Data affects almost all functions of a Credit Union. Some functions might depend on analytics more than others. In this article, we will discuss such opportunities and challenges which can incur within an organization. We will discuss questions like –

• What are the major challenges that lead to the need for data warehouses?
• What are the evaluation factors that help to determine the same?
• What are the things that people should look out for while investing in data management capabilities?

We have taken insights from Sound Credit Union, STCU, St.Mary’s Bank Credit Union, and Our Community Credit Union. These credit Unions although have distinct data analytics teams and structures, have provided useful insights that are presented below.

What is the motivation for Credit Unions behind investing in data warehouses?

Each Credit Union has its own set of objectives and a plan for how it wishes to achieve the results through the available data. In our discussion, we observed the following motivations -

1. Having a dynamic approach and considering how it will help all departments. Example- It can mean quick wins for the lending and operations department. Finding value for each department is the right approach that pays off.
2. Want to see a 360-degree view of members and compile different data resources. Finance and lending departments are departments that have been using and benefitting the most.
3. Being prompt in operational reporting. Building on quick wins through strategic moves.

What is the Approach to investing in these data management solutions?

When Credit Unions decide to invest in data management solutions, how do they want to execute their systems and processes? We have listed below some popular approaches.

1. Building Extract, Transform, and Load side of the data, with an intention to do things out of the box.
2. Providing custom-built solutions, and being a little more self-reliant by having in-house capabilities.
3. Having consistency in networking for example- Sharing reports within and outside the organization.
4. Obtaining automation and self-serving functions.

Relevance of Type of Data in a data warehouse-

What is more important, to have all the relevant data or to make it easier to plug in new data?

It is true that all data in the data warehouse might not be used, but it is important to not leave out any important data. One useful way is to divide data into data sets according to the categories you know will help you out the most. It is crucial to a data warehouse that data can be plugged in through different resources and made readily available and accessible as and when required

What are the considerations and criteria of Credit Unions while choosing a data warehouse? 

Based on the motivations and approaches of the credit union, it will have a set of considerations to pick out the most relevant software. Here are some popular considerations-

1. Pulling data into the data warehouse from different resources should be timely and efficient.
2. Defining resources and capabilities which you need in the organization and syncing these resources and capabilities in the data warehouse.
3. The ability of users to self-serve on a certain level and standards. The team having insights into meaningful information which is not obvious is an important consideration.
4. Having an easy user interface.
5. Data Warehouse should not compromise on data quality and provide functional data governance features.

Some of the best use cases of data in data warehouses- We discussed events where the Credit Unions feel they have benefitted the most from investing in data warehouses, which are mentioned below for you to be able to gain insights.

1. Recognizing members who were being laid off, calculating the impact on members, and organizing community outreach within three days.
2. Tracking stimulus money, unemployment benefits, asset sizes, and being able to generate a report showing the details of every member using such benefits, their loans, payments, etc., and reaching out to such members.
3. Releasing funds for good standing members, through having access to all data and intelligent insights.

Biggest Challenges and Obstacles faced in this journey.-

Data governance and implementation of data warehousing solutions is a long and often cumbersome journey. Here are some challenges and obstacles that the above-mentioned credit unions faced.

1. Creating cultural change within the organization and getting every department to trust the data. To make this cultural shift, one approach which can be made is to give the users exactly what they want and help them build on strategic efficiencies.
2. The use is restricted to operational functioning and not spreading as swiftly in other departments. This can be pushed through by encouraging the presence of the right guiding questions.
3. Challenge of the traditional thought processes. This obstacle can be removed by asking the question - ‘What you don't know today, that if you knew, would help you and your team to perform better?’ And then, providing this accurate, timely data to stewards of this data management process.

CONCLUSION-

The need for data warehouses and business intelligence comes from the need for the concept of one truth- The need to have one true source of all data and recognize the accurate answers to important questions. It is important to start, with or without clean data, with the present resources and find allies hidden in the organization. Marketing should be the one department that benefits the most from such investments, although all departments derive value from it. Prior to investing it should be known that it is crucial to have data when it is required and make it as accessible and useful as possible. Business practices should be in line with the investments and insights provided through their medium.