Both the approaches are used to address the fluctuating demands of the customers and ultimately aim to eliminate waste, reduce lead time and achieve an overall equipment and people effectiveness. A few comparisons are listed below:
Demand Levelling
Production Levelling
1). A carefully thought-out proactive approach that influences the demand itself of the customer to arrive at a more stable and predictable demand pattern that drives a levelled production.
1). Popularly known as “Heijunka”, it is a mixture of both proactive and reactive approaches in which the production schedule, based on predicted customers’ demands, is fine-tuned in such a way that there no overburden on the systems, resources and equipment while producing products in a consistent manner.
2). An example in manufacturing industry could be – Build-to-Order approach especially used in automobile industry to arrive at a predictable near-approximate demands.
In service industry, concept of happy-hours in restaurants and pubs can be used to level the demand surges in peak hours. Another example, could be passport generation in Passport Seva Kendra, where demand is levelled by allocating appointment slots.
2). An example here could be a shoe company producing shoe types A, B, C, and D averages weekly demands of A (5), B (3), C (2), D (2).
A mass manufacturer with apparent changeover challenges, interested in economies of scale would follow the following sequence – AAAAABBBCCDD – known as levelling by volume.
On the other hand, a lean manufacturer who want to leverage the benefits of a product type along with volume may want to follow this sequence –AABCDAABCDAB - known as levelling by type.
3). Preferable at the beginning of lean implementation to gauge the demand levels of the customers.
3). Is mostly used towards the later stages of lean implementation once value-streams are finalized and takt time is known. A final production schedule is made visible by the use of Heijunka Box.
4). Not feasible in situations when there is rush of demands due to emergencies, pandemic, and low-price high-volume scenarios.
4). Less effective in situations where there are infrastructure and resource challenges to carry out SMED especially when the manufacturer intends to level the production by the product type.
Vital Trade-offs: Despite being two different concepts, they both complement each other in a variety of ways. In situations where there are limitations in implementing production levelling due to various capacity constraints, demand levelling is done to meet customer’s demands by modifying its various product offerings and by triggering a change in the way the customers place their orders. The insights obtained from this subsequently feeds into a production/service schedule thereby enabling Heijunka.
Similarly, where demand levelling is not possible, a TAKT time provides an approximation on the customer demands and drives the overall production schedule where customer’s requirements are fulfilled via small batches (levelling by volume and type), single-minute exchange of die (SMED) and standardized work.
Limitations: Despite all its benefits, Heijunka to an extent walks a tightrope by trading inventory or lead times for stability and is a short-term workaround intended to smoothen the crests and valleys of customer’s demands. Another limitation is that it is responsive only to moderate demand fluctuations. Unusual variations in demand need more extreme measures.
With most of the organizations these days moving towards agility by taking steps towards creating a more responsive production system that is more flexible and could cater to varying levels of customer’s demands, Heijunka more or less limits oneself to an approach that revolves around various constraints. You never know when the swings in demands which are perceived as a constraint in Heijunka might be perceived as an opportunity by an agile competitor that is ready to pounce on it with its advanced tools and techniques. A workforce with T-shaped skills, working in a cellular layout with an adaptive production schedule could be a starting step to exploit these constraints.