In order to achieve results in a compressed time frame, many insurance organizations have moved away from traditional software development practices and towards the ‘Agile’ approach. This has been the norm, especially in the installation of modern administration systems.
Such has not been the case with data management — until recently. There are seeds sprouting out there which are challenging traditional approaches to implementing Master Data Management (MDM). Our question to you: Would a method for accelerating data management implementation in your organization help achieve business goals? Or is this a reprise of the bad old days of data definitions on the fly?
What is MDM, why you care and why you don’t have it …
One of the better business focused definitions of MDM we’ve seen comes from SearchDataManagement.com:
Master data management (MDM) is a comprehensive method of enabling an enterprise to link all of its critical data to one file, called a master file, that provides a common point of reference. When properly done, MDM streamlines data sharing among personnel and departments.
For many working marketers in insurance companies, this translates to: Nirvana. To be able to get all customer data combined with all policies and other activities is the portal to a state of profitable bliss. However, it is fair to say that like Siddhartha, most insurers have a tortured path to follow to get to MDM.
The traditional method of developing MDM prescribes a very disciplined approach which encompasses the entire organization, requires careful governance, and, as a result, gets very big. Failure rates are high.
What does Agile Data Management change?
Over the last 10 years, the world of software has moved away from the traditional ‘waterfall’ approach – a serial approach which requires complete finalization of one full set of tasks (e.g., ‘gather requirements’) before embarking on the next (e.g., ‘develop specifications’). The alternative approach is ‘Agile’ – which, according to Wikipedia, is “based on iterative and incremental development, where requirements and solutions evolve through collaboration between self-organizing, cross-functional teams.”
Scott Wambler, principal at Scott Wambler + Associates, has developed techniques and best practices to use the Agile method in implementation of data management. Wambler contends that like every other element of software development and delivery, data management can benefit from using iterative, test-driven methods espoused in the Agile methodology.
In addition to improving productivity and reducing errors, having Agile as a common development model “will enable IT professionals within your organization to work together effectively when it comes to the data aspects of software-based systems.”
Are Data different? Is Agile different?
Having data and software development linked takes some of us back to the bad old days when programmers developed data definitions ‘on the fly’. The emergence of data modeling as a discipline was a reaction to that. One principle was that managing data should be separate from software development to ensure data integrity.
This separation comes with increases in overhead. However, it brings much freedom when introducing new applications and supporting integration with internal and external applications.
One such application is Customer Relationship Management which, in the new world, is what the Marketers are looking for.
What do You think?
We’d like your thoughts. Could Agile be mature enough to support data modelling as well as programming? Or are Data requirements so different that the tried and true, albeit old, standards are necessary?
Get agile and leave your thoughts below.