Attribute-based Demand Planning: A Powerful Tool for Process Manufacturers

Originally published - February 11, 2008

Today, manufacturing is a global activity. As supply chain management (SCM) becomes more prevalent in this industry, process manufacturers need to know what raw materials, or ingredients, are available in inventory and when they are needed, since sourcing these ingredients is a complex process.

Demand management (DM) software has been developed so that it can be integrated within the supply chain in order to help manufacturers meet sales forecast objectives and increase customer satisfaction. DM software also helps manufacturers deal with customers' expectations of what can be produced and how much will be available.

Process manufacturers are seeing other issues as well:

  • increasing manufacturing costs in the process industry, and the need to get a handle on these costs

  • difficulty in measuring sales forecasts accurately due to issues of seasonality, changing customer demand, and availability of materials, if no demand planning software is in place

  • diminished visibility of data and materials across the entire supply chain if systems are not integrated together, leaving departments to rely on previous forecasts to manufacture the product(s)

  • longer lead times if proper procurement practices are not taken, and either too much of the wrong inventory or not enough of the right inventory is in the warehouse, increasing inventory holding costs

  • decreased customer satisfaction as responsiveness to changing customer demands decreases

In order to combat the above issues, attribute-based demand planning (ABDP) has been developed within DM software—an approach based on just in time (JIT) inventory methods and DM software. ABDP can reduce inventory levels and supply chain connections, as well as allow organizations to become adaptable to changing customer demands.

The main goal of ABDP is to eliminate the holding of inventory as much as possible, which is achieved by planning for materials needed based on attributes as opposed to the whole product itself. This means that if an ingredient or part with a particular specification is needed, then the product demand will be triggered in the system, and the needed material will be ordered. Normally within DM for manufacturing, the component is ordered based on historical data as opposed to the need for that particular item.


DM, or demand planning, is a method that gives managers the ability to forecast needed inventory stock, parts, or components within the supply chain in order to manufacture a final good. DM helps to manage a firm's inventory by way of setting minimum and maximum levels of stock, and letting the system indicate to the appropriate managers what to buy and if the stock is needed either immediately or in the next period.

ABDP takes the above process one step further. It is, in essence, a method of lean inventory management that focuses on the next level down. Using a DM software solution, a manager can not only forecast how many products will be needed, but also which type of components will be needed to produce the products, as well as if any modifications are to be made to those components.

With ABDP, the system can accurately decide what stock is needed, as well as when it is needed, in order to adapt to changes in customer demands—a capability that will invariably increase the manufacturer's bottom line by reducing inventory holding costs.

How Can ABDP Help Manufacturers?

With regards to the business issues listed above, ABDP can help firms decrease manufacturing costs and accurately measure the precise components or materials needed for JIT types of manufacturing. DM software in combination with ABDP methodologies can also increase visibility of both data and materials, and help in the procurement of these goods.

In process manufacturing specifically, ingredients management is a very important component to the production of the goods. Whether launching a new product, changing or modifying present products, or discontinuing old products, managing this process can be tricky, especially when selling multiple products at the same time. ABDP can help manufacturers avoid problems and mitigate the business issues outlined above.

Let's take a closer look at what ABDP is and how it can help manufacturers.

ABDP has to do with manufacturing the product itself and managing the inventory for that product. ABDP takes into account a larger amount of data than a typical DM solution does, as each item is attributed particular characteristics, and forecasting is done for each of those characteristics, depending on the needs of the customer.

The system analyzes demand against available supply, and performs a rebalancing of supply and demand based on the needs of the customer and the availability of each characteristic for that item. Requirements that can be measured may include specific consumption, location of manufacture, and specifications of raw materials that would also be calculated into the price of the item.

ABDP also helps managers avoid building up too much inventory to accommodate every scenario, which is a situation that could lead to excess holding costs. Instead, the system will perform two functions:

  1. Minimize and maximize stock levels for each attribute specified by the manufacturer, allowing for minimum stock to be carried. If more stock is needed, the ABDP solution will be able to forecast and directly order new stock, so as to not run short.

  2. Allow the customer to pick attributes of a product, such as type of item, color, size, location of the manufacturer, etc. Only the attributes of the product are managed, not the entire inventory unit, which lowers inventory carrying costs.

How Demand Planning Works: An Example

Let's take a manufacturer that produces chemical fibres, namely, nylon. Due to advances in chemical fibre technology, the number of variations and types of nylon materials is practically endless.

In this example, the manufacturer will be producing two types of nylon—one particular type for two unique customers. Both customers have completely different requirements, as the first client is from the garment industry, and the other client is from the safety industry, and provides nets for construction workers. Because of these differences, the ingredients for each type of nylon to be produced are different.

An ABDM software solution will allow the manufacturer to order only what is necessary for each customer requirement, and at the same time, meet customer expectations by allowing the customers choose the attributes of the each nylon fibre, such as color, strength of the material, etc.

In this example, the DM system would input the following attributes:

  • different chemicals needed
  • manufacturing delivery date
  • fibre color
  • fibre thickness
  • fibre shape

Furthermore, based on these factors, the system would be able to calculate when, how much, and for whom the products are to be produced. Using the ABDP method, the DM software will enable the organization to lower inventory levels rather than stocking several different types of fibre, which would tie up working capital.

This is strictly an example, but the benefits of ABDM can extend to any type of manufacturing environment, as the system can accommodate any type of component or material needed to manufacture a product.

Products to Review in the Market Space

ABDP is a very effective method to reduce inventory costs and increase customer satisfaction. It takes into account customer expectations, and can help to shape those expectations, as well as minimize the risk of having too little or too much stock.

The solutions of software vendors such as Supply Chain Consultants, which carries Zemeter software (; Oracle, which offers Demantra Demand Management (; and RockySoft Corporation, with its RockySoft Demand Manager (, will enable manufacturers to increase profitability and improve overall manufacturing activities.

Each of the above DM solutions has specific advantages, but all will help with the issue of increased manufacturing costs. These solutions will allow for more accurate sales forecasting methods that will coincide with the product attributes needed, help out purchasing, and finally, increase overall customer satisfaction.

Following are some of the specific advantages of each DM software listed above:

1. Zemeter

  • advanced methods such as baseline forecasting, which uses more than 20 statistical methods, including optimal "best fit" methods for any series of data

  • business intelligence, which consolidates data from sales, marketing, and operations, and provides visibility across different business units

  • adaptive collaboration—a forecasting process that "learns" to use the right data from different data sources

2. Demantra Demand Management

  • a proprietary Bayesian algorithm that can handle multiple and simultaneous causal factors, including pricing and promotions

  • a hybrid online analytical processing (OLAP) data architecture design that is able to handle massive volumes of data

  • chaining and attribute-based forecasting that will help shape modeling to predict new product phase-out and phase-in

3. RockySoft Demand Manager

  • Web-based solutions for easy access to updates

  • integration to a requirements-procurement program to increase real-time supply chain decisions

  • custom seasonality index forecasting that allows modification of algorithms by seasonality factors

The Final Word

ABDP is a very effective method of reducing inventory levels—and thus costs—within the manufacturing environment. To that end, the DM software solutions mentioned above have very strong functionality. Among the many benefits for the process manufacturing environment specifically, ABDP and DM software can help manufacturers obtain specific materials in an efficient and cost-cutting way, improve workflow by procuring specific materials only when they are needed, and increase customer satisfaction by adhering to the needs of the client.

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