Learn about different types of real-time information, and how each relates to industrial automation, manufacturing operations and business operations
Like any industry, manufacturing requires effective leading and lagging indicators to benchmark, understand, and predict performance. These measurements are the lifeblood of continuous improvement professionals. Without them, it would be very difficult to validate past efforts and trends, and even more challenging to plan for and anticipate future events.
There has been plenty of discussion and debate over which leading and lagging indicators are the most effective for a given manufacturing operation. While not everyone agrees on the merits of individual metrics and KPIs, everyone agrees that the proper mix is important for gaining full visibility into areas of strength and areas for improvement.
As any seasoned manufacturing professional knows, your balanced metrics scorecard will ultimately consist of what makes the most sense for your organization. So you can ensure that you're on the right track, in this post we’ll give an overview of what you need to know about leading and lagging indicators. And we'll also discuss how emerging mega-trends like Big Data and the Internet of Things (Iot) are poised to reshape how these measurements are used in the future.
Leading and Lagging Indicators: An Overview
While some metrics are good predictors of future events, others are more effective at confirming and reinforcing established trends. These are referred to as leading and lagging indicators, respectively.
A leading indicator can be defined simply as a performance measurement that occurs before a process begins to follow a particular trend. A lagging indicator is the opposite: it is a measurement that indicates results after the process is complete.
Leading indicators are often measurements of behaviors, such as say, operator care or standards of work, while lagging indicators tend to be measurements of results, like OEE or the ultimate lagging indicator - profitability.
Since behaviors are typically precursors of results, it’s important for manufacturers to optimize the use of leading indicators where possible to nip potential problems in the bud upstream from the undesired results. Historically, manufacturers had a performance scorecard weighted towards lagging indicators, and then tried to work backwards to improve results.
But the emerging and disruptive technologies of Big Data and the IoT are rapidly changing how manufacturers think about these metrics in the future.
How Big Data and the Internet of Things Will Change Performance Management
The coming Big Data revolution and its promises of unprecedented predictive analytics will have a profound effect on the way leading indicators factor into operational decision making.
Just think, instead of costly and time-consuming post-production testing of drugs or semi-conductors that may be commonplace today, data mining capabilities will help manufacturers gain a comprehensive understanding of the manufacturing process conditions under which quality and yields are highest beforehand.
As these types of predictive analytics models are further developed, they will become more prevalent across businesses overtime, moving the measurement and potential actions further upstream, from lagging toward leading.
The interconnected network of “smart” objects and assets enabled by IoT capabilities will further these trends by creating a massive circulatory system in which manufacturing assets, people, the plant, and the enterprise are all interconnected. As everything becomes more connected, we are poised to have an onslaught over new data on our hands.
This new data will, as technology capabilities evolve over time, help us react and adapt to local and expanded environments. And across many levels, provide predictive alerts for areas such as production equipment maintenance, supplier quality issues, or on-time delivery rates - thereby shifting these from lagging to leading indicators on the performance scorecard.
Making Data Work For You
While the full potential of these and other technologies on manufacturing performance measurement methodologies is still a long way off, leading manufacturers are beginning to develop balanced performance scorecards that comprise a set of increasingly predictive, or leading indicators to drive toward the goal of raising the ultimate lagging indicator—sustainable operational profitability.
For more information on developing an optimized framework for manufacturing performance, click here to read the LNS Research Manufacturing Operations Management Best Practices Guide or follow the button below.
All entries in this Industrial Transformation blog represent the opinions of the authors based on their industry experience and their view of the information collected using the methods described in our Research Integrity. All product and company names are trademarks™ or registered® trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.