This major consulting firm has the enviable problem of having every possible desirable expertise somewhere within their ranks of 300,000 employees, and the unenviable problem of trying to find those needles in such a gigantic haystack.
It’s not that they are unaware of the problem. They have launched many projects over the years to address this, some of which cost hundreds of millions of dollars (and a problem easily worth this much to solve, but very small increases in chargeability or win rates on proposals as a result are worth that on an annual basis).
We built an ontology to integrate projects and proposals around skills and proficiency. We have harvested as much as is known about current employees in terms of skills and proficiency (and we are beginning to get subcontractors and partners), but we know that this information is not being kept up to date. We are at the early stages of two more initiatives, one that will nudge people to update their profiles when it becomes known that there is demand in a particular area; the other, to combine externally available information with this primarily internally sourced graph.
The other side of this project is to replace the game of telephone that is currently the primary way to find key people in the firm. Currently, senior staff or partners rely on their network to find experts. Junior people are more often left out. In either case the process is quite haphazard as each request gets forwarded on to another subset of the network. There is a great deal of reluctance to “spam” their internal network, but there is also the need to find the right people as rapidly as possible.
We have built an early prototype model with the vision that a chat based service will leverage the graph network, but keep track of the results, such that over time the requests will get smarter, smaller, and resolve faster.