In this competitive and data-driven world, there are more possibilities for credit unions to leverage the personal relationships with members that have helped them in achieving a high success rate over other competitors in the market. Keeping a check with the members’ data can provide CUs with the deep member understanding they need to flourish their relations.

Institutions that are harnessing the value of data are successful in gaining a deeper understanding of their memberships’ trends, purchasing influences, and behavior. This knowledge of data-centric operations is leading to improved financial performance, long-lasting member relationships, reduced risks, and greater member loyalty.

At CULytics’s Virtual 2021 summit, Amanda Paleta shared her experience at RBFCU. She has been serving RBFCU as a Metadata Analyst for 20+ years. Here are key points that are worth reading:

Bring data house in-order: Realize the requirement

There was heavy dependence on data for reporting. When someone asked for a specific aspect of data, it was realized that either data was not correct or it didn’t lead in the correct direction. This forced the team to go back and re-tweak the approach to get the final and correct result. As a solution, a strategy was prepared to ensure the accuracy and consistency of data, and every individual in the organization should have the same idea about the data elements. And, it was realized to put a brake on artificial intelligence and predictive analysis as it is not possible to reach the right goal if the right information is not provided. So, it is important to analyze and identify the data-related foundational requirements.

Role of Analytics: To be successful

It is important to check everything after the fact to understand the mistakes and areas that need to be improved. Also, try to understand how these were handled in past and what measures are required to be taken to not repeat them in the future. As a solution, it was realized that a proactive approach is required to eliminate the barriers. Other parameters were forecasting- what is coming, analyzing the market during Covid-19 and a new way of life for both an organization and members at present, after 6 months or a year. It is important to make a strategy and work on analytics to serve the best to the members in the future.

Data Organization: Culture Shift and Mindset Shift

It is vital to realize that data is everywhere; like in– different systems, spreadsheets, as a piece of information in people’s minds. And the requirement is to maintain this data at one central location. While organizing data, one thing that should be in mind is to not miss data at any point and do not keep any bad data. This data can be used to exponentially grow analytical and reporting power. Not just this, an organized data can help in analyzing the trends and make useful decisions.

Prioritization: What needs to be Looked at First?

It is not always known, what the best approach is. So, flexibility towards making amendments in actions is the key to achieve better outcomes. Working on current issues, clarify data-related issues, clean them up across the business can be helpful in building a solid foundation.

Used Case Scenario: Multiple outcomes and activations

The definition of one element varies from department to department. For example - Loan officers have different roles for different work scenarios. Business lending is defined differently than mortgage and consumer lending. So while doing conversations with officers, it might be difficult to figure out the right answer and to understand why analytics is not working. So, as a solution, one simple report was prepared for overall management but it was realized that there are terminologies that are unified and cleaned up in each of the lending areas and this affects the frontline staff and branches to do their work effectively.

Data Governance: A part of a revolution

If the steps are not taken in the right order, the right answer will not be attained. Keeping things recorded and in order is a must to move forward towards the set organizational goals. With the new regulations and compliances coming on board, data governance will be able to tell where the data came from, what it means, how it’s been used, what the intent behind it is. The regulators can see it and make a decision accordingly.

Predictive Analytics: It’s important, not mandatory

Every organization has different ways of working and serving its members. With predictive models, it becomes easier to understand to know the members’ needs and fulfill them. If it is not around, sometimes; members might be served with what they don’t need. So it is important, to know the members’ behavior, buying habits, etc.

Communication: That can’t be ignored

Communication should be at the core so that there is a successful execution of the operation. During Covid-19, many people are working from home. So, maintaining some resources, which can assist the staff in solving their doubts and queries, will be beneficial to improve the work efficiency. Techniques like Power BI can be used for this.

Due to covid-19, member behavior has significantly changed. They are experiencing much more digital engagement and expecting it. As a credit union, an organization has to show that it knows them better than any other company out there. So, strategies are very important in today’s competitive environment.

So, these were the approaches on which RBFCU worked during their data transformation journey. Strategy based approach is a must to entertain the requirements of members. For effective functionality, make flexibility, in operations, a norm. Data is important for the organization as well as member experience. Understand the organizational goals- long term and short term – and ease your data transformation journey.

Checkout the full discussion here.