company is losing money because of the vast time used for set-up and cleaning between the production of different items. However, from a business perspective, these shorter production runs might be required for on-time deliveries and inventory reduction.

Information is the possession of another stakeholder

Planning incorporates numerous stakeholders and operations within a company. Specifically, a plan sets the tone for the entire value chain. Even though the team responsible for supply chain planning is usually located at the same site, communication processes and information flows remain challenging.

For example, what if the truck delivery planned for cannot be booked as intended? Most likely, this disruption will be relayed by the dispatch office. Let’s say, to avoid late delivery, the truck will arrive two days before the initially scheduled date. The vital question then is, what happens next to facilitate the change?

• The supply chain planner needs to be informed, and the new Transfer Order timetable has to be updated. The optimal solution would be integrating this information directly into the advanced planning solution.
• The production order must have a new due date, and it needs to be simulated and updated. When setting the new plan, it’s dependant on the production capacity and lead time whether the new trucking schedule is feasible.
• If the truck isn’t able to linger at the distribution center, this will cause an early delivery, and the customer needs to be informed about the new timing.

Communication is the key

Until we possess a miraculous crystal ball that tells us the future, it is imperative to prepare for the unpredictable by maintaining an open mind to adapt and react promptly. It’s impossible to consider every variable while planning; the attempt would probably result in a bewildering case of complexity. Ultimately, understanding and empowering the roles of different stakeholders and securing the information flow means more ease in managing unpredictable variables.