Measuring Food Safety Culture in Food Manufacturing-59-173-1-50
Measuring Food Safety Culture in Food Manufacturing-59-173-1-50
Measuring Food Safety Culture in Food Manufacturing-59-173-1-50
Introduction
Maturity models and social cognitive models were identified in the literature review as a
possible way of measuring food safety culture and both of these methods were explored to seek
answers to the overall research questions posed by this work. Approval was given from the
Research Ethics Board at the University of Guelph to collect data involving humans.
Through the literature review, it was evident that to understand what food safety culture
culture, food science and social cognitive science. Organizational culture can be considered
different from other cultural definitions (e.g., geographical, national culture) and consists of
generic attributes such as artifacts, espoused values, beliefs, and ways to characterize culture
regardless of the area, function or discipline. The perspective from food science brings food-
specific considerations, such as working environments, and how to measure and evaluate these.
Food science searches for answers to questions related to the definition and quantitation of risks
associated with a given product and process, introducing risk management concepts, such as
HACCP, to evaluate how an organization manages its long term and daily decisions to ensure the
safety of their products. The third perspective from social cognitive science brings methods to
define, measure, and predict human behaviours. Methods from social cognitive science can be
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the scope of its own rules and values. For example, a manufacturer is guided by a set of values,
one may be, for example, dare to be transparent. This value could be translated into a behaviour
such as this: “Today I told a new colleague that he missed sanitizing his hands after washing and
helped him understand why this is important to the safety of our food.”
Cultural dimensions
Five dimensions of culture were chosen as the theoretical framework to organize the
various theoretical perspectives, food safety capability areas, and food safety culture measures.
The cultural dimensions defined by Schein (2009) were used to characterize culture and have
been applied extensively in research and practical culture studies (Table 1-2). It is important to
note that a dimension contains many characteristics. These attributes guided the literature review
in determining where studies have already been completed and where gaps still exist.
Method
Two methods were applied to develop the food safety maturity model and the behaviour-
based scale. An industry panel was engaged to assist in the development of the content of the
model and a social scientist to assist in breaking down the individual components of the model to
pinpoint behaviours.
Capability areas
The capability areas, and the subsequent food safety maturity model, were developed
with a panel of industry experts: Dr. John Butts, Raul Fajardo, Martha Gonzalez, Holly Mockus,
Sara Mortimore, Dr. Payton Pruett, and John Weisgerber. The experience of leaders in food
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manufacturing was critical to capture as no reference was found to an existing food safety
maturity model. The individual expert was chosen based on the person’s demonstrated
knowledge, experience, and leadership as evident in their biographies (Appendix C). A seven-
member panel was struck to meet quarterly during the development phase of the maturity model.
The purpose of a capability area is to translate a generic cultural dimension into areas of specific
importance to food manufacturers. As such, the capability area links a generic cultural attribute,
e.g., training, as part of the cultural dimension reality and truth to food manufacturing specific
language and priorities, such as performance of a manufacturer’s people system, which also
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Table 3-1: Mapping theoretical perspective to cultural dimensions and capability areas
relationship
relationship
The five capability areas represent the core of the food safety culture measurement
system and the capability areas were all defined individually on a scale of maturity in the food
safety maturity model. The Perceived value describes the extent to which food safety is seen as
only a regulatory must (stage 1) or as critical to business performance (stage 5). People systems
Process thinking describes how problems are solved as independent tasks (stage 1) or problem
solving is seen as an iterative process built on critical thinking and data (stage 5). Technology
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enabled describes how the organization turns data into information; manual and independent
(stage 1) compared to automatically and as part of a company-wide information system (stage 5).
Tools and infrastructure can be illustrated by whether an employee needs to walk far to a sink
(stage 1) or sinks are conveniently located (stage 5). These descriptors are similar to those
developed by Greenstreet Berman Ltd. and adopted in the Food Standards Agency Food Safety
Behaviours were defined based on the descriptors in each maturity stage and capability
area with the guidance of social scientist, Deirdre Conway. The list was discussed with
stakeholders in the participating company to pinpoint and select those behaviours believed to
have the most impact on the descriptor in the maturity model. All pinpointed behaviours were
The objective of the scale was to collect data related to the overall group segments (plant,
function, and role). The scale was constructed as a self-assessment tool and each participant was
asked to rate their own behaviour against a series of questions and statements. Answers were
grouped into demographic attributes and the behaviour predicting variables; attitude, perceived
control, social norm and past behaviour and intention for each of the capability areas.
Each question in the scale was structured the same way for each variable and for each
pinpointed behaviour. For example, a question regarding the variable attitude would read “My
behaviour to always design my own tools such as spreadsheets and forms to gather food safety
data is…” and the participant was asked to rate how strongly this reflected the respondents
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attitude on a scale from 1 (beneficial) to 5 (harmful). Every question related to the variable
attitude was structured this way and rated on similar scales (Table 3-2).
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data…
Perceived I am confident that for the …always design my own tools e.g.
data
Social Norm Most people, outside –and …always design my own tools e.g.
Past Behaviour I have in the past three …always design my own tools e.g.
data
data
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The responses from survey participants were analyzed in data were imported into Minitab
10 (Minitab Inc. State College, PA) using an anonymised numbering convention. Minitab 10 is a
general-purpose statistical software package designed as a primary tool for analyzing research
data. The examination of the data was conducted using descriptive statistical principles and
statistical tests (e.g., ANOVA) to explore differences between levels, roles, plants, and maturity
stages.
Scale administration.
The data were collected in a Canadian food manufacturing company from February to
April 2014. The company employed approximately 19,000 employees across 48 plants at the
time of data collection and produced meat and meals. The scale (Appendix E) was constructed to
gather data for all capability areas in the food safety maturity model. The scale was administered
through an online survey tool and all responses were anonymous and each respondent was
rewarded with a $5 product voucher for their participation. Employees in supervisory roles and
leadership positions (n=1,030) within the two functions food safety and quality and
manufacturing were given the opportunity to participate. Survey responses were received from
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Results
The food safety maturity model (Table 3-3) was developed based on learnings from the
literature review and input from the industry expert council. There are five stages of maturity in
the model. Stage 1 is Doubt and is described by questions such as “Who messed up?” and “Food
safety – QA does that?” Stage 2 is React to and described by questions and situations such as
“How much time will it take?” and “We are good at fire-fighting and reward it.” Stage 3 is Know
of and is described by statements such as “I know it is important but I can fix only one problem
at a time.” Stage 4 is Predict and described by statements such as “Here we plan and execute
with knowledge, data and patience.” Stage 5 is Internalize and described by situations such as
Each intersection of a stage (e.g., doubt) and a capability area (e.g., perceived value) was
defined by completing the sentence “We [STAGE] food safety and our [CAPABILITY AREA]
are described by X.” For example, in the case of doubt the perceived value X would become
“completing tasks because regulations makes us.” Each definition was discussed and the industry
expert panel reached a consensus on the most important one or two definitions and did not
produce a comprehensive list of definitions, as this was thought to be of little value when
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Capability Area
Tasks are completed Little to no investment in Issues are solved one at a Preventing issues from We consider food safety
because regulatory systems (people or time to the root of the occurring based on past an avenue to continuous
agents tell us to. processes) to prevent food issue because we know it history and leading improvement.
Perceived Value
Performance data is not Little understanding of true Strong, data-based
stakeholders.
Completing tasks by top- Responsibility for problems Evidence of Defining and proving Strategic directions
People System down "tell" without is established as problems understanding the need antecedents for improving across the organization
evidence of individual are discovered and solved for food safety systems. processes through and its functions to
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Capability Area
responsibility and mostly by use of negative knowledge and data. include food safety as a
accountability and
safety performance.
People Systems Tasks being completed Antecedents being invented Improvements are made Responsibilities and Pinpointed behaviours
out of fear for negative as problems are solved and one issue at a time with accountabilities are and consequences are
consequences. seldom incorporated in clear responsibility discussed and carefully defined and continuously
communicated.
approve the accuracy of managed when an error and negative - are defined
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Capability Area
planned consequences.
Process Thinking Unstructured problem Continuous improvement Structured problem Continuous improvement Risks are identified
solving to remove the with emphasis on solving with a high risk with emphasis on study through horizon scanning
immediate pain. checking/inspecting and of over analyzing not checking or and continuous
expectation of 100% problems and continuous inspecting .It is generally improvement as part of
perfect solutions from the improvement accepted that the food safety system.
iterative.
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Capability Area
Technology Little to no technology Responsibility left to the Standard technology is Data is collected in a Data is used in an
Enabler adopted and few people individual to identify data adopted and provided to consistent and accurate integrated way to
realize this to be an needed and a high degree the individual user in a manner to inform the automate workflows,
issue. of reliance on the standardized way. continuous improvement provide tools to improve
is used sporadically to
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Capability Area
Tools & Necessary tools are not Need for tools or Investing readily in the Food safety tools and Investment in tools and
Infrastructure available to everybody. infrastructure changes right tools and infrastructures are in place infrastructure is
when problems arise that infrastructure when and continuously evaluated at part with
require immediate solves. solving a problem improved for ease of use other business
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Pinpointed behaviours.
Each role and function had a minimum of 25 pinpointed behaviours that were used in the
self-assessment scale to determine maturity level (Table 3-4). As such, a Food Safety and
Quality supervisor might associate with the following behaviour “I rarely have time to identify
root cause of problems and mostly find myself firefighting.” This behaviour is the pinpointed
behaviour for the process thinking capability area when the supervisor finds her or himself at the
maturity stage of doubt. If the supervisor found her or himself in the maturity stage of
internalized within the process thinking capability area the behaviour “I collect, analyze and
report food safety data daily to plant staff to bring transparency to emerging challenges” might
resonate more.
Each pinpointed behaviour was designed to include four components: action, target,
context and timing for consistency and specificity in definition of each of the behaviours
(Fishbein & Ajzen, 2009). For example, “I always design my own tools such as spreadsheets and
forms to gather food safety data,” which was a pinpointed behaviour for the Food Safety
supervisors in a maturity stage of doubt and within the capability area technology enabled.
important to the individual role but were suggested as the most critical behaviours in each
It was hypothesized that pinpointed behaviours were different for the two functional
areas: manufacturing and food safety. It was also hypothesised that pinpointed behaviours
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differed between the four roles: supervisor, leader, functional leader and executive. Pinpointed
behaviours were defined for the two end-point maturity stages doubt and internalized (Tables 3-4
and 3-5). The complete set of pinpointed behaviours by function, role, and maturity stage can be
found in Appendix D.
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Table 3-4: Sample pinpointed behaviours by function (food safety and quality), role and competency
People System I immediately remove I provide my direct I always have to I make sure
I check if my teams
I always have to learn I plan improvements have the needed food I seldom get involved
without asking
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others .
Table 3-5: Pinpointed behaviours by function (food safety and quality), role and competency areas in
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People System I take action daily to I take action daily to I take action daily to I minimum monthly
and beyond for food others take action to functions of their business leaders to
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business decisions
The overall company behaviour-based maturity is in maturity stages react to and know of.
The capability areas perceived value and tools & infrastructure scored the highest average scores
of 3.1 in both areas. The capability areas people systems and process thinking scored within the
maturity stage of react to just ahead of the capability area technology enabler also within the
maturity stage of react to. Mean maturity score for each capability area and range (minimum and
maximum average by plant) were plotted on the maturity model (Table 3-6).
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Capability Area 0 .1 0 .2 0 .3 0 .4 0 .5 0 .6 0 .7 0 .8 0 .9 0 .1 0 .2 0 .3 0 .4 0 .5 0 .6 0 .7 0 .8 0 .9 0 .1 0 .2 0 .3 0 .4 0 .5 0 .6 0 .7 0 .8 0 .9 0 .1 0 .2 0 .3 0 .4 0 .5 0 .6 0 .7 0 .8 0 .9 0 .1 0 .2 0 .3 0 .4 0 .5 0 .6 0 .7 0 .8 0 .9
(Identifier)
Perceived Value l
l
People System l
l l
Process Thinking l
l l
Technology
Enabler
l l l
Tools &
Infrastructure
l l
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MEASURING FOOD SAFETY CULTURE IN FOOD MANUFACTURING.
The results would indicate that the organization’s mean maturity lies in the stages react to
and know of. Overall, no significant difference (p = 0.003) was found between maturity of the
food safety and quality function (N=306) and the manufacturing function (N=724). A difference
was found for one of the five capability areas namely technology enabled with the manufacturing
function being more mature than the food safety and quality function. The data collected by role,
supervisory (N = 890), leader (N = 223), and functional leader (N = 98), showed a significant (p
= 0.000) difference in overall maturity; ranking leaders highest on the maturity scale (mean =
2.096), followed by functional leader (mean = 2.080), and lastly supervisors (mean = 1.983).
A maturity model was developed for each of the eight plants (Appendix E) and the
difference between the plant’s overall maturity rating was evaluated using a one-way ANOVA
analysis. It was determined that there was a statistically significant difference between one or
The mean maturity score was calculated for each capability area and the overall maturity
of the plant. Percentage of maximum score (5) for each plant’s overall maturity was calculated as
a measure of the individual plant’s food safety culture strength (Table 3-7).
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Table 3-7: Mean maturity score by plant, capability area and total
Capability Area
infra- of total)
structure
Table legend: Food safety culture score by plant for each capability area. Each capability
area could average scores between 1 and 5 depending on the participants responds to each
capability area question. Maximum maturity level equals a score of 5 indicating a internalized
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state of maturity and minimum score of 1 indicating a doubt state of maturity. Average for each
plant was calculated and a percentage achieved calculated to quantify strength of each plants
The results would indicate that the average maturity of all plants are in the stages react to
and know of. Three plants (1, 6, and 7) had the strongest food safety culture with scores between
58% and 60% and ranging from 2.9 - 3.0 in average maturity score. Extrapolating from these
scores and the food safety maturity model, the culture in these plants can be described as one
where food safety issues are solved one at a time and a solid understanding of food safety
performance through data acquisition and analysis exists. There is a clear understanding of
responsibility and consequences are mostly managed when a problem occurs. These plants make
good use of data but can over analyze them. Technology has been adopted to help manage food
safety systems but it is unlikely that these plants uses their data to prevent problems from
occurring. Investments in tools and infrastructure are made when required to solve a problem.
The plant with the lowest score (Plant #5) scored 48% and its maturity scored placed it
in the react to stage. The culture in this plant can be described as one where there is little to no
investment in food safety and the perceived value of such an investment is not clear.
Responsibility for problems is assigned as they occur and antecedents (e.g., training, job
Problems are solved as they arise and there is little evidence of systematic continuous
improvement. In this plant the responsibility to decide what data to collect is placed on the
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individual and not the collective group and needs for investment in tools and infrastructure
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Discussion
The purpose of this research is to investigate existing literature for measures of food
safety culture and meet two objectives. The primary objective of the current study was to define
characteristics to assess food safety culture in food manufacturing. A second objective was to
assess and improve food safety culture. The result was, in this context, successful and it was
shown that a maturity model approach incorporated with a behaviour-based scale could be used
to characterize food safety culture and describe a roadmap for any given plant for maturing its
food safety culture. A detailed measurement tool was developed to assess overall food safety
The overall food safety culture was measured on a scale based on the reasoned action
model and food safety specific maturity stages. As a result, the food safety culture in plants of
this specific company ranges between maturity stage 2 react to and maturity stage 3 know of.
The organization finds itself in a stage of maturity where food safety is accepted as an important
part of business, decisions are increasingly made based on science and data, training is
increasingly standardized, and investment in infrastructure and tools are readily available as
needs arise. However, in certain plants, there is also a tendency to not invest in systems
(protocols or technology), that responsibilities for problems are assigned as problems arise, and
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When ranking the eight plants by maturity score and strength of their food safety culture
these all fell into the same maturity stages as the overall company and the strongest food safety
culture was measured at 60% (Plant 7) with the weakest at 48% (Plant 5). When the ability of
plants to meet food safety performance standards was assessed, Plant 7 was in the top half and
Plant 5 in the bottom half, which suggests that the two measures are related. There is no
correlation between the two strength measures (R-squared = 0.040) which is likely due to the
degree of clustering of the data around the 49% to 61% scores (Figure 3-1).
100%
90%
80%
70%
60%
Strength
50%
40%
30%
20%
Maturity strength
10% Performance standard strength
0%
1 2 3 4 5 6 7 8
Plant
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Figure legend: Food safety culture measures by plant. Strength of each measure;
performance standards and maturity was calculated by plant as percentage achieved of total
available score; performance standard max score was 53 (100%) and maturity max score 50
(100%).
Table 3-8: Plant ranking by performance standard score and maturity score
Performance
Maturity score
standard
Plant Plant
Mean score
Total score
(% of total)
(% of total)
Table legend: Food safety culture measures by plant. Strength of each measure;
performance standards and maturity was calculated by plant as percentage achieved of total
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available score; performance standard max score was 53 (100%) and maturity max score 50
(100%).
The overall company measures were segmented by function (food safety and quality and
Manufacturing) and role (Functional leader, Leader, and Supervisor). The role segmentation is
similar to that proposed by Griffith et al. (Griffith, Livesey, & Clayton, 2010a). The purpose was
to measure maturity for each function and test for differences. This can help a company target
In this specific case there was no difference in maturity between functions – food safety
and quality compared to manufacturing - and it would not be valuable for this company to
differentiate interventions as both functions are at the same food safety maturity level.
The purpose of the role segmentation was to measure maturity across the different formal
working groups and test if any group was more or less mature in their food safety sub-culture
than others. In this specific case a difference was detected. Both functional leaders and leaders
rated the level of food safety maturity significantly higher than the ratings provided by
supervisors. This is very useful as the company can use this to re-evaluate its current food safety
interventions and decide if they are adequate for enhancing the rated maturity across the
supervisory group. This difference could infer that supervisors are less mature or actually
assessing the situation as it truly is. This should be explored in future research as an important
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The difference between roles is not surprising given the many references from
researchers of organizational culture and food safety culture to the importance of the group (Ball,
Wilcock, & Aung, 2009; Hinsz, Nickell, & Park, 2007). As such, the analysis would indicate that
the focus of this particular company on functional leaders and leaders is different to supervisors
and this represents a significant opportunity for improving food safety culture within each of the
eight plants. Each role is represented in all of the plants e.g., plant manager, quality supervisor,
and maintenance lead hand and by closing the gaps between roles a plant could improve its
overall food safety culture by bringing behaviours of different roles closer and potentially make
the strength of the plants food safety culture stronger and more sustainable.
The limitation with this research resides in the behaviour-based scale. The questionnaire
was long (96 questions) and it is believed to have influenced the final response rate. Measuring
food safety culture is a complicated matter and further research is suggested to modify the survey
questions based on the findings of this research. The expert panel was not selected at random but
built on knowledge and experience in the individual’s resume. This too could be perceived as a
This research suggests that combining a food safety maturity model with a self-
assessment, behaviour-based scale does provide factual answers for one meat processing
company, which can be applied to other food manufacturing facilities to characterize and
measure food safety culture. It brings a method to a question asked by many “what is food safety
culture?” and how to measure food safety culture that can influence a food manufacturing
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company’s intervention effort and priorities on its chosen maturity path. Is is suggested that
further data analysis is completed of questions to determine the basic questions for measuring
foods safety culture through a responds surface methodology with a multivariate responds.
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The purpose of this research was to search for ways to characterize and measure food
safety culture. The results suggest that some generic characteristic found in organization culture
theory can be applied to food safety. Two methods were identified to measure food safety
culture; a performance standard scoring system and a behaviour-based food safety maturity
model.
The food safety maturity model was built on the experience from food safety industry
expert panel and learnings from working maturity models in other disciplines (e.g., quality and
occupational health and safety). The overall food safety culture was measured using a behaviour-
based scale derived from the reasoned action model and food safety specific maturity stages. As
a result, the food safety culture for plants in one manufacturing company ranges between
maturity stage 2 react to and maturity stage 3 know of. The food safety maturity model describes
each maturity stage and qualitative descriptions of the manufacturing company can be drawn. As
such, the organization finds itself in a stage of maturity where food safety is accepted as an
important part of business, decisions are increasingly made based on science and data, training is
increasingly standardized, and investment in infrastructure and tools are readily available as
needs arise. There is also a tendency to not invest in systems (protocols or technology), that
responsibilities for problems are assigned as problems arise, and on occasions, the company
reacts to problems more than prevents them. Knowing its position the company can now make
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the literature review but it was also clearly stated that such a system would not cover all culture
characteristics. Although a difference was detected between the eight plants, no plant was found
with a maximum potential score and the strength of any plant’s food safety culture, measured as
percentage of maximum score, ranged between 48% to 62%. The scoring system is found
valuable as an input to a food safety culture measurement system but limited by coverage of
organizational culture dimensions in the three performance standard documents to stand alone as
In comparing the plant scores for each measurement system there does appear to be some
correlation between the performance standard and maturity scores. As such, six of eight plants
had less than 8%-points difference in the two scores and the other two had higher than 9%-points
difference. This suggests that in this specific context a relationship does exist and that the two
scores can be used to guide the individual plant food safety team on where to priorities efforts for
improvement.
The measurement system is unique in that it combines food safety performance standard
scoring with behaviour-based maturity. Performance scoring systems such as the Baldridge
award follow a similar model but in contrast to this research the Baldridge model does not take
specific food safety requirements or situations into account. Behaviour-based studies have
proved the applicability of social cognitive models to assess food safety (Ball, Wilcock, & Aung,
2009; Nickell & Hinsz, 2011b) and these studies clearly indicate the opportunity for the use of
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generic models in food safety. Maturity models are widely used in organizations to improve
processes and cultures (Crosby, 1972; Goonan, Muzikowski, & Stoltz, 2009), however, no model
has been developed specifically for food safety. The measurement system developed in this
research combines all of these learnings into one food safety culture measurement system. This
adds to our current knowledge of food safety culture by providing a quantifiable method for
Given the lack of a control group or other validation activities it cannot be precluded that
the performance scoring and self-assessment score covers all characteristics of food safety
culture. The research could be strengthened through validation activities such as focus group
interviews at a participating plant. The research was conducted within one food manufacturing
organization and without the opportunity to compare with other organizations. It is difficult to
say if the measurement system is robust enough to detect differences caused by the individual
organization, their geographical location, and the role they play in the global food chain (e.g.,
grower versus manufacturer versus retailer). It is recommended that research be carried out to
validate the measurement system in other organizations across the food chain and test the
model’s applicability to assess food safety culture across multiple organizations in the food chain.
The measurement system developed in this research can be used as a practical tool for
manufacturers to gain visibility as to the strength of their food safety culture and allocate
resources in those areas that need it the most in this changing environment.
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Appendix
Quantity.
Thirty-two publications were published in the period 2002 to 2014 (YTD) with 69% of
literature published after 2008 (from total 10 publications until and including 2008 to 22 from
Applied methods.
Of all studies under review, 53% used quantitative research methods such as
questionnaires and surveys. Some findings, 22%, was not classified as research and no method
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was assigned followed by 19% making use of empirical methods such as case studies and
literature reviews. Surprisingly only two studies applied a qualitative method and this was
interesting in a field that historically have been referred to as hard measure. Quantitative
measurement methods are the once most often used. (figure 2).
18
16
14
Count of References
12
10
8
6
4
2
0
Emperical Literature n/a Qualitative Quantitative
Review
Sector analysis.
Majority of the publications are related to food service (42%) followed by literature in the
category of general (22%). General publications are content related to the broader food industry
and not sector specific. Fewer publications were specific to food manufactures (19%) and the
remaining was found to target the retail sector and consumers (figure 3). Majority of the
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MEASURING FOOD SAFETY CULTURE IN FOOD MANUFACTURING.
publications were found in peer reviewed journals (75%) and the remaining in books and
magazines.
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Document Sub-measure Plant Plant Plant Plant Plant Plant Plant Plant
1 2 3 4 5 6 7 8
conformances
conformances
scorecard Performance
scorecard performance
(Visual inspection)
scorecard
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MEASURING FOOD SAFETY CULTURE IN FOOD MANUFACTURING.
Document Sub-measure Plant Plant Plant Plant Plant Plant Plant Plant
1 2 3 4 5 6 7 8
scorecard
scorecard
minutes
minutes engagement
minutes
minutes
Total 36 30 36 36 30 28 34 30
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Dr. John Butts, Ph.D. Food Safety By Design LLC and Vice President – Research,
Land O’ Frost is a privately held company and is the 3rd largest sliced lunchmeat brand
in the US. Dr. Butts has been in the primary technical role for 40 years and continues full time
employment with Land O’ Frost. As part of his succession plan Food Safety By Design LLC
was founded and consulting services outside of LOF are ongoing with the full consent and
support of LOF.
In 2010 FoodSafetyByDesign, LLC. was founded to help producers of high risk products
learn how to prevent and manage food safety risks. Risk identification and management by
methodology. Dr. Butts’ specialty is the incorporation of Food Safety Practices into company
culture. Preventative Controls have proven to be the most successful method to manage the risk
of environmental pathogens. Root cause identification using the Seek and Destroy Strategy
enables visualization of need. Interventions to manage high risk areas eliminate firefighting and
the solving of the same problem over and over again. The company culture next moves into the
preventative state and companies learn how to use data collected in their own facility to predict
In the early eighties LOF entered the shelf stable meal business with retort pouches. Dr.
Assurance.
Serving as a host and liaison for a technical exchange with a Japanese food
manufacturing company
Dr. Butts also provided technical and management support to Frigorifico Canelones, the
largest beef processing plant in Uruguay, from 1991-2001. LOF owned and managed this
Implemented a HACCP program to qualify for export to the US, EU, and Japan
The further processing portion of the facility was designed and built to
administration.
Active member of the Scientific Affairs Committee (SAC) for over thirty five
years
Board Membership’s,
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Dr. Butts is actively involved in pathogen reduction and control of pathogenic organisms
in cooked processed meat products, seafood, leafy greens and other RTE products .
From 1998-2000 he worked to develop practices and procedures to minimize and control
construction risk at an LOF plant undergoing multiple major high-risk construction projects
A focus has been on development of investigative tools enabling plants to identify and
control growth niches. The use of hurdle technology to minimize transfer to and within high risk
Current work includes the application of scientific principles and quality management
technology to develop Sanitation Process Control Methods and Procedures. This includes
identification and control of critical factors coupled with the deployment of a real-time
monitoring and visual training program delivered by a ruggedized tablet computer during the
sanitation process.
equipment design principles to allied trade groups, equipment manufactures and customers in the
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Equipment design and pathogen control presentations given to our equipment suppliers
both domestically and in Germany to top management as well as the design engineers
responsible for the sanitary design of equipment used in the United States.
Worked with Ireland Sea Fisheries Board and Australian (NSW Food Authority & Food
Standards Australia New Zealand (FSANZ)) to develop an Industry wide process for Listeria
Awards:
2005 Food Safety Leadership Award , NSF International presented at NRA national
convention
2006 Food Safety Magazine Distinguished Service Award recipient presented at Food
2008 Meat Processing Award from the American Meat Science Association. Presented at
2013 Certificate of Distinction, the highest award given by the Ag Alumni of Purdue
University
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