A company starts a supply chain initiative with a focus on production planning and purchases an appropriate software application. During the solution design phase, a long list of business and functional requirements are identified, which include many requirements that are beyond the actual scope of the designed functional capabilities of the software. A simple example of this is a requirement to be able to model the sequencing of material for a hot rolling mill. The project team decides that these sequencing requirements are important and, even though the tool is not really designed for it, they believe that customizations can always be implemented to ‘make it work.’
Later in the build phase of the project, such customizations effectively fail because the application is being forced to do things it was never designed to do. As a result, the project struggles, users become dissatisfied because the software does not function according to their expectations, and ultimately the company does not receive the benefits expected.
Because of such initial experiences that many companies have with advanced supply chain software tools, often the software is blamed for not being good enough and the company is reluctant to make further investments in the supply chain area.
A critical aspect of any supply chain transformation is, therefore, to have a deep understanding of the capabilities of different software applications being considered, and to be able to map these capabilities in the correct way to business and functional requirements.
Demand planning and supply planning combine to provide sales and operations planning (S&OP) capability. S&OP provides a medium-/long-term tactical plan for the business—taking a consensus sales forecast that is balanced against production capabilities. Tools often provide capabilities for characteristic dependent planning, capacity reservations and the ability to create plans optimized based on relative margin contribution of different products (so called ‘profit optimization’).
Order promising enables both available-to-promise (ATP) and capable-to-promise (CTP) capabilities. ATP provides a reliable ‘due week’ order confirmation to customers, based on allocations driven from the S&OP process. CTP provides a ‘due date’ order confirmation, based on the current production plan, reflecting actual material and capacity availability.
Production planning generates a feasible short-term, order-based plan that is key to seeking to achieving the on-time delivery of customer orders.
Scheduling creates material-based sequences based on detailed manufacturing constraints of the production plan. Typically, multiple scheduling tools are used at different stages of the steelmaking supply chain.
Planning model granularity
Due to the complexities of steelmaking manufacturing processes and products, it is not practically possible to manage all planning decisions that are relevant to different time horizons in one single planning tool. Therefore, different planning horizons require different tools and levels of granularity in what they model.
A good example of this is S&OP. In the steel industry, because of the large number of end products involved (up to hundreds of thousands), S&OP should be performed at an aggregated product family, or group, level. A product family represents a logical grouping of individual sold products that have similar attributes, follow similar production routings and consume similar product capacity (as measured in terms of machine run rates and yield). In some cases, it also may be appropriate to differentiate between sales forecast product groups and supply planning product groups, which can be managed on different aggregation levels. The optimum level at which to perform product group aggregation is different for each steel company—depending, for example, on product mix and process route complexity—and is a function of the trade-off between requirements for planning accuracy and control, versus model complexity and usability.
It is important to recognize that small differences between individual products—for example, steel grade specification, width and thickness—does not automatically drive a need to proliferate the number of product groups that are defined. Conversely, the defined product groups need to be able to provide a reasonable model of production capacity consumption, to allow realistic mid- and long-term planning decisions to be made, and to allow the business to make correct product/market allocation decisions.
A further key consideration is that the level at which planning groups are defined should be a level of aggregation at which the company can make a sales forecast with a reasonable degree of accuracy. At the S&OP planning level, steelmakers are not trying to create a sales forecast and plan for the next week; therefore, an aggregated view of demand based on a few key product attributes, such as steel grade and thickness, will suffice and result in a much higher degree of forecast accuracy.