There is often a misunderstanding. How, by implementing software, can we reduce lead times?
The answer is, we can’t… Reducing lead times does not come from magical software.
Reducing lead times comes from reviewing the design of your flow model. The software facilitates this, particularly through an efficient process of decoupling points replenishment and the calculation of decoupled lead times.
But the real wealth, the intelligence, you already have it within your teams, you don’t need to buy software for that, you just have to observe. “Learning to see” – this should sound familiar to Lean practitioners…
One of the strengths of the implementation of the DDMRP methodology is in the first step, an essential prerequisite: positioning decoupling points.
It is not so common to first redesign the operating model before setting up a software program. How many ERP implementations start with a “phase 1: we don’t question everything; we transpose into the new ERP what we do today”. And as the journey is long, painful and costly, we often stick to this phase 1 design…
How to redesign the operating model? It’s usually quite simple:
- Gather a team that knows your flows
- Map your flows (in a macro way)
- Position your (realistic) lead times along your flows, and the expectations of your customers.
- Identify common, recurring components or assemblies
- Design your target cartography, and the associated management modes, in a collective intelligence process.
Sometimes the lead time gains are already there in your current supply chain, without any structural change, it is just a matter of translating them in the planning & execution processes.
Let’s take some examples from recent projects:
1. Manufacturer of assembled medical devices
This manufacturer assembles a variety of medical devices, most of which are made to stock and some of which are made to order. The assembly itself is relatively simple and agile, it is carried out in a few hours on flexible means. After assembly there is a long quality and release process. Assembly and release take about 4 weeks. The assemblies involve a significant of components and sub-assemblies.
Until the implementation of DDMRP, the lead time to replenish finished goods inventory, or to build to order, was approximately 3 months. Why 3 months when assembly and release takes only 4 weeks? “Because we’re not sure we have the components ready for assembly, so we have a 6-week firmed MPS to secure the components supply”.
After the setting of DDMRP buffers to secure the components before assembly, the lead time fell to 2 weeks firm MPS + 3 weeks release, i.e. 5 weeks instead of 10.
In addition, now that the teams are confident, new opportunities to reduce lead times are being identified.
2. Manufacturer of machined parts
This manufacturer machines common parts in a first part of the process – this is a succession of machining steps and external treatments, with routings that can include about fifteen operations. The second part of the process uses these machined components to produce finished products incorporating assemblies, finishing and differentiation operations. The customers are served from stock.
The early stages of the manufacturing process are very constrained from a capacity point of view. Therefore, even though there had long been the idea of decoupling the process with a stock of semi-finished products after machining, this had never been possible.
Finished goods inventories were therefore sized for a replenishment lead time of 16 weeks. Therefore, leading to high inventory targets. To maintain this level of finished goods inventory, any machined sub-assemblies had to be immediately committed to finishing and pushed into finished goods inventory.
After reviewing this process, the replenishment lead time for finished products has been reduced to 4 weeks instead of 16 weeks. Within a few weeks to smooth the drop in workload on the finishing operations.
The effect? The stock target on finished products dropped sharply, and the machining flow that was in process allowed to build up fast the stock of semi-finished products that the company desperately needed… It was just a matter of daring.
3. Packaging manufacturer
This manufacturer manufactures packaging components. The plant supplies a distribution center. The replenishment lead time set in the ERP is 4 weeks. This is a firm horizon designed to stabilize the factory’s load.
On reading the first DDMRP analytics graphs within R+, it immediately appeared that the historical net flow equation with the existing model was evolving at about 50% of the buffers, whereas it should have been at the level of the green zone.
– Um, are you sure you have a four-week deadline? Asked the consultant.
– We don’t have enough capacity to cover four weeks’ needs, so every week I only do emergencies to cover the requirements of the current week and next week. Answered the production planner.
– Does that mean your lead time is actually two weeks?
– Oh yeah, you’re right, let’s change it.
Now this plant works with a 2 weeks lead time, with much less stress and emergencies as this became the normal model, the inventory target on the distribution center have been reduced which has given a little more flexibility… and the plant’s production schedule is more stable than when it was supposed to be “frozen” on 4 weeks.
Many similar examples could be added here, and you will find many of them in the published DDMRP case studies. It is not magic. It is about putting the common sense of your teams at work, with the support of relevant software…
