The use of Tacit Risk Knowledge as Practical Wisdom and MCDA/MCDM in Risk Management

Author's Disclaimer

The use of Tacit Risk Knowledge as Practical Wisdom and MCDA/MCDM in the context of risk management presented in this paper is intended solely for academic discussion and personal reflection. Readers and participants are welcome to express their concerns or offer alternative viewpoints.

This work is a conceptual analysis that integrates a range of theoretical frameworks, scholarly literature, and professional insights encountered throughout my academic and career journey. The models, examples, and visual representations included herein are illustrative and exploratory in nature, designed to guide thinking rather than prescribe solutions. They do not represent definitive conclusions or empirically validated models.

The content should not be interpreted as an official guideline for decision-making, policy formulation, or strategic planning. It does not reflect the formal position of any government entity, academic institution, or organization, and it is not backed by empirical research at this stage.

Readers are strongly encouraged to exercise critical judgment, consult relevant literature, and seek advice from qualified professionals before applying any concepts discussed to real-world scenarios. This paper is best viewed as a starting point for deeper inquiry and informed dialogue, rather than a substitute for data-driven or expert-informed decision-making.

By blending structured decision-making tools such as Multi-Criteria Decision Analysis (MCDA/MCDM) with the philosophical and experiential depth of practical wisdom (phronesis), the article aspires to outline a flexible and thoughtful approach to managing both measurable and immeasurable risks in a complex and evolving world.

Tacit Risk Knowledge as Practical Wisdom and MCDA/MCDM in Risk Management

Practical Wisdom or  Phronesis upholds the democratic disposition of the dynamic configuration of risk management, with structured tools such as MCDA (multi-criteria decision analysis) or MCDM (multi-criteria decision-making) that offer a strong support framework for quantifiable and unquantifiable risk management.

1. Practical Wisdom as Tacit Risk Knowledge

To Aristotle, phronesis, or practical wisdom, defined the ability to know intuitively the dilemma situations, where to act morally and sensibly, and when to make use of which rule. It is knowledge gained through experience and reflection that emphasizes moral judgement rather than textbook principles or set rules. The importance of such knowledge in risk management can be central since decisions will need to be made with poor information, complex variables, or human consequences. This making Phronesis an essential adjunct to technical knowledge for a more intricate and flexible response to uncertainties.

Using Intuition to Guide Decisions in the Face of Ambiguity

One of the key characteristics of tacit risk knowledge is its capacity to guide decision-making when information is ambiguous or insufficient. Risk decision-making for experts, leaders, and risk managers usually has to deal with a lack of hard data or at least with an environment where risk factors are not manifest. In these circumstances, intuition born out of experience and knowledge becomes an important means of achieving clarity for an informed decision. 

An experienced disaster recovery specialist, for instance, may feel that certain early indicators (for example, unusual weather patterns or supply chain delays) seem to signal an impending crisis before any tangible proof is available. This intuition, though somewhat tricky to put a number on, could lead to early intervention that saves lives and resources. In this way, tacit knowledge is often used to fill in knowledge gaps.

Making Ethical Decisions within Risk Management

Implicit knowledge becomes even more important if risks are highly damaging human consequences that cannot be captured in technical measurement. This ethical evaluation usually becomes more complicated than quantitative data and requires a consideration by decision-makers of wider social-moral dimensions of their options. For example, in public health, resources-limited like vaccines-that are typically used during an outbreak cannot be directly allocated based on technical metrics (for example, infection rates). They also need consideration of the welfare of marginalized groups, equity, and justice.

Leaders can have an experience-shaped tacit kind that enables them to make hard choices while considering human needs, social dynamics, and effects that stretch further into the future. It may involve making trade-offs between competing priorities or values, so that the ethics have this dimension.

Sensitivity to Context

Some examples of practical wisdom are learning that "one size fits all" rarely applies in risk management, and that it is usually context sensitive. This is especially relevant to the tension between strict regulations and the need for flexibility. Thus, an experienced leader understands how to apply regulations properly to the given situation and knows the context of the risk.

Cybersecurity breach regulations may provide for a standard response, but the specifics of a given attack scenario (e.g., if other attributes like the attacker characteristics, the size of the organisation, or the potential societal ramifications) dictate that it needs something more tailored. The ability to adapt to changing situational circumstances, oftentimes grounded in intuition or seasoned judgment, is what distinguishes tacit knowledge in practice.

The Function of Tacit Knowledge in Emergencies

Implicit risk knowledge becomes difficult to define or codify, considering it is usually tacit. This is difficult to document since it is embedded in the cultural norms of an institution or the habits of experienced professionals. For example, an experienced public health official may "feel" the early warning signs of a potential crisis (e.g. an increase in calls to healthcare providers or strange patterns in medical data) even before any formal or concrete indications of a crisis emerge. Such soft signals are sine qua non for being able to discern threats swiftly, with formal detection mechanisms usually lagging behind. 

These "soft signals," anyway, often represent a deep pattern and behavioural comprehension developed across a lifetime of experience and situational learning. Although they are considered anecdotal evidence or intuition by some, soft signals, in the hands of leaders who possess an internalized sense of risk knowledge, carry great weight. Another factor that favors a leader in applying tacit knowledge for risk perceptions is that he or she gets to respond quickly to an emerging situation and perhaps shield their organization from any impending damage.

Inclusion of Useful Knowledge in Organizations
An organization's capacity to respond to risks can be greatly improved by integrating tacit knowledge and practical wisdom into organizational procedures:

Adaptability: 

Leaders depend on tacit knowledge to adapt to the realities of any situation when existing procedures and protocols fail. This kind of flexibility is critical in dealing with the kinds of risks that vary with time or take an unexpected turn.

Early Risk Detection: 

By identifying "soft signals," an organization could undertake early intervention to mitigate circumstances from deteriorating. Such early warning signs could emanate from the cumulative experiences or instinctive knowledge of individuals who have been part of similar incidents in the past.

Ethical Decision-Making: 

The higher the stakes become, be it morally or socially, leaders are able to make decisions that are better choices helped by their implicit knowledge. Also, factors such as information and computational analysis become less significant.

Problems with Tacit Knowledge in Institutional Settings:
Tacit knowledge has many advantages for risk management, but it also has disadvantages, particularly in institutional or policy contexts where accountability and transparency are essential. Implicit knowledge is difficult to document, defend, or reproduce in a way that can be examined or assessed by outside parties because it is subjective and opaque by nature.

For example, a public health official's "gut feeling" to close certain economic sectors during a disease outbreak may not have an immediate, quantifiable justification. In settings like government or business, where accountability is essential, decisions based on tacit knowledge may be disputed for being opaque or unreproducible.

In these circumstances, relying too heavily on implicit knowledge could also lead to biases or inconsistencies, particularly if the decision-makers' judgement is impacted by cultural norms or personal experiences. Therefore, organisations need to strike a balance between tacit knowledge and explicit knowledge, which are open, described decision-making processes that can be reviewed, audited, and improved over time.

In conclusion, implicit risk knowledge—a form of practical wisdom—is incredibly helpful when managing complex, high-stakes situations where precise information is either missing or insufficient. It enables leaders to make morally sound, situation-specific, and adaptable decisions by drawing on their intuition and experience. Its inherent lack of transparency and documentation issues, however, pose challenges in circumstances where accountability and reproducibility are necessary. Therefore, even though tacit knowledge is essential, organisations must find a way to balance it with explicit processes to ensure flexibility and accountability in risk management..

2. Structured Decision-Making in the Face of Uncertainty: Multi-Criteria Decision Analysis (MCDA/MCDM)

Where practical wisdom relies on experience and intuition, Multi-Criteria Decision Analysis (MCDA) — also known as Multi-Criteria Decision-Making (MCDM) — provides a structured, transparent, and replicable framework for evaluating complex decisions that involve trade-offs among multiple, often conflicting objectives. It is particularly valuable in risk management because it allows decision-makers to systematically rank alternatives by integrating quantitative data with qualitative judgments across diverse criteria.

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Purpose and Benefits of MCDA in Risk Management

MCDA is useful in contexts where:

• Decisions involve trade-offs (e.g., cost vs. safety).

• Uncertainty is present, and no single “best” option exists.

• Stakeholder input is necessary or desirable.

• Impacts occur across multiple dimensions, such as health, economics, environment, and ethics.

It enhances practical wisdom by structuring the use of subjective judgments (like ethical considerations or local knowledge) and combining them with objective measures (like cost or pollution levels).

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MCDA Framework – A Simple Example with Computation

Let’s apply MCDA to a real-world example:
A Local Government Unit (LGU) is evaluating three strategies to manage a spike in tourism. The alternatives are:

• A1: Increase infrastructure capacity

• A2: Impose tourist limits

• A3: Promote off-peak tourism

They will be evaluated on 4 criteria:

1. C1: Economic Gain (benefit)

2. C2: Health Risk (cost/negative)

3. C3: Environmental Impact (cost/negative)

4. C4: Community Well-being (benefit)

The LGU assigns the following weights to these criteria based on stakeholder input:

Criterion	Weight
C1: Economic Gain	0.30
C2: Health Risk	0.25
C3: Environmental Impact	0.20
C4: Community Well-being	0.25

Step 1: Score Alternatives on Each Criterion (on a 0–10 scale)

Alternative	C1 (Gain)	C2 (Risk)*	C3 (Impact)*	C4 (Well-being)
A1	9	3	4	6
A2	5	9	8	7
A3	7	7	6	9

*Note: Since C2 and C3 are negative impacts, we invert their scores during normalization to reflect lower is better.

Step 2: Normalize Scores (Benefit criteria stay; Cost criteria are inverted)

We normalize by dividing each score by the maximum in its column:

Alternative	C1 (Benefit)	C2 (1 - Risk/Max)	C3 (1 - Impact/Max)	C4 (Benefit)
A1	9/9 = 1.00	1 - 3/9 = 0.667	1 - 4/8 = 0.50	6/9 = 0.667
A2	5/9 = 0.556	1 - 9/9 = 0.00	1 - 8/8 = 0.00	7/9 = 0.778
A3	7/9 = 0.778	1 - 7/9 = 0.222	1 - 6/8 = 0.25	9/9 = 1.00

Step 3: Multiply Scores by Weights and Sum

Let’s compute the weighted sum for each alternative:

A1:

= (1.00 × 0.30) + (0.667 × 0.25) + (0.50 × 0.20) + (0.667 × 0.25)
= 0.30 + 0.167 + 0.10 + 0.167
= **0.734**

A2:

= (0.556 × 0.30) + (0.00 × 0.25) + (0.00 × 0.20) + (0.778 × 0.25)
= 0.167 + 0.00 + 0.00 + 0.195
= **0.362**

A3:

= (0.778 × 0.30) + (0.222 × 0.25) + (0.25 × 0.20) + (1.00 × 0.25)
= 0.233 + 0.056 + 0.05 + 0.25
= **0.589**

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Final Ranking Based on Total Scores:

1. A1 (Increase infrastructure) – 0.734

2. A3 (Promote off-peak tourism) – 0.589

3. A2 (Impose limits) – 0.362

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Interpretation and Real-World Insights

• A1 ranks highest, driven by high economic gain and moderate impacts, even though health and environmental costs are moderate.

• A3 is a balanced second, with strong well-being and moderate performance on all criteria, reflecting a more sustainable, less disruptive strategy.

• A2 performs worst, primarily because it minimizes risks but sacrifices economic and environmental performance—potentially making it politically or socially unpopular.

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Why It Matters: Bridging Tacit and Structured Wisdom

MCDA doesn't replace practical wisdom, but enhances it:

• Subjective judgments (like ethical importance or local experience) are incorporated through weights and scoring.

• Stakeholder perspectives become transparent and traceable.

• It enables repeatable decisions, avoiding reliance on personal intuition alone — a key requirement in institutional or public governance contexts.

3. Combining the Two Methods
Combining MCDA/MCDM with common sense results in a thorough risk management framework that connects analysis and intuition:

Combining MCDA/MCDM and Tacit Risk Knowledge for Holistic Risk Management

Dimension of Useful Knowledge	Tacit Risk / Practical Wisdom	MCDA / MCDM	Integrated Value
Nature	Context-specific, experience-driven, intuitive	Structured, objective, and methodical	Merges lived experience with transparent decision logic
Usefulness	Navigating ambiguity, moral complexity, rapid decisions	Prioritizing, comparing, and making traceable, evidence-based decisions	Ensures both speed and accountability in complex decision-making
Restrictions / Limitations	Subjective, hard to document or replicate	Can oversimplify complex socio-cultural or ethical realities	Balance between nuance and clarity; avoids both rigidity and arbitrariness
Best Use Case	High-uncertainty, low-data, morally sensitive or urgent scenarios	Multi-factor comparison with defined objectives and available data	Handles both clear-cut evaluations and “grey area” judgments
Decision Basis	Common sense, moral judgment, professional intuition	Criteria weights, scoring, normalization, and aggregation	Grounded choices informed by both ethical grounding and analytical reasoning
Stakeholder Engagement	Informal through cultural norms, trust, or dialogue	Formalized via weighted input and defined criteria	Supports both tacit consensus and documented stakeholder representation
Transparency & Accountability	Low—decisions may be hard to justify externally	High—method enables auditability and justification	Ensures that intuition-based insights can be explained within a transparent framework
Example Scenario	Sensing the early stages of a health crisis before data confirms it	Choosing the best containment strategy based on cost, impact, and feasibility	Responds early based on intuition, then chooses action via structured analysis

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How They Complement Each Other

Tacit Wisdom	MCDA Enhance	Result
Moral grounding, early perception, and contextual awareness	Quantitative rigor, documentation, and stakeholder traceability	Decisions that are both ethically grounded and analytically defensible
Rapid decision-making under pressure	Post-event analysis and decision traceability	Agile action with learnings captured for future improvement
Culture-sensitive responses	Cross-criteria comparability	Community-responsive policies that still meet broader standards

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Conclusion

Combining MCDA/MCDM with Tacit Knowledge (Practical Wisdom) provides a dual-lens approach to risk management:

• MCDA/MCDM ensures systematic evaluation, objectivity, and reproducibility, essential for institutional decision-making and accountability.

• Tacit knowledge ensures adaptability, cultural relevance, and moral intuition, especially under uncertainty or when data is incomplete.

This integrated model is especially critical in the public sector, where decisions often span technical, social, ethical, and spiritual dimensions. By honoring both measurable evidence and human judgment, organizations become better equipped to anticipate, assess, and respond to risks in a way that is both competent and compassionate.

References:

Asana. (n.d.). Risk management process: Step-by-step guide. https://asana.com/resources/project-risk-management-process

BibleRef. (n.d.). What does Proverbs 16:9 mean? https://www.bibleref.com/Proverbs/16/Proverbs-16-9.html

1000minds. (n.d.). Multi-Criteria Decision Analysis (MCDA/MCDM). Retrieved from https://www.1000minds.com/decision-making/what-is-mcdm-mcda

Pressbooks. (n.d.). Aristotelian Virtue Ethics – Phronesis. Pressbooks. https://pressbooks.pub/phronesis/chapter/virtue-ethics/

Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their foundation. European Journal of Operational Research, 253(1), 1–13. https://doi.org/10.1016/j.ejor.2015.12.023