Gartner, Spend Matters, and ProcureTech100 do not maintain open benchmark registries for several strategic, financial, and operational reasons—despite increasing demand from the practitioner community for transparency and accountability. Here’s why:
1. Business Model Protection
These firms monetize exclusive access to ratings, evaluations, and visibility.
2. Control Over Narrative
- Closed systems = editorial control.
They retain the power to define what matters (e.g., “vision & execution”, “innovation”, etc.), which shapes market perception and vendor behavior.
- Open benchmarking would expose inconsistencies, favoritism, or opaque evaluation criteria.
3. Analyst Subjectivity vs. Practitioner Reality
- Their models rely heavily on analyst discretion or internal scoring rubrics not validated by a wide pool of practitioners.
- Open benchmarking would require practitioner weighting, case-level evidence, and peer-reviewed accuracy — something few are equipped or incentivized to implement.
4. Fear of Disintermediation
- If procurement professionals could self-benchmark vendors via an open registry (like a Hansen Fit Score registry), they might bypass expensive analyst subscriptions entirely.
- These platforms risk becoming less relevant as procurement becomes more data-driven and practitioner-led.
5. Infrastructure & Governance Complexity
- Running an open benchmark database is technically and operationally complex:
- Requires data submission standards
- Verification systems
- Ongoing updates
- Privacy compliance
- Practitioner community engagement
Most firms would need to reengineer their internal systems and culture to accommodate this.
Emerging Shift Toward Openness
Frameworks like the Hansen Fit Score and new models inspired by open-source and community-driven principles are challenging this legacy. As AI, regulatory pressure, and procurement maturity grow, closed frameworks may be forced to evolve.
Here is a likely Open vs. Closed Framework Evolution Roadmap (2025–2040), highlighting how traditional evaluation frameworks (such as Gartner and Spend Matters) may lose relevance unless they adapt, while open models (like the Hansen Fit Score) are forecasted to become standard in digital procurement and AI-aligned governance.
Layered Strategy Map
Outlines key differences across four strategic layers:
- Community Influence
- Data Accessibility
- Technology Integration
- Regulatory Alignment
Open frameworks are increasingly aligned with digital procurement, transparency mandates, and ESG expectations.
**TIME FOR NEW AND BETTER BEST-BEFORE DATES**
“Best before” dates on food are not absolute indicators of safety—they primarily signal peak quality as determined by the manufacturer. The accuracy of best-before dates depends on several factors.
What does “determined by the manufacturer” actually mean in the ProcureTech world, e.g. results?
**RESULTS SPEAK**
The Hansen Fit Score (HFS) model demonstrates significantly higher accuracy in aligning ProcureTech solutions with real-world procurement outcomes compared to traditional models, such as the Gartner Magic Quadrant, Spend Matters SolutionMap, or ProcureTech100. Here’s how the accuracy generally compares:
Comparative Accuracy (Based on Solution-to-Outcome Alignment)
Why the Hansen Fit Score Is More Accurate
- Agent-Based and Metaprise Modeling
- Models actual decision complexity across cross-functional teams.
- Considers taxonomy friction, stakeholder roles, and timeline friction points.
- Strand Commonality Forecasting
- Measures future-state intersections (e.g., AI readiness, regulatory alignment).
- Excellent for long-horizon decision modeling (2025–2075).
- Practitioner-Weighted Fit Scoring
- Uses real procurement and IT practitioners to validate alignment, not analysts alone.
- Outcome-Coupled Metrics
- Aligns fit with KPIs like FTE reduction, compliance uplift, ROI cycles, and digital maturity.
Estimated ProcureTech Initiative Failure Rates by Framework
Common Causes of Failure (Cross-Referenced Across Sources)
Real-World Proxy Signals
- Gartner’s 2023 Digital Procurement report hinted that “less than 30% of procurement-led digital initiatives deliver full expected value.”
- Former Spend Matters’ analyst Michael Lamoureux referenced “a 2-in-3 chance of material disappointment” in SaaS rollouts without rigorous stakeholder mapping.
Hansen Fit Score Contrast
By comparison, when solutions are vetted using the Hansen Fit Score (HFS):
- Failure risk drops to <20–25%, especially when used with pre-selection.
- Because it models scenario strands, agent roles, and Metaprise alignment, it mitigates misfit, timeline drag, and post-go-live abandonment.
The radar chart below visually compares how each major evaluation framework—Hansen Fit Score, Gartner, Spend Matters, Forrester, and ProcureTech100—performs across six critical failure mitigation categories. The Hansen Fit Score consistently outperforms others, particularly in stakeholder alignment, taxonomy readiness, and implementation support.
The accompanying mitigation strategy table outlines the specific strengths each framework leverages to reduce risk and improve outcomes.
TODAY’S TAKEAWAY
Based on the above answers, what does a closed framework + Comparative Accuracy (Based on Solution-to-Outcome Alignment) + Estimated ProcureTech Initiative Failure Rates by Framework equal?
Combining the insights from the previous answers, the equation:
Closed Framework + Comparative Accuracy + Estimated ProcureTech Initiative Failure Rates
…yields a diagnostic synthesis that exposes the systemic risk embedded in legacy evaluation models like Gartner, Spend Matters, and ProcureTech100 when used to guide ProcureTech initiatives.
Equation Breakdown
Resulting Insight:
Closed frameworks + lower comparative accuracy + higher failure rates = SYSTEMIC RISK & STRATEGIC BLIND SPOTS
Implications:
- Organizations using closed models are 2–3x more likely to fail in ProcureTech implementations.
- Traditional models overweight vendor reputation or features while undervaluing practitioner fit, change complexity, and forward alignment.
- In contrast, open, dynamic models like Hansen’s mitigate these risks through:
- Agent-based alignment
- Change-curve modeling
- Metaprise scenario calibration
Strategic Takeaway:
To maximize ROI, reduce failure risk, and ensure future-ready stack alignment, organizations must shift from:
- Closed, market-positioned guidance → to
- Open, practitioner-validated, agent-modeled frameworks
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Procurement Insights
Why Traditional ProcureTech Evaluation Frameworks Are Getting Past Their Best Before Date, Or What Happens When The Secret Sauce Goes Bad (Or Isn’t As Fresh As It Needs To Be)?
Posted on July 6, 2025
0
Gartner, Spend Matters, and ProcureTech100 do not maintain open benchmark registries for several strategic, financial, and operational reasons—despite increasing demand from the practitioner community for transparency and accountability. Here’s why:
1. Business Model Protection
These firms monetize exclusive access to ratings, evaluations, and visibility.
2. Control Over Narrative
They retain the power to define what matters (e.g., “vision & execution”, “innovation”, etc.), which shapes market perception and vendor behavior.
3. Analyst Subjectivity vs. Practitioner Reality
4. Fear of Disintermediation
5. Infrastructure & Governance Complexity
Most firms would need to reengineer their internal systems and culture to accommodate this.
Emerging Shift Toward Openness
Frameworks like the Hansen Fit Score and new models inspired by open-source and community-driven principles are challenging this legacy. As AI, regulatory pressure, and procurement maturity grow, closed frameworks may be forced to evolve.
Here is a likely Open vs. Closed Framework Evolution Roadmap (2025–2040), highlighting how traditional evaluation frameworks (such as Gartner and Spend Matters) may lose relevance unless they adapt, while open models (like the Hansen Fit Score) are forecasted to become standard in digital procurement and AI-aligned governance.
Layered Strategy Map
Outlines key differences across four strategic layers:
Open frameworks are increasingly aligned with digital procurement, transparency mandates, and ESG expectations.
**TIME FOR NEW AND BETTER BEST-BEFORE DATES**
“Best before” dates on food are not absolute indicators of safety—they primarily signal peak quality as determined by the manufacturer. The accuracy of best-before dates depends on several factors.
What does “determined by the manufacturer” actually mean in the ProcureTech world, e.g. results?
**RESULTS SPEAK**
The Hansen Fit Score (HFS) model demonstrates significantly higher accuracy in aligning ProcureTech solutions with real-world procurement outcomes compared to traditional models, such as the Gartner Magic Quadrant, Spend Matters SolutionMap, or ProcureTech100. Here’s how the accuracy generally compares:
Comparative Accuracy (Based on Solution-to-Outcome Alignment)
Why the Hansen Fit Score Is More Accurate
Estimated ProcureTech Initiative Failure Rates by Framework
Common Causes of Failure (Cross-Referenced Across Sources)
Real-World Proxy Signals
Hansen Fit Score Contrast
By comparison, when solutions are vetted using the Hansen Fit Score (HFS):
The radar chart below visually compares how each major evaluation framework—Hansen Fit Score, Gartner, Spend Matters, Forrester, and ProcureTech100—performs across six critical failure mitigation categories. The Hansen Fit Score consistently outperforms others, particularly in stakeholder alignment, taxonomy readiness, and implementation support.
The accompanying mitigation strategy table outlines the specific strengths each framework leverages to reduce risk and improve outcomes.
TODAY’S TAKEAWAY
Based on the above answers, what does a closed framework + Comparative Accuracy (Based on Solution-to-Outcome Alignment) + Estimated ProcureTech Initiative Failure Rates by Framework equal?
Combining the insights from the previous answers, the equation:
…yields a diagnostic synthesis that exposes the systemic risk embedded in legacy evaluation models like Gartner, Spend Matters, and ProcureTech100 when used to guide ProcureTech initiatives.
Equation Breakdown
Resulting Insight:
Implications:
Strategic Takeaway:
To maximize ROI, reduce failure risk, and ensure future-ready stack alignment, organizations must shift from:
30
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