Creating a clear path to design your data analytics initiatives around the Credit Union’s business goals. 
Summary:
As organizations look to accelerate their data analytics competency, one of the big strategy questions is “what is the best approach to getting there?”. The key to unlocking your credit union’s analytics potential includes:

·        A thoroughly articulated data strategy and business plan

·        Quick implementation of a scalable/adaptable data warehouse

·        Robust visualization tools

·        Expertise of a data scientist and/or chief data officer

Today, analytics needs to dive deeper into the behavior and decision-making processes of members through analysis of critical, real-time data.  In our new digital and data analytics age, credit unions are relying more on data than even just a year ago, pre-pandemic, to serve members and thrive in a highly competitive market.  If using data to its full potential is something your credit union struggles with, you are in luck.  This quick read shares four actionable strategies you can put in place to get the most value and ROI from data analysis.

A Strategic Road Map for Success

Like most successful ventures, you need to start with a plan – a roadmap – that drives accountability, goal-setting and metrics for success.

We encounter countless organizations that are ready to transform their data into knowledge, growth and profits, but they are still hazy on that first step – Defining the desired business outcome(s) of data analytics.

Teams will need to clearly understand and outline the long-term strategic goals of the credit union (i.e. growth, branching, new products and services, etc.) to identify and select technology solutions that fit the requirements both today and, more importantly, where you want to be in the future. Otherwise, you run the risk of investing in technology, resources, vendors, and staff that might not fit the credit union’s vision; and the cost of pivoting later can be significant.

Analytics efforts should empower data-driven decisions and fuel growth.  As part of this strategy assessment, it’s essential to understand the specific, measurable actions your credit union wants to undertake.  In our experience, we’ve seen tremendous success with past CUs by driving digital branch growth through a focus on identifying member segments and delivering targeted marketing actions.

Too often, executive management teams have an unclear strategic direction with regards to their technology investments and how they align with their corporate objectives. Take the time to clarify the overall strategic direction and outlook. Without this direction as a guide, the credit union’s technology decisions end up driving the overall strategic direction by accident.

Maximize the Value of a Data Warehouse

Are your data strategy and business objectives clarified?  Are you driving growth through measured, systematic, recurring action lists from analytics? If not, now it is time to ramp up the data analytics potential by using a data warehouse. Data warehouses can yield a tremendous ROI for organizations that leverage them to their greatest potential.

Rapidly evolving and improving data warehouse technologies have greatly benefited the financial services industry.  They allow organizations to easily retrieve and store valuable data about members, products, services and more. Data Warehousing solves the ongoing problem of analyzing data from disparate systems and transforming it into actionable information you can use.  It provides a plethora of benefits to a credit union, such as ensuring data consistency, providing a single source of truth to store and cleanse data, improving speed and accuracy on insights, and generating greater efficiency and time-saving solutions.

Developing and maintaining sophisticated data warehouse systems is often too expensive for individual organizations, so many have partnered with service vendors and their cloud-based platforms. To successfully build and deploy your data warehouse, start with a strong plan and foundation. Be sure you have executive sponsorship, adequate architecture and documentation, an implementation team, a sophisticated data integration plan and scalable and adaptable data warehouse.

Waiting to get a data warehouse solution implemented will lead to lost opportunities and insights that could have been gained through an analytics solution. The Knowlton Group’s guide: Buying vs. Building a Data Warehouse drills deep into the advantages, and some of the hiccups, of both scenarios.  Fortunately, our 72 hour Data Warehouse, VeriCU, is designed with a strong pre-built foundation and tons of customizable components. It blends the cost and speed of implementation of a pre-built solution with the flexibility and customization of a custom-built data warehouse.

Extracting Needed Business Insights

With a robust data warehouse in place, you can now get the insights that lead to innovation, superior member services, greater efficiency and so much more. The faster you can extract key insights and analyze data through sets of queries, the further your credit union can achieve business goals.  Visualization tools are paramount to make this happen.

Sophisticated visualization tools allow you to dial into the most important aspects of your member data, such as the profitability of member, branch, region, household, or product.  Visualization tools allow you to segment members based on any segmentation you define, so you can further improve member engagement and marketing messages. You can run reports that share defined information on member attrition, including which members are most at risk of leaving, with specific action plans to boost retainment. Imagine assigning an engagement score to each member based on their overall activity and tracking progress as targeted action helps drive members to the segment-specific ideal-product-bundle.

 Putting Data Science in Practice

Sure, most credit unions don’t need an army of data scientists to put their data to action. But, they need experience, expertise, and real analysis to solve key challenges and unlock what’s working and what can be improved within the organization.

One of the big impediments to implementing a data and analytics program that delivers business value is a misalignment between the business organization and the data organization.  The guidance and experience of a data expert, such as a Data Scientist, Chief Data Officer, or Data Strategy Officer, will help overcome this challenge.

A 2021 survey1 reveals that 65% of organizations have appointed a CDO, up from just 12% in 2012.  Why?  A CDO keeps everyone accountable and aligned with the overall strategic business objectives associated with your data and analytics projects.  Whether hiring a full-time executive or an outsourced expert like The Knowlton Group,  you will view them as a trusted advisor and strategic partner.  Consultants and data scientists will work with your data analytics teams to pour through the data and train your staff to uncover and act on new opportunities that lead to your desired goals. These experts can advise decision-makers, monitor progress, track success, and establish best practices that will position your data analytics project for success. Striking the right balance and partnership with the business side of the organization and the data analytics initiatives through a CDO is a winning formula.

While many success stories confirm data can add enormous value, most organizations still struggle to build data analytics into their business strategies, and to align their data efforts to the needs of the business.

With proper integration, data can accelerate many business strategies by improving the processes and empowering the people needed to execute them. Propelling your data, unlocking its full potential, and solving key business issues with data does not happen overnight.  Let’s help you lay the groundwork today.  For guidance, contact The Knowlton Group http://knowlton-group.com/

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Sources

  1. CXO Today Survey Report

https://www.cxotoday.com/big-data/companies-continue-to-struggle-with-big-data-ai-investments-finds-study/