How Can Production Planning Improve Measurably in 4 Weeks?

Start with the most important decision

Welcome back to Circonomit Labs. The last video was about how we set up digitalization projects and focus on value: good decisions after four weeks instead of two years, with a small investment instead of a million sunk into a master data project. Today we go deeper and show, very pragmatically, how we do it.

The situation at the customer: we usually work with executive management, heads of controlling, process owners and operations management. In other words, the people who know the company inside and out and are responsible for operational and financial KPIs. A strategy on nice slides for the next three to five years can only be answered if we break it down to operational KPIs. That's why these people are at the table. It has to work in the long run, but also create tangible value every day, for example when the production manager says: today I had to reprioritize one order less.

We always start with the most important decision, for example: accept an order, yes or no? Behind it is the question of whether on-time delivery or the contribution margin of orders currently has higher priority in the company, for instance in trading, where margins are lower. About two thirds of the customers we talk to have exactly this question, with a slight weighting towards contribution margin, another financial KPI or on-time delivery.

Collect disruptions, bottlenecks and measures

Let's take contribution margin. Finance is always a reflection of the entire company, the sum of an enormous number of relationships. So that we don't get lost in complexity, we sit down with the customer, sometimes with one person, sometimes with ten, and ask: what are currently the biggest operational disruptions that make the contribution margin fluctuate? The method works the same way for on-time delivery.

Within a company, people usually know where the shoe pinches. We help to structure the many relationships in daily operations: an employee is sick, so nobody can operate the machine that needs this specialist. The order stops, another order is delayed. Building such chain reactions as cause-and-effect relationships and making them steerable is our daily work. The starting point is always the knowledge within the company.

So we collect disruptions and bottlenecks. Employee qualification came up in five out of five recent customer conversations: machine capacity is there, but there are specialists for individual work steps, such as the electrician on a machine or the person who can operate the large lathe.

Third, we collect measures. Because the question of which orders or products we accept and what makes us money is a daily operational question with a strategic direction: do I want to be the manufacturer of custom-made products, or the one where series production runs stably and who delivers fastest? Especially in family businesses this is a central consideration. And usually, besides the biggest disruption, for example the key specialist who is often absent, people already know two or three measures they have calculated with a rule of three and are convinced will improve, say, on-time delivery by 5% or contribution margin by 2%. With small margins 2% is a lot, with large margins less so.

From up to 100 points to the 5 to 8 most important drivers

Then we use a funnel. Everyone writes down their thoughts, whether two or twenty ideas. This produces a list of 8 to 100 points. In under an hour we go through it pragmatically: what can we exclude? What can be solved operationally, what only through investment? What does everyone consider less important?

The goal is not to get stuck in complexity but to improve the most important KPI and the most important decision. Nobody can build a complete simulation model of their company right away, so we start with the most important drivers. In a workshop of two to three hours we rank the points in two or three rounds until it is clear: for contribution margin it is, for example, the underutilization of the warehouse. For on-time delivery the most important driver is often the absence of the specialist. So we need to be able to reprioritize better when this specialist becomes the bottleneck or is absent.

A first model in 4 weeks

In the end it's about the basics: we know where to look. Maybe one point is still missing, and that's fine. For the five to eight most important points we chain ten building blocks and look at how they are connected. Remember the decision chain: an employee is absent, an order shifts, that affects another order, the customer receives the delivery late, a contractual penalty is due, and we see it in the financials. Five steps, and the operational disruption is linked to the financial effect.

Before you brainstorm yourself tired: whatever we forget will very likely come up again later. What matters is getting started. This way we create a first model in under four weeks; our ambition is to one day build the entire model in four hours. Having a model after four weeks that creates transparency on the most important drivers and enables first simulations is already a big step in any decision or digitalization project. Sometimes the simple holds the solution for a very complex world.