Reducing long and inflexible lead times

Reducing long and inflexible lead times

Industry 4.0 and the Industrial Internet of Things (IIoT) provide insights into demand patterns that we have never had access to before. However, they also raise the need for service-driven and agile low cost supply chains that challenge traditional lean thinking and its application.

In our work with manufacturing businesses we have found that the adoption of lean and the elimination of waste remain the overriding manufacturing ideologies. Waste elimination is often seen narrowly in a way that undervalues flexibility and focuses too heavily on reductions in cost and working capital.

As manufacturing operations become increasingly tied to delivering the differing needs of the fragmented markets they serve, agility needs to be integrated into the design of the product and manufacturing process. Inventory needs to be used strategically to support market needs where the supply chain cannot be agile enough.

For example, in a major global pharmaceutical business we work with, we developed the concept of “inventory entitlement”. This is the minimum inventory needed to meet the market requirement with the existing level of flexibility.

We injected significant inventory into areas with low agility that provided a consistent supply to areas with greater agility. The overall impact was lower supply chain inventory, reduced lead time to key markets and greater flexibility to deal with unforecast demand. It also gave a clear understanding where the focus on creating greater agility lay.

Strategies for Success

Segmenting Demand

Industry 4.0 analytics is helping define ever narrower customer segments, as well as the demand within each segment. The challenge is to structure your supply chain and configure your manufacturing facilities to balance cost, agility and service – recognising that agility comes at a cost and is therefore used only where required.

For example, we recently segmented demand for a single product family into three. High volume demands were produced at lowest cost with inflexible machines using a strict product wheel. Mid volume demands that were predictable were made on the same machines, just not on every cycle of the product wheel.

This produced the same efficiency but with a stock cost (i.e. inventory entitlement). Low level or erratic demand was produced on agile machinery- a higher production cost that minimised both stock cost, and more importantly obsolescence risk.

Agile Manufacturing

Lean manufacturing has been the overriding ideology for many years, but with the greater fragmentation of markets and customers expecting more variety and improved lead times, the need for agility becomes paramount.

Within an Agile Framework, manufacturing can be designed and structured to satisfy customers quickly with personalised products and services. However, agility comes at a price. Creating bespoke products and moving from one product to another in the production process will not be the lowest cost solution. This cost, however, will be offset by greater customer satisfaction and loyalty.

A supplier of PCBs with a low volume, high variety order book, was experiencing inflexible, order-to-order production. By analysing product usage and demand we helped this business set up their lines to manufacture a high variety of products with minimum disruption.

Agility is becoming the key driver in creating low manufacturing costs and simplifying the business, whilst providing greater flexibility.

Operating Models

A greater understanding of customer segments needs to be translated into manufacturing approaches. Whilst there are many nuances to meet specific circumstances, there are three core operating models:

1. Make to stock (MTS)

When your agile supply chain cannot economically meet customer service expectations, stock needs to be integrated into the design of the supply chain. Finished goods is the obvious stock point, but the most economic point is where the number of SKUs grows most significantly.

A pharmaceutical client of ours operates with three base Active Pharmaceutical Ingredients (APIs), that grows to nearly one hundred semi-finished SKU’s and multiple thousands of finished goods. The solution to their service issues was to put a managed stock at the semi-finished level and invest in agility to convert this to finished goods. The result was a two week reduction in market lead-time, improved OTIF and a lower overall supply chain stock.

2. Make to Forecast (MTF)

An MTF operating model has the same fundamental driver as MTS – insufficient agility requiring some element of manufacturing and stock without a customer order. The difference is that a greater understanding of likely demand (i.e. forecast) means that the uncertainty is reduced, and your supply chain can run with lower levels of stock.

3. Made to Order (MTO)

The operation of an MTO model is obvious: lead times are either long or in the context of this article, the levels of agility are high, which enable you to economically manufacture within the required lead time.

Wherever it can be made to work economically, we suggest operating an MTO based manufacturing supply chain. However, there is a simple relationship between operating cost and agility, so the use of `costly’ agility has to be focused. Most well-designed supply chains use a mix of operating models. The skill is understanding the nature of demand for each product at each stage of manufacture and then applying the most appropriate operating model at that stage and integrating it across the supply chain.

Overcoming Obstables

Moving to an agile manufacturing methodology takes planning and education. Operations teams maybe advocates of lean and resistant to change but in our experience, they can be easily persuaded if they are presented with the right information.

The best way to do this is to build models of the supply chain and decide what inventory needs to be where. A mindset change is required, so that there is a more holistic view of inventory. It is only a problem when there is too much of it, or it is wrongly located. The supply chain needs to be looked at as a whole with a recognition that parts may need to be sub-optimised, in order optimise the whole.

This more sophisticated approach provides the way to act simply and have an easily managed supply chain.

Conclusion

While IIoT and Industry 4.0 provide great insight and analytics, the ability to exploit the insight in physical manufacturing operations is essential to providing the diverse and fragmented range of services required. This necessitates rethinking some of the ways that we have applied lean in ways that deliver greater agility where it is really needed.

Manufacturing supply chains are getting a lot more complex and only by understanding them in a sophisticated and segmented way can simple solutions be designed and delivered with the right balance of agility, operating cost and working capital.

Tim Richardson
Development Director
Iter Consulting