Achieving consistently high levels of quality is a primary goal of all managers, especially those working with advanced analytics. Quality management techniques developed over time across different industries can provide advanced analytics leaders with a blueprint to achieve this goal. For example, my first job was as a Tank Platoon Leader in the U.S. Army, where I learned to apply several quality management techniques. More than twenty years later, I apply these same techniques to better manage the quality of IRI’s Advanced Analytics Insights project deliverables.
- Process Management – This quality technique organizes work into standard, repeatable processes to ensure consistency and scalability of results. For my tank platoon, we created and documented standard operating procedures (SOPs) for key processes such as firing weapons systems, executing tank battle maneuvers, and performing maintenance activities. Applying this technique to advanced analytics today means defining work steps for our key deliverables as standard processes. These core process steps are then documented into SOPs that include quality checklists and effort estimates that are useful references for project pricing, planning and management.
- Quality Metrics – This quality technique includes measuring and evaluating key performance metrics to proactively manage quality results. As a platoon leader, I captured metrics on target accuracy rate, cycle time to shoot targets, and accuracy rate of crew fire commands to certify each tank crew in my platoon during gunnery training. For advanced analytics, my current team captures and reviews quality metrics on each project using a survey across the project team focused on a best practice checklist. These quality metrics are a great management tool that serves as a key input to quality and performance management.
- Process Improvements – This quality technique involves managing the quality processes and metrics to achieve continuous improvements. For the tank unit, each crew received metrics and evaluations of their training results through After Action Reviews (AAR) resulting in targeted process improvements. In the world of advanced analytics, my current team reviews the quality metrics and processes to identify and then execute improvement projects to improve quality, reduce cost, and lower project cycle times.
As you can see, quality management techniques used successfully in areas such as training a tank platoon for combat can also help advanced analytics teams consistently deliver high levels of quality that translate into increased value for clients.
Are you using these time-tested quality management techniques with your analytics solutions today?