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The direction of water flowing in a stream can be altered and diverted. But imagine if you could turn it around entirely. Many aspects of business operations require information to flow. Individually, these data streams may not always appear to indicate that things are on or off-track. It’s only when we gather them all up and identify relationships or trends across many of these data streams that indications emerge whether projects or business units might be headed for particular outcomes.
Indicators classified as “lagging” and “leading” are two types of measurement discussed a lot in performance management. We use them to assess and manage everything from individual projects to an entire organization.
In this column, I’ll demonstrate how these metrics apply to risk management in our industry and explain how you can not only leverage them to impact project outcomes, but also enhance overall performance.
Understanding lagging, leading indicators
Let’s start with the basics: What are lagging and leading indicators?
A lagging indicator shows the aftereffects of your work, or how well you did. It’s an output measurement, meaning it indicates past performance, such as the number of accidents or worker injuries sustained on a particular job.
Conversely, a leading indicator is a predictive measurement. Leading indicators help you anticipate specific outcomes or predict future success; for example, the use of safety equipment or the number of people wearing hard hats on a construction site.
While lagging indicators are typically easier to identify, they can only tell you what has already happened. Leading indicators can influence change, but they are usually much more difficult to develop. Many of the traditional financial indicators (e.g., costs, profit, revenue) are lagging, meaning they are the results of the activities of the company.
While interesting and essential to any organization’s stakeholders, lagging indicators are ultimately ineffective until it is too late to impact outcomes. That said, they are still an integral component of a leading indicator.
Leading indicators are often related to activities undertaken by workers. Where things become really interesting is in the analysis of human behaviors, such as tracking and assessing if employees are on time or late relative to known milestones. While these indicators are still lagging in form, they provide a much earlier indication of challenges to come.
In other words — in terms of risk management, specifically — when you combine lagging indicators and leading indicators, you can apply acceptable tolerances to track the relationships between them.
The result is you’ll begin to detect earlier warning signs that one can flag within the organization or project team. What’s more, this enables you to run forward-looking (predictive) hypothetical models to test notions of desirable or undesirable outcomes even sooner. It allows a business unit and a project owner/team to either advance toward ensuring a desirable outcome (secure an opportunity) or change course to prevent an undesirable outcome (mitigate a risk).
From lagging to leading
Recognizing and understanding how to turn lagging indicators into leading indicators is the key to turning instinct into insight. For managers, the process of identifying leading indicators requires a combination of historical data and their insight. Once one observes an alignment of the two, you can formulate a hypothesis and test it to corroborate any direct relationship.
If you’re able to confirm a direct connection, the next step is to establish a threshold. Herein lies the key to turning lagging indicators into leading indicators.
To put this in the context of a real-world example, let’s take a closer look at the impact overtime can have on a construction project. Jobs experiencing significant amounts of overtime tend to perform poorly. We’ve recognized this as a lagging indicator for many years. Supported by that historical data, looking forward — assuming future instances of this trend pass a certain threshold — we can trust the outcome will be consistent unless there’s an intervention.
When requests for overtime start to come in on a project, having already established the threshold for how much overtime the project can accommodate (the point where cost overruns might arise if crossed) enables managers to identify the project risk in real time, course-correct before it’s too late, and adapt accordingly going forward. Or, at the very least, the project manager will understand the anticipated impact and outcome.
Here’s another example: We monitor purchase order duration to correlate projects that have an unusual number of purchase orders with an extremely short period. This would appear to be an indication of either a lack of planning or some constraint at the project level that doesn’t allow for planning. Thus, an unusual number of short duration lead times would be an indication of a project that is going to underperform financially.
We’re leveraging the data already captured by our purchasing system and have established departmental thresholds for purchase order lead times to identify these leading indicators. When a project exceeds the established limit for some extended duration, it’s a red flag for the manager. Exceeding this duration threshold is a lagging indication that something is wrong with the project, but it’s also a leading indication that the project could underperform.
What happens in the case of the first example if 200 percent or even 300 percent of overtime is spent before identifying the indicator? Or what if that amount is necessary to see the project through to completion? Either way, you can’t recover that much overtime and it will ultimately impact the project’s gross margin.
Even though you can’t always do something to solve for an indicator, you at least have this insight ahead of time so managers and their organizations can be much more agile if given enough lead time to foresee such outcomes.
Similar to any construction project, you need to complete certain groundwork to facilitate a robust and stable foundation from the outset. Here are four infrastructure needs required to leverage data, along with lagging and leading indicators to successfully impact project outcomes:
1. People. First, human capacity is needed to gather the necessary data sources, distill the data and elegantly present the predictive results to those responsible for the outcomes. There must be a data or financial analyst — what we call a “Head Distiller” — available to manage this process.
2. Platforms. The requisite data comes from platforms allowing for aggregation across projects and business units, but it must be centrally stored and easily accessible. If the data lives in individual project folders and electronic files, then it becomes virtually impossible to tap into this information.
This data typically comes from multiple sources within an organization, such as finance and accounting enterprise-resource-planning systems; accounts payable and accounts receivable; project managers doing forecasting and productivity tracking; contracts and other legal documents; the substantiation team; detailing, manufacturing, shop managers and others.
3. Policy via standards. A critical piece of the infrastructure is a documented set of standards for tracking costs, as well as where and how information is stored. These should be included in policy documents in a governed library.
4. Policing. Lastly, there must be some version of quality control, or policing, for adherence to the standards and policy. In other words, inspect what you expect.
As the construction industry evolves and projects become increasingly complex, it’s more important than ever to be at the forefront of efficiency and innovation. When applied to risk management, teams can leverage key performance metrics such as lagging and leading indicators to enhance the overall performance of a project or organization.
The holy grail for teams, of course, is the ability to hypothesize that these indicators can help your organization impact business outcomes such as profitability. The key to making this a reality on your projects is to put the required infrastructure in place and follow the necessary guidelines outlined here.
By taking this approach, you’ll realize better results, continue optimizing processes, and ensure operational excellence in the planning and execution of construction projects.