How to build your organization’s data analytic proficiency; Part Three.
Data and data analytics is more than just a resource for reporting and decision-making support. Rather than succumbing to the weight of a new business model, financial institutions have an opportunity to create a timely strategy to take part in the global digital ecosystem and uncover the many hidden benefits of centering data and analytics in strategic planning and investment.
For financial institutions that cannot immediately participate in the data economy, there are still opportunities to play a critical role. How will you participate? Take a look at the remaining steps for banks and credit unions to create a competitive strategy now. These steps will provide insight to assess whether new business units, joint ventures, and/or acquisitions will be required.
1. An enterprise approach to using data analytics is key.
The tone at the top should drive expectations for data use. Consistent reinforcement from the C-Suite sets the objectives of the culture. Data strategies and expectations for data use will need to be communicated and prioritized by the bank’s leaders. Inconsistent, siloed use of data could jeopardize the desired culture.
2. Personalize marketing and sales efforts.
Once you have data in an actionable format, relevant customer information can be used in targeted and personalized interactions – increasing the value of both the interaction as well as the transaction. High-touch sales are a reality using this strategy and sales efforts will become more meaningful when personalized.
3. Train sales personnel on how to use the information once it is provided to them.
Supplying sales personnel with multiple reports or turning on a data analytics tool is only one step in the process. Assess your bank’s sales environment and provide training consistent with your culture to ensure the enterprise can be unified to embrace data and understand how to use the information effectively.
4. If current resources and capabilities are insufficient, partner with a third-party to supplement. The idea is to limit the staffing resources required to meet your data analytical goals. Build a relationship with a provider that understands your organization and strategic ambitions so that the solution is tailored to your unique circumstances and environment. There will be compromises between complexity and accessibility: More complex software may require additional resources and staff to deploy and fully utilize. Pair this partnership with an internal champion and subject-matter expert to create the most bang for your buck.
Community financial institutions cannot afford to remain on the sidelines. As the volume, velocity, and variety of data grow daily, the tools needed to manage and master all available data will require more time and investment. If executives understand their needs and the realistic bounds of their organizations’ analytical capabilities, proper planning can move their organization forward to better use the valuable cache of data that is only available to them and fully participate in the growing data economy.
