Following on yesterday post it is clear that the explosion of knowledge has created challenges to both individuals and companies.
A single individual is seen is hard won competence losing value as time goes by, at an ever faster pace. Keeping on learning to make up for the lost knowledge and working at the same time is getting tougher and tougher and in many areas it wouldn’t even work. By the time a medical doctor has finished reading an article on the leading edge of medicine in his very specific field over 10 more articles will have been published on that topic, superseding the knowledge he has just acquired.
A company is facing a double dilemma: hiring new people fresh from study, since their knowledge is more up-to-date then the one of people inside the company (see the Gartner press release on the topic) letting go the obsolete employees (and losing the bit of experience they have gained inside the company)? Getting and relying on up-to-date people only to discovered that in a short while they quit to join another company because their knowledge has strong market value?
The truth is that a successful company needs smart and up-to-date people but it cannot rely on them. Were it to do so the company would collapse when those people decide to camp on some other turf.
Companies need to “extract” knowledge from their employees, from their partners and institutionalise that knowledge in the company processes, something that remain with the company and that cannot be stolen from it.
The web of connections, both at individual and company level, connecting a person, or a business, to the knowledge needed, as it is needed, is the most important asset in the future (and it is starting to be very much relevant today).
Of course once you design such a connection web you have to take cost and efficiency into account. Hence the question: where is knowledge to be “stored”? Which knowledge should be owned? Which one should be up-to-date?
It might well be that the answer to these questions is not to update the knowledge of the employees, rather to rely on machines to become reservoir of updated knowledge. Employees need to learn how to use that knowledge and be aware when they need to access the knowledge base.
Now, this is interesting. If knowledge keeps growing at a fast pace it gets difficult for a person to know when to check for updates that are relevant to the problem at end. One would risk drowning in the overflow of information. Here is where the technology of digital twin may come handy.
A digital twin is a soft (digital) entity mirroring a physical entity. We can imagine (and create) a digital twin to represent the knowledge space of a person, an employee. As this knowledge space grows, because of working experiences, training courses, attended conferences so does the digital twin knowledge space grow.
A digital twin, differently from the real, physical twin, does not have time limitation, it is only limited by the computation capability that today are huge. Hence, that digital twin, in the cyberspace can connect to the digital twin of the project that will have to be developed and understand the possible knowledge gap. An intelligent knowledge manager (a software program) can then evaluate where the missing competence is and what would be the more efficient way to make use of it: train the employee, hire a temp, subcontract a part of the project, have a machine taking over?
In any case, that knowledge manager can in a blink of an eye assess what is the latest useful knowledge and use that accordingly.
This might seem a bit futuristic, but first steps in this direction have already been taken.
The Symbiotic Autonomous System Initiative is discussing these issues in the new White Paper due in November 2018 (I’ll let you know when it will be available) and will be discussing these aspects at the coming Workshop in conjunction with TTM 2018 (try to be there and contribute!).