MRX plorer
5-Pillar Tech Evaluation Framework
A Decision Guide for Evaluating Tech Tools
by Z Johnson, MRXplorer.com
💡 Remember: Strategy First, Tools Second
Before evaluating or committing to ANY tool, ask yourself:
What problem are we trying to solve?
How does this align with our 5-year strategy?
What's the business case for this investment?
What happens if we do nothing?
Are we solving a real problem or just attracted to the promises being made?
A tool with a perfect 25/25 score is still the WRONG tool if it doesn't serve your strategy.
Tool Name:
Pillar 1: Usability
Key Question: Can my team actually USE this without extensive training or technical expertise?
Questions to Ask:
How long does onboarding typically take?
Is the interface intuitive, or does it require specialized knowledge?
What kind of support is available (chat, phone, documentation)?
Can I see examples of how other teams use this day-to-day?
Will junior team members be able to use this, or just senior staff?
🚩 Red Flags:
Requires extensive training, complicated setup, poor documentation, unresponsive support
✅ Green Flags:
Quick onboarding, intuitive interface, excellent support, clear documentation
Pillar 2: Interoperability
Key Question: Does this work well with the tools we already use?
Questions to Ask:
What file formats does it import/export?
Does it have APIs or integrations with our current tools?
Can we easily move data in and out?
What happens to data if we cancel the service?
Will this create data silos, or will it connect with our workflow?
What happens to our data if we decide to leave this platform?
🚩 Red Flags:
Proprietary formats, no integrations, difficult data export, vendor lock-in
✅ Green Flags:
Open APIs, standard file formats, existing integrations, easy data portability
Pillar 3: Flexibility
Key Question: Can this grow and change with our business?
Questions to Ask:
Can it handle different types of projects/clients/industries?
Is it customizable to our specific workflows?
Can we scale up or down as needed?
What happens if our needs change in 6 months? 2 years?
Does it force us into rigid processes, or adapt to how we work?
🚩 Red Flags:
Rigid workflows, limited customization, "one size fits all" approach, can't scale
✅ Green Flags:
Highly customizable, scalable, adapts to different use cases, grows with you
Pillar 4: Data Privacy and Security
Key Question: Can we trust this with our clients' sensitive data?
Questions to Ask:
Where is data stored (which countries/servers)?
What certifications do they have (SOC 2, ISO 27001, GDPR compliance)?
What's their data retention policy? Can we control when our data is removed?
Have they had any security breaches? How did they handle it?
Can we control who has access to our data?
For AI tools specifically: Who owns the prompts and the outputs? Is our data used to train your AI models? Is our data shared with any third-party AI tools?
🚩 Red Flags:
Unclear data policies, no compliance certifications, indefinite data storage, past breaches with poor response
✅ Green Flags:
Clear privacy policy, relevant compliance certifications, data residency options, guaranteed deletion
Pillar 5: Price
Key Question: What's the TOTAL cost of ownership - not just the sticker price?
Questions to Ask:
What's included in the base price vs. add-ons?
Are there setup fees? Training costs? Implementation fees? Support fees? Data storage fees?
How much time will implementation take (hours = money)?
Is pricing per user, per project, flat rate, or usage-based?
What's the contract length? Can we cancel easily?
What's the true monthly/annual cost when everything is included?
🚩 Red Flags:
Hidden fees, forced annual contracts, expensive add-ons, costly training requirements
✅ Green Flags:
Transparent pricing, flexible plans, free trial, month-to-month option, included support
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