I recall a conversation (various really that led to it) but one specific recently with a Dynamics CRM partner about over-sharing, corporate knowledge creation and management in context of what they were building. I drew a diagram on the white-board and that is the basis of this post.

Rewind to the 90’s when Knowledge Management was top of mind and the biggest issue we were grappling was how to incentivize the creation of knowledge and the tools that would surface that knowledge at the most appropriate time.

Fast Forward to today: Incentive is no longer necessary, people are over-sharing, the question is are they sharing what is termed conversation or knowledge and this is where I will start splitting hairs.

The tools that facilitate over-sharing through your CRM (tools for ERP should arrive any day) tell you what is going on in the enterprise on the Corporate Telegraph. Posts like: a. “Jeremy just won an opportunity for 50 bicycles at Fabrikam” or b. “A new lead – Contoso for 200 gears was just created” or c. “Customer A is experiencing _____ issue with our product”. I chose these three examples because they represent Sales, Marketing (OK: result of a marketing campaign) and Service. The next thing I would like to analyze is the conversation(s) that might occur on these posts.

Meta points: We need to agree on a few of things first.

1.       That these items have relevance that is time bound i.e. as time goes on they are not as interesting.

2.       At some point in time, the conversation may become interesting, more people will converge on it, and then it will decay due to many different factors.

3.       Corporate systems will all but forget about these conversations and they will be relegated in some database which will be deemed non-searchable due to the loose nature of the conversation.

Now let’s analyze (a) where Jeremy just won the opportunity (this is one of many but realistic outcome).

There could be 10-15 congratulations messages, depending on what this opportunity represents. There could be motivational messages like “on to the next one”. There could be humorous comments like “hope you didn’t have to give the farm away for it”… you get the picture, and it’s highly likely that there could be questions like “they are a tough customer – how did you do it”. I’ll stop here and move to the next one.

(b) where a new lead was just created.

“Wow. Marketing came through on this one”… “They usually go with our competitor, which campaign did they come through”

(c) where the customer is having an issue.

“I also had a customer with a similar issue and they did ______”

OK. So what’s happening here? Amongst this conversation, knowledge that can be re-used is being created, and this knowledge is actually being thrown away in most circumstances. The diagram below represents my experiences in this context (open to suggestions from KM experts to alter/improve).

In the diagram above a topic goes through phases, if it is deemed relevant to the organization, it gains traction and if there is enough interest, active conversation ensues. Once the conversation starts to subside, summarization or understanding occurs in a similar manner as did interest generation. There are various points in the conversation cycle where knowledge is created and even fine-tuned but this knowledge is simply thrown away in most systems today. Imagine if it could be harnessed, stored and automatically surfaced in areas where it was relevant. Add to that rating and ranking tools to ensure that only the right knowledge set is surfaced in the right places and I think it starts looking like a self-tuning crowd-sourced knowledge management system.

Why not just index everything and provide search capabilities then simply let the users search through pages and pages of this stuff. I don’t think that is the answer since users will have to re-live the discovery of the content over and over again.

In my opinion the answer lies in taking this conversation, cleansing it, extracting knowledge and then surfacing it up at a relevant point(s) i.e. when there is a new opportunity for the same or similar customer. In the case of customer service, a possibility could be putting it in the knowledge base.

While publishing to the organization telegraph is definitely a plus and involves the entire company in a conversation, the signal to noise ratio is very low since there is virtually no cost to share and the speed of conversation might leave parties who would be interested out of the conversation. Therefore in my mind the clear winner here will be one who can take this data and produce meaningful analysis that can be perused at a later date when the relevance of the conversation has long subsided.