Production planning managers face three persistent challenges: managing dependencies, handling rapid changes, and drowning in manual work. Mathematical optimization addresses all three—and the results can be dramatic.
Transforming Dependencies into Transparency
Mathematical optimization algorithms can model numerous interdependent factors simultaneously and optimize their coordination. One case study showed a nearly 27% decrease in total manufacturing costs at an automotive company—achieved by jointly planning inspections and maintenance rather than handling them sequentially.
When you can see all the dependencies at once, you can optimize across them rather than sub-optimizing each piece independently.
Handling Rapid Changes
Systems using mathematical optimization are inherently designed to generate revised plans quickly. When circumstances shift and stakes are high, decision-makers gain access to near-optimal solutions almost instantly.
Companies like Siemens and Herlitz have implemented such approaches successfully. The key advantage: when conditions change, you don't start from scratch—you re-optimize from your current state.
Eliminating Manual Planning
While experienced planners are valuable, mathematical optimization can consistently produce optimal or near-optimal solutions automatically. This reduces the time burden on planning staff when conditions become unstable.
Applications range from electricity cost savings to improving accuracy in radiation therapy planning. The common thread: taking repetitive planning decisions out of human hands and letting algorithms handle the combinatorial complexity.
Competitive Advantage
The technology enables companies to maintain planning effectiveness despite instability and frequent requirement changes. This provides meaningful competitive advantage—not just for large enterprises, but even for smaller companies willing to invest in better tools.
The question isn't whether mathematical optimization can help your production planning. It's whether you can afford to compete against companies that are already using it.
Written by
Jonasz Staszek