The pace of business is relentlessly increasing, with customers demanding ever shorter lead times and greater choice. The ability to satisfy this need is becoming a differentiator for many suppliers and an order winning competitive advantage in many of today’s marketplaces.

Within traditional mass production environments, being able to service the customer has often meant holding inventory. The amount of inventory is driven by factors such as replenishment lead time, demand variation and the frequency at which a product is batch processed. As we all know, holding inventory impacts on cash flow and adds risk to a business. The Value Added Ratio (VAR – usually illustrated as a ”castellated” line drawn along the bottom of a Value Stream Map) is a frequently used measure of the efficiency of the supplying value stream.

 

The VAR compares the sum of the actual processing times (”touch time”) for one individual item going through the value stream, against the overall elapsed (or ”calendar”) time taken. The elapsed time includes all queuing, setup, transportation and waiting time whilst the item is held in inventory. This is not an issue where demand is high and fairly stable, and inventory will turn over fairly rapidly. In this environment, companies often hold stock, either finished goods or WIP, as a buffer to demand and process variations.

But what about in a Make-to-Order environment, where demands can be volatile, and holding such buffers is too expensive and risky?

Quick Response Manufacturing (QRM) has been developed as an approach to drive lead time improvement within ”Low Volume/High Variety” manufacturing environments (for example, Aerospace, Motorsport, Rail and Nuclear). The overriding measure used within QRM is Manufacturing Critical-Path Time, or MCT for short.

MCT measures the total response time from a customer placing an order to when they receive their item. It differs from VAR in that it takes account of the information flow time through Customer Service, Planning, Purchasing and Engineering, as well as Manufacturing and Logistics. MCT therefore gives one unifying system-wide metric that all functions can, and do affect – defined in a single number.

We all know the old adage “what gets measured,  gets done!” – but it really is true!

“Human beings adjust behaviour based on the metrics they’re held against. Anything you measure will impel a person to optimize his score on that metric. What you measure is what you’ll get. Period. This phenomenon plays out time and again in research studies. Give someone frequent flyer miles, and he’ll fly in absurd ways to optimize his miles.” – Harvard Business Review

Before explaining MCT with an example, it’s important to understand the concept of “Grey” and “White” space aligned to the lead times shown on a MCT map.

“Grey space” indicates the time when someone is working on an order. It’s similar to the “touch time” used in the VAR calculation – but it is not the same. It includes the time taken to produce one end item, but crucially, it also includes the full setup time for processes requiring changeovers (as you would still have to set up the process to produce a one-off).

“White space” indicates the remaining time when nothing is happening to the order. Again, we are considering one end item. So, if we are processing a batch of 100 parts, then only the time for one part is added to grey space, and the time for processing the remaining  99 parts is classed as white space. Add to this any queue time whilst the batch waits its turn with other orders going through a work centre, and transportation and warehouse times etc.

The MCT process map follows similar conventions to a Value Stream Map, with Information Flow going from right to left across the top of the map, and Material Flow going from left to right across the bottom. Both processing and inventory lead times are shown, as illustrated in the example below:

The corresponding lead times can then be illustrated in a MCT timeline map, which is illustrated below:

 

The convention here is that the “grey space” within each element bar is shown at the right-hand end of that bar.

From the above map, we can see this process has a MCT of 94 days. It also illustrates clearly which branch (and therefore, which process steps) is on the critical-path. From this, it becomes obvious that working on reducing the sheet metal or motor supply lead times is not going to affect the overall MCT number!

A traditional, process waste elimination focus might only attack the grey space portion of the lead time, when the greatest opportunity to cut lead time here is clearly to reduce the reasons causing the white space delays.

Also, every business function can, and does, affect MCT. Consequently, the MCT measure combats ‘silo thinking’, where local measures may drive an Area Manager to optimise local performance, but inadvertently sub-optimise the overall value stream. For example, to improve machine utilisation, the changeover frequency could be reduced. This would result in improved machine utilisation, but at the cost of extended lead times and increased WIP, as a result of producing very large batches!

MCT provides a simple, one number measure to understand both order fulfilment and system-wide waste, highlighting where to focus your elimination efforts. It drives behaviour to relentlessly attack the causes for lead time without “sandbagging” customer service through expensive stock holding. It is the overriding measure within Quick Response Manufacturing.

– July 2019 authored by Mike Scull

A Bit More About Mike
Mike Scull has over 30 years of manufacturing experience within the automotive, aerospace, electronics, off highway, white goods and apparel sectors. Joining Industry Forum in January 1998, Mike underwent training and mentoring in the implementation of Lean Manufacturing with Japanese Master Engineers from Toyota, Nissan and Honda. Mike’s current role at Industry Forum is Principal Consultant – Lean Manufacturing.

Mike is a Chartered Engineer (CEng MIMechE), and has a BSc (Hons) in Civil Engineering. He has professional qualifications including APICS Certified Supply Chain Professional (CSCP) and Certified Production and Inventory Management (CPIM), Certified Demand Driven Planner, PRINCE2 Practitioner and is a Certified Six Sigma Black Belt. He is also an Assessor for the National Manufacturing Competitiveness Levels (NMCL) programme.

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