"No one is going to own a car any more." "We need to do that in the future." "AI will fix that." Our industry is rapidly morphing from building vehicles to providing mobility. Resultantly, a number of new work faces have opened up demanding attention — and working out where to place our best efforts is vital.
With the sheer level of disruption from new technology and ideas, it's easy to assume that everything will change and that improving today's products and processes is worthless. That's not the case. This article looks at how we can improve processes — ones that'll be required both now and in the future, as well as those that'll evolve rather than take a giant, disruptive leap. Developing these processes should be high on everyone's priority list: they address real challenges now and firm the foundations for the future.
CAD to line: a rich opportunity
Of the many challenges, we should be focused on those with the highest value and most frequent use. One such challenge — underestimated and misunderstood for the last 30 years — is the flow of accurate, timely information from design to the production line. This complex set of transactions involves hundreds of fields of data for thousands of parts, passing through many hands, with dozens of hand-offs and interfaces — some of which aren't even known to the people using the data. It's no surprise this creates some big challenges, or, with the right focus, some big opportunities.
Buckets and leaks
We tend to think of this as the drawing board finding its convoluted way to the production line. It has many valves, restrictors, diversions, filters, holding tanks — and a surprising number of people moving buckets to and fro, alongside some quite significant leaks. Each leak is a data point that is lost, or not as accurate as it could be. Product Data Management and Product Lifecycle Management have been on the agenda for some time — so why have we failed?
Extending the analogy: a lot of effort and expense has been spent on fixing and improving the valves, filters, and restrictors — but the leaks and data buckets are still leaking. Complexity has grown — through increased customer choice, more global products, and greater use of platform approaches — and coping with it has absorbed much of the improvement effort. There is limited evidence of meaningful improvement in the last 2-3 decades.
Until we suspend our instinct to reach for the universal big solution (new system, new org) and begin focusing on the individual detailed problems — and the real human elements of each one — it'll be difficult to make progress, and easy to rack up big bills.
Case study: global prototype builds
The prototype process is a smaller version of the whole programme, and a good example of a process that needs to be tackled. A design team is commissioned to design a number of vehicles to be built; sourcing and production then arrive for a vast number of vehicles to be built.
One major global OEM, suffering from delays to their first production vehicle in successive programmes, found a direct correlation between lateness of prototype builds and lateness of first production vehicle. The biggest cause of prototype lateness was product data issues — specific data issues.
They brought QR_ in. The approach was two-fold: tactical support to drive increased performance — plugging the leaks and increasing the building rate — followed by strategic improvement workstreams to underpin that increased performance, such that the tactical support could be reduced and eventually removed. No new systems were implemented. Process changes were limited to those that addressed the specific causes of errors, lates, and omissions. The real effort went into connecting and visualising the information flows — and, in particular, the specific human interactions within the flow.
A year in, the results speak for themselves. On this Commercial Vehicle programme, we achieved a higher-quality prototype build than ever before, and parts are being sourced earlier than ever before. The Material Required On-Time (MROT) metric moved from 75% in the previous year to over 95% in 2018 — a measurable shift on every programme globally.