Before I get to the “new” idea part of this post I think a little tech / business history is in order. The way business change happens I think, often is a repeat of a process or pattern from the past but applying new innovative concepts and technologies. If you look back to the evolution of the software that supported the widespread adoption of ERP (which was itself an evolution from the old MRP software in manufacturing) you can see a definite pattern. The systems, which often originated in manufacturing divisions, spread across finance, human resources, supply chain and eventually all across the enterprise, processing transactions and capturing mountains of data. The data itself was mostly trapped in silos that surrounded each department (and each department system) and although the ERP suites were integrated (in a transaction process way that is), data itself was compartmented. The implementation of ERP suites was generally accompanied by an effort to reengineer the business processes that the systems supported (which in effect was driven by the inflexibility and non-vertical specific nature of the ERP systems of the 1990’s). The reengineering was also accompanied by quite a bit of customization to the core software but that’s a part of the story for another post. The point is that at this point in history the ERP systems added value by tracking transactions around business processes and storing the data generated by each process. To move to the next step of evolution the ERP systems had to provide some way to get the data out of the silos and combine it in such a way that information was created. That information could then be used to support business decisions. At first this process involved creating custom reports to extract and “mash up” the data in predetermined ways. The daily sales report, weekly manufacturing summary, accounts receivable invoices outstanding, things like that. To go much beyond those static reports innovation was required, and in this case that innovation was data warehousing and analytics software. The data warehouse moved the transaction data offline or out of the production environment and into a repository that could support real-time data query without impacting performance of the transaction systems. On top of the warehouse software vendors started building analytic applications, data cubes, etc. Processes like enterprise performance management and key performance indicators rolled out of the large consulting firms and educational institutions. These all combined to form what we now know as the business intelligence markets (BI). Once organizations had BI tools in place the next logical step was to start using the BI output to make business decisions and eventually to automate some of these decisions (the ones with predictable outcomes) so that the emerging class of information workers could be freed up to handle exception processing and higher value decision making. (a now somewhat infamous example of this are the housing loan credit scoring systems that are now attributed by many to have contributed to the current housing crisis but again, thats a topic for another discussion).
A second example of this progression from transaction processing, data creation, analytics and decision support can be found in the evolution of Customer Relationship Management (CRM) software. CRM followed this progression exactly and in fact is often implemented in those exact phases. CRM is also the best example of continuing evolution with the emerging social CRM movement that starts to move into the e2.0 or social enterprise era.
So back to my new thought around the social enterprise change. What if the current business transformation follows the same path as ERP / BPE and CRM? One could argue that we have already created mountains of social data as a result of web 2.0 social networking, blogging, social bookmarking, and microblogging. After all one of the key principals of web 2.0 is transparency, which has lead to much more openness in our life “mash ups” that merge our personal and professional lives online. As businesses implement the use of social tools (or I should say continue to implement social tools, all businesses at least have email, even if it’s a consumer provided alternative like gmail or yahoo that has been generating social data for years). I’ve been thinking about how the social concepts and tools move into the enterprise and more importantly how we create scalable, enterprise class processes to support this. I also have said repeatedly that the key to success in the social enterprise is not in the technology but in the fundamental culture shift required to create a social enterprise. That said (I couldn’t resist getting on my culture shift soapbox one more time) we are creating the social transaction systems that mirror the previous system examples. Now enter Trampoline Systems and my conversation with Charles. The “ah ha” for me (which happened a day or so later) was that we are repeating the same path this time with the social enterprise shift and that to reach the ultimate goal we will need to create a whole new class of analytics. Trampoline has done this in one specific vertical, professional services, by building an analytics platform and applications that collect social data and provide insight to resource expertise and business networks at the individual and business / partner level…all very cool and you definitely have to see it to totally “get” what I’m saying. Now don’t get me wrong, the idea of social analytics brings up all sorts of new issues around privacy, network portability, network ownership, etc. that we will have to deal with. At this point of course we can just add them to the growing list of open issues like governance, regulatory compliance, data protection, openness and transparency, etc. that are popping up as challenges to the social enterprise. As history has shown we’ll work our way through those issues as we learn and grow through this business transformation cycle. It’s an exciting time but it is still the wild west at present as we struggle through through the changes and learn new ways of doing business and driving additional business value.