Author: Yoshiyuki Hongoh
Abstract
Classical decision‐making models typically treat the definition of evaluation criteria as a single event that precedes the generation and assessment of alternatives. This paper argues that, under conditions of complexity and uncertainty, evaluation criteria themselves must be handled iteratively. Building on—but extending—rational decision theory (jespersimonsen.dk), design thinking’s reframing cycle (readings.design), and the continuous loops found in the OODA framework (thedecisionlab.com), I propose a Two-Stage Criteria-Focused Decision-Making Model (TCF-DM). In the TCF-DM model decision makers (1) establish provisional criteria before data collection, (2) gather and analyse information, and then (3) re-calibrate their criteria in light of the evidence prior to generating and selecting alternatives. Two illustrative cases—a corporate diversification choice and a municipal policy design—demonstrate improvements in transparency, stakeholder alignment, and outcome robustness. The model contributes a missing link in the decision‐making literature by elevating criteria management to a first-class, iterative activity, and offers organisations a structured yet flexible template for high‐stakes choices.
Keywords: Decision Making, Evaluation Criteria, Iterative Processes, Design Thinking, OODA, Multi-Criteria Decision Analysis
1 Introduction
Evaluation criteria are the yardsticks against which alternatives are judged; they encode values, risk tolerance, and strategic intent. Yet most mainstream frameworks—from Simon’s rational model (jespersimonsen.dk) to standard multi-criteria decision analysis (MCDA) toolkits (sciencedirect.com, mdpi.com)—treat criteria specification as a one-shot task. In volatile, uncertain, complex, and ambiguous (VUCA) environments, new evidence often reveals that initial yardsticks were incomplete or mis-weighted. This paper therefore asks:
How can decision makers systematically incorporate learning into the very criteria they use to judge alternatives?
To answer, I introduce the Two-Stage Criteria-Focused Decision-Making Model (TCF-DM) and position it within contemporary theory.
2 Literature Review
2.1 Classical Rational Models
Simon’s Administrative Behavior frames decision making as a linear sequence culminating in a single evaluation phase (jespersimonsen.dk). Bounded rationality softens optimisation assumptions but still presumes fixed criteria.
2.2 Iterative & Adaptive Frameworks
- Design Thinking cycles repeatedly through problem framing and solution generation; reframing mirrors criteria adjustment but is seldom formalised as such (readings.design).
- OODA Loop emphasises constant orientation shifts based on new observations (thedecisionlab.com).
- Means–End Chain Theory links values to product attributes, hinting that higher-order values can revise lower-order criteria (researchgate.net).
Despite these advances, none explicitly embed a second criteria-setting checkpoint.
3 The TCF-DM Model
| Phase | Purpose | Key Outputs |
|---|---|---|
| 1. Problem Identification | Clarify decision scope and success definition. | Decision statement |
| 2. Provisional Criteria Setting | Translate mission, values, and constraints into an initial yardstick set. | Criteria list v1 & weightings |
| 3. Information Gathering & Analysis | Collect internal and external data relevant to both the problem and the provisional criteria. | Fact base |
| 4. Criteria Re-Calibration | Examine how new evidence challenges completeness or weights of criteria; revise accordingly. | Criteria list v2 |
| 5. Alternative Generation | Develop options consistent with the updated criteria. | Option set |
| 6. Evaluation & Choice | Score and rank alternatives, make selection, justify via criteria v2. | Decision & rationale |
| 7. Implementation & Feedback | Execute, monitor, and feed learning back to Phase 1. | Outcomes, lessons |
3.1 Rationale for the Two-Stage Approach
- Bias Mitigation – Early criteria expose tacit values; later revision tempers initial anchoring.
- Resource Focus – Provisional criteria guide efficient data collection; re-calibration prevents over‐commitment to obsolete metrics.
- Stakeholder Alignment – Iteration invites dialogue, increasing acceptance of the final choice.
4 Illustrative Cases
4.1 Corporate Diversification Decision
An electronics manufacturer considered entering renewable-energy storage. Provisional criteria emphasised market size and EBITDA. Market research, however, revealed regulatory risk and supply-chain volatility. Criteria were re-weighted to elevate risk exposure and capital intensity. The firm ultimately chose a minority joint venture, balancing growth with downside containment. Decision clarity improved the board’s consensus.
4.2 Municipal Policy Design
A city contemplated congestion pricing. Initial criteria centred on traffic reduction and revenue. Public‐consultation data exposed equity concerns. Criteria were expanded to include socio-economic impact, resulting in a tiered fee system with resident rebates. The revised criteria defused opposition and yielded a smoother council approval.
5 Discussion
5.1 Theoretical Contributions
TCF-DM formalises the otherwise implicit reframing act noted in design thinking and OODA, supplying a clear gate for criteria revision. It bridges rational and adaptive schools by grafting learning loops onto a structured backbone.
5.2 Practical Implications
- Governance: Documenting both criteria versions creates an audit trail for accountability.
- MCDA Integration: Existing scoring tools can plug into Phase 6 with minimal change.
- Training: Facilitators can teach teams to surface and negotiate values early.
5.3 Limitations & Future Work
Empirical validation remains limited to qualitative cases. Controlled experiments comparing TCF-DM with single-criteria-setting processes on decision quality, speed, and stakeholder satisfaction constitute a logical next step. Cross-cultural studies may reveal contextual moderators.
6 Conclusion
In uncertain contexts, what we value can change as quickly as what we know. By deliberately installing a second, evidence-informed criteria checkpoint, the TCF-DM model offers a pragmatic pathway to more robust, transparent, and value-aligned decisions. Organisations seeking both rigour and adaptability may find in this model a compelling new standard.
References
- Boyd, J. (1976). Destruction and Creation. (OODA foundational paper). (dau.edu)
- Brown, T. (2008). Design Thinking. Harvard Business Review. (readings.design)
- MDPI. (2023). “Multi-Criteria Decision Making (MCDM) Methods and Concepts.” (mdpi.com)
- Reynolds, T. J., & Olson, J. C. (2001). Understanding Consumer Decision Making: The Means-End Approach. (researchgate.net)
- Simon, H. A. (1947). Administrative Behavior: A Study of Decision-Making Processes in Administrative Organizations. Macmillan. (jespersimonsen.dk)
- Smith, L. et al. (2024). “The Use of Multicriteria Decision Analysis to Support Decision Making in Healthcare.” Value in Health. (sciencedirect.com)
