Food Safety Risk Assessments are “Data Hungry”

December 29, 2023

Video Transcript

TITLE CARD: Neogen Analytics

[Music]

TITLE CARD: Re-synchronizing the Gears: Make Data Actionable

TITLE CARD: David Hatch — VP, Digital Solutions Marketing, Neogen

[A screen shows videos of David Hatch and Dan Dwyer speaking.]

Dan Dwyer: Dave, you were recently at a customers annual food safety summit. While you were there, you were able to experience a sophisticated risk assessment workshop and you had mentioned that risk assessments are "data hungry". What did you mean by that?

David Hatch: Yes. You know, it was quite an experience, Dan. I got to sit in a room with the food safety team from a global organization. They were looking at both a hazard analysis and a risk assessment. The hazard is the thing that causes danger. The risk assessment is determining how probable is this thing to happen? And, if it happens, at what frequency does it happen? And, then how severe is the problem, if it happens? So there's multiple factors in a risk assessment and as the group went through this, it occurred to me just how data hungry this process really is! Right? Because for each different hazard, you have to understand things like, well, "How frequently could this happen?" And without data around the actual occurrences of how frequently it happens, you have to kind of guess at it.

[The screen shows the Floorplans screen of the Neogen Analytics software with a facility floorplan marked with different colored dots for testing points. The screen returns to showing videos of David Hatch and Dan Dwyer speaking.]

David: And it occurred to me that, "Gosh, would be really important in a risk assessment to have records of how many times has a certain pathogen has been discovered in a food production facility; how frequently was that discovered, and, then, what's been the severity of the outcome? Did an entire run of production need to get scrapped as a result? Was there a recall or was it discovered soon enough that something could have been done to defray that risk?

Dan: Dave, what were your takeaways coming out of that risk assessment?

David Hatch: That had to do with managing and accessing data. There's a huge difference between that perceived risk and then the real risk assessment using data. So for me, I came away feeling like, you know, it's really important what we're doing here with Neogen® Analytics. Our customers are able to see that data on a daily basis.

[The screen shows the Insights screen of the Neogen Analytics software. The tab for "FSQA" is highlighted. Other tabs are for "Drill Anywhere", "Pathogens", "Indicators", "Audit", and "Corrective Actions". There is a line graph showing "# Non-conformance" along the y-axis and "Sample Week" along the x-axis. Also shown are a table for "# Tests" and a grid of "Nonconformances by Zone". The "Nonconformance by Zone" heat grid is a 4 by 4 squares. Along the y-axis of the grid are labels of zones. Along the x-axis of the grid are labels for facilities. The screen returns to showing videos of David Hatch and Dan Dwyer speaking.]

David: They can update the trend line and show, you know: "Are we seeing an increase of incidences that really are adding to our risk?" "What are we doing about that?" "How effective is that over time?" And with that kind of information, when you come back to do a risk assessment, you're able to really pinpoint the actions that are going to have an impact on lowering your risk.

[Music]

TITLE CARD: Neogen Analytics

 

By: David Hatch
Vice President of Digital Solutions Marketing
Neogen Corporation

Recently, I was invited to be a guest speaker at a customer food safety team summit and was also privileged to participate in a risk assessment workshop led by a third-party consultant at the event. During my 30-plus-year career, I have been through many different types of risk assessments across several industry segments. I have been a participant seeking to define and address risk at my own organization, as well as a consultant helping my clients perform their own risk assessments. Each time I experienced a risk assessment exercise, I learned something new — and this time was no different. The key learning for me in this case is encapsulated in the title of this blog: Food Safety Risk Assessments are “Data Hungry.”

What does this mean?

As we went through the workshop exercise, we explored the elements of risk. Specifically, risk is defined as a combination of three factors: Is something POSSIBLE; how PROBABLE is it to occur; and what is the potential SEVERITY if it were to occur?

  • The first element – POSSIBILITY. This is a yes/no question. Anything that CAN POSSIBLY happen should be included in the assessment.
  • The second element – PROBABILITY. This is measured on a scale. In our exercise, we assigned probability to a scale of 1–5 (least to most probable).
    • A subset of probability is the expected FREQUENCY. This is a tricky one. If something has been occurring over time, then the frequency is known and can be easily factored into the PROBABILITY scale. If it is a newly discovered issue, then “expected frequency” becomes an exercise in guesswork — one that must be refined over time. In our exercise, frequency was measured on a scale of 1–5 (least to most frequent).
  • The third element – SEVERITY. As with probability, we also used a 1–5 scale (least to most severe) to measure severity.

The room then proceeded to use these elements and measurement techniques to assess risk across ten different scenarios. These included descriptions of foodborne illness, food safety testing outcomes, discovery of allergens, labelling mishaps, chemical contamination, food fraud, supply chain disruptions, and other risks.

The risk assessment included a worksheet laid out as a table, where each scenario could be prioritized and scored according to the risk measurement elements (Figure 1).

Figure 1: Example Risk Scoring Table

The room was divided into three teams, and each was asked to prioritize the various scenarios in order of highest to lowest risk. Each group completed this task, and here is where things got interesting…

EACH TEAM HAD DIFFERENT RESULTS! As shown in the example table, a lower priority may yield a risk score above that of something that was originally considered a higher priority. Each team’s tables looked significantly different from the others. To be clear, these were not strangers performing the exercise with no knowledge of each other’s priorities. In fact, the three teams comprised the global food safety leadership of one company — yet each team seemed to have VERY different ideas on risk prioritization. This unexpected result caused some lively discussion; meanwhile, the consultant leading the exercise was the only one in the room who was not surprised at all by the results.

Here's why:

There was one more factor to consider — one that was on the minds of each team, but not openly expressed as a factor for prioritizing risk. The consultant then asked the room to describe what TYPE of risk they were thinking about from the following four categories:

  • Public Health
  • Reputation
  • Regulatory
  • Business Operations

The room concluded that the TYPE of risk had a definite impact on how the risk was originally prioritized. Each team had set out their prioritization criteria based on a preconceived risk category, and each team’s selected category turned out to be different. Depending on which of the four risk types or objectives was dominant, a different prioritization and risk scoring resulted.

Finally, this is where the “data hungry” concept factors in. The final analysis revealed that a risk scoring exercise conducted in this manner is capable of yielding only a “perceived risk” score. While perception is a good start, an actionable risk assessment should be based on actual outcomes and experiences. The availability of real-world data, collected over time, has a dramatic impact on validating perceptions.

For example, the availability of pathogen testing diagnostic data, along with the probability, frequency, and likeliness of occurrences, would allow a risk assessment score to be based on a historical trend, rather than a perceived level of frequency and probability. A risk assessment exercise would be informed by the data, and a score of 1–5 could be applied with far more confidence.

Data, in the words of one of the participants, “removes the guesswork and assumptions” within a risk assessment. My new learning was just as succinctly felt: “Data is the necessary element to transform risk perception into risk knowledge.” While it is useful to perform a risk assessment based on perceived scoring and prioritization, it is ESSENTIAL that a risk assessment be validated with real data.

To learn more about Neogen’s food safety testing automation capabilities, and how real-world data can be collected, aggregated, and delivered with reporting and analytics that can feed a risk assessment exercise, click here.

Learn More About Neogen Analytics


Category: Food Safety, Consumer Goods, Dietary Supplements, Food & Beverage, Pet Food, Allergens, Microbiology, Pathogens, Environmental Monitoring