Conclusions

In the following sections we present our conclusions from the previous chapters. 7.1.1. Current situation

In Chapter 2 we answered RQ 1 to understand how the processes are currently organized and where the bottlenecks are at this moment. We analysed the current processes and made flowcharts that can be used for further analysis by the management of B&F. We discussed the system of B&F and how the system is controlled. In short there is few control to organize the inventory, to keep the stock low and to keep the costs within certain boundaries. The current inventory policy is based on a (s, Q)-policy. Reorder point s is determined by keeping a minimum of 21 days on stock and the order-up-to-level Q is determined by the lead time + 14 days of stock. The predicted demand is based on the naïve method. B&F wants to provide a high service level and does not want to have lost sales or have stock out, especially for their own label. The safety stock for the own label is extremely high which causes no space left in the warehouse to keep new products in stock. Besides the high stock levels, the next problem is the low cash flow and no cash for new product investments. We therefore conclude that B&F misses a system to control the inventory and predict the future demand. We limit this research to the stock of the own brand of B&F delivered by X.

7.1.2. Solution space (literature research)

The solution of our research begins to create a program in Access 2013 to be able to know what happens with the sales history and the stock history. Next we try to identify constant demand, trend demand, and seasonal (trend) demand in the data of B&F. We were able to identify constant demand and trend demand in the data. Seasonality is more difficult because of the limited data available. We propose to apply seasonal indices to the data once the SKU is forecasted. The solution we propose is to make use of relatively easy to implement forecasting techniques such like moving averages, simple exponential smoothing, exponential smoothing with trend and exponential smoothing with damped trend. In order to

pick the right forecasting model we developed an algorithm procedure for selecting the most suitable model.

The forecasting model delivers the forecasted demand for one period ahead and delivers the lead time demand and the standard deviation during the lead time. The delivered data is used as an input for the (s, S)-policy. We keep the (s, S)-policy because in general this policy works best in a service level environment. The service level used is set on 99.5 % with a lead time of 5 days.

7.1.3. Decision model formulation

We formulate a forecasting system with the following methods:  Naïve method

 Average over historical data

 Moving average (MA-2, MA-3, MA-4)  Simple exponential smoothing  Holt´s method, trend model

 Gardner and McKenzie method, damped trend model

When applying the proposed system first the outliers are detected and the data is smoothed. When the data is smoothed each model is initialized using RMSE. We set some boundaries for the parameters and remove the models that do not meet the parameter boundaries. Next, the best model is selected based on MASE. If the selected model is a linear model, it is tested for linearity by using the R-squared method. When there is no appropriate model, the user has to make own judgement. When there is a usable forecasting model the forecast is shown to the user. Next the EOQ formula is used to determine the parameters of the (s, S)- policy.

7.1.4. Financial savings and space reduction

When implementing the forecasting and inventory control system we propose, B&F can achieve savings by reducing the working capital that is captured in the current inventories and additional space can be created for new products. The savings are:

 176 products delivered by X with a service level between 99.5 % and 95.0 %, with a lead time of 5 days, we have yearly savings on working capital between:

<<CONFIDENTIAL>>

 176 products delivered by X with a service level between 99.5 % and 95.0 %, with a lead time of 5 days, we have on average less stock in a range between:

<<CONFIDENTIAL>>.

 When we take into account the capital cost r of 19.7 % we have a yearly savings in a range between:

<<CONFIDENTIAL>>.

B&F can reduce their working capital and the amount of items on stock. We identify several benefits for B&F to reduce the stock levels:

 Less space needed

 Less risk when a product is not sellable anymore  Less cash needed to hold the stock

7.1.5. Implementation

We describe the information we need and the information that should be provided by the proposed system.

We gather support by presenting the results of the savings to the executive board of B&F. Next we present the findings and the process steps of the proposed system to the Logistics manager, BIE, and ordering employee.