Description
Summarize both the assigned articles. Briefly introduce each, summarize each of the key points provided, including methodology if applicable, and provide your reflection on the relevance to you and your future practice of OSH.
¨Safety Climate – How Can you Measure it & Why Does it Matter?
¨Safety Across Cultures – Understanding the Challenges.
APA format (double space, page numbers, 12 point font with citations).
AI is expressly not allowed for any portion of your work. Do not plagiarize the work of others.
FYI, ” provide your reflection on the relevance to you and your future practice of OSH.” in future, I’m going to work in construction with people have different nationalities and cultures. Ask me anything if you want my opinion on the reflection thing
thank you
Unformatted Attachment Preview
Safety Management
Peer-Reviewed
Safety
Climate
How Can You Measure It
& Why Does It Matter?
J
By Yueng-Hsiang (Emily) Huang, Susan Jeffries,
George D. (Don) Tolbert and Marvin J. Dainoff
ane, a truck driver, is
en route to an important customer site and
road conditions change—a
crash, construction, a detour—resulting in heavy
traffic. Unless she speeds,
the delivery will be late. The
driver knows she should adhere to the speed limit, but
the customer is waiting and
the boss is expecting results.
What does she do?
The pressure is on all utility
crews to restore power for an
important customer. Despite
having already worked a regular shift, Joe, a lineman feels
obligated to stay on duty. He
knows the company’s reputation is at stake and the boss
is being pressured, but exhaustion has set in and he
cannot think straight. What does he do?
In Brief
•This article discusses a study
designed to better understand safety
climate in the lone worker environment and its potential impact on safety
performance.
•The authors developed and tested the
validity of a generic safety climate survey geared toward the lone working
situation, then developed two safety
climate surveys designed for trucking
and utility workers.
•The article presents the scientific
integrity of the survey development
process, and discusses the concepts of
survey reliability and validity evidence.
It also offers practical suggestions on
how to implement surveys in the field.
Yueng-Hsiang (Emily) Huang, Ph.D., is a senior research scientist
at Liberty Mutual Research Institute for Safety (LMRIS) in Hopkinton, MA. She holds a Ph.D. in Industrial-Organizational Psychology/
Systems Science from Portland State University. She conducts both
laboratory and field research in areas such as occupational injury and
accident prevention, and organizational culture and climate. She is a
Fellow of the American Psychological Association and the Society for
Industrial-Organizational Psychology. Huang is an associate editor of
Accident Analysis and Prevention.
Susan Jeffries is a research specialist at LMRIS where she recruits
companies as potential partners in research for field studies and
serves as liaison between the institute and corporate safety professionals in such initiatives. She conducts qualitative research through
in-depth interviews and focus groups to investigate issues relating to
safety in the trucking industry and other lone worker environments.
Jeffries holds a B.S. in Marketing from Boston College.
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Every day, truck drivers, utility workers and other lone workers encounter situations in which safety conflicts with job demands. Because they work
remotely, these individuals must often resolve the
conflicts alone, without the direct support or input
of supervisors or management. Liberty Mutual Research Institute for Safety (LMRIS) found that even
for lone workers a company’s safety climate (employees’ safety perceptions) is strongly associated
with safety behaviors and injury outcomes.
Safety Climate
In recent years, risk managers and safety directors have begun exploring organizational and
psychosocial factors in the workplace to complement traditional safety approaches (e.g., engineering design, protective equipment, training). One
prominent area being explored is safety climate,
which was first introduced by Zohar (1980). Zohar
defined safety climate as workers’ shared perception of an organization’s policies, procedures and
practices as they relate to the true/relative value
and importance of safety within the organization
George D. (Don) Tolbert, CSP, is technical director, organizational
practices, with Liberty Mutual’s Risk Control Service department.
His responsibilities include development of process and resources
to support consulting services to help companies improve efficacy of
safety management systems across all industries. Tolbert holds a B.S.
from University of Georgia. He is a professional member of ASSE’s
Georgia Chapter.
Marvin J. Dainoff, Ph.D., CPE, is director of the Center for Behavioral Sciences at LMRIS. He has research interests in workplace ergonomics and systems approaches to complex systems. He is a Fellow
and past president of the Human Factors and Ergonomics Society,
and director, emeritus, of the Board of Certification in Professional Ergonomics. He is professor emeritus in the Department of Psychology
and founding director of the Center for Ergonomic Research, Miami
University, Oxford, OH.
by observing the actions of
supervisors and managers.
These perceptions are reinforced by social interaction
with coworkers, resulting
in a kind of consensus regarding the company’s true/
relative safety priorities (e.g.,
safety vs. productivity).
(Zohar, 1980). Safety climate reflects a company’s
state of safety at a discrete point in time.
The number of scientific studies on the topic
has rapidly increased in recent years, with emerging evidence supporting safety climate as a robust
predictor of safety outcomes (Christian, Bradley,
Wallace, et al., 2009). In 2009, Zohar joined author
Huang of LMRIS’s Center for Behavioral Sciences
to launch an extensive safety climate research initiative that continues today.
©istockphoto.com/andresrimaging
Safety Climate vs. Culture
Safety climate is often confused with safety culture. In fact, these terms describe two related but
somewhat different phenomena. Safety culture is described as shared norms, values and beliefs that set
expectations for acceptable behavior within an organization and are taught to new employees through
socialization (i.e., the way we do things around here).
On the other hand, safety climate refers to employees’ shared perceptions of the true/relative priority of
safety (i.e., how employees perceive the company’s
commitment to safety as it is lived out, or not, every day). Research indicates that safety climate can
be used to predict safety behavior and safety-related
outcomes (e.g., incidents, injuries) in a wide variety of
settings. While safety culture cannot be easily measured directly, safety climate can serve as an indicator/measure of safety culture.
Importance of Safety Climate
Safety climate can serve as a frame of reference
for developing clear expectations regarding employees’ safety-related actions and the expected reaction from management. Thus, in a company with
a high safety climate level, employees might perceive that they are encouraged to maintain good
safety practices despite increased production pressure. Consequently, they behave safely. Employees
usually develop these perceptions and expectations
Perceptions at Different
Management Levels
The question can then be
raised: Who is the company?
Is it the executives, my supervisor or my coworkers? Since
organizational consistency
throughout different levels of
managers is a key aspect of
climate, safety climate is best
measured at different cascading levels. Scientific research
suggests that it is important
to capture the employee’s
perceptions of his/her immediate supervisor with
regard to safety, as well as his/her perceptions of
the overall company or top management with regard to the value placed on safety. Safety climate
researchers refer to employees’ perceptions of their
immediate supervisors as group-level safety climate, while their perceptions of top management
are referred to as organization-level safety climate.
A comprehensive safety climate study would include questions regarding both levels.
The Safety Climate Lone Worker Study
Safety climate research has typically focused on
traditional workplaces in which supervisors and
employees share the same physical location. Zohar and Luria (2005) gained industry acclaim with
their development of a safety climate survey containing 32 questions, which laid the groundwork for
measuring safety in organizations. This survey was
generic in the sense that it was intended to apply
to different types of industries and work settings.
The LMRIS study team sought to expand on this
research to examine the safety climate of lone workers. A lone worker is an employee who works alone
and who performs an activity intended to be carried
out in isolation from other workers, without close or
direct supervision (Hughes & Ferrett, 2009).
Given that lone working is becoming increasingly prevalent across various industries (e.g., truck
drivers, utility workers, teleworkers), it is important
to conceptualize the effect of this work environment on organizational climate emergence. Safety
climate can be important for this unique population because it can act as a frame of reference that
guides safety behavior. Employees receive cues
from others within the company and formulate
perceptions that may ultimately impact their own
behavior. This was an opportunity to see how lone
workers process these cues from afar and how they
behave when no one is watching. With this goal
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in mind, the LMRIS researchers developed a new
safety climate survey with items applicable to all
lone workers and two industry-specific surveys
with additional content focused on truck drivers
and electric utility workers.
Research Objectives
The LMRIS study’s primary objective was to better understand safety climate in the lone worker
environment and its potential impact on safety
performance. To accomplish this goal, the authors
first developed and tested the validity of a generic
safety climate survey geared toward lone workers.
As a first step, researchers adapted 12 of the 32
items from the Zohar and Luria (2005) scale that
would apply to lone workers. The second step involved expanding on this knowledge to develop
two valid, reliable safety climate surveys designed
specifically for truck drivers and for utility workers. These surveys would be more comprehensive,
considering the specific attributes of these industries. Each survey gathered information on the two
levels noted: top management (organization-level)
and immediate supervisors (group-level).
Scientific Integrity of the Surveys
In this case, the survey measures the construct
of safety climate and assesses the quality of the
measuring process itself. How can one know
whether the survey is measuring what it is intended to measure? A person need not be a scientist to
create a survey, hand it out to a group of people
and analyze the responses. However, the responses may be difficult to interpret and may potentially
be ambiguous (i.e., not reliable or valid). Therefore,
Psychometric Measures
Arising with the advent of psychology as a field of experimental
study in the late 19th century, psychometric methods are central
to the scientific study of behavior and mental processes. Some of
the methods used in this study are (Guilford, 1954; Psychometric
Society, 2016):
•Psychological scaling: Originating in psychophysics, the
measurement of subjective perceptions by examining responses
to stimuli using models established empirically.
1) Reliability: Consistent patterns in the measures obtained.
2) Validity: Measurement of what is intended.
•Correlation: A statistical method to determine the relationship between two variables that results in a correlation coefficient
(values ranging from -1 to +1). The further the coefficient is from
zero, the stronger the relationship is between variables. A positive correlation means that as the value of one variable increases,
so does the value of the second variable. A negative correlation
means that as the value of one variable increases, the value of the
second variable decreases.
•Regression: A statistical technique used to predict criterion
performance on the basis of predictor scores. Regression permits
the prediction of the score on one variable (the criterion) based
on the score changes on another variable (the predictor). Multiple
regression allows prediction on the basis of multiple predictors.
•Factor analysis: A statistical procedure for describing the
interrelationships among a number of scale items. Factor analysis
tests these relationships and determines how items cluster into
different dimensions/factors.
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when a company plans to conduct a survey, either
directly or through a consultant, it is important to
carefully evaluate the evidence, specifically, the reliability and validity of the scales.
Psychometric measurement is one aspect of the
general field of measurement that also includes
physical measurement (see “Psychometric Measures” sidebar). For example, consider a familiar
physical scale. Imagine that you are standing in
front of two bathroom scales. Your true weight
is 150 lb. You step on the first scale three times,
resulting in the readings 150, 120 and 140 lb. You
step on the second scale three times, resulting in
the readings 172, 172 and 171 lb. The first scale
gives inconsistent readings. Clearly, something is
wrong with that scale’s mechanism, therefore it
is not reliable. The second scale gives consistent
readings that do not indicate your true weight. The
scale may be incorrectly calibrated, therefore it is
not valid. Simply put, a valid scale measures what
it is supposed to measure. While the principles of
reliability and validity apply to any measurement
activity, psychometric methods are sets of scientific
best practices that help to ensure that these surveys result in scales that can accurately measure
psychological concepts such as safety climate.
Reliability
Reliability, in scientific terms, is usually described
as the repeatability and consistency of a test. Various scientific methods assess whether a scale is
reliable. For the purpose of safety climate scales,
researchers examined the internal consistency reliability, which looks at the patterns of response from
a single administration of a survey. This approach
estimates what would happen if we split the survey
response into two halves multiple times. The estimated average correlation between these halves is
called the coefficient alpha, which is a measure of
consistency. From a practical perspective, unless a
measurement scale has a reasonable degree of reliability (coefficient alpha equal to at least 0.7) it is
not useful for interpretation purposes.
Validity
Validity signifies the strength of a test and
whether its results are accurate. Many different
methods assess whether a scale is actually measuring what we think it should; for this study, researchers used three basic approaches.
1) Content validity indicates whether the content of items actually corresponds to the underlying concept that the survey is supposed to measure
(e.g., safety climate), and whether the meaning of
each item is clear and intuitive. This is typically attained by careful review of potential items by fieldbased subject-matter experts.
2) Criterion-related validity is assessed by correlating individual scores on the measurement
scale with some corresponding outcome (criterion)
measure. Outcome measures can be collected at
the same time as the survey (i.e., concurrent validity) or at some time in the future (i.e., predictive validity). For example, if we include a scale of safety
Figure 1
Correlation Table of Safety Climate Scores
& DOT Records
behaviors when we measure safety climate, these
behaviors can be considered outcome measures.
In this case, each individual is reporting the likelihood of his/her specific safety-related actions. To
the extent that a positive correlation exists between
self-reports of carrying out these actions and safety
climate, the safety climate scale has some degree of
concurrent validity.
If we can collect actual incidents (e.g., injuries,
near-hits) 6 months following the initial safety climate survey, then correlate each person’s safety
climate score with his/her incident score, we have
a stronger argument. This is called predictive validity since we can argue that safety climate predicts
lagged safety outcomes (i.e., a sustaining predictive relationship between safety climate and safety
outcomes). In practice, it is more difficult to collect outcome data 6 months later, so most studies
rely on concurrent validity. However, the LMRIS
team could collect both participants’ self-reported
safety behaviors and objective incidences of accidents, injuries and near-hits, one concurrently and
the other 6 months after survey implementation
(Figure 1).
3) Factorial validity assesses how well the items
cluster together into factors, which can relate to the
underlying construct we are trying to measure. An
advanced statistical procedure called factor analysis
is used for this purpose. Survey designers generate more items than will appear on the final survey. Factor analysis is an effective method through
which good items can be selected and bad items
can be excluded, based on factor loadings.
These statistical methods may not be practical or
feasible for everyone, but they are excellent tools
to help researchers develop a scientific survey. In
this case, it helped to ensure that the surveys being
developed would result in a trustworthy scale for
practitioners. It would benefit anyone considering
implementation to inquire about the scientific reliability and validity of a survey being considered.
Survey Process
For the lone worker safety climate study, researchers utilized scientific best practices to develop a procedure that was systematic and exhaustive.
They wanted to ensure that the content of the surveys would reflect an organization’s state of safety,
and be relevant to the participants in their respective jobs. The process entailed several steps.
Information Gathering
First, the project team conducted an extensive
literature search and review on trucking, utility and
lone work for contextual background information.
Team members talked with subject-matter experts
in each industry to build on this knowledge. The
team conducted in-depth interviews with 53 truck
drivers and supervisors, and 38 utility workers to
learn from lone workers about their jobs and what
safety issues are important to them. Team members also spent several days in the field shadowing
workers on the job and observing these safety issues in practice.
Question Development/Item Generation
Raw items were generated to formulate potential
survey questions. Items were based on the information gathered from both the available literature
and directly from workers and industry experts.
Given the large number of participants and various
issues that surfaced, a large number of initial items
were generated. For example, for the trucking survey, more than 100 initial items were developed;
many overlapped in basic content, but it was important to capture everything.
Cognitive Testing & Pilot Testing
Once questions were developed, they had to be
tested. Researchers needed to make sure they addressed issues that were meaningful to the workers
as related to safety in their jobs. The researchers
also wanted to ensure that the wording was clearly
understood by respondents, and that the terms
and phrasing were applicable to their industry.
To accomplish this objective, the team conducted
think-aloud cognitive interviews with 38 truck
drivers and 45 utility workers. These interviews allowed researchers to examine the meaning of the
survey responses (for clarification) and to observe
respondents for potential issues (e.g., events such
as long pauses, answers that are changed, indications of confusion).
Based on this feedback, researchers revised or
deleted some items, resulting in smaller, more refined sets of questions. Researchers pilot-tested
the revised surveys with 64 truck drivers for one
survey and 139 utility workers for the other to ensure that the instructions and questions were clear
and the overall survey administration was practical.
The researchers refined the surveys again based on
this feedback.
Implementation to Subsample
The two revised surveys were then implemented
at the pilot companies in both industries, with 1,891
truck driver respondents and 1,560 utility workers. The researchers conducted exploratory factor
analysis and coefficient alpha reliability to learn
what the responses were, how the items may have
grouped into themes, and whether these items
made sense within the context of the organization.
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The final surveys included 12 items adapted from
the original generic safety climate survey appropriate for lone workers, and additional items tailored
to jobs in each of the two lone worker industries
(28 items for trucking, 36 for utility). Incorporating
industry-specific factors provides a stronger value,
which makes these surveys a useful tool for the appropriate participants.
Implementation to Full Sample
The final industry-specific safety climate surveys
were then implemented at seven additional trucking companies with 6,556 respondents and one
additional utility company with 869 respondents.
At this point, researchers ran confirmatory factor
analysis on each to measure the validity of what
was found with the two pilot companies, reinforc-
Figure 2
Survey Process
Generation of initial questions based on:
•Review of scientific literature
•Interviews with subject matter experts
•Field observations
•Cognitive interviews
•Pilot tests
Development
Refinement of questions from pilot company
feedback
•Exploratory factor analysis
•Coefficient alpha reliability
Testing
Administration to full sample to confirm factor
structure
•Confirmatory factor analysis
Implementation
Matching survey results to outcomes to provide
criterion-related validity
•Subjective behavior ratings
•Subjective injury data
•Objective injury data
Validation
ing the grouping of potential themes for future
analysis. This provided an excellent basis on which
to offer these surveys to LMRIS risk control consultants to share with safety professionals and to the
public at large for use in the field (Figure 2).
Results
Study results showed that safety climate affects
safety behavior, even in the context of the lone
work environment. It found that safety climate is
a predictor of future injuries among these workers,
substantiated by objective outcome measures. Researchers validated that the generic safety climate
scale/survey was applicable to lone workers. They
also found that the industry-specific surveys were
even more predictive of future injuries than their
generic counterparts (Huang, Zohar, Robertson, et
al., 2013a, b).
Table 1 shows items contained in the lone worker survey, and Figure 3 shows mean ratings from
workers sampled in the studies by Huang, et al.
(2013a, b). The circled items in Figure 3 represent
the highest and lowest scoring elements according to the mean score statistic. Users of safety climate survey findings value the insights provided
by identifying high and low scoring items. This enables building on strengths to engage opportunities. The highest and lowest mean scores in Figure
3 indicate that participating companies tend to do
well, according to workers’ perceptions, in the area
of safety training (organization-level item 4), but
that management may not listen carefully enough
to their ideas about safety (organization-level item
5). Regarding supervisors, results showed that in
general workers felt that their supervisors do fairly
well discussing with them how to improve safety
(group-level item 1), but that they may sometimes
ignore safety rules when work falls behind schedule (group-level item 5).
table 1
Lone Worker Survey Items
Level
My company . . .
(organization-level)
My supervisor . . .
(group-level)
Survey item
1) reacts quickly to solve the problem when told about safety concerns.
2) is strict about working safely when work falls behind schedule.
3) uses any available information to improve existing safety rules.
4) invests a lot in safety training for workers.
5) listens carefully to our ideas about improving safety.
6) tries to continually improve safety levels in each department.
1) discusses with us how to improve safety.
2) compliments employees who pay special attention to safety.
3) is strict about working safely even when we are tired or stressed.
4) frequently talks about safety issues throughout the work week.
5) refuses to ignore safety rules when work falls behind schedule.
6) uses explanations (not just compliance) to get us to act safely.
Note. From “Development and Validation of Safety Climate Scales for Lone Workers Using Truck Drivers as Exemplar,”
by Y.H. Huang, D. Zohar, M.M. Robertson, et al., 2013, Transportation Research Part F: Traffic Psychology and
Behavior, 17, pp. 5-19; and “Development and Validation of Safety Climate Scales for Remote Workers Using Utility/
Electric Workers as Exemplar,” by Y.H. Huang, D. Zohar, M.M. Robertson, et al., 2013, Accident Analysis and Prevention, 59, pp. 76-86.
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Survey Use in the Field
More than ever, stakeholders in safety are interested in sustainable and
affordable risk-reduction
strategies. In essence, an increased demand exists for
safety process initiatives that
are smarter, more lasting and
produce higher returns. Surveys that combine science
with efficient technology can
diagnose the current state of
an organization’s safety climate and identify opportunities for real improvements.
It would be counterproductive for all concerned if a
survey designed to measure
safety climate were administered and interpreted in such
a way that reliability and/or
validity were compromised.
Certain measures can help to
figure 3
Mean Scores of Lone Worker Survey Items
maintain a survey’s scientific integrity when used
in the field and strengthen employees’ engagement in the process.
•Invite all company employees for equal opportunity to participate.
•Emphasize that participation is voluntary and
confidential.
•If possible, utilize a third-party administrator to
collect, store and process data.
•Analyze responses in a systematic and objective process.
•Present results to all company representatives.
•Engage all employees in follow-up action steps.
There may be pressure to drop certain items or
add others, perhaps for fear of exposing weaknesses. This is not an option; the integrity of the scales
is based on keeping them intact.
Adequate Participation
The first requirement for successful application
of the safety climate survey is sufficient time and
resources to engage in the process. For results to
be meaningful, it is important that all employees
have an opportunity to take the survey and that the
response rate is adequate. For a sample to be representative, more data are ideal. Fewer responses
from a group offer less representation and could
also lead to a breach of anonymity. Random selection means that each employee has an equal
chance of being selected. The more data obtained
from a random sample, the more representative it
will be of the entire organization.
The company should inform employees of the
opportunity to participate, explain the confidentiality of individual information and the purpose of the
survey, and convey management’s commitment to
improving safety. A fine line exists between encouraging employees to participate in the survey
and pressuring them to do so. Coercion may result
in response bias (i.e., respondents giving answers
that differ from their true feelings). Response bias
can make it difficult, if not impossible, to interpret
survey results. It is critical to emphasize that, although encouraged by the company, participation
is strictly voluntary and confidential.
Management Commitment & Support
The second and likely most important requirement is management’s commitment to act on the
results. By definition, safety climate surveys focus
on discrepancies between management statements
and actions regarding true priorities toward safety.
Management must commit to recognize, share and
act positively on results.
The behavioral safety community warns against
soliciting input from the employee population,
then failing to act or change accordingly. In addition to acting on the results, the response must be
viewed as timely by the employee base. Management acting too late may be just as problematic
as not responding at all. If the organization is not
prepared to address possible gaps identified by the
evaluation, it may not be ready to participate in a
safety climate survey.
Note. n = 9,895 from 10 participating companies. From “Development and Validation of
Safety Climate Scales for Lone Workers Using Truck Drivers as Exemplar,” by Y.H. Huang,
D. Zohar, M.M. Robertson, et al., 2013, Transportation Research Part F: Traffic Psychology and Behavior, 17, pp. 5-19; and “Development and Validation of Safety Climate Scales
for Remote Workers Using Utility/Electric Workers as Exemplar,” by Y.H. Huang, D.
Zohar, M.M. Robertson, 2013, Accident Analysis and Prevention, 59, pp. 76-86.
Survey Format
Web-based survey technology makes it easy
to collect responses anonymously and to archive
them confidentially. While computer access is
not universal, access to web-enabled devices has
grown. Popular electronic survey platforms provide ease of use on many devices. Paper should
be considered a last-resort means for safety climate surveys. In such cases, OSH professionals
should develop contingencies to demonstrate that
respondent anonymity and response confidentiality are preserved. An example would be to have a
transcriptionist input sealed paper responses into
a web-based platform, then destroy the paper version after input. Accessibility by illiterate respondents should also be addressed. This can involve
recruiting a trusted coworker (not a supervisor) to
assist in completing the survey.
Results Analysis & Interpretation
OSH professionals must recognize that measuring safety climate is not an end in itself but a point
of departure for discussion. The act of surveying is
a diagnostic process, not an intervention. The fact
that strong evidence shows that safety climate is
a leading indicator of safety outcomes does not
mean that measuring it leads to a quick fix or automatic result. Rather, measuring safety climate
is a useful tool for focusing examination of safety
management systems to reveal actionable insights
on how to improve those systems. Organizations
should view safety climate findings as opportunities to engage the entire organization in elevating
safety as a daily priority, not as performance measures for individuals.
The scientific rigor used to develop valid and
reliable survey instruments draws on complex
statistical methods, as shown in Figure 2. Companies using these instruments will find value in
much simpler analytics and findings. Mean scores
derived from aggregated safety climate survey responses have significant value as comparative statistics. As noted, they are used in research to assess
and verify reliability and validity. The proliferation
of safety climate studies has made possible categowww.asse.org
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ProfessionalSafety 33
acted on is critical. This can be viewed as a springboard for fresh ideas to produce impactful, lasting
improvement and should incorporate:
•sincere thanks to respondents;
•reiteration of the survey purpose;
•summary of findings, including both strengths
and opportunities;
•outline of what will be done to act on the opportunities;
•encouragement for everyone to contribute to
the plan;
•commitment to continuous improvement.
Companies that use group-process problem
solving will recognize the value and utility of a
team approach to sustainable safety climate improvement. OSH professionals have a pivotal role
as facilitators of the group process, resources for
technical guidance and overseers of adjustments
made to safety management systems. Everyone
in the organization has a stake in the output of
cross-functional teams, but, practically speaking,
not all can participate in them. Operational leadership is the investing sponsor of the team’s efforts.
These individuals should be highly visible through
presence in key discussions and responsive to recommendations by the teams, providing periodic
progress updates for all.
Reviews of survey findings summaries, such as
those illustrated in Table 2, have been put to good
use by companies to initiate team discussions.
Meeting facilitators find value in establishing that
the team’s focus is understanding contributing
factors to items with both the highest and lowest
percentage of agreement, leveraging perceived
strengths to act on potential opportunities. Companies using safety climate surveys typically find
that this approach produces a flow of ideas from
which adjustments can be made. A best practice in
one group often can be adopted by another (see
“Listening Carefully” sidebar).
Su
