In practice, decisions in food operations are driven by a combination of:

• Available information 
• Perceived risk
• Experience-based judgment (i.e., "gut feel")
• Organizational signals about what really matters—speed, cost, compliance, or safety.

When food safety systems prioritize audit readiness and rules over judgment, leaders and production employees rely on habit and assumptions. When conditions change, those habits are often slow to adapt.

This may explain why food safety incidents continue to occur despite extensive foundational training, detailed HACCP plans, and increasingly sophisticated digital systems. An underlying issue is decision capability: the ability to recognize and interpret risk, challenge assumptions, and act appropriately at the point of risk.

In a 2023 article on decision-making,² McKinsey & Company describe decision capability as a process of choosing among options, a task that becomes more complex in organizational settings where roles, context, and competing priorities matter. Meaningful decisions emerge not just from data or rules, McKinsey & Company argues, but from clarity about who makes the decisions, the empowerment of those closest to the work, and the capacity to make choices in context.

This article moves the conversation forward. Rather than revisiting why audits and traditional compliance training fall short, the focus is on what actually improves food safety outcomes: how quality assurance professionals and frontline leaders can build better decision-making capabilities across the food supply chain.

These ideas align with the work of W. Edwards Deming,³ who emphasized that quality is not achieved through inspection alone, but also through systems and leadership practices that enable people to make good decisions. In food safety, this means designing processes, training, and culture to support sound judgement where it matters most.

Central to this shift is moving quality assurance (QA) from an audit-driven role to a strategic business partner, supported by senior leadership, frontline leaders, and a culture that reinforces risk-based thinking rather than adopting a compliance mindset.

Bloom's Digital Taxonomy Reframed: From Knowledge to Decision Capability

Bloom's Digital Taxonomy^4,5 is widely used to align educational outcomes to suit the intended learners. In this article, it is presented not as an abstract educational theory but as a framework for understanding how knowledge becomes actionable in the workplace.

Applied to food safety, the taxonomy describes a progression from simply recalling procedures to making informed decisions at the point of risk. Each level of training builds decision-making capability: understanding why procedures matter, applying them in context, analyzing deviations, evaluating risk, and ultimately creating improvements that prevent incidents.

This provides a clear roadmap for transitioning employees from understanding the rules to consistently making the right decisions in the workplace.

Viewed this way, the taxonomy describes a progression from basic knowledge to decision-making capability at the point of risk (Table 1).

Most training remains focused on the lower-order cognitive processes, remembering and understanding, leaving employees capable of reciting rules.

Audit-Ready is Not the Same as Food-Safe

Across industry events and professional networks, being audit-ready is considered the end goal. Teams seek to ensure documentation is current, records are complete, and non-conformances are closed.

Audits confirm the existence of a system, but not necessarily how it performs when conditions change. They acknowledge documentation (digital or paper-based), but do not identify the quality of decisions made.

Blind Spots in Food Safety Investigations

Similar gaps are evident in how food safety incidents are investigated. John Guzewich, M.P.H., a retired U.S. Food and Drug Administration (FDA) official, created and managed the FDA Center for Food Safety and Applied Nutrition (CFSAN) foodborne disease surveillance and response coordination program. In a recent LinkedIn post,³

Build Decision Capability Where the Work Happens

Decision-making is not a personality trait. It is a capability that can be deliberately developed or unintentionally weakened by the design of systems, training, and leadership.

Better decisions are built on the job, not in classrooms or with online modules alone. While these can be an essential foundation, they are not designed to provide the situational understanding required. Frontline leaders and the QA team play a critical role in making decision-making practical, visible, and consistent in everyday work.

Using clear, open, and inclusive language matters. When conversations about food safety are simple and non-judgmental, people are more willing to speak up, explain what they did, and ask questions. That trust and confidence are essential for making good decisions.

Using Workplace Examples

People learn to make better decisions by talking through work issues, not abstract "what if" scenarios (Figure 1). This applies whether the task is processing, packing, cleaning, cooking, transporting, or serving food.

Short, practical discussions work best:

• What was the task, and what was the food safety risk involved?
• What decisions did you have to make at that time?
• What mattered most for food safety in that task?

These conversations help operational employees connect procedures to the reality of their job, where decisions are made.

A Training Shift is Needed

Traditional training focuses on procedures. Decision-focused training helps people:

• Recognize changing conditions
• Notice weak signals
• Understand consequences
• Choose between competing priorities.

This is where Bloom's higher levels become practical for analyzing situations, evaluating options, and learning from outcomes—not just recalling rules.

Create a Safe Space to Practice Judgement

People do not develop judgment in audits or online learning modules. They develop it during supervised work, through coaching, and by talking through decisions made. Frontline leaders are critical in this process. They must ask questions and listen, rather than just correcting behavior.

Simple questions make a difference:

• What factors influenced the decision you made?
• What made this task easier or harder to do safely today?
• What information or support would have helped?

These questions encourage reflection without blame, help surface system constraints, and assist employees in strengthening judgment under operating conditions.

Make Risk Visible, and Talk About It Daily

Risk-based thinking only works when it is understood and applied in context. Short, focused toolbox conversations build more decision capability than annual refresher training. Such conversations may involve the following questions:

• What are the highest food safety risks in today's tasks?
• What is different or unusual compared to a normal day?
• Where are things most likely to go wrong if conditions change?
• What early signs would tell us that there is an increased risk?

These brief, task-based discussions help individual employees and teams anticipate issues, prioritize attention, and adjust decisions before problems escalate, thereby building more decision capability than periodic refresher training.

QA Maturity: From Audit-Driven to Strategic Partner

QA capability strongly influences decision quality across a site. A simple maturity model helps illustrate this:

• Level 1: Reactive/Compliance-Only
   QA exists to satisfy external certification and food law requirements. Activity is reactive, triggered by incidents, complaints, or regulator attention. The focus is on meeting minimum compliance, responding after failures, and failing to fix causes. QA has limited authority or influence, and food safety is seen as "QA's job" rather than a shared operational responsibility.
• Level 2: Audit-Driven
   QA focuses on documentation, verification, and closing non-conformances. Problems are often identified after they occur.
• Level 3: System-Focused
   QA manages processes and data, but its influence on day-to-day decisions is limited.
• Level 4: Capability Builder
   QA coaches teams, anticipates issues, and supports better decisions on the floor.
• Level 5: Strategic Partner
   QA is embedded in operational and leadership decisions, shaping systems, behaviors, and culture.

Many businesses stall at Level 2. The solution is not more audits, but instead elevating QA's role so it actively improves decision-making capability across the organization.

At higher maturity levels, QA supports decision-making rather than simply verifying compliance. QA helps teams interpret signals, test assumptions, and learn from near misses. This is the shift from QA as auditor (Level 2) to QA as strategic partner (Level 5).

Why Risk-Based Thinking Matters

Higher-quality decisions still need direction. Risk-based thinking is applicable here. 

For food operations, not every deviation carries the same consequence. A bad practice that does not result in a problem on one occasion may lead to serious consequences under different circumstances. Risk-based thinking enables QA teams, frontline leaders, and employees to prioritize attention and resources on the issues that have the greatest impact on food safety.

When combined with strong decision capability, it allows them to:

• Identify (spot) emerging hazards early
• Distinguish between minor issues and critical failures
• Act proportionately and effectively
• Prevent escalation

This combination—decision capability plus risk-based thinking—is what turns training into safer outcomes.

Leadership and Frontline Supervisors 

QA cannot do this alone. Leadership determines whether decision capability is encouraged or suppressed.

Leaders who only ask, "Are we compliant?" unintentionally reinforce "ticking-the-box" behavior. Leaders should instead ask, "What decisions were made today to keep food safe and to prevent waste, rework, or product loss?" The second question creates an environment that fosters learning and informed decision-making, ultimately protecting profits.

Frontline supervisors are critical. They translate expectations into daily behavior through:

• Toolbox talks that focus on today's risks
• Supporting employees while they are making decisions
• Reinforcing good decisions, not just pointing out mistakes
• Encouraging people to speak up.

Clear expectations help teams focus on quality decisions. One practical approach is to define "above the line" and "below the line" behaviors. Above-the-line behaviors are actions that protect food safety and support good decisions: speaking up early, stopping or slowing a task when risk increases, escalating concerns, asking questions, and making conservative choices when uncertainty arises.

Below-the-line behaviors increase risk and are unacceptable, even if no incident occurs: bypassing controls, staying silent about deviations, relying on assumptions, prioritizing speed over safety, or continuing work when conditions have changed.

Making these behaviors explicit and contextualizing them in a specific food production system helps everyone understand what good decisions look like in practice, reinforcing a culture where safe, risk-aware decisions are the norm (Figure 2).

Culture determines whether people feel safe to think, question, and act. In compliance-driven cultures, deviations are hidden and decisions are defensive. In mature cultures, issues are surfaced early and treated as opportunities to learn.

Food safety culture maturity is ultimately a reflection of how well an organization supports good decisions, not how strictly it enforces rules.

Case Study: Decisions in Action

An Australian consultancy assisted a client with challenges related to the shelf life of ready-to-cook fish. The product had been validated two years earlier, with no issues until the previous 12 months, when high total plate count and out-of-specification Enterobacteriaceae levels increased.

A review of operations identified no raw material or equipment failures. Cleaning met visual and microbiological standards. However, observation of employees revealed poor handwashing, excessive product handling, and prolonged glove use—outcomes of training that focused on procedures rather than decision-making.

The underlying causes were insufficient, compliance-driven training, compounded over time by staff turnover and the gradual dilution of capability. A "business-as-usual" culture.

The response, a three-month holistic program, focused on:

• Boardroom training
• Observing decisions on the job
• Coaching hygiene and handling practices
• Prioritizing behaviors with the highest food safety impact
• Peer feedback and shared accountability
• Daily reinforcement.

The consultants recommended the client undertake a review of all food safety training to move toward competency-based training rather than "ticking-the-box" compliance. Outcomes of the three-month program and training review included improved food safety, restored shelf life, reductions in staff turnover, improved worker health and safety, sustained behavioral change, improved culture, and estimated annual savings of $230,000 AUS, with QA moving from auditor to strategic partner.

What This Means for the Food Supply Chain

If our earlier articles highlighted the problem, then this article clarifies the solution. Safe food is not produced by audits alone. It is produced by capable people making good decisions in supportive systems and workplace settings. This requires:

• Decision-focused training
• Risk-based prioritization
• QA operating as a strategic partner
• Leadership reinforcing critical thinking, not just compliance
• Culture that supports learning and accountability.

Decision Ownership in an AI-Supported World

As organizations increasingly adopt digital tools, automation, and artificial intelligence (AI)-driven insights, there is a growing risk of confusing information with judgment. Technology can identify patterns and deviations and support analysis, but it cannot replace accountability for decisions.

Recent, high-profile cases outside of the food industry emphasize this risk. In Australia, several high-profile attorneys (a solicitor and two barristers, with one a King's Counsel) were required to explain to the Federal Court of Australia why submissions contained erroneous citations generated using AI. The judgment made it clear that reliance on AI without appropriate professional oversight led directly to incorrect evidence being presented.

A similar risk exists in food safety. AI can inform risk assessments, but it is not contextual enough to recognize behavioral change or challenge assumptions. Risk assessment is not a purely computational task. High-reliability food safety systems are defined not by technological sophistication, but by how well people are trained, supported, and expected to think critically.

AI can support better decision-making by providing valuable data and insights, but it does not replace human judgment. Responsibility for food safety outcomes ultimately remains with those accountable for ensuring food safety.

Conclusion: From Compliance to Capability

Audit-ready systems can create a false sense of control. Compliance alone does not make food safer; better-informed decisions do. When organizations shift their focus from rules to decision-making, from compliance to capability, and from QA as verifier to QA as strategic partner, food safety performance improves—and those improvements endure.

The question for leaders is no longer whether people know the rules. It is whether the system equips them to make the right decisions when it matters most. Safe food is not the result of perfect compliance—it is the result of making the right decisions, every time.

References

1. Food Safety Magazine Editorial Team. "FAO: Human Oversight Remains Critical in Using AI for Food Safety Foresight." Food Safety Magazine. January 1, 2026. https://www.food-safety.com/articles/11013-fao-human-oversight-remains-critical-in-using-ai-for-food-safety-foresight. 
2. McKinsey & Company. "What is Decision Making?" March 13, 2023. https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-decision-making. 
3. See the W. Edwards Deming Institute. https://deming.org/.
4. Anderson, L.W. and D.R. Krathwohl. A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives. New York: Longman Academic Series, Pearson, 2001.
5. Bloom, B.S. Taxonomy of Educational Objectives: The Classification of Educational Goals. New York: D. McKay Co., 1956.
6. John Guzewich, M.P.H. "Commentary: The Blind Spot in Food Safety Investigations: Incomplete Root Cause Analysis." LinkedIn post. December 17, 2025. https://www.linkedin.com/posts/john-guzewich-mph-97a881252_commentary-the-blind-spot-in-food-safety-share-7407150507129044992-Kp9S/.