The tipping point: Could technology save your talent?
Organisations seem consumed with the idea of collaboration (knowledge sharing), but research has demonstrated that collaboration usually means more work and lower levels of satisfaction for your "go to " people (e.g. see HBR, Jan/Feb 2016 "Collaboration overload").
What happens is that your "go to" people (super collaborators/users - the people with answers to questions) experience overload and end up reaching a tipping point (demand overwhelms supply) where sustained pressure from dealing with overwhelming demand drives them to leave the organisation. Of greater concern is the damage caused in the run up to this tipping point, where super collaborators can become so disaffected that they end up polluting their network with negativity, encouraging disengagement.
We did a small piece of research to demonstrate just how valuable time is to people and how inefficient/ineffective practice (people and/or technology-led) can impact work-life-balance. Looking at the table below, select your salary band and ask yourself, if you were/are a super collaborator, a "go to" person or information, where would be/is your tipping point (based on remuneration, hours worked and impact upon perceptions of value) and what are the consequences?
This is where we have been helping organisations to understand the problems of knowledge sharing cultures anddevelop higher levels of performance through technology. You could begin to do this yourself, just start with three basic questions and actions:
1. Do you know who your key nodes (super collaborators/"go to" people) are? Conduct a network analysis to determine the load upon your key nodes. (Super collaborators) 2. Have you explored how they collaborate? Analyse the types of questions the super collaborators get asked - remember, questions drive solutions (see our Q&A gap analysis framework below) 3. Could you substitute the person for technology to relieve demand? Check for efficiency/effectiveness/quality/cost implications via a technology audit.
The bottom line, we work in a talent-led knowledge economy. Your top talent (super collaborators) only have a finite amount of time (supply). Could technology save your talent and enhance your knowledge capability?
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