Do you have a data strategy?

When Alice wandered through Wonderland, she came to a crossroads and encountered a Cat. The following dialogue ensued between them: 'Can you tell me which way I ought to go?' Alice asked. 'That depends a good deal on where you want to get to,' said the Cat. 'I don't much care where,' said Alice. 'Then it doesn't matter which way you go.'

I often remind my clients of this passage when we work on various strategy-related topics. It illustrates a paradox. In our insurance companies, we are eager to create financial, sales, or marketing strategies. However, when we begin to discuss one of the most important current business assets – the gold of the 21st century, the new oil – data, we suddenly focus solely on immediate issues and the quickest paths to their resolution. Yet, data, like other crucial corporate assets, require the development of both data management and usage strategies. What constitutes such a strategy? It is based on describing four key elements.

Data

The first element of the mentioned strategy is to describe the data owned by our organization. In the strategy document itself, it is impossible to specify every data source and every table in detail. The key is to, first, catalog the existing data sources based on their type, the criticality of stored data, and the general characteristics of the information that can be sought in each source.

Second, it is important to establish a standard for documenting data in the organization: who, how, and with what tools should thoroughly describe each of the existing data sources and manage the updating of this information. In addition to source systems, presenting analytical systems, such as data warehouses or data lakes, in the same standard is essential.

Expectations

The second element of the strategy involves gathering business expectations: how we want to use the data we possess. It is best to gather such information during meetings with representatives from business departments and the IT department of our insurance company. The key in this step is to pay attention to three specific areas. The first, the most obvious, is the area of reporting and data analysis. The second, also obvious and currently trendy, is the area of process automation using data, utilizing technologies such as artificial intelligence.

The third area is the least obvious but can significantly improve the daily work of our employees. It involves providing data in places where they are needed as part of business processes. For instance, specialists in the Customer Service Office will find it much easier to work if they have all the necessary customer data on one or two screens rather than spread across five different applications.

Technology

The third element of the strategy is the technology for processing and using data. This element comes into play after gathering information about data sources and business expectations. Why is that? Because data technology should not be chosen based on current trends or misguided intuition. The technology must be chosen in such a way that the data we have can be optimally converted functionally, efficiently and cost-effectively into the information or decision we need for the business needs we describe. In other words - the choice of technology is to serve our business, not to reflect the marketing messages of IT market giants.

Quality

The final and crucial element of the data strategy is data quality management. This is crucial because every business initiative relying on data depends directly on data quality. It's what contributes to IT projects being delayed, exceeding their budgets, reducing the effectiveness of the solutions being built or, in extreme cases, even cancelling ongoing projects.

Data quality is based on two elements. The first is the data quality assurance process, which consists of the following stages: evaluating existing data, determining the expected level of data quality, implementing rules based on these considerations, and later monitoring data quality. The second element here is the allocation of roles and responsibilities for data management, both on the IT side and on the business owner side.

The Right Direction

Only when such a data management and usage strategy is constructed, comprising descriptions of source data, business expectations, technology, and methods to ensure data quality, does it become the basis for long-term planning and development of our insurance company as a data-driven organization. I know from experience that creating such a strategy requires a significant amount of work and dedication from the organization and its employees. However, this investment will pay off because it will prevent the loss of valuable resources and time on projects that do not bring us closer to our desired goals.

This article was published in 'Insurance Magazine' No. 4/2023