Dashboards exist to help you see connections between different kinds of data. Unfortunately, in practice, it doesn’t always turn out this way.
Even though dashboards can display tallies or summaries of nearly any kind, uncovering high-impact business and operations insights may require an extra step or two.
From the perspective of the quality manager or the operations manager, being able to see your data is essential. But what you really want is not just to see what you’ve collected -- to find out how many nonconformances are still open, or how many corrective actions you’ve completed -- but be able to use that data to make better decisions. These decisions could include:
- Where should I focus my resources?
- What risks are the most risky, and need my attention now?
- Is there an incident or quality event about to happen, and should I intervene?
- What should my team work on first?
In many organizations, all of this processing has to happen in your head – but there are two ways that you can make it easier. The more complex path is to implement machine learning algorithms to continuously scan your operations data and make recommendations about these questions. The easier (and more immediate) path is just to spend a little more time making your dashboards meaningful.
What does this mean? The Baldrige Excellence Framework (NIST, 2019) provides four guidelines on the kinds of information that can be useful for creating a story around business results:
- Levels. For each value on your dashboard, how can you tell if that value is good or bad? How do you know? Is there variation between each measurement that you should also examine? Consider adding context that helps you interpret those levels.
- Trends. How are the levels changing over time, and are these changes desirable or undesirable? How will you know when to take action?
- Comparisons. Are you using standards, benchmarks, or goals to gauge your performance? If so, consider adding them to your dashboard to guide decision making.
- Integration. There should be no gratuitous information displayed on a dashboard. Have you double checked to make sure all the displayed data is being used? Have you critically evaluated each data display to see if there are alternative leading indicators that might be even more valuable?
Agile practices can be extremely valuable for making dashboards meaningful. When developers are paired with subject matter experts, and can observe them attempting to make business decisions based on what they see on the screen, opportunities for improvement can be identified.
Choosing information to display on dashboards should also be done with consideration of your organization’s data management and data governance processes. Security, visibility and transparency are often important, but they have to be weighed against confidentiality. As a result, you have to think carefully about the data and information made visible through dashboards, and who is permitted to see and use it.
Dashboards don’t have to be like your car dashboard, even though the name is the same. Design your dashboards so they’re more like navigation systems! Instead of displaying summary data for any objects or events you collect, start imagining how these displays might guide daily decision making.
National Institute of Standards and Technology (NIST). (2019). Baldrige Excellence Framework (Business/Nonprofit): Proven leadership and management practices for high performance. Available from https://www.nist.gov/baldrige/publications/baldrige-excellence-framework/businessnonprofit
About the Author: Nicole Radziwill is the Vice President, Global Practice Leader, Quality & Supply Chain at Intelex Technologies. Before Intelex, she was an Associate Professor of Data Science and Production Systems, Assistant Director (VP) End-to-End Operations at the National Radio Astronomy Observatory (NRAO), and manager and consultant for several other organizations since the late 1990's bringing quality management to technologically-oriented operations. She is a Fellow of the American Society for Quality (ASQ) with a Ph.D. in Quality Systems from Indiana State University. Nicole serves as Editor of Software Quality Professional (SQP) journal and is a former Chair of the ASQ Software Division. She is an ASQ Certified Manager of Quality and Organizational Excellence (CMQ/OE) and Certified Six Sigma Black Belt (CSSBB).
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