Rather than listing features, we document real comparison journeys. Below you'll find two complete case narratives showing how structured evaluation changed procurement outcomes, followed by the decision frameworks we used and how you can apply them.
Client context: A 78-employee logistics operation in the Irish midlands was using three separate fleet management vendors. Annual combined spend exceeded €410,000 with overlapping coverage and inconsistent SLA terms.
The comparison challenge: Each vendor presented data differently. One quoted per-vehicle rates, another used monthly retainers, and the third bundled fuel management into a flat fee. Direct comparison was impossible without normalisation.
We constructed a normalised cost-per-unit framework across 14 service dimensions. Every vendor's offering was decomposed into atomic service units, then reassembled into comparable packages.
| Dimension | Vendor X | Vendor Y | Vendor Z | Normalised Winner |
|---|---|---|---|---|
| Tracking per vehicle/month | €38 | €45 (bundled) | €32 | Vendor Z |
| SLA response (critical) | 4 hrs | 2 hrs | 6 hrs | Vendor Y |
| Fuel management | Separate | Included | Separate | Vendor Y |
| Contract flexibility | 12-month lock | Rolling quarterly | 24-month lock | Vendor Y |
| Data export format | CSV only | API + CSV | PDF only | Vendor Y |
Outcome: The client consolidated to a single vendor (Y), reducing annual spend by €127,000 while improving average SLA response by 58%. The decision was made in 19 working days from engagement start.
"We'd been comparing apples to oranges for two years. The normalisation framework made the answer obvious." — Operations Director, Midlands Logistics
In 6 out of every 10 engagements, organisations discover they're paying premium rates for services they've already outgrown. The comparison isn't just about cost — it's about alignment between what you need now and what each provider actually delivers.
Client context: A 12-person EdTech team needed to select a learning management system (LMS) before a Series A funding milestone. They had shortlisted five platforms but couldn't agree on evaluation criteria.
The comparison challenge: Technical team prioritised API extensibility. The CEO wanted brand perception. The content team needed authoring workflow speed. Each stakeholder scored platforms differently, creating decision paralysis.
We didn't just compare features. We mapped each stakeholder's priorities, assigned weights through a facilitated session, then scored each platform against the weighted criteria.
| Criteria | Weight | Platform A | Platform B | Platform C |
|---|---|---|---|---|
| API extensibility | 25% | 9/10 | 7/10 | 8/10 |
| Authoring speed | 20% | 5/10 | 8/10 | 7/10 |
| Brand alignment | 15% | 8/10 | 6/10 | 9/10 |
| Pricing scalability | 25% | 6/10 | 9/10 | 5/10 |
| Support quality | 15% | 7/10 | 8/10 | 6/10 |
| Weighted total | 7.05 | 7.75 | 6.90 |
Outcome: Platform B won despite not being the CEO's initial preference. The weighted framework made the reasoning transparent. The team signed within 11 days and launched on schedule for their funding milestone.
"The structured scoring ended three months of circular debate in a single afternoon." — CTO, Dublin EdTech
Best when vendors use different pricing structures. We decompose each offering into atomic units and rebuild on a common baseline. Ideal for procurement teams managing 2–5 vendors with overlapping services.
Best when multiple stakeholders disagree on priorities. We facilitate weight assignment, then score independently. Ideal for technology selection, platform migration, or any decision with competing internal perspectives.
Best when historical performance data exists. We map each vendor's past delivery against your specific KPIs. Ideal for contract renewals and long-term partnership evaluations where track record matters more than promises.
We define what's being compared, who the stakeholders are, and what a successful outcome looks like. This prevents scope creep and ensures the comparison stays relevant.
We gather pricing, SLA terms, feature lists, and performance data from each provider. Everything gets normalised into comparable units before any analysis begins.
We apply the appropriate comparison model — cost normalisation, weighted scoring, or outcome mapping — based on your situation. Mixed models are used when complexity demands it.
Results are presented in a structured format that every stakeholder can interpret. We facilitate the discussion, not dictate the answer.
Every comparison produces a decision record — the rationale, the data, the trade-offs. This protects your organisation if the decision is ever questioned later.
Phone: +353 22 69459
Email: [email protected]
853 Fisher Land, Domenicoview, Illinois, W76 5S71, Ireland
Engagements completed since 2021: 143
Average decision time reduction: 63%
Client retention on follow-up comparisons: 81%
"They turned a chaotic vendor review into a clear, defensible decision in under three weeks."
— Procurement Lead, Cork Manufacturing
Most service comparisons fail not because of bad data, but because the comparison framework itself is biased. When a vendor provides the comparison template, the criteria naturally favour their strengths. When an internal team builds the framework without facilitation, the loudest voice in the room sets the weights.
Independent comparison isn't about neutrality for its own sake — it's about ensuring the decision framework itself is fit for purpose before any scoring begins. That's the difference between a comparison that confirms an existing bias and one that reveals the actual best fit.
We've seen organisations save between €40,000 and €300,000 annually simply by re-examining the criteria they use to evaluate vendors. The service itself often isn't the problem. The evaluation lens is.
Tell us what you're evaluating. We'll respond within one business day with a recommended framework and estimated timeline.
No obligation. No vendor partnerships. Our revenue comes from you, not from the services we evaluate.
Alternatively, call us directly at +353 22 69459 or email [email protected]
Last revised: January 2026
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