AGR Inventory optimiser generates sales forecasts based on proven statistical forecasting methods, taking into account many key features, including historical sales, seasonal fluctuations and promotional activities. The forecasting module is an important factor within the system and adds new dimensions to inventory management.
A common inventory management method used by wholesalers and distributors for demand forecasting is to average the sales over the previous few months. This method can work well for items in consistent demand, but it does not work so well for others. Due to the fact that different items can have a very different demand pattern, it is extremely important to choose the most relevant forecasting method for each item. Examples of forecasting methods that can be used based on different types of data are:
- Exponential smoothing – covers a wide range of data characteristics
- Simple methods - for short or volatile data
- Curve fitting - identifies the general form of the curve that the data is following
- Low volume models - for low volume and/or sparse data
- Box-Jenkins - for stable data sets
Forecast excellence is inevitably dependent on the quality of the underlying data. One-off events, such as a major increase in sales or an unusual drop in demand, can dramatically change demand forecasting for the worse. It is therefore important to have a system in place that draws attention to unusual activities and takes them into account when forcasting.
To increase vendor collaboration and information sharing throughout the supply chain, purchase plans and order plans can be scheduled at regular intervals. Purchase plans can be created for any defined product group in the system. They can be scheduled weekly, monthly or on specific dates based on the underlying sales forecast.
Purchase plans can then be arranged to utilise container space in order to ensure similar shelf life in each container without breaking volume, weight and number of pallets constraints. This feature can also be used to fill up to a certain price of an order or up to a certain number of days when ordering for some seasonal products.
Inventory Optimiser can take promotional activities into account when creating sales forecasts. It is possible to adjust the sales history for entire groups of items to influence future forecasts. This can be useful for example if there was a promotion at a specific location or for a specific group of items and the user wants to adjust the historical figures for more realistic forecasts. If the changes are confirmed, the history for all underlying items in the group is changed proportionally. In addition the generated sales forecasts can be adjusted for future promotional activity before they are confirmed and sent off as purchase orders.
Manage by Exceptions
The Manage By Exceptions (MBE) module enables the user to define exceptions reports to identify items that need special attention e.g. potential stockouts, late deliveries, high forecasting errors, slow movers etc. E-mail alerts can be sent to chosen e-mail addresses whenever certain products appear in these types of reports. Advanced users can define their own criteria by writing SQL statements using an advanced filter which is included in the system.
"We recently decided to invest in the AGR Inventory Optimiser for our UK operations. The implementation was both quick and within budget. Within weeks we are starting to see the benefits in terms of reduced stock levels, improved service levels and less time spent on the buying process. The system also provides us with valuable exceptions reports that enables us to focus on those items that need special attention. We are planning to implement the system in our global operations as well."-Ashley Cooper, MD of Labelon UK, (www.labelon.co.uk)
Materials Requirement Planning
The Materials Requirement Planning (MRP) module makes it possible to calculate raw material needs for certain production items, as these items can be created from several components. The system uses a Bill-Of-Materials (BOM) to specify how an end-item is constructed from various components. The MRP module, then combines the purchase plans and the BOM to show the amount that is needed of each component for an end-item. The MRP calculations take into account the dates the components are needed based on the purchase plan for the end-item, as well as considering lead and assembly time.
Traditional ABC analysis classify A items as items that account for 80% of the turnover or units sold, B items account for 15% and C items for the remaining 5%. Inventory Optimiser will, however, create a two-dimensional ABC analysis, classifying items simultaneously based on two variables, turnover value and units sold, e.g. AA, AC, BA, etc. This enables users to prioritise their inventory management efforts in terms of the importance of each product. The analysis can be made for the whole company, a single location, a product group, supplier, etc.
"We were offered the opportunity to test the system for a period of 3 months. After the testing period we bought the system without hesitation as it was clear to us that it will help reduce stock levels, improve service levels and save valuable time in the buying process. The system also increases our overview by giving us various reports such as stock and turnover development and twofold ABC analysis." - Niels Brun Hansen, Financial director, Oluf Brönnum A/S, Denmark
Management overview makes it possible to evaluate the performance of various factors in the inventory management system, such as stock value development, turnover, turnover ratios for products, groups or locations, allowing them to closely monitor the performance of the system. If a future time horizon is chosen the system will forecast and display sales figures for the future.