There was a great ZDNet article by Scott Lawley from SAP that examined the business value of using enterprise social networking technology to rapidly find experts within an organization. Lawley made the point that sales and marketing people view online communities very differently and argued “online communities as they are today do not help sales reps close more deals.”

In order to understand what sales reps need from online communities, he examined the way sales reps work, their challenges and the limitations of current enterprise systems. He discovered sales reps spent 80% of their time out of the office, needed timely access to key information and readily accessible experts willing able to answer technical questions for customers.

In order to facilitate better access to experts, Lawley explored what an “expert” is and concluded they have the following qualities:

• Trustworthiness
• Extent of Knowledge
• Communications Skills
• Willingness to Help (Collaborative)
• Experience
• Currency of Knowledge
• Awareness of Other Resources

He then described an interesting use case for solving this “rapid expertise access issue” discussing how each of these dimensions could be pulled into a mobile device from a variety of sources like a corporate address book, CRM, HR, Twitter, LinkedIn, blogs, wikis, etc.

While each of these sources have value, there is one major missing source: data about the people doing the work (PDW). To add even more value, the mobile application needs to go a step further and tell the rep about the expert himself.

Using Analytics to find Experts Internally

Analytics Found the Expert, but What’s the Best Approach?

For example, when the data has already been gathered and the expert identified the chatty sales rep, excited he’s found an expert to answer a prospect’s questions, may unintentionally annoy the more subdued expert by stopping by his office when he prefers to communicate by email. If talent analytics were available as an additional data source when finding experts, the rep would know this about their expert ahead of time and could adjust their approach accordingly.

Using a People Finder which includes the talent analytics about the experts, a pre-calculated Talent Analytics collaboration score (a number) would be sent via API as one of the inputs to identify would-be experts. The analytics guide the rep to find the most collaborative person to ask for their expertise directly inside their mobile, enabling to quickly select and connect, know exactly how to approach the expert, perhaps resulting in a closed deal.

This is just one example of the power of embedded analytics-driven talent content inside a social enterprise application – and we’re warming up.

If the goal of  your enterprise social software is to encourage collaboration and productivity, having a mobile device similar to a People Finder with analytics-driven talent content may achieve the goal.

Differentiation is just an API away. Why not get started?

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet.

Mike Kennedy is a Technical Evangelist at Talent Analytics, Corp. He can be reached via mike@talentanalytics.com and @talentanalytics.