Data Analytics in the Workplace
Did you know that the United State Postal Service (USPS) photographs and documents every single piece of mail it processes? In 2012, this accumulated to 160 billion pieces. This huge data set serves the purpose of facilitating collaboration across law enforcement agencies. It’s just one example of how collecting, analyzing, and reacting to data can lead organizations to make strategic decisions.
In our world of connected devices, email, instant messaging, and wearable technologies, collecting data is becoming the easy part. The hard part is analyzing large, complicated data sets in order to improve organizations and employees alike, especially when many tools are designed for use by “data scientists” rather than the everyday user.
Nonetheless, even without advanced software, organizations and employees can still use data analysis strategies and techniques in their everyday work. The following suggestions are ways leadership and management can promote data analytics in Federal agencies, based on a report from the IBM Center for The Business of Government and the Partnership for Public Service:
- Ensure and encourage access to data. Allow and encourage employee access to performance data as it promotes ownership over professional development, transparency, and reminds employees of the agency’s mission. Over time, this will establish data usage as a workplace norm at your agency.
- Collaborate with other agencies. Look to acquire preexisting interagency data sets, tools, and services that can enhance your agency’s performance. If your agency has found success with certain data sets, tools, or services, consider establishing an agency partnership through a memorandum of understanding so each agency can improve their work.
- Track the benefits of data analytics. As competition for funding continues, tracking specific outcomes of data analysis initiatives and programs is vital in proving their worth for your agency. Top leadership needs cost-benefit metrics.
- Present clear and concise analysis. Most data sets are massive, overwhelming, and complicated. Give high-level analysis to stakeholders who are unfamiliar with the data so it’s easier to absorb and understand. Tie the data and analysis to your agency’s mission.
- Acknowledge your assumptions. Reflect on your assumptions so you manage their influence on your judgments prior to starting work with a data set or information. Rethink them, not abandon them, to see the big picture.
- Question your information. Challenge your data set or information to ensure you come to a valid, reliable conclusion.
- Respect all possible conclusions. Consider all competing conclusions so you’re not simply picking the first one that’s satisfactory enough. All perspectives should be given equal weight in order to find the best conclusion.
- Be the devil’s advocate. Question the strongly held assumptions and conclusions of those around you working with the same data or information. Look for gaps, assumptions, or moments of groupthink that are being overlooked. Ask, “What if?”
Data analysis will continue to be a major influence in our lives in ways that are seen and unseen. In the workplace, employees at all levels can encourage the role of data and use analytic techniques to improve organizational and personal performance. The best solutions and conclusions are made when people have access to data and are empowered to connect the dots.