From a leadership perspective agency technology is complicated, confusing and expensive. In many agencies it can also be quite disappointing, requiring a fair amount of manual processing in order to create even the most basic reports. Outside of our agency walls we live in a world of easy access to even the most arcane information. Want to settle a debate over whether Alexander Hamilton was a US President? That debate can be settled in about 10 seconds from anywhere in the world with a Google search. The answer is quantitative information, a fact available through a simple data lookup. The magic is that you can type (or speak) only his name into your smartphone and receive a result showing the aggregated answer from multiple sources. With a quick scan of the results you’d find that he was in fact not a US President but the first Secretary of the Treasury.
Let’s translate this example to your agency and refine the question to this:
“Is Alexander Hamilton, Inc. a customer of our agency?”
It’s a simple question but for most agencies getting to the answer is not a simple proposition. Manually searching the P&C management system, the employee benefits system, the surety system, and the CRM system for the term “Alexander Hamilton” may not do the job. In addition your agency systems may not actually have a useable search function so you’d likely have to pore over customer lists while accounting for potential misspellings, creative naming conventions, archaic codes and the like. This manual processing intensive, unmanaged data scenario actually creates an environment where it’s hard to create even a yes or no answer with certainty:
“Is Alexander Hamilton, Inc. a customer of our agency?”
“Based on three hours of analysis I’m pretty sure the answer is no.”
It doesn’t have to be this way. While the complexity of individual lines of business and the limited choice of available transactional systems forces us to spread our data among multiple sources there are solutions that allow agencies to regain control over their data.
Data Warehouse to the Rescue
The concept of a data warehouse has been around for decades but has not seen widespread adoption in our industry. Simply put a data warehouse is a database designed and maintained by the agency that receives all of the key data from your different management and transactional systems. This central database can then be used to report and eventually provide analytics across the entire organization. By pulling all of your agency data together you can create an environment that allows for across the board reporting.
Motivated agencies can go further down the rabbit hole and build a query-capable dashboard. Type in an insured name and see a pre-defined overview of the customer showing current coverages across all lines of business, endorsement & claims activity, upcoming renewal actions, producer touch-points and relevant accounting information. Want more? Tie the dashboard into external sources of information like SEC filings, real-time web search on the customer or a feed from the press release section of the customer’s website. Did they just announce a significant expansion? It’s probably time for a visit.
But wait, there’s more! Now that you have a complete picture of the customer why not provide access to this dashboard to the customer? Your systems have compiled a unique view of their risk management that is unavailable to them through any other source. Share the love.
What is a Data Warehouse?
This part gets technical but don’t stop reading, we won’t go into the weeds here. From the perspective of your technology team a data warehouse encompasses fun terms like ETL, star schema and data federation. From the perspective of agency leadership a data warehouse represents a big project, a healthy price tag and probably some outside help. Most agency IT teams have a strong handle on computers, servers and networks. Very few have existing resources with a deep background on data structures and manipulation. It’s a different animal. Get some help on this one.
Like all technology projects a data warehouse will take a phased approach. Before you start you have to know where you want to go. Defining the end first allows your team to clearly identify what data points to collect from your various systems and more accurately design the warehouse database structure. Once the warehouse is designed the heavy lifting begins. The sole purpose of the data warehouse is to aggregate data from systems that were never designed to work together. Each originating system will require a different approach to pull the data out, normalize it and inject it into the warehouse. This process will take time so prepare to be patient. The results will reward the effort.
What about Data Analytics?
It’s a common mistake to use the terms Data Warehouse and Data Analytics interchangeably. While a data warehouse allows for the easy retrieval of quantitative information (how much premium do we have placed agency-wide with Chubb?) it does not provide qualitative information (based on current placement trends how can I restructure a program to provide a greater return?). Data analytics are the next level up. You will want to go there but take this one step at a time. Without a data warehouse your agency would struggle to make any sense of trending data. Start with the warehouse but keep an eye towards the horizon.