4 steps to excellence in data analysis
- By Jake Bittner
- Aug 15, 2018
Data management and analysis are cornerstones of the 2018 President’s Management Agenda (PMA), which calls “full utilization of four cross-cutting drivers of change”: policy, people, process and platform.
Unfortunately, data analytics efforts across the federal government too often fall short of their desired results because agencies tend to focus on the platform (i.e. technology) part of the equation at the expense of the other components. They may start the journey toward a data analytics program by piloting basic analytics solutions. However, they fail to take the next vital step: creating a culture that understands and embraces the importance of data analytics.
Creating analytical centers of excellence
As the PMA correctly points out, effective data analysis is a holistic process that must involve all aspects of an organization, including buy-in from the organization’s leadership. Incorporating all of the “drivers of change,” not just technology, is important to creating their own analytical center of excellence.
To create an analytical CoE, an agency must successfully institutionalize the belief that data analysis is essential to its success. Senior management must be fully behind the importance of data analysis and must be committed to finding the right people for the job. Furthermore, leadership must be ready to fund the required resources and execute upon a vision for a continually innovative and mature data management practice.
Although a few agencies have made this level of commitment, many feel they can simply buy their way to data analytics mastery. But successful analytical CoE cannot simply be purchased. It must be built.
Building -- not buying -- analytical CoEs
While purchasing the right software platform is important, there are additional steps that agencies must take to successfully build this essential analytics framework and meet the goals outlined in the PMA.
Get leadership on board. Agency CIOs, CTOs and others in leadership functions should recognize, understand and embrace the importance of in-depth data analysis. Those who do will be more inclined to create and support an agencywide culture dedicated to establishing an analytical CoE. With top-level support and advocacy, data analysis can spread beyond individual units and groups and become ingrained in the agency.
Establish agencywide processes and policies. Once leaders are onboard, they can help break down data silos and make analysis a foundational element of the entire agency. Services, processes and best practices can be centralized, shared, refined and used in a consistent manner within all teams. These teams should, in turn, share analytical capabilities and results with each other to ensure that information is being used effectively to improve the whole organization.
Create adoption plans. Adoption plans can help users understand the importance of data analysis and encourage them to learn about analytical tools. These plans can take different forms depending on each agency's priorities. At a minimum, they should articulate specific goals for analytical solutions, present a clear vision on what teams are expected to know and be held accountable for, enable the adoption of analytical technologies, provide metrics for measuring implementation and promote the importance of data analysis agencywide.
Invest in skilled employees. Agencies need people who can not only read data but also create actionable recommendations based on their insights that will improve organizational efficiency and deliver on mission goals. This talent should be valued and frequently consulted.
Striving for higher levels of value
Meeting the requirements of the PMA means thinking beyond a simple technology play and using analytics to provide higher levels of value. It requires making data-based decision-making an integral part of an agency's critical business practices.
Analytics excellence cannot be solely about software. As the PMA states, data analysis should become part of the very fabric of the agency, much like security and other important initiatives. Agencies that take this approach can create mature and highly successful data analytics operations that, to quote the PMA, will “deliver mission outcomes, provide excellent service, and effectively steward taxpayer dollars on behalf of the American people.”
Jake Bittner is CEO of Qlarion.