Tools for Know-How Transfer
Transferring Know-How of a Retiring Expert at Scale
2020 will be a record year in retirement numbers for industrial organizations across DACH and the US.
It all started with the Baby Boom after 2nd World War: A whole generation surpassing the age of 67 until 2028.
Age Source: CIA World Factbook
Industrial manufacturers face a challenge having to replace up to 50% of their organization within the next 8 years: This means up to 1 years of know-how loss every day per 200-500 employees employed if you’re working for an "old economy" organization.
Note: We've carefully estimated based on the information we have
In combination with the lack of new workers to hire, the estimated economical damage sums over USD 3 Trillion just in the United States in the next 8 years according to a study by Deloitte and the Manufacturing Institute in 2018. By taking income per employee difference, amount of workers employed and calculating, our combined outcome for DACH and US summed up opportunity loss and damage lies at USD 6.16 Trillion.
Not only is retirement age for many individuals either too late or too early, the size of the pension usually also doesn't match the expectations of the retiree. To capture an opportunity for both parties of employer and employee, post-retirement programs can be developed. Such a program allows the retiree to support her/his organization with a couple of hours of work every week while the employer benefits from decades of expertise.
Post-retirement programs of part-time jobs for the ex-employees are planned to reduce the incoming disappearance of operating certain areas of ones organization. Intergenerational knowledge-gaps can be closed.
The most commonly used example lies in Live-remote calls where retirees can work from home and be "onsite" through remote systems.
Organizations are already using similar mechanisms between younger and older employees. Such post-retirement program would amplify existing the effect.
The chart shows program to retain an employee over the age of retirement, assuming the commitment decreases over time based on personal well-being and capabilities. Departments integrating such programs require an onboarding to the new process system which would reduce available know-how in the immediate period before the day of exit.
However, the stretch has its limits.
Our conclusion here would be to start thinking of knowledge capturing and storing mechanisms for timeless retreival.
Remotely being able to see what the other one sees
Without live connection, the flexibility of information access could be achieved.
The Know-How challenge
In case of knowledge transfer known as "instructor led training" or "coaching" both trainer and trainee spend their time synchronizing knowledge.
→ Organizations decrease revenue by pulling workers out of day-to-day work for a longer period of time for training, especially if this training is ineffective and has to be repeated
→ Opportunity costs of workers being trained effects the "time-to-readiness" key performance indicator, an important metric in ramp-up phases and onboardings.
→ The effectiveness of know-how transfer depends purely on the method. Schooling teams for 1 hour with no significant results in long-term memorization (retention) is fatal
What is Know-How?
The Problem with Know-How is, it can range from problem diagnosis, tacit understanding and many more skills that come by experience. It's typically not the surface level knowledge inside of a manual.
An expert car mechanic and his trainee would both be able to replace the same part, maybe even in a similar time, but it’s the expert who would need only 1 minute to diagnose the problem while the trainee would be clueless and not able to tell you what’s wrong, or even worse just fixing the consequence of a problem with deeper roots. The expert has deeper understanding.
The junior mechanic is capable of recognizing a broken ignition coil from his monitoring device and then proceed to replace it. The expert may identify the root of the problem, for example a coolant leak caused by a rusty intake manifold.
The cause, but not the root
In applied medicine, doctors at hospitals and decades of experience apply a method they call „differential diagnosis“ which is simplified an experience based „intuition“ applied when simple „decision trees“ don’t apply.
In software engineering, developers spend days trying to fix software bugs, often with baby steps of identifying why things are not working. Over time they learn where to apply the debugger and where to look for as a logical analysis and interestingly also tap into collective intelligence and swarm intelligence via platforms like stackoverflow to save time and unnecessary memorization. The challenges being comparable to the doctor or car mechanic.
Every profession has its experts and the magical way they work.
Tools for Knowledge Transfer
So how can we create tools for the upcoming challenges of
→ Lack of new employees → Identifying which knowledge needs to be saved and in which form → Increased complexity and required flexibility in the work place → Storing Knowledge without binding people to a live-call
One of the answers lies in improving knowledge transfer. Industrial organizations have much of their knowledge stored in deprecated data formats like 2D documents, even for knowledge and know-how in the third dimension.
Our mission at AUCTA is helping industrial companies harness the power of their data, to create and deploy 3D instructions anywhere, on any device.
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Last Updated on Sep 8, 9:20 PM.