A well-constructed plan that is shared across the entire organization is a necessary starting point.
By Mark Gibson
Data analytics and data strategy are at the top of many banks’ agendas, and for good reason. Understanding your customer base through data allows you to refine your strategy and enhance customer satisfaction and profitability. However, many banks have found that it is easier said than done. They have spent years investing in expensive data sources and staff, without deriving the elusive benefit from the investment.
This article is the first in a series that illuminates a process for bankers, especially bank marketers, to build and harness a data strategy to enable more intelligent decisions, increase customer engagement and develop more productive acquisition programs. This article focuses on establishing a firm foundation—a well-conceived and useful data strategy.
What is a data strategy and why is it critical?
A common mistake, particularly for community banks, is to invest in buying data, in technology and in hiring analysts without having a data strategy. This is typically a recipe for costly disappointment. What exactly IS a data strategy and why is it so important?
A data strategy is a written plan that documents how your organization will use, manage and leverage its data to achieve its business objectives. Critical components of the strategy include data sources and acquisition; data quality; data storage and infrastructure; data usage; and data security and compliance.
Why is having an effective data strategy so important? It’s probably easier to highlight the common pitfalls of not having a well-defined data strategy:
- Data definitions are not clear and one department’s profitability reports do not match another department’s (aka: finance doesn’t believe marketing’s numbers).
- Departments such as marketing do not have access to customer data and need to wait in line sometimes for months to receive information from a central data or business intelligence team;
- Organizations purchase data from many different organizations, and it is not consistent, comparable, accessible, or useful.
- Organizations purchase analytics tools such as profitability systems but do not have quality data to feed into the system, creating a ‘garbage in, garbage out’ situation.
This list is certainly not exhaustive and each of us can add similar frustrating examples. Now that we understand what it is and how essential it is to move our business forward, let’s explore how to build your data strategy.
Important steps in building a bank’s data strategy
While there are many paths to achieve a successful data strategy, there are a few common steps an organization should take:
Begin with the end in mind—You want to make sure that business leaders agree on what they want the data strategy to achieve, and what success looks like. For instance: “We want a unified 360-degree-look at our customers so we know how valuable they are, and what other financial needs they have.”
Understand where you are—An essential step is taking an inventory of the data sources and data management tools your organization already has. One bank performed this analysis and found out it had five different CRMs using inconsistent data definitions that could not easily be consolidated. Identifying overlap and critical gaps is common and is the objective of this step. Banks will probably find they are paying for things they do not really need or are not even using.
Sample data tools and source inventory deliverable
Source: Capital Performance Group.
Agree on data management fundamentals—Sometimes called data governance, this step outlines who owns the data, how it is acquired and used, and how it is managed to ensure quality and consistency.
Ensure the data is secure—In this era of growing cyber threats, one of the most important steps is to understand the risks and establish robust security protocols to protect your customer data and ensure data is being stored and used in a manner consistent with bank regulations.
Determining data infrastructure—This is where the rubber meets the road, where you define your data structure which enables you to combine data from a variety of sources in a consistent manner, decide where the data is going to be stored (inside or outside the organization), determine your data analytics tools (and which are inside and outside), and ensure that each user group (such as marketing) has access to the information they need when they need it.
Establishing a data strategy can be, and often is, more complicated than this, but these are the essential steps that at a minimum should be included to effectively leverage customer data.
How to get started
The chief data officer is typically tasked with creating the data strategy in larger organizations, which creates another stumbling block for organizations that do not have someone in that position. However, that is no reason not to be able to create an effective and actionable data strategy.
The best approach is to establish a cross-departmental team consisting of both subject matter experts and critical users such as marketing and lines of business. This approach is essential to overcoming some common pitfalls, according to Jamie Clisham, VP, data and analytics manager at Machias Savings Bank. She adds: “Many teams can be lured by new shiny objects (new platforms and data sources) before fully exploring existing platforms for additional functionality, resulting in duplication and wasted expense. The importance of implementing a cross-functional team that engages in open and honest collaboration cannot be stressed enough to ensure that data and vendor investments are fully maximized and leveraged across the organization.”
The cross-departmental team is typically made up of:
- A project manager
- IT/Systems
- Data management and analytics (including business intelligence)
- Lines of business
- Other critical users such as marketing and finance
- Compliance and information security
It’s also essential for executive management to assign clear responsibility and authority for this team or committee to do whatever is necessary to make effective company-wide decisions to establish the best solution possible to accomplish the organization’s business objectives. This includes abandoning certain existing vendor contracts and pursuing others, as well as over-ruling entrenched programs a particular department may be advocating to continue on.
Finally, involve an outside subject matter expert if no team member has established a data strategy before, to provide necessary experience concerning available external data sources, insourcing vs. outsourcing various data infrastructure and analytics functions, best practices for data storage for your particular needs (data lake vs. data warehouse vs. customer data platform) and other essential decisions that will make the difference between an informed efficient solution and a sub-optimal one.
Pulling it all together
Today, it is a given that managing and leveraging customer data are essential for financial institutions. The question now is how to effectively do it. A well-constructed data strategy that is shared among the entire organization is a necessary starting point. This will provide marketing and other departments with the reliable and timely customer data they need to build engagement with customers at the individual level. The end result is happier customers, deeper relationships and more effective new customer acquisition programs. The next article in the series will explore the data analytics function, which is needed to transform customer data into usable insight to fuel business decision-making and intelligent marketing programs.
Mark Gibson is the marketing practice leader at Capital Performance Group, a strategic consulting firm that assists banks in leveraging data analytics to improve the productivity of their marketing efforts. He can also be reached on LinkedIn.
