In many manufacturing companies, executive orders are an everyday part of business. Often the sales department or even the managing director stands in front of the production planner and pushes to realize an order for an important customer at short notice or to complete an existing order more quickly. However, these unexpected requests and changes can lead to stress and chaos in both production and production planning.
The question is obvious: Are executive orders even useful?
In the past, such decisions were often made on the basis of gut feeling and soft factors, with the word of the managing director often being decisive. The turnover generated by sales is easy to quantify, and the importance of a customer can often be directly measured in terms of turnover. However, the question of whether an order is feasible and at what price is much more complex.
Planners often rely on Excel spreadsheets to analyze the current workload, but these often provide an inadequate basis. They need to communicate with production to understand what is feasible in the short term, and ultimately they have to rely on production's gut feeling. While this gut feeling can sometimes say that the boss order could be accepted, it often also points to possible consequences such as delayed orders, increased set-up times or losses in throughput.
The challenge is to quantify these effects and create a basis for discussion between sales, management, production planners and production. This is where PAILOT comes in with its AI-powered detailed planning. By analyzing the effects of executive orders, PAILOT creates a common basis for decision-making, which was often lacking in the past. Everyone involved then has a common picture and can make decisions together. Scenarios can be used to find sensible alternatives that both satisfy the customer and minimize the negative impact on production and other customer orders.
Ultimately, there is no general answer to the question of whether boss assignments make sense. It depends on the specific circumstances and requires a sound analysis of the potential impact. However, with PAILOT and a transparent, data-based decision-making basis, companies can respond better to such challenges.
