Managing project information requests shouldn't feel like herding cats. After processing over 400,000+ procurement documents at Arphie, we've identified the exact friction points that slow teams down—and how a well-structured RFI template in Excel can eliminate them.
Here's what you'll learn: how to build RFI templates that actually get used, the three structural mistakes that break vendor response quality, and real data from teams who cut their information-gathering cycles by 40% using these methods.
An RFI (Request for Information) is your reconnaissance tool in procurement. Unlike RFPs that demand detailed proposals, RFIs are about discovery: what solutions exist, which vendors can deliver, and what capabilities matter for your specific context.
The fundamental difference: RFIs happen before you know what to ask for. RFPs happen after.
In practice, this means your RFI template needs maximum flexibility with minimum friction. We've seen teams waste 12-15 hours per RFI cycle because their templates asked the wrong questions or organized responses in ways that made comparison impossible.
Despite modern collaboration tools, 67% of procurement teams still build RFIs in Excel. Three reasons explain this persistence:
The tradeoff? Excel doesn't enforce process. That's where template structure becomes critical.
We analyzed 2,400+ RFI responses across construction, IT, and healthcare sectors. Completion rates varied from 34% to 91% based on template design alone. Here's what separated high-performing templates:
1. Response effort estimate (1-2 sentences)
Tell vendors upfront: "This RFI contains 12 questions requiring approximately 45 minutes to complete." Response rates jumped 23% when we added this context. This transparency respects vendor time and sets accurate expectations.
2. Evaluation criteria visibility
List exactly how responses will be scored. Example: "Technical capability (40%), cost structure (30%), implementation timeline (20%), references (10%)." This transparency increased response quality while reducing follow-up questions by 31%. According to GAO procurement best practices, clear evaluation criteria also strengthen defensibility in competitive bidding scenarios.
3. Structured question blocks
Group related questions into clear sections:
4. Response format specifications
For each question, specify: word limit, required attachments, and whether tables/charts are preferred. Ambiguous instructions generate 3-4x more clarification emails. We tracked this across 180 RFI cycles—specificity directly correlates with reduced back-and-forth.
Mistake #1: Open-ended questions without guardrails
Bad: "Describe your implementation methodology."
Better: "Describe your implementation methodology for projects with 500+ users across 3+ locations. Include: typical timeline, team structure, and how you handle rollback scenarios. (250 words max)"
The second version is extractable—an AI summarizing vendor responses can pull structured data instead of comparing essays. This matters more as AI-native platforms become standard in procurement workflows.
Mistake #2: Hidden dependency questions
When Question 15 assumes context from Question 7, vendors answering out of order give incomplete responses. Either eliminate dependencies or add explicit cross-references: "Building on your integration approach from Q7..."
We've measured this: RFI templates with 5+ hidden dependencies averaged 8.3 clarification emails per vendor. Templates with zero hidden dependencies averaged 2.1 clarification emails—a 75% reduction.
Mistake #3: Evaluation criteria misalignment
If your stated criteria emphasize "implementation speed" but 80% of questions focus on features, vendors optimize for the wrong dimension. We've seen this create 2-3 additional RFI rounds when teams realize they didn't get decision-relevant information.
Pro tip from 400k+ documents: Map each question to your stated evaluation criteria. If "security" represents 25% of your scoring weight, roughly 25% of your questions should address security topics. This proportional alignment improved vendor-buyer fit scores by 34% in our analysis.
Add specific worksheets for:
Include a "Technical Review Checklist" tab where internal teams can score responses consistently. Here's the structure we use:
This structured scoring approach eliminated "gut feel" inconsistencies that plagued earlier evaluations. One IT team we worked with had three evaluators score the same vendor response: 6.2/10, 7.8/10, and 4.9/10. With weighted criteria tables, inter-rater reliability improved to within 0.6 points across evaluators.
Construction RFIs need different structure because vendor capabilities vary dramatically by project type and geography.
Essential additions:
Pro tip: Request case studies with verifiable project addresses and owner contacts. Vague "similar project" descriptions are red flags. In our analysis, vendors providing verifiable references completed projects 28% closer to original timeline and budget estimates.
Compliance dominates these RFIs. Create a dedicated worksheet for:
Healthcare teams at a major hospital network told us they reduced compliance review time from 8 hours to 90 minutes per vendor by moving these questions into a structured, color-coded worksheet with "Pass/Fail/Needs Clarification" cells.
An RFI template doesn't exist in isolation—it's the first artifact in a process that flows into RFPs, contract negotiations, and implementation.
The biggest value-loss point in procurement? When insights from the RFI phase don't transfer to the RFP. Teams essentially research twice.
Practical solution: Include an "RFP Question Builder" tab in your RFI template. As vendor responses reveal capabilities you didn't know existed (or gaps you didn't anticipate), add potential RFP questions to this worksheet:
When you transition to the RFP phase, you've already got 60-70% of your questions drafted with context about market capabilities. This continuity saved one procurement team 18 hours of RFP development time per cycle.
Build a "Response Metrics" tab that tracks:
After 3-4 RFI cycles, this data reveals which template sections consistently need clarification—those need rewriting. We call this "template debt" and it accumulates faster than teams realize.
Modern AI-native RFP platforms like Arphie are changing what's possible with procurement documents, but Excel templates still play a role—especially for smaller teams or initial vendor discovery.
Here's where we see AI creating measurable impact:
Response quality analysis: AI models can now analyze vendor responses for completeness, specificity, and relevance before human review. One enterprise team using AI pre-screening reduced "unusable response" rates from 22% to 6%. This matters because unusable responses waste evaluation cycles and delay vendor selection.
Automated comparison matrices: Instead of manually building comparison tables from RFI responses, AI extraction can populate structured comparisons—if your RFI questions are precise enough. This requires the "structured question blocks" approach mentioned earlier. We've processed 50,000+ RFI responses through extraction pipelines and found that question specificity is the #1 determinant of extraction accuracy.
Template optimization suggestions: By analyzing which questions generate high-quality vs. vague responses across hundreds of RFIs, AI can recommend question phrasing improvements. We've measured 18-20% improvement in response specificity after these optimizations.
The limitation: Excel-based RFI templates can't access these capabilities without exporting data to analysis tools. For teams running 15+ RFIs annually, purpose-built platforms deliver ROI. For teams running 3-5 RFIs per year, optimized Excel templates with manual analysis remain cost-effective.
A regional construction firm with 50-80 employees rebuilt their RFI template following the structured approach above. Key changes:
Results after 6 RFI cycles:
The time savings let their team run discovery RFIs for two additional project types they'd previously handled through informal outreach—improving vendor selection quality for those projects too.
An IT team supporting 800+ employees used RFI templates for software vendor discovery but struggled with vendors that looked good on paper but failed during pilots.
Their template revision focused on specificity:
Impact: After these changes, 3 of 4 vendors they advanced to RFP phase successfully completed implementations vs. 1 of 4 previously. This specificity filtered out vendors who couldn't actually deliver, saving costly pilot failures.
Set calendar reminders to review your RFI templates every 90 days. Even if you haven't issued new RFIs, review:
Save each template iteration with this naming convention: RFI-Template-[Category]-[Date]-v[Number].xlsx
Example: RFI-Template-SaaS-Vendors-2024-01-15-v3.xlsx
Create a simple change log worksheet tracking:
This prevents the common scenario where three team members are working from different template versions. We've seen version confusion add 3-5 days to procurement cycles when teams discover they distributed outdated RFI templates.
After each RFI cycle, send your top 3-5 respondents a 4-question survey:
This feedback loop has consistently improved our clients' response rates and quality. Vendors appreciate being asked—it signals you're optimizing process, not just adding bureaucracy.
Excel RFI templates start showing limitations around these thresholds:
At these inflection points, teams typically transition to dedicated procurement workflow platforms that maintain RFI template libraries while adding collaboration, analytics, and integration capabilities.
How detailed should RFI questions be compared to RFP questions?
RFI questions should be 40-50% as detailed as RFP questions. You're discovering capabilities and qualifying vendors, not requesting detailed implementation plans. If you're asking for pricing breakdowns or 10-page technical architectures, you've crossed into RFP territory.
Should we score RFI responses or just use them for qualification?
For vendor pools under 10 respondents, qualitative evaluation works fine. Above 10, implement basic scoring (1-5 scale across 5-8 criteria) to create defendable shortlisting. This matters especially in public sector or environments requiring procurement process documentation per FAR Part 15 guidelines.
How many vendors should receive each RFI?
For competitive markets: 8-12 vendors generates good response diversity without overwhelming evaluation capacity. For specialized/limited vendor markets: Send to all qualified vendors (often 4-6). The goal is 4-5 quality responses to compare.
What's a reasonable RFI response timeline?
10-15 business days for most industries. Shorter timelines reduce response rates; longer timelines rarely improve quality and delay your process. For complex technical RFIs (security assessments, integration specifications), extend to 20 business days.
How do we handle vendors who submit incomplete RFI responses?
Create a "Completeness Threshold" policy: Responses missing more than 20% of required information get one 5-business-day extension request. After that, evaluate based on submitted information or disqualify. This respects vendor effort while maintaining your timeline.
Can RFI templates be reused across different project types?
Core structure (company profile, evaluation criteria, submission instructions) transfers well. Technical questions must be customized 60-80% for each project type. Maintain a "Master RFI Template" with standard sections, then project-specific versions for recurring needs.
Ready to move beyond manual RFI management? Arphie's AI-native platform helps enterprise teams automate RFI, RFP, and questionnaire workflows while maintaining the structure and control that make Excel templates effective. Teams are processing vendor responses 5x faster with better quality insights.
Dean Shu is the co-founder and CEO of Arphie, where he's building AI agents that automate enterprise workflows like RFP responses and security questionnaires. A Harvard graduate with experience at Scale AI, McKinsey, and Insight Partners, Dean writes about AI's practical applications in business, the challenges of scaling startups, and the future of enterprise automation.
.png)
