Final session of the conference, and I’m in the financial services breakout track to hear Lee Atkinson, SVP at iDNA, and Marc Hebert, CMO of Virtusa, discuss a real-world example of using enterprise search to build a true 360-degree customer view. They started with some background on the problems with enterprise applications and how dynamic business applications (Forrester’s term for composite applications; he’s quoting from a Forrester report) are starting to take on some of the functionality. Enterprise search applications provide a layer on top of the enterprise applications, files and databases to create search solutions such as corporate search or intelligence solutions. They see enterprise search as a key enabler of dynamic business applications in order to provide both speed and agility of those applications.
The case study that they presented is the implementation of enterprise search in a top ten global bank, providing fast retrieval of structured and unstructured data, and integration with business process management (not a term that I expected to hear at this conference!) to manage events being generated by the system. Their technology platform included enterprise search, BPM, SOA and enterprise portals, and they addressed the 360-degree customer view and a GRC (governance, risk and compliance) event management system. They didn’t use search because of its inherent properties — in fact, the users don’t even see this as a search application, and the applications look like standard structured data extracted from operational systems — they use it to extract information quickly from heterogeneous data sources. Prior to this, the bank had point solutions, multiple data warehouses, and no commonality between systems and databases to provide any sort of consolidated customer view. They needed to integrate data from multiple sources, and also meet their compliance regulations.
They started by providing a compliance and risk view, plus product and customer profiling, in 2005, then expanded to include event-driven business processes and exception management in 2006. In 2007, they brought in the single customer view and more advanced business processes and analysis. Of course, there is no such thing as a single view of a customer in a large organization: different business areas (compliance, operations) have different needs, and each user type’s customized view of a customer is actually a subset of the entire customer model, with other supplementary information pulled in and additional analysis added appropriate to the task at hand. The result is a number of different end-to-end processes, such as know-your-client, anti-money laundering and sanction lists in account opening.
For them, search technology is a way to integrate legacy systems — not an application that I thought of when I considered search — although it requires a deep knowledge of the business domain and the nature of the underlying data. Once the core integration structure has been created, additional data sets and applications can be added quickly and at a fairly low cost. The focus on event-driven business applications based on search results is where search really contributes value to their applications.
This appears to be an attempt to deal with perennial adoption problem – people like to communicate using unformalized data supported by email and wiki technologies, while CRM applications need normalized data to process into meaningful information to support business process. The root of this problem is the desire to gain great value of 360-degree visibility at a minimum of user keystrokes, which in my opinion is not a technological issue, but a change management one.
I’m not sure that I understand why you would characterize this as a change management issue. The difficulty in many cases is that the technology is only geared to displaying structured data (e.g., within a CRM system), and there are many unstructured data sources about a customer within any company. Search technology such as was applied in this case study can locate and present the unstructured data as if it were structured data, which is in many cases the format required for a user’s needs.