Client name: A retail financial services group

Our client's strategy is to increase revenues by cross-selling retail banking and insurance products to its customer base. The two product lines are currently managed independently. Delivering the strategy involves a major organisational change programme plus substantial changes in underlying technology platforms.

The client's business needs cover a variety of different functions. The marketing team needs a single customer view as the basis for better campaigning. The financial team is looking for improved business intelligence for financial reporting and the risk team require a consolidated view of customer risk. The technology solution for these various needs is a centralised data warehouse, containing the group's customer and product data. This solution is under construction.

In the past, the group's understanding of its customer and product performance has suffered from underlying problems in data quality. The key business challenge now is to engineer high data quality into the new warehouse and then to maintain it over the warehouse's lifetime.

We were engaged by the client as advisors to address these data quality challenges. Our work began by agreeing a new data governance strategy with the group. The strategy covers issues such as:

The second part of our work was to implement a series of quick wins from the strategy. These included, for example, rationalising the number of sources of data and cleansing specific existing data sets. We also implemented a simple and cost-efficient MIS (Management Information System) interface to enable our client to monitor data quality on a continuous basis.

In addition to the benefits of the cross-selling project itself, the data quality work is leading to substantial benefits for the client. A key area is a reduction in costs of data cleansing, which has traditionally been done manually. The improvement in data quality has also reduced marketing costs by ensuring more accurate targeting and improved campaign response.