Whether you’re in the airlines industry, managing field crews in an industry like utilities or construction, or coordinating deliveries for a third-party logistics provider, planning and scheduling your resources optimally is critical to keeping your operations moving and your customers satisfied.
This process, while already complex when planning only a single resource, such as workers, vehicles, or orders, becomes infinitely more complex as the number of variables increases. For instance, what about pairing up field crews with a particular piece of heavy equipment? What if a vehicle is needed to get them to the work site? With a large and/or highly skilled workforce, the number of possible pairings multiples exponentially. It becomes incredibly difficult to determine the optimal way to schedule these resources for maximum efficiency.
Multi-resource scheduling is an area where many organizations are losing money, defeated by complexity.
In a recent conversation with Adrian Gonzalez of Talking Logistics, we discussed some of the keys to aligning multiple resource types when creating schedules. Here are a few of the takeaways for organizations struggling with this complex planning challenge:
1. The more resources being scheduled, the greater the chance for inefficiency
When a planner is creating a schedule for just a few variables, say 5 workers and 5 tasks, the number of possible schedules already numbers in the thousands. Now, expand that number to meet the scale of a typical operations team, with thousands of workers who each must accomplish 5-10 tasks per day, and the number of possible outcomes expand into the millions.
When we add an additional resource, such as trucks, equipment, or even personnel types, finding an efficient schedule, let alone the most efficient one, is nearly impossible.
This is a puzzle that simply cannot be solved by even the most accomplished of human planners. Only best-in-class optimization technology can provide profitable solutions to puzzles of this scale.
2. Integrate resource scheduling to improve efficiency
When it comes to scheduling multiple resources, a common school of thought is that planners should start with scheduling their most constrained resource –equipment, trucks, etc. – which are also typically the more costly resource. This step-by-step planning works, when only the more costly resources are a bottleneck. In many situations, planning isn’t that easy: when planners then begin to schedule a more complex resource such as their workers, they run into challenges aligning skillsets, certifications, and other specializations that are required to complete a task, with the existing plan for the more costly resources.
This siloed way of working results in costly efficiencies. A more effective approach is to bring all of your resource data into one system in order to schedule it simultaneously. Rather than trying to fix schedules on the back end of your planning process, scheduling resources together keeps them in greater alignment and improves overall utilization.
3. Dealing with change on the day of operations
Creating a profitable multi-resource schedule in the long-term, even with some kind of optimization technology, is clearly a challenge. But the real test is in maintaining efficiency on the day of operations. One of the best examples I can think of is in the airline industry.
One of DELMIA Quintiq’s customers, KLM Catering Services (KCS), is faced with the puzzle of efficiently re-loading meals onto arriving flights. Their challenge, of course, as any frequent flier can relate to, is dealing with the moving target of flight delays, cancellations, and gate changes. This means that their vehicles, meals, and tarmac crews must be frequently re-assigned to meet the demands of this variable schedule. By linking directly to Schiphol Airport’s flight information system, DELMIA Quintiq give KCS’s planners a quick and accurate overview of the changes in flight times and positions at the airport, and then automatically adjusts the assigned tasks, alerting the planner to possible outcomes based upon pattern recognition.
This type of rapid optimization and decision support for planners is a crucial step in solving the multi-resource scheduling puzzle.