In the 16th century, Sir Francis Bacon remarked that “knowledge is power”. Certainly those sentiments ring true today. Unlike the 16th century, when acquiring knowledge was primarily an effort around acquiring data, today’s issue is sifting through tremendous amounts of data to “connect-the-dots” and turn data into intelligence. While the sheer volume of data itself presents a tremendous challenge, so too does the process of collecting, organizing, and accessing the data in a timely fashion.
A recent National Underwriter Survey (November 5, 2012) points out just how challenging this is to producers. One respondent wrote “Carriers could make policy, claims, and financial data more accessible…all the data…should be available at any time, to anyone.” How pervasive is this opinion? 21% of all respondents said that no carrier websites are useful to them. Does that mean that one fifth of IT spend on carrier websites is completely useless in the eyes of the customer? Ouch.
What is the solution to the challenge? First and foremost, we need to understand that data is not the product of our industry but the lifeblood. As such, we need to bring a data-centric perspective to our businesses in order to build processes and implement systems designed to capture the key data elements, ensure data quality, automate the flow of data, and make the data accessible to the business people with the speed necessitated by the business cycle.
Too often, we take a systems-oriented approach. Companies break their business processes into discrete pieces (CRM, Underwriting, Policy Issuance, Billing, Claims Management, etc.) and seek out technology solutions to automate those discrete functions. However, these “islands of automation” don’t really solve the challenges; they just transfer them to the next level. A business isn’t successful because discrete business processes work well; success is based on the entire business ecosystem working well.
A data-centric approach asks the following questions:
- What are the key business metrics needed to outperform the market?
- In what timeframe are those metrics needed?
- What are the data elements which comprise those metrics?
- Where do I obtain those data elements?
- How do I architect systems/solutions to capture those data elements, create the metrics, and make them available to the business in a timely fashion?
It’s this last question I want to focus on in a little more detail. Notice I didn’t ask the question about how to “deliver” the metrics to the business. Delivering the metrics in a series of reports presupposes two things. First, the business is able to see into the crystal ball and create a finite list of reports needed to run the business, and second, the IT team will fully understand those requirements and push reports to the business. In my experience, reality doesn’t conform to this paradigm.
Of course, there are standard reports in our industry which are used to measure results. However, any report worth producing is simply going to create more questions. In addition, different constituencies inside the business need to view the metrics through different lenses. Finally, there will always be the element of “I’ll know what I need when I see it.” For these reasons, counting on the business to pre-define reporting needs simply creates a situation of every-increasing numbers of reports until the corpus of reports itself is unwieldy and confusing.
This paradigm also places the burden of understanding the spirit of the business requirements, to include the logical follow-on questions, in the hands of an IT staff to which most of the intricacies of the business are lost. Good luck with that. Pulling this all together, not only do we need to take a data-oriented approach, we need to provide a mechanism for the business to interact with the data/metrics in business-time without relying on the IT staff to “build a report”.
Our ability to compete, and win, in the 21st century increasingly hinges on our ability to make better business decisions, faster than the competition. In order to accomplish this we need to embrace the concept that data is not a by-product of our work, it is the essence of our work. As such, we must take a data-centric view of our business processes and our systems and architect both with the end in mind.
