I was not able to attend Day 1, except remotely via the live stream. Today I'm in person at the Hynes Convention Center in Boston, my hometown and base for the Stanley Cup Champion Bruins (sorry, had to slip that in here somewhere).
Below are my notes for the first set of keynotes.
Lee Bryant of Headshift is first up.
"Social Business Intelligence: The Future of Listening"
He's talking about data-driven business improvement, the subject of a recent study by Andrew McAfee.
The term "Humanizing" the enterprise predates the term "Enterprise 2.0." All those using wikis, blogs and so forth are generating lots of data. How can this data be leveraged to help the business?
Some at this conference have already talked about "Big Data" "activity streams" "actionable insight" and mapping social activity to key business KPIs.
Social business is not just about direct collaboration with others. We're also interested in using signals and filters to share "ambient intelligence"
Lee's colleague Dave Gray is a "visual thinking" guru. He calls small teams with a high degree of autonomy "pods." Amazon is an example of pods. No team should be bigger than what you can feed with two pizzas.
Data is not just about aggregate measures, it's about specific insights into how teams behave.
We can leverage the analysis strategies that companies are using to look at consumer web behavior. The practice of social media monitoring in the past has been too narcissistic--"Do you love me" "Do you like my brand in this place" etc. We'll see a move to a more intelligence-driven approach. We should be looking at things the business can change.
People have been hiring "quants" primarily so far to "get people to click ads." This is not ideal.
Google person says that they have the data to predict divorce two years in advance based solely on spending (searching). It's not about showing off the size of your data (insert NY U.S. Congressional Representative joke here).
We can learn lessons for approaching data from sports. Two Red Sox championships were driven by "Moneyball." People are also starting to map soccer data. They track kilometers run "at top speed" versus "total amount run" because the former correlates with goals scored.
We need to immerse ourselves in the data. Insights too often stop at the marketing department, although they might not be in a position to make the changes required.
We need to move to machines that generate signals of key events, and pipe them around the organization, making sense of them with social analaysis.
Social analysis is applying "many eyes" to the data. How can we stimulate people to take action based on information derived from socially derived information.
Nothing motivates people more than feedback given in the course of the workflow.
He talked at a very abstract level. I wish there had been more concrete examples of social business intelligence and analysis in action.