This page outlines how AssessmentFocus builds evaluations and what we consider credible evidence.
1) Our model: “fit > features”
Tools don’t fail because they lack features. They fail because:
- workflows don’t match reality,
- the data isn’t structured to support the tool,
- and the team cannot sustain the implementation load.
Our assessments are designed to answer a practical question:
“Given a typical operations team, does this product reliably support the workflow it promises?”
2) The AssessmentFocus evaluation workflow
We use a structured approach:
Step A — Operating context
- operating model (asset / non-asset / hybrid)
- customer mix (contract / spot / dedicated)
- constraints (time, people, compliance, cash)
Step B — Workflow mapping
- what tasks the tool must support
- handoffs (dispatch → driver → customer → billing)
- failure modes (exceptions, late events, missing signals)
Step C — Evidence
We rely on:
- product documentation and release notes
- standards or official guidance where relevant
- user-reported experiences (carefully framed)
- practical demos, sandbox reviews, or pilot feedback (when available)
Step D — Findings
We publish:
- who the product fits
- who should avoid it
- what must be true for success (data/process/team)
- implementation risk and common pitfalls
3) Sources we prefer
We prioritize:
- primary documentation (official vendor docs, standards bodies)
- reputable industry publications and research
- transparent operator experiences with clear constraints
We avoid:
- anonymous, unverifiable claims
- sensationalized comparisons without evidence
- “one-size-fits-all” statements for jurisdiction- or contract-dependent issues
4) Handling uncertainty
Many claims vary by:
- pricing tier
- contract terms
- region and compliance requirements
- integration landscape
When that uncertainty matters, we will:
- state assumptions and scope,
- describe what to verify during procurement,
- avoid presenting variable claims as universal facts.
5) Ratings and scorecards (if used)
If we use numeric scores, we aim to:
- define criteria and weights,
- keep scoring consistent within a category,
- separate “fit” from “quality” where possible.
A product can be “good” but wrong for your environment.
6) Reader contributions
If you want to:
- suggest a tool for evaluation,
- submit a correction,
- share anonymized implementation lessons,
use the Contact page.