In previous articles on the state of data in the insurance industry , I've  explored how companies operate and where insurance companies are missing opportunities. While these efforts are important in the long run for the health of a company, it's also important to make sure that a businesses' current data infrastructure is fully up to date.

So, how does an insurance organization determine if it has the right data to support its growing needs? For many insurance organizations, the database is something that has not evolved in years. In fact, for many companies, the technology and the processes that are used for tracking clients are based on systems from the 1980s when policy systems were first being used to automate the insurance industry.

The continuity of a policy system can be beneficial for a company: It can provide a streamlined process for capturing information, become a single source of truth and can be easier to maintain. On the other hand, this single system that has not been updated can cause serious issues:

• Users can become complacent with entering data, meaning they are not diligent about updating new information about customers, such as Twitter handles and social connections.
• The data itself is never scrubbed or reviewed for accuracy.
• Due to uncorrected errors, the singular truth may not be the truth at all.
• It may not be able to leverage current technology for analytics or data mining.

When it's time to update the data warehouse

For some companies, a data warehouse overhaul may seem to be an unnecessary expense on the outset. While committing funds for a data warehouse overhaul may seem unnecessary, it's critical. But how can a company determine if it should update its entire data warehouse?

• Review the fields being tracked: The goal of any data warehouse is to track information about the company and its clients to make sure it can be analyzed. However, if a company has not reassessed which fields are deemed critical, it may not be capturing essential information that can help provide the customer with superior customer service.
• Scrub the list for errors and duplicates: Have you ever looked through contact list and found multiple entries for the same customer? If so, your database should be cleansed, meaning that all information must be verified and duplicates have to be removed. Without this step, the analysis of data might be wrong.
• Use business intelligence software to analyze patterns: For some data, analysis software cannot be used, possibly because the fields are not uniform, lack of structured data or because the data file is not accessible. Regardless, this means that the data warehouse needs a thorough review to ensure it is as effective as possible.

Data analysis is relatively new in relation to business, but does provide significant advantages if it's implemented correctly. Data analysis can provide the detail companies need to ensure the right customer gets the right offering at the right time so that the insurance company gets the best opportunity with each customer.