Full shelves and good margins

Technical article, S4B, issue KW33 2014
by Andreas Capellmann and Götz-Andreas Kemmner

If suppliers to DIY markets want to offer their customers full shelves and good margins at all times, it is not enough to feed the JIT Supply Chain 4.0 from the finished goods warehouse or the last available machine. If you want to be successful in the long term, you need a much more far-reaching replenishment strategy, as this is the only way to reduce the stock of finished goods while maintaining maximum delivery readiness and thus save enormous costs.

DIY stores always want full shelves – ideally with fast-moving items and good margins. Suppliers sometimes provide their own rack jobbers or hire sales service companies to present a perfectly stocked range at all times. With solutions such as ‘Logistics 4.0’, the aim is to get sales figures even closer to the point and ideally respond with batch size 1. However, all these efforts do not lead to success if suppliers always want to meet these sometimes highly fluctuating demand reports as quickly as possible, for example within 24 hours.

To do this, they would have to maintain very high stocks in the finished goods warehouse or JIT capacities for production. Both are superfluous outside of peak times and are therefore expensive and tie up capital. This is why supplying companies are looking for ways to implement all of this more cheaply in order to ultimately be able to offer attractive prices to the construction market. The potential is enormous: in addition to tying up capital, which in itself leads to dead capital, there are even 18 to 30 percent more costs in the inventories, resulting from capital costs, insurance, administration, storage capacities and so on. The DIY store has to pay these costs if the logistics chain is not right. But how can you actually increase delivery readiness and reduce stock levels at the same time?

Optimize scheduling processes

First and foremost, it is a question of better scheduling processes. For example, fast-moving items can be delivered at shorter intervals. This reduces storage capacity. In turn, products that are rarely in demand can be produced on demand and removed directly from the finished goods warehouse. In addition, the logistical decoupling point can be placed as far as possible towards the end of the supply chain through modularization, thus reducing inventories across the entire supply chain. Many logistical variables are also planned by hand 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 company from the metal industry that supplies DIY stores, for example, has managed to significantly reduce its inventories while increasing its delivery readiness: GAH Alberts. The manufacturer of fittings, profiles and fencing technology, among other things, was able to reduce stocks by 13% in the short term and a whopping 53% in nine months. More than half of the finished goods warehouse was therefore stocked with material that was not immediately required in order to maintain a high level of delivery readiness.

Another supplier to DIY stores in the lighting sector had to overcome the challenge that the components for the products, which are mainly manufactured according to the company’s own designs, were largely procured in China. The delivery times here are between 60 and 150 days. However, the customers, specialist and wholesale companies, demand the highest delivery readiness at all times. Around 20,000 customer order items are received every day, most of them with a delivery time of 24 hours. A sufficiently high stock level is therefore required on the procurement side. However, if the demand situation changes on the customer side, items that were previously procured well in advance are no longer required and become excess stock. Such problems therefore need to be managed.

Managing fluctuations in demand

Almost every company has to contend with fluctuations in demand, be it the introduction of new products or the discontinuation of old ones, competitive campaigns or a general change in demand. The special feature of GAH Albers was the fact that its products are subject to extremely strong seasonal fluctuations, as it manufactures and sells many materials for the garden sector, among others. During the peak season, the available production capacities are not sufficient to produce completely in line with the market. This means that the quantities that are planned to be sold sometimes have to be produced weeks or even months before the planned sales. However, if sales planning is inaccurate, sales cannot be realized due to a lack of material and other materials remain in the warehouse as slow-moving items.

Method and tool skills

Method and tool skills are required for this. At the lamp manufacturer, for example, an extended ABC analysis was carried out. In other words, a classification of the complete product range according to

• ABC – economic significance,
• XYZ – Regularity of consumption,
• STU – number of customers per item and
• ELA – Life cycle

These classification characteristics are important parameters for deciding which planning and scheduling parameters should be set for which article. In addition, a set of rules was created that precisely defines which article classes are to be planned and scheduled and how. With such fundamental analyses, existing stocks can be quickly reduced and delivery readiness increased at the same time.

But all such analyses and the measures derived from them are not enough if, for example, dispatchers are not supported by suitable software. At one valve manufacturer, for example, the reporting and safety stocks had to be determined by the ERP 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 on a needs basis, but once a week. Despite the ERP system, the overall process at this point was therefore highly manual, very time-consuming and therefore prone to errors despite the utmost care. In order to be able to use all the “big data” from Supply Chain 4.0 at all, many series and variant manufacturers must first structure and optimize the scheduling processes before the finished goods warehouse or the last production machine before packaging. And this is no 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 imagine these as a mathematical equation, it is easy to understand that you cannot calculate them in your head. However, major mistakes are made when individual parameters are combined for the sake of simplicity. For example, safety stocks for fluctuating demand, safety stocks for fluctuating production times and safety stocks for fluctuating delivery times of the upstream suppliers are mapped in a common safety value. Cumulatively, this can only lead to more stock. Highly oscillating graphs with many different peaks turn into curves until a “smooth” forecast is ultimately achieved, which, however, only covers up the problems and ends up costing a lot of money. Optimal scheduling therefore also requires correspondingly differentiating tools.

ERP alone is not enough

Most companies already have a suitable 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 practically never encountered. Rather, demand is subject to constant seasonal, cyclical or other fluctuations. 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 %.

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 achieve this, dispatchers need advanced planning and scheduling software, or APS software for short. Such precision tools for specialists, such as DISKOVER SCO from SCT, are usually much more precisely tailored to scheduling tasks than generalist ERP systems and offer much finer, range-oriented forecasting functionalities for improved planning, for example, 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 turnover volume of around EUR 10 million or more. There are basically no further restrictions for DIY suppliers, although the product range itself should include a certain level of complexity. Suitable sectors therefore range from A for fittings to bathroom accessories, fittings and hardware as well as electrical accessories, small ironmongery, lights, tools and Z for fencing elements. The fact that the introduction of such a system requires a certain amount of preparation should be clear to every user who also uses ERP systems. It should also be clear that the software providers know the right consultants for this.

Technical article, S4B, issue KW33 2014
by Andreas Capellmann and Götz-Andreas Kemmner

Andreas Capellmann is Managing Director of SCT GmbH from Herzogenrath near Aachen, which specializes in supply chain optimization. Prof. Dr.-Ing. Dipl.-Wirt.-Ing. Götz Andreas Kemmner is Managing Partner of the management consultancy Abels & Kemmner GmbH, Herzogenrath/Aachen. He has been an honorary professor at the West Saxon University of Applied Sciences in Zwickau since 12.06.2012.