Disposition expertise for three-stage distribution

If suppliers want to offer specialist retailers a high level of delivery readiness and good margins, it is not enough to provide a 24-hour delivery service from the finished goods warehouse. If you want to be successful in the long term, you need a much more far-reaching replenishment strategy. This is the only way to reduce stock levels and save enormous costs while maintaining maximum delivery readiness.

Storing finished goods is very expensive and ties up capital. And if you want to have a high level of delivery readiness, you have to build up immense stocks without sophisticated planning and scheduling of the value chain: The high delivery capability of a stocked product requires that stock is available so that picking and shipping can be initiated immediately. A high readiness for delivery for complete orders with several order items requires an even higher readiness for delivery of the individual items: With 95 percent readiness for delivery of the individual items, there is only an approx. 60 percent probability of being able to deliver the entire order completely for an order with ten order items. Only at 99.8 percent availability of the individual item do the chances improve to 98 percent, but with 75 percent more safety stock on each of the ten individual items.

This is why manufacturers are looking for ways to implement a high level of supply availability at a lower cost in order to ultimately be able to offer attractive prices to specialist retailers. The interdependencies mentioned above cannot be overridden. Nevertheless, there is enormous potential to save costs by optimizing replenishment: In addition to the capital tied up in the value of goods, inventories cause annual costs of 18 to 30 percent of the inventory value, resulting from capital costs, insurance, administration, storage capacity and so on. Retailers ultimately have to pay these costs if the logistics chain is not right. But how can you increase delivery readiness and reduce stock levels at the same time?

Optimize scheduling processes

First and foremost, this is a question of better scheduling processes. For example, fast-moving items can be delivered at shorter intervals and in correspondingly smaller quantities. This reduces storage capacity. In turn, products that are rarely in demand can be produced on demand and completely removed from the finished goods warehouse. In addition, by cleverly shifting the logistical decoupling point, inventories can be reduced across the entire supply chain. Many logistical variables are often still planned by instinct and executed manually. Filling a pallet space in the truck with slow-moving items just to save freight costs quickly drives up stock levels. It is therefore important to optimize many things across the entire supply chain.

One well-known specialist trade partner, for example, has managed to significantly reduce its stock levels while at the same time increasing its readiness to deliver: Hansa Armaturen GmbH, manufacturer of high-quality designer fittings and innovative shower and shower systems. Stocks were reduced by between 18 and 40 percent in just six months. The total inventory reduction potential for finished goods and semi-finished products was over 50 percent in some cases.

Method and tool skills

Method and tool skills are required for this. For example, extensive article classifications need to be carried out in order to build disposition strategies. Of particular importance here are the classifications according to

• ABC → economic importance,
• XYZ → Regularity of consumption,
• STU → Number of customers per material number and
• ELA → Life cycle
• WMQ → Demand frequency
• LMQ → Dimensions

These classification characteristics are important parameters for deciding which planning and scheduling parameters should be set for which article. In addition, rules and regulations must be created that precisely define which article classes are to be planned and scheduled and how. Even such basic analyses can quickly reduce existing stocks and at the same time increase delivery readiness.

But all analyses and the measures derived from them are not enough if dispatchers are not supported by suitable software. At Hansa, for example, reporting and safety stocks had to be determined by the ERP system without system support. It was particularly noticeable in the case of safety stocks that they were calculated in different ways depending on responsibility or were merely the result of empirical values. In the planning of purchased parts, order requirements were not checked based on demand, but once a week. The overall process at this point was therefore highly manual despite the ERP system, very time-consuming and therefore prone to errors despite the greatest care. Scheduling optimization is therefore not a trivial undertaking.

Good disposition is a complex matter

The complexity of scheduling can be seen from the amount of master data required alone: Depending on the cut of the item, you have to take care of up to 130 logistical parameters. If you represent these in a mathematical equation, it is easy to understand that their complex interaction cannot be grasped either by instinct or by simple calculations.

Another common mistake is to combine several influencing variables in one parameter. For example, safety stocks for fluctuating demand, safety stocks for fluctuating production times and safety stocks for fluctuating delivery times of upstream suppliers are often mapped in a common safety value. Cumulatively, this can only lead to more stock. Optimum scheduling requires correspondingly differentiating tools.

ERP alone is not enough

Most companies already have a software tool for scheduling purposes: the existing ERP system or corresponding extensions. However, ERP systems originally have other tasks, which means that the options for demand forecasting and scheduling are usually very limited and these functionalities are not sufficiently differentiated. For example, there are practically no automatic mechanisms for the continuous optimization of MRP parameters. In addition, virtually all known ERP systems work exclusively with statistical methods that assume a so-called “normally distributed” demand, such as mean value methods or exponential smoothing. In practice, however, normally distributed demand is only found for a small proportion of items. As a result, calculations based on the assumption of normally distributed demand lead to systematically incorrect demand forecasts and inventory errors of up to 40 percent.

Precise special tool for dispatchers

It should therefore be noted that forecasting and scheduling tasks can be performed with an ERP system. However, the result is usually far from optimal. To be able to plan much better, planners need advanced planning and scheduling (APS) software. Such precision tools for specialists, such as DISKOVER SCO from SCT GmbH, are much more precisely tailored to scheduling tasks than generalist ERP systems. For example, they offer much finer forecasting functionalities for improved planning and can therefore predict actual demand much more accurately. For the “generalists” – i.e. the ERP providers – this specialist market is of little interest, as very in-depth and specific specialist knowledge is required here. Nevertheless, there is a great need for action, as companies with a varied portfolio can regularly save hundreds of thousands of euros in stored material and therefore dead capital. This is important capital that can be invested in solutions for Supply Chain 4.0. Incidentally, APS software is generally suitable for companies with a sales volume of around EUR 15 million or more. There are basically no further restrictions for specialist trade suppliers, although the product range itself should include a certain level of complexity.

Technical article, RAS International – Issue 6 2015, p. 24 – 25ByDr. Bernd Reineke (Abels & Kemmner GmbH) and Andreas Capellmann (SCT GmbH)