There is a fact cited on the IBM Social Business web page that I found intriguing: The world now spends more than 110 billion minutes on social networks and blog sites per month. This equates to 22 percent of all time online―or one in every 4.5 minutes.
The page goes on to further describe three characteristics of a Social Business, which make great sense to me: ...
1. A Social Business is engaged—deeply connecting people, including customers, employees, and partners, to be involved in productive, efficient ways.
2. A Social Business is transparent—removing boundaries to information, experts and assets, helping people align every action to drive business results.
3. A Social Business is nimble—speeding up business with information and insight to anticipate and address evolving opportunities. Clearly social media is creating new information that can be harnessed in interesting new ways. A new breed of applications can harvest data, both structured and unstructured, to tackle exciting new business opportunities.
In 2012, we will look to apply aspects of social business to BPM and Decision processing. I can easily imagine using the “wisdom of the crowd” as input to a business rule. Social BPM can leverage several aspects of social technology. For example, trust and reputation are an important part of conducting business. Today, our BPM solutions “hard-code” these trust relationships. With Social BPM, trust & reputation can be explicitly represented and enforced at run time, and used directly in the business process as it progresses. The book “Social BPM: Work, Planning and Collaboration Under the Impact of Social Technology” does a great job of describing the art of the possible of Social business.
An important piece of social technology is the ability to go beyond monitoring social data and to start listening instead. You see, monitoring implies a passive action. If we’re monitoring, we watch for mentions of our brand for the purposes of acting in case our reputation is threatened. If we’re listening, we’re using that data for more aggressive action, for example, real-time event correlation and sentiment analysis in support of advanced decision processing. Our WebSphere Operational Decision Management platform will play an important role in the listening and acting on social data. We’ve recently added predictive modeling using our ILOG and SPSS technology, which will help us predict trends in our business based on this social data. Last, our work on 20/20 Analytics, where we use Big Data style processing of unstructured data for real-time query, will also play an important role. This will be another exciting space to watch evolve in 2012.