It’s the process of determining the level of work that is demanded and then establish the resources needed to accomplish it. There are two main strategies for meeting demand and capacity planning is usually about finding an optimum combination of the two.
- Level-capacity is about setting the production rate at an aggregated average output level, to smoothen out the supply to meet the demand over time. This brings peaks and troughs to the delivery time, which can sometimes result in an order backlog and missed promises.
- Chase-demand varies the production rate in response to demand fluctuations – through flexible work shifts, overtime, hire/fire, sub-contracting, and maybe adjusting demand through pricing.
Usually a trade-off must be struck between the wastes associated with too much or too little capacity. Pareto’s 20/80 rule tells that 80% of costs from waste tend to be hidden. For example, failing to deliver to the customer on time can have indefinable longer-term costs from loss of trust in the relationship. This hidden element means that it is not always obviously easy to determine the optimum trade-off point.
The effective planning and optimisation should recognise and consider the 3 levels of capacity:
- Designed system capacity is the rate of output that the technical system could theoretically produce under continuous ideal conditions.
- Effective capacity is the realistic output, given the foreseeable product mix, scheduling complexity, flow control, bottlenecks, operator competency, stability, work tools, facility and necessary down time for planned equipment/vehicle maintenance.
- Actual capacity includes the unforeseeable, unplanned problems such as sudden equipment breakdown, mistakes, material supply shortage, sickness epidemic, industrial relations and natural events/disasters.
Productivity and efficiency are both measures of the actual output, but using different references. In the chart above, the efficiency is rated 83% and productivity is 50%. Efficiency has the lesser potential for growing the actual output. The table below lists some efficiency ranges, which kind of have to be accepted in different types of operations. It would demand an exceptional system to improve on these. There tends to be significantly more potential for growing the actual output by instead improving the effective capacity, because the latter acts as the principle limiting factor to productivity. Efficiency improvement, while not un-important, has less actual effect on the overall productivity gap.
The optimum production system is not necessarily the one with the highest designed capacity. It is conceivable that a system with high designed capacity translates into a lower actual capacity, by the way it influences the various detractors for productivity and efficiency. Capacity improvement should focus on the design of products, processes and technology for achieving the highest effective capacity.
The determining factors of effective capacity:
- Job size or batch quantities. Frequent start-stop, change-over and set-up time detracts significantly. Excessively large batches may however make the system less demanding to demand fluctuations and could operator boredom could detract from operator.
- Product design. High similarity, standardisation of methods and materials can lead to greater capacity. A greater the mix of components manufactured at different rates of output will reduce capacity.
- Process design. Demand flow techniques, such as Kanban with balanced ‘takt’ times, can enable a higher effective capacity. Mistake-proofing devices will reduce stoppages and time-stealing rework. Where cost permits, automate low skilled repetitive tasks that would otherwise detract from operator motivation. Adopt artificial intelligence (AI) and robotics, as the technologies evolve and become realistic alternatives.
- Work environment, including facility layout, heating, lighting and ventilation, will affect people’s concentration and how they perform their work.
- Operational factors, including scheduling complexity, inventory stocking decisions, waiting-lines control, supplier delivery reliability and materials acceptance criteria.
- Location factors such as distance to suppliers, the market, labour supply and space sufficiency for facility expansion.
- Human factors, including performance, knowledge, skills and experience. In manual systems the inherent operator motivation has an important relationship to capacity. Good leadership and empowerment can help unlock discretionary talents – as opposed to suppressed people holding back what they are good at.
- Dynamic pricing. Think about how the holidaying sector and budget airlines optimally fill their capacity.
- External factors such as product standards, environmental or safety regulations can at times restrict certain options in increasing capacity.
In general, capacity and quality are improved by focussing on what works well. Remember, the Kano model tells that a strategy based solely on removing dissatisfaction can over time never result in satisfaction. People should be empowered to apply their talents – as opposed to be subordinated to a controlling pressure. Motivated people will naturally feel good about putting themselves under pressure to perform well and shouldn’t need to be told to work hard. Work tends to happen in episodes. When people start to pick tasks that are the shortest work episodes and when they take more downtime in between the episodes, with extra coffee and social media breaks, then it is a sign that they are switched off and that capacity might be slacking.