Many times a technology adoption discussion starts out with a question around why an insurer should adopt a specific technology. That’s a good question. But maybe the more telling question is – what happens if you don’t adopt one? It’s a pessimistic approach to technology adoption, perhaps, but it is important to assess the implications of not adopting specific technologies. When it comes to business intelligence tools and data warehouse modernization, there are some very serious downsides to not putting these critical components of an enterprise data strategy first.
Data strategy as a precedent to a core technology initiative.
SMA research shows that 53% of insurers believe that establishing a data strategy should precede a core technology initiative. That still leaves a good percentage of insurers who see it differently. And simply believing that establishing your data strategy first is the right way to go, doesn’t mean that executing it is easy. However, insurers who put off data strategies until after core system choices have been made actually run the risk of choosing the wrong provider (architecturally) relative to a data and warehouse strategy that will work best for the organization.
Legacy data migration to modern technology.
The endeavor of migrating legacy data to modern technology is no easy task for information technology (IT) and business leaders. The sheer magnitude of conducting a legacy data migration has led many insurers to decide to leave legacy data alone, resulting in a myriad of work-arounds. This potentially leads to poor service for both customers and distributors. It also leads to a great deal of added expense and employees who are frustrated by having to deal with work-arounds. A solid data strategy with business intelligence (BI) tools and a modern data warehouse makes the migration of legacy data into the new systems significantly easier.
Analytics tell the greater story.
Business leaders are clamoring for analytics. Most of the technology demonstrations that we see at SMA address or at least mention the value of analytics. However, without a data strategy, there may be a disconnect between the data architecture and the data structures decided upon in a later data initiative. In the era of BI, analytics has taken on a new meaning. Through data warehousing, we now have the capability to dive into the complex relationship of diverse data points and understand not just what the data is telling us, but also, what the relationships between the data points can illuminate.
The value of unified data.
Many insurers have accelerated core modernization initiatives because of the pressing need for modern portals and expanded mobile capabilities. However, if customer and distributor data is still fragmented, not centralized in a modern data warehouse, and not unified with a common data strategy, the full value of portals and mobile will not be attained. Insurers should consider potential ramifications of not fully delivering in these areas.
The importance of business intelligence tools.
Across a whole host of technology categories, software with out-of-the-box reporting tools is fairly common. On the surface, this seems to solve a lot of problems. However, while technology-specific reporting tools have value, without an enterprise BI reporting tool, an insurer can be creating reporting siloes. Additionally, while software-specific reporting tools may be useful for a specific category of data, such as operational data (which can be very good), they may not be what insurers need to gain deep insights into all categories of data.
This blog was prepared by SMA for the exclusive use of S&P Global Market Intelligence. The views and opinions expressed by SMA do not necessarily reflect those of S&P Global Market Intelligence. SMA is not an affiliate of S&P Global Market Intelligence.