Demand Driven Supply Chain Management results in reliable supply of smart meters

Long and unreliable lead times on the one hand, and uncertainty about demand on the other… In the Netherlands, the collaboration between the suppliers of smart energy meters and four grid operators, including Stedin and Liander, was far from smooth. Here Alex Tjalsma, a partner at Involvation, explains how his company used Demand Driven Supply Chain Management (DDSCM) to help these grid operators improve the availability of the smart meters at lower costs and with less hassle.

All old electricity meters in the Netherlands are currently being replaced by smart ones, but the grid operators are dependent on the reliability and agility of the meter suppliers. Tjalsma: “When availability has greater priority than costs, holding a large amount of inventory can seem like the right solution, but that approach didn’t work in practice. Not only was availability still not guaranteed, but all that stock often turned out to be a heavy burden in the case of quality issues and technical amendments.”

Closer investigation revealed that supply chain partners had to make key decisions early on in the process. “Grid operators were required to make forecasts and place orders at item level several months in advance, so it’s not surprising that their ordering behaviour was very erratic and their forecasts turned out to be extremely unreliable,” says Tjalsma. “To maintain a stable capacity utilization rate, suppliers did their capacity planning way in advance for the orders they had received, ignoring the unreliable forecasts. This resulted in long lead times and incidental stock shortages, followed by strongly fluctuating demand levels and more uncertain forecasts from the grid operators – a recipe for disappointment and stress.”

This problem is nothing new according to Tjalsma, who has seen it many times before: “It’s a classic vicious circle that arises when supply chain partners have to make decisions based on information that is still unreliable. They end up choosing based on their own interests rather than the interests of the chain as a whole. At Involvation we call this the ‘planning mismatch’. It is characterized by long lead times, poor performance and fire-fighting. These are all symptoms of an ineffective supply chain model.”

Solution

To help the grid operators, Involvation went in search of a model that would lessen the meter chain’s dependence on unreliable forecasts. “By delaying high-risk decisions and eliminating unnecessary variation and uncertainty, you escape the planning mismatch, and that is the very essence of Demand Driven Supply Chain Management. Thanks to DDSCM, organizations no longer have to accept being dependent on unreliable forecasts.”

Tjalsma explains that the grid operators’ old system was based on two errors in reasoning: “Firstly they managed stock based on MRP, which unintentionally increased variation rather than eliminating it, so we replaced MRP with a simple inventory buffer method. Secondly they managed their suppliers based on ‘On Time In Full’ (OTIF), which led to them working with very long lead times in order to deliver as much as possible on time. We put an end to that too. In its place, we’ve introduced KPIs that stimulate the availability without compromising on agility.”

The benefits of this new approach are blatantly clear, continues Tjalsma: “The lead times have been reduced from four months to just a few weeks, which means that the grid operators can now place orders based on their actual inventory status rather than an unreliable forecast. Even more importantly, the suppliers now receive commitment for the capacity and components, so they are willing to heed the grid operators’ signals. The results: guaranteed availability and maximum scalability. As an added advantage, there is much less inventory in the supply chain, efficiency has been improved and unnecessary hassle has become a thing of the past. Grid operators and suppliers are starting to trust one another again.

Everything should be made as simple as possible, but not simpler
Albert Einstein