SCA integrally optimises production and inventory

sca 180pxSCA Hoogezand manufactures personal-care products, primarily for the European market. Some of its well-known brands include Tena Lady and Libero Up & Go. The company is part of the SCA Group, a Swedish company with more than 50,000 employees worldwide.

Integral optimisation

Having already significantly reduced its stock levels, SCA decided to work with Involvation to explore further opportunities. The task was to look at integrally minimising inventory and changeover costs. This was not a unique task as such, but the particular circumstances within the company meant that it was a more complex puzzle. A number of aspects were important for the optimisation process, as follows:

Cycle stock depends on the production frequency; more changeovers mean smaller batches and hence less cycle stock. However, changeovers lead to the loss of more manufacturing capacity, which in turn sets an upper limit for the frequencies. Moreover, the variable changeover costs (primarily material waste) increase too.

When determining the production frequencies, it is not enough to take an item-driven approach because SCA’s product range is subdivided into product ‘families’. A changeover within a product family is much cheaper than one between two different families. Therefore, an advanced algorithm which factors in these asymmetrical interdependencies is used to determine the production frequencies. This can result in a slow mover being manufactured frequently, for instance, because it is part of a fast-moving product family. In that case, the inventory saving outweighs the extra changeover time and associated costs.

Ultimately, production frequencies and safety stock cannot be optimised independently of one another because the production frequency has an impact on the stock level and hence the service level. Put simply, a low production frequency will result in high cycle stock and less need for safety stock. After all, fluctuations in demand can in that case be partially absorbed by the cycle stock.

With the aid of a simulation model, Involvation optimised SCA’s integral logistics costs and inventory. To achieve optimisation, the model took into account the aspects mentioned above and their interdependencies. The result formed the basis for a rhythm wheel per production line and associated safety stock. Although SCA had already achieved considerable costs savings, this method enabled the company to identify further significant reductions.

More potential for improvement

Once the manufacturing and planning processes had been carefully modelled, it was a relatively small step to test other hypotheses. The most important examples were as follows:

The forecast methodology that was used by the countries was shown to be heavily biased; it was structurally higher than the actual demand, resulting in the inventory generally being higher than necessary. While this is certainly not unique within the FMCG sector, it is important to reduce the bias.

The effect of lower changeover costs on the inventory level could be determined precisely, which also immediately revealed how much could be spent on an SMED type of project, for instance. It became apparent that it was important to halve the changeover costs in order to make it financially viable to achieve the strategic inventory levels.

It became apparent that rationalising the product range (e.g. by extending the language clusters) had a much greater effect than expected; armed with hard facts and figures, the logistics department can now enter into a constructive discussion with the marketing department.

The matter of whether the current basic form is optimal could hold further potential. Most of the inventory of most products is now held centrally, with only a limited amount of stock held decentrally in the countries. Because there are considerable differences in both the exchangeability of the products between countries and the demand characteristics, it is fair to hypothesise that differentiating the basic form used would lead to a more efficient and easier-to-manage supply chain.

It is very difficult to predict, especially the future
Niels Bohr