Smart asynchronous Meetings and Knowhow Networks
In the previous two articles we initially described the observed unfavorable status quo that limits performance. Then we depicted a desirable vision for operational knowhow workflows and organizational overview. You can read into these thoughts here: Status Quo + Vision.
What has previously been left out was what needs to be done to put this vision into practice. We are going to elaborate on this here.
Smart asynchronous Meetings
Those employees that are sought out to add value to current topics are busy. Therefore, inquiries need to happen on their terms, next to their daily business and at no unnecessary efforts for them. They need a relief through less fixed meetings. Also they need to be empowered to manage their time and contributions by themselves, yet still be able to synergize. Smart asynchronous Meetings enable that.
Focus is achieved through automatic prioritization directly within the meetings. By that time is available to give thoughtful as opposed to on-the-spot answers. Synergies across functional and language barriers can further be enhanced through freedom of contributions and real time translation. Thus the opportunity to include international experts at lower barriers of entry is given.
A solution needs to be as simple as possible. Employees should only need to fulfill two expectations: Provide their impulses once they arise and participate as experts once they are called upon. For this, as discussed above, a solution should make their current business life easier. Synergies from human intelligence are optimized whereas arduous complexities are taken care of by algorithms in the background.
No one has time or energy to manually document. Thus it is no surprise that databases are usually more dead than alive. Therefore, documentation needs to be an automized byproduct of a living workflow. The most important results should continuously and intelligently be filtered out and finally be presented in automated reports. To ensure overview, managers need to be empowered to advance topics further and round off topics by formulating a final conclusion for the participants.
Create a Know How and Expert Network
Self-learning algorithms should create automated expert networks of employees, based on their qualitative contributions. These should change dynamically throughout usage and build the basis for prediction models. These directly recommend experts within the organization based on expected likelihood of valuable contributions to the topic at hand. Even if a company culture might hinder knowledge sharing across silos due to internal competition, others can still profit from their knowledge. Lessons Learned should always be collected and intelligently linked across silos, locations, and language barriers. By that they can offer value to newly upcoming causes.