Belimo sets new standards in demand forecasting with DISKOVER!

A very innovative and useful new function of the APS system is the ability to forecast materials for customer order-related products generated in SAP – a functionality that was not previously available to Belimo. Belimo had also requested the integration of the bearing characteristic curve method for determining safety stocks.

Both functions were newly created in DISKOVER for this purpose, so that the already very powerful APS system is now even more powerful. In particular, the ability to create demand forecasts for customer order-related materials opens up new horizons for many machine and plant manufacturers. After all, they are often project or one-off manufacturers who produce in individual batches and therefore generally cannot cope with SAP’s requirements planning. But back to Belimo and the need to create much more precise demand forecasts much earlier and to determine the necessary safety stocks.

Belimo, which is listed on the Swiss stock exchange (SIX), is the global market leader in the development, manufacture and sale of field devices for the energy-efficient control of heating, ventilation and air conditioning systems and employs around 2,300 people in over 30 countries worldwide. Customers of the products include OEM customers, system integrators and building technicians as well as tradesmen, who can also order Belimo products online.

The needs of these customer groups are heterogeneous in terms of order quantities and configuration requirements. There are also seasonal and product-specific fluctuations in demand. However, all customer groups want to be supplied within the shortest possible time at all times – even for the smallest order quantities. Belimo aims to meet this customer requirement in full at all times, because in addition to outstanding products, readiness to deliver is also a decisive success factor for the world market leader.

Achieving top performance on the operational side

“We want to inspire our customers with unique solutions and operational excellence,” explains Louis Scheidegger, Head of Group Division Production.

In order to be able to deliver this top performance globally, Belimo operates two production sites worldwide, nine local logistics and customization centers and more than 30 branches in order to be as close to the customer as possible and to be able to deliver ordered goods within a few days or even hours. Belimo’s suppliers, who deliver assemblies and components, are located upstream of the production sites, logistics and customization centers and branches. 88% of manufacturing costs are incurred in procurement and 12% are attributable to in-house value creation. Supplier management and procurement processes therefore have a correspondingly high priority for the high level of delivery readiness required. However, excellent procurement processes are not enough. The demand forecasts must also be correct.

Belimo prepares these at the level of the nine local logistics and customization centers and the two production sites. Three planning centers in APAC, America and Europe are responsible for this. The sales branches are stocked with standard products based on consumption. This means that if the order point is not reached, subsequent deliveries are made. With this setup, Belimo is very well positioned in the market. Previously, the company had used an internally developed requirements planning system that was integrated into SAP. It enabled a linear extrapolation of past values to the next 12 months and was no longer able to cope with the increased requirements and complexity due to the company’s growth and the demands of the supply chain. As part of the migration of the ERP system to SAP S/4, a decision had to be made as to whether this existing in-house requirements planning should also be migrated and optimized or whether there was a better solution, perhaps even off-the-shelf.

Facing the turning point

Optimization was sought here primarily due to growth, limited storage capacity and increased inventories due to supply chain problems in recent years. The aim is to forecast with much greater foresight and sophistication in order to reduce inventories without compromising delivery readiness. Belimo needed a longer forecast horizon than the previous 12 months in order to be able to procure motors and microcontrollers more efficiently, for example. Delivery times here are often over six months and suppliers want forecasts that go well beyond one year. In addition, the options for responding to different demand characteristics were not differentiated enough: there were hardly any options for adjusting consumption curves and forecast weighting factors. There was only one standard factor that could be adjusted.

Public vacations and vacation periods such as China’s New Year vacations or Thanksgiving in the USA had to be adjusted manually, and seasonal factors could only be planned manually. Belimo also has to adjust its forecasts for specific product groups in the fall months, as this is when the heating season begins and heating systems are serviced and replaced. Holiday-related shifts of requirements due to company vacations could also only be adjusted manually and were correspondingly error-prone and control-intensive in order to avoid errors and their effects. There was also insufficient support for the phase-in/phase-out planning of new and discontinued products.

Reporting was limited to what was possible within the in-house development in SAP. Classic key figures for planning accuracy such as MAD (Mean Absolute Deviation) / MAPE (Mean Absolute Percentage Error) or an evolution index could not be determined automatically, which only enabled rough KPI reporting.