Demand and Capacity - Develop a Strategy

 Effective capacity planning requires a planner that knows the true manufacturing capacity of a given plant. The complicated task of matching supply with current demand, however, is affected by a number of elusive factors.

Identifying the Bottleneck

Looking at overall plant capacity relative to overall demand will not work because that will not take into account the capacity of individual resources that make up the plant. For example, if a crucial step in the production process can only be accomplished on one specific piece of equipment, it does not matter if capacity on other machines is available. Furthermore, if workers with the right skill-set to run that pivotal piece of equipment are not on shift when needed, the entire line may be endangered.

The Unpredictability of Constraints

Constraints at any step along the manufacturing work flow will limit capacity. Unless these bottlenecks are identified in advance, they are almost impossible to manage. An insufficient supply of raw materials is a good example of a bottleneck that limits production capacity. At times, needed materials may not be delivered to individual work sites in a timely manner. Alternatively, a particular piece of equipment may become a constraint if the right operator is not available to run it, or if unexpected downtime takes it out of commission.

Market demand for finished products is never stable and can add to internal plant complexities; it may even vary cyclically or with economic serendipity. Demand also fluctuates with sales force effort, unrealistic sales goals, or by a sales or customer service department that promises too much or too little.

Demand variability can mean there is more demand than a plant can handle, too. When a plant is running at capacity, adding extra jobs may put plant efficiency in jeopardy. This results in negative feedback loops as customers begin to complain about delivery dates due to strained resources. In an effort to correct superfluous demand, floor supervisors sometimes respond by leapfrogging one job over another. If not properly managed, the routine of compensation and over-compensation can whipsaw the production schedule until it crumbles into chaos.

Maximize Capacity to Meet Demands

Without excess capacity available to supply these market demand surges, the attempt to deal with variability in demand continually seesaws back and forth. Surge capacity can be fulfilled by outsourcing work to other suppliers temporarily, bringing equipment online that is not normally in use, or switching equipment or personnel from one production area to another.

Solutions that successfully work with set capacity to meet variable demand can benefit from an Advanced Planning and Scheduling (APS) system. An APS system provides realistic data analysis that empowers managers to make intelligent capacity planning decisions. More importantly, it allows the user to run models that suggest solutions to complex scenarios. These “what-if” trials map out paths that enable a plant to close in on a capacity supply=demand solution, no matter what the supply or the demand situation.