The 5-3-1 Approach to Improving Your Data Management Strategy

Find out 5 best practices for your data management program, 3 ways to drive greater ROI, and 1 fatal mistake to avoid.

Data is an asset for any organization. However, data alone is useless. It needs a purpose, and it needs to be managed effectively. It also needs to consistently and holistically be collected, stored, processed, and analyzed to inform business decisions. While business operations and business data are closely linked, it’s a constant challenge for operators to manage a profitable business, while investing in data-centric initiatives to better inform their decisions.

That’s why clients come to Concord. Our end-to-end data delivery capabilities enable organizations to increase speed to market, unlock data value and mitigate risk. Ultimately, Concord’s approach and expertise in data management allows clients to focus on what they do best, while granting piece of mind that their data is being both managed and maximized for greatest returns.

In this blog, we’ll take you under the hood – sharing best practices from the data experts at our firm. We’ll cover:

• 5 things that organizations can do now to improve their data management programs
• 3 keys to increasing ROI from their data strategy
• 1 mistake to avoid with data governance

5 Things You Can Do Now to Improve Your Data Management Program:

Modernizing enterprise data ecosystems is a multi-faceted, multi-year journey. However, here are five immediate steps you can take to build incremental improvements today.

1. Define data governance policies: Establish policies for data quality, security, privacy, and compliance to ensure that data is managed consistently across the organization.
2. Invest in data infrastructure: Build a data infrastructure that can store, process, and analyze large volumes of data efficiently. Cloud-based platforms and technologies can provide cost-effective and scalable solutions for data management.
3. Improve data analytics: Use modern data analytics technologies to gain insights and drive decision making. I know for a fact most teams love that one big Excel report that tells them everything they need to know. But even limited investments in machine learning and artificial intelligence can uncover new and valuable trends that skyrocket the organization’s data driven decision making.
4. Develop data literacy: Ensure that employees across the organization have the necessary data literacy skills to understand, interpret, and use data effectively. Different roles have vastly different data consumption needs and patterns. While it’s critical to train and upskill, it is necessary to provide numerous easy options for understanding and using data at different levels.
5. Adopt agile data management practices: Adopt agile data management practices, such as iterative development, continuous integration, and DevOps, to improve the speed and efficiency of data management processes.

3 Keys to Increasing ROI from Your Data Strategy:

Investing in building a more robust data strategy will result in long-term gains. To build a strong foundation and maximize your returns, focus on these three areas:

1. Align data strategy with business goals: Ensure that the data strategy is aligned with the organization's business goals and objectives. This will help to prioritize data initiatives that deliver the most value to the business.
2. Measure and monitor data performance: Establish metrics to measure the performance of data initiatives and monitor progress against targets. This will help to identify areas for improvement and ensure that data initiatives are delivering the expected ROI.
3. Continuously optimize data initiatives: Continuously optimize data initiatives based on feedback and insights to ensure that they are delivering the expected ROI. This can be achieved through agile data management practices and by leveraging new technologies and best practices.

1 Fatal Mistake: Perceiving Data Management as a One-Off Effort

Data management is not a single initiative, but a continuous investment to ensure data is managed effectively and efficiently.

The biggest mistake organizations can make with data governance is to view it as a one-time project rather than an ongoing process. Data governance requires continuous attention and investment to ensure that data is managed effectively and in compliance with regulations and standards. Organizations should establish a data governance framework that is scalable, adaptable, and can evolve over time to meet changing business needs.

Final Thoughts

In conclusion, data management is a critical function for any organization looking to leverage data to drive business outcomes. These five best practices for data management represent real improvements for most data management programs. The three keys to increasing ROI will ensure the program delivers continuous and incremental value to business. Finally, reinvest that generated value back into your data modernization program to establish long-term data governance processes that build excitement and adoption across the organization.  

For a deeper dive into data management best practices, download Concord’s Data Management Assessment and Roadmap, or set up a conversation with the team today.