In the past, the most common way to
measure the safety performance of a business was to look at “lagging”
indicators. The number of incidents and injuries would be metrics
tasked with painting a comprehensive picture of the EHS performance of an organization, even if they entirely were based on historic data. Lagging indicators are easy to measure, but typically offer insight into the outcome of a process only after an incident has taken place. That means they’re rather tricky to influence.
Let’s think about our oldest of EHS friends: the numbers of incidents and injuries. They’re useful, sure, but only
to measure safety performance to date. Thus, they’re of extremely
limited use when attempting to improve future performance and prevent
further incidents from taking place.
Leading indicators can provide actionable EHS information
that can help reduce risk and encourage teams to be more proactive in
preventing incidents. You therefore can think of a leading indicator as
a form of predictive analysis. Predictive data can go one step
further than the “what” and “why” of an incident by giving an
indication as to what might happen next.
Research Into Leading Indicators
We recently worked with several companies on a leading indicator
initiative. Each of these companies is applying a common approach to
collect and analyze data from myriad risk-reduction activities such as
incident investigations, near-miss reports, management system audits,
risk assessments, assurance reviews, behavioral observations,
field-level inspection programs, hazard analysis and many other
processes. A recent analysis of a data set spanning 14 companies showed
an average of 58 sources of data totaling millions of records over
several years.
On the surface, each of these organizations simply have been using a
common “mechanism” to manage their own unique set of environmental,
health, safety and sustainability risk-reduction processes and
ultimately analyze the resulting data, i.e., the “outcome” (EHSS) data.
However, at a deeper level, these companies not only are
collecting data resulting from the outcomes (e.g., incident reports,
injury details, spill quantities, near-miss types, root causes, audit
results, assessment scores, inspection findings, etc.) but also the
work practice behaviors reflecting the organization’s tendencies in
executing such processes, such as the mean times between completion of
critical process steps, rate of leadership involvement in nonmandatory proactive steps, distribution of employee involvement in proactive activities and more.
With such a vast data set from both the outcomes and the work
practice behaviors, these companies created a unique opportunity not only
for themselves but also for anyone in the industry who is interested
in finding the real leading indicators of performance – those
activities, practices, factors, conditions, etc. – that are practically
measurable and are proven to have a mathematical relationship to loss outcomes.[DD1]
Drawing Leading Data from Lagging Events
It has become common to find companies that have implemented an enterprise-wide incident database
to collect data resulting from the outcomes of incidents. However,
some companies also are executing corporate-wide incident management
process improvement projects along with an information system that not only collects incident data, but also enables/facilitates each major step of the business process.
As depicted in Figure 1 below, applying a risk-reduction solution for
managing incident/near-miss events enables the full event life cycle –
from front-line worker reporting events to leadership involvement and
the remediation of action items – of the business process.
Sphera
Figure 1
By comprehensively facilitating the entire risk-reduction cycle
business process, the various levels of the workforce simply are
carrying out the routine incident/near-miss work practice using a
business process automation (BPA) tool. However, the byproduct of
facilitating each major step of all near-misses and incident events on
an integrated software platform is the ability to practically draw
measurements from both the incident/near-miss event outcome data and the
data reflecting the workers’ interaction with each step of those
business processes.
By analyzing the business process data to study the organizational
treatment of these lagging events, leading metrics such as the
percentage of the workforce involved in near-miss reporting, the ratio
of near-miss to high-consequence reports, the rate of leadership participating in nonmandatory events, consistency of manager response to key steps, and many other potential Leading Indicators of culture and leadership can be created.
Through this automation of lagging incident/near-miss business
processes, the data for calculating both lagging outcome metrics and
leading indicators is efficiently generated. The companies executing in
this manner are achieving the ironic accomplishment of drawing leading data values from the occurrence of lagging incident/near-miss events.
Sphera
Figure 2 and Figure 3
Integrating Key Work Steps
Most companies deploy a vast array of different proactive business
processes that fit the risk-reduction cycle pattern, ranging from formal
corporate-level auditing processes to more casual field-level
suggestion box/hazard ID type initiatives. Typically, the data resulting
from the outcomes of such proactive activities is scattered throughout
the organization on pieces of paper, spreadsheets, isolated databases and other nonintegrated systems, rendering broad measurements highly impractical.
An enterprise-wide risk-reduction solution enables the integration of
the key work practice steps and data elements across a wide array of
different proactive processes.
Per the previously mentioned average of 58 sources of
activities fitting this pattern, [DD2] roughly 90 percent of those
activities are proactive, assessment-based activities. By
facilitating a wide array of processes on a common BPA tool, the data
from both the outcomes of the activities and the work-practice
behaviors is available for trending across previously segregated
processes.
With this approach, common measurements can be drawn from processes,
which are routinely viewed as dissimilar. For example, the rate of
employee participation per a behavioral-based safety (BBS)
process can be combined with the rate of participation in other
dissimilar processes such as risk assessments, hazard ID reports,
inspections, self-assessments, walk-through audits and many others to
calculate a comprehensive rate of proactive employee involvement, a key
measure of reporting culture.
In addition, the final major step for all risk reduction cycle
activities entails the process of managing the action items required to
install protective controls and ultimately reduce the risk. With
efficient access to action item data from so many different processes,
the leading indicator metrics that can be drawn from action item
execution are broadly applicable and readily measurable as well.
The Key: Buy-in From Operational Management
Gaining the support of top management is in the critical path for
leading indicators to capture their fair share of this KPI landscape. In
a recent workshop conducted with leaders in environment,
health, safety and sustainability (EHSS) from several global operator
and service companies in the energy industry, the overwhelming choice
as the greatest obstacle to executing leading indicators was the
propensity of top leadership to use lagging metrics in annual
management performance objectives and in some cases as key components of manager incentive pay programs.
In today’s cost-competitive marketplace, budgets already are tight. Therefore, convincing operational
management to allocate the necessary resources for execution of the
programs that support a leading indicator initiative is met with
resistance rooted in skepticism. If you cannot convincingly demonstrate
that investing in such “leading” activities will result in better EHSS
performance, they won’t allocate the resources to execute such a
program. To overcome this obstacle, the most effective leading
indicators must meet the two following criteria:
1. Minimize additional resources required for execution.
2. Provide sufficient proof that executing leading indicators will improve EHSS performance.
Practical, usable, efficiently calculated metrics with a strong value
proposition are required to compel top leadership to give leading
indicators a prominent place on the KPI score cards of operational management.
The key components of leading indicators, which effectively may rival the practicality and importance of lagging metrics as KPIs to be executed on an enterprise scale are:
Simple, close connectivity to the outcome/results.
Objectively and reliably measurable.
Interpreted by different groups in the same way.
Broadly applicable across company operations.
Easily and accurately communicated.
Why do Lagging Metrics Still Dominate?
Many companies are tracking and analyzing leading indicators in
isolated areas of their businesses but few are applying leading
indicators to rival the age-old incident rate as the primary KPI for
judging an operation’s EHSS performance. One reason for this dominance
is the practicality of having a near standard in producing a
normalized performance metric, which can deliver an apples-to-apples
comparison of loss rates across the enterprise.
Whether a company uses a calculation similar to the OSHA standard or prefers the more internationally used denominator of 1 million exposure hours, the two key components
of safety loss rate measurement – the number of incidents and the
quantity of work hours – are much more broadly applicable and readily
measurable, thus rendering this type of lagging indicator a more
efficient and practical alternative.
In addition to the convenience of lagging indicators, how
many times have you heard: “It hasn’t happened here, so it is not a
problem”? Given both this human reactionary tendency and the convenience
of lagging metrics, leading indicators have quite a battle ahead if
they are to gain equal share of the KPI landscape for operations
management.
about the authors: Carrie Young is vice president of Consulting Services at Sphera, and is an expert in providing environmental and safety performance improvement through the development of integrated management systems, analytics, organizational
capability, enterprise software and governance. She has been helping
companies with business process transformation and insights for over 20
years. Todd Lunsford is director of Process Improvement at Sphera, and serves operational
excellence project advisor to Sphera customers, enabling them to make
critical decisions using the insights gained from their business
process data. Lunsford leads business process and usage assessments to
advance operational excellence maturity, drawing upon years of experience leading global deployments of operation risk solutions.
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