How to Predict the Success of your Advanced Data & Analytics Project
How your institution manages and governs its data is a key indicator of the success, or failure, of your next data and analytics project. Here is an approach for quickly assessing your organization’s data governance and data management proficiency.
Gain Insight with a Data Governance Assessment
Successful credit unions regard data as a key business asset. They use advanced data analytics to maximize income generation, reduce member churn, and create the right product offerings for their customers. They also know data quality, reliability and usability are essential and require constant vigilance.
Just as your doctor checks your vitals and a few minutes later can determine if you’re healthy, need further tests, or need immediate surgery, a good data governance assessment will measure the four key data governance competencies: organization, policy, security, and operations. Poor performance in any of these competencies indicates potential cracks in your data governance foundation. This warns of data management challenges, a weak data strategy, and suspect data quality.
Data Governance as an Indicator
Weaknesses in data governance has both visible and hidden side effects. Visibly, poor data governance will increase the level of effort and reduce the level of success of your advanced data and analytics efforts. Poor data governance practices are the tell-tale sign of poor data quality. Bad data is the leading barrier to successful advanced data and analytics projects. It is common for organizations to spend as much time and effort cleaning up bad data as implementing new advanced analytics capabilities. How likely are you to trust a predictive model for customer churn if your customer data is suspect?
Most companies assume that their current reporting and analytics are accurate and valid. That may not be the case if you have poor data governance practices. If a data governance assessment reveals significant weaknesses, be prepared to revisit your current reports and analytics to be certain bad data has not corrupted your findings and data-based assumptions.
Credit Unions Are Gearing Up
“Nearly half (45%) of respondents expect to adopt advanced data and analytics by year-end 2022.” - according to Cuna Mutual Group’s recent research project, What Strategic Choices Are Credit Unions Making to Drive Growth?
The Inherent Value of an Automated Data Governance Assessment
It can be difficult to know where to start and what to focus on. Leveraging a pre-defined, structured data governance assessment template provides rapid, reliable, and valuable insights. It is common for data governance assessments to take weeks or months to complete and deliver results that are ambiguous, IT-centered or not instructive. An automated assessment should be succinct and intuitively simple to complete with results that pinpoint the competencies to be addressed. It should also be geared to both business and IT leadership. The Analytics TO WIN® Data Governance Assessment has been developed to address these key requirements. What’s more, it serves as a necessary component of an overall method for crafting a data management and analytics strategy.
Here's How it Works — the Analytics TO WIN® Data Governance Assessment in 3 simple steps:
Selected participants receive an introductory email for assessment registration purposes
Once registered, the participants complete the online assessment where they select the most appropriate answers to 36 multiple-choice questions, which takes about 15-20 minutes
A results summary screen is generated upon completion of the assessment, providing immediate insight into relative strengths and weaknesses across all four data governance competencies
(As an optional service, the assessment results from all stakeholders can be evaluated and combined into an overall score.)
The Data Governance Assessment from Analytics TO WIN® is available at no charge and can be accessed at analyticstowin.com/dga
Leveraging greater value from the Data Governance Assessment
Experience has shown that the potential value of the Data Governance Assessment is enhanced by encouraging business leaders and key stakeholders across multiple disciplines to take the assessment. The collective assessment results will highlight any discrepancies in perspectives regarding data capabilities across the organization. They will also identify business areas where data deficiencies are recognized and understood as limiting factors to future success.
In some cases, poor results from the Data Governance Assessment (or other assessments) will indicate that establishing a proper data management and analytics strategy is required. Conducting the entire Analytics TO WIN® method is a proven approach for crafting such a strategy in a focused, timely fashion.
Credit unions today need to focus more pro-actively on their data capabilities and dig deep to build true insights that will guide and underpin their growth plans. They need to understand that the quality, reliability, and usability of their data are essential to generate more income, to mitigate member churn and create a product mix that is tune with their members’ interests. It is becoming a necessity to craft a data management and analytics strategy to determine the potential investment required to achieve their strategic goals.
Even if a data management and analytics strategy isn’t on the agenda yet, the data governance assessment itself can serve as an effective starting point in ascertaining the quality, reliability and usability of your organization’s data. It can also serve as a vital diagnostic to determine if your advanced data and analytics efforts are likely to succeed or fail.
Shawn Helwig is the Managing Partner of Total View Analytics and the creator of Analytics TO WIN®. He has been helping companies use their data to solve problems for more than 25 years and has the passion, integrity, personality and expertise to help your organization make better data-driven decisions.
Additionally, the Total View Analytics team has over 30 years of experience working with Private Equity firms.