Demand management in a make-to-stock environment

Make-to-stock environment is a traditional production strategy adopted by businesses. The motive is to match the inventory with the anticipated consumer demand (Rodrigues & Otávio, 2010). Make-to-stock which is also known as a push system is typically employed in the production of consumer goods. Consumer goods and commodified goods are products which are rapidly consumed. Thus, this method requires accurate forecasting of demand.

Forecasting in a make-to-stock environment is done using historical data of revenues, sales, and production statistics. Firms also store a small, ‘safety’ stock of finished goods and raw material for emergencies. As compared to other production systems such as make-to-order and assemble-to-order, raw materials and other components are purchased in bulk. Due to its anticipated production system make-to-stock generally uses the work-in-process technique. Hence the partially finished or processed stock can be supplied to all stages of the production process. It helps to maintain a smooth flow of the production process. The main advantage of make-to-stock is that it helps to better utilize labour and achieve overall efficiency in the supply chain (Gupta, 2010).

Demand management is an important function of supply chain management. The previous article explained how the demand management process takes place in an organization. Demand management is handled differently in different environments in the manufacturing industry. These environments differ on the basis of inventory and production. The three main environments are (Akçay & Xu, 2004; Wemmerlov, 1984):

  • Make to-stock (MTS)
  • Make-to-order (MTO)
  • Assemble-to-order (ATO)

Drawbacks of the make-to-stock environment

Although the make-to-stock strategy is useful in controlling cost and protects the firms against opportunity loss, it does have some disadvantages. For example, using inaccurate sales data can lead to the wrong anticipation and thus causing long term shocks in the system. Furthermore, there could be cash flow concerns. Moreover, the inventory count must be accurate which involves raw material, work-in-progress and finished goods since any variation in these at any phase can certainly impact the cost. Along with this, the risk of obsolescence or perishability is always there (Goyena, 2019).

Management in a make-to-stock environment

All the drawbacks mentioned above have a common element. Each stage requires accurate planning, forecasting, analysis and decision making. The small to medium companies can improve their make-to-stock performance by focusing on certain aspects such as:

Developing an accurate inventory management system

No forecasting can prove effective if the inventory system is inaccurate. Thus, the inbound inventory should be tracked accurately, starting from the acquisition of the raw materials. The records should be appropriately created for quick use in production. Moreover, the finished goods should be tracked, recorded and streamlined. Any inefficiency in this stage is generally the result of either the human component or system failure. Thus, a close check should be maintained on both the systems i.e. raw material procurement and finished goods distribution, to overcome any complications in the supply chain (Croxton, García-Dastugue, Lambert, & Rogers, 2001).

Managing the long and short-term supply chain legs

The make-to-stock environment requires bulk purchase of the raw material. However there are other materials that can be purchased locally or regionally and do not require bulk purchase. This long and short-term planning differences that arise within the supply chain must be managed for maintaining a balance. To efficiently manage make-to-stock, businesses can adopt software applications with integrated purchasing and lead time monitoring (Veatch & Wein, 1992).

Developing a workflow-based production system

The medium and small manufacturers using the make-to-stock strategy generally, adopt a spreadsheet-based production workflow planning. This causes latency within the system which reduces its overall effectiveness. Instead, businesses can use a workflow-based production system which provides an infrastructure set up for performance and monitoring of the defined sequence of a task, arranged as a workflow application. This ties in with purchasing, supply chain and inventory management thus providing a clear vision over the production flow and the transactional level (Huang, Trappey, & Yao, 2006).

Case study of Apple Inc.

A prominent example of a business that uses the make-to-stock strategy is Apple Inc. Apple applies the make-to-stock strategy to sell its products in the stores. The company first through forecasting estimates the demand for its product. Then calculates its manufacturing capacity and the availability of raw material to build enough inventory to meet the consumer demand. In order to maximize its cost efficiency, it purchases the raw material ahead of time. Finally through its contract manufactures, Apple ships its inventory to the Apple stores and other retail outlets.

References

  • Akçay, Y., & Xu, S. H. (2004). Joint Inventory Replenishment and Component Allocation Optimization in an Assemble-to-Order System. Management Science, 50(1), 99–116.
  • Croxton, K. L., García-Dastugue, S. J., Lambert, D. M., & Rogers, D. S. (2001). The Supply Chain Management Processes. The International Journal of Logistics Management, 12(2), 13–37.
  • Goyena, R. (2019). make to order vs make to stock:the role of inventory in delivery-time competition. Journal of Chemical Information and Modeling, 53(9), 1689–1699. https://doi.org/10.1017/CBO9781107415324.004
  • gupta, D. (2010). differentiation ? A common framework for modeling and analysis Make-to-order , make-to-stock , or delay product differentiation ? A common framework for modeling and analysis. (December 2014), 37–41. https://doi.org/10.1080/07408170490438519
  • Huang, C. J., Trappey, A. J. C., & Yao, Y. H. (2006). Developing an agent-based workflow management system for collaborative product design. Industrial Management and Data Systems, 106(5), 680–699. https://doi.org/10.1108/02635570610666449
  • Rodrigues, P. C. C., & Otávio, O. J. de. (2010). Engineering-To-Order Versus Make-To-Stock Strategy: an Analysis At Two Printing Companies. Independent Journal of Management & Production, 1(1), 1–23. https://doi.org/10.14807/ijmp.v1i1.28
  • Veatch, M., & Wein, L. (1992). Schedulling a make to stock queue: index polocies and hedging points. (September), 5–6.
  • Wemmerlov, U. (1984). Assemble-to-order manufacturing: Implications for materials management. Journal of Operations Management, 4(4), 347–368.

Priya Chetty

Partner at Project Guru
Priya is a master in business administration with majors in marketing and finance. She is fluent with data modelling, time series analysis, various regression models, forecasting and interpretation of the data. She has assisted data scientists, corporates, scholars in the field of finance, banking, economics and marketing.
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