How to Improve RFP Processes

Just got off a call with a CCO at a biopharma provider (also our customer) who shared their monthly RFP volume. I wasn't ready for the number. 1,000+ RFPs. Every. Single. Month. Here's what he told me: - They were disqualified from 60% of RFPs due to slow turnaround - Every department gets pulled in (BD, Quality, Finance, Lab, Legal, Data Privacy) - Questions range from 20 (small biotech) to full platform submissions (Big Pharma) Their solution? Throw people at it. But here's the kicker: "Everyone hates the process." The math doesn't lie: 1,000 RFPs × 2h per team * 9 teams = 18,000 hours/month That's 112 full-time employees just answering RFPs (not realistic) With a 60% disqualification rate from being too slow Meanwhile, their competitors are responding in days, not weeks. The hidden cost isn't just time - it's lost business. The real killer came when they partnered with a major CRO. Overnight, they got 350+ more RFPs per month. They couldn't scale. Lost deals. Damaged relationships. Left money on the table. They tried building a question repository. Failed. Why? Every RFI words things slightly differently. Copy-paste doesn't work when context matters. Now they're investing in better processes and technology: ✅ BD owns the process AND the tools (not just the outcome) ✅ Pull from validated, contextual knowledge bases (constantly updated) ✅ SMEs review exceptions only, not routine questions ✅ AI agents handle the 80% that's routine, and delegate the 20% The difference between winning and losing? It's not your science. It's not your pricing. It's whether you can respond before your competitor. Speed is the new competitive advantage. What's your monthly RFP volume? And who's really writing those responses?

RFP responses can be a real challenge. They’re often slow and inconsistent due to scattered knowledge and manual processes. This was the case for a global consultancy that wanted to speed up how it brought its offerings to market. Sales teams struggled to access past proposals, relevant case studies, and client-specific context. This customer was an early Glean Agent adopter, and we’re thankful for their feedback along the journey. To address this challenge, they deployed a suite of Glean agents. The goal was to unify content discovery and streamline proposal workflows, pulling from their company knowledge bases, CRM systems, and external research to support end-to-end RFP generation. This was paired with a methodical approach to enablement and adoption. Some examples of agents they built: • A Client Need Triage agent that maps client requirements to standard service offerings • A Research agent to pull together industry and company-specific insights • A Historian agent to surface past engagements and account activity right from the CRM • A Proposal Helper agent to accelerate proposal creation with standardized, offering-aligned drafts This foundation delivered real business value: • Proposal development time dropped from 4 weeks to just a few hours. That’s a 97% productivity gain. • A heuristic metric of deflecting over $150K if a single point enablement Saas solution was chosen. By embedding agents directly into the sales workflow, the consultancy improved both speed and precision in proposal development. Now, they’re looking to apply the same agent-driven approach to other parts of the business, like managed services and engineering, to bring that same efficiency and intelligence everywhere.

RFPs are meant to bring clarity and fairness to vendor selection. So why do they so often lead to frustration, confusion, and subpar outcomes? If you've been on the receiving end of an RFP process that felt like an information black hole—or worse, a checkbox exercise—you’re not alone. Too many organizations treat RFPs as a formality rather than a strategic tool. That’s why we’re talking about RFP best practices—because when done right, RFPs can deliver alignment, speed, and quality outcomes. But to get there, the process needs to evolve. From our latest post on the Bridgepointe blog, here are three practical takeaways for improving your next RFP process: ✅ Define the Problem, Not Just the Product Start with a clear articulation of the business need. Vendors can’t solve what they don’t understand—and a spec sheet isn’t a strategy. Be explicit about what’s broken and what success looks like. ✅ Engage Internal Stakeholders Early IT, security, finance, and business users all have skin in the game. Make sure they’re part of shaping the requirements—not just rubber-stamping the solution at the end. ✅ Be Transparent About Evaluation Criteria No one wins when vendors have to guess what matters most. Sharing how responses will be evaluated creates a more level playing field and helps you make faster, more confident decisions. RFPs don’t need to be painful. With the right strategy, they can be a catalyst for smarter, faster tech investments. 📘 Read the full post for more insights: https://bit.ly/4jx6z9D If you're navigating a complex IT project and want support in running a streamlined RFP process, let's talk. #RFPBestPractices #ProposalManagement #RFPProcess

How We Use AI to Streamline Our Processes: A Real-Life Example Responding to Requests for Proposals (RFPs) is a common yet resource intensive task for many businesses, including ours at Verimatrix. While many RFPs request similar types of information, each company's unique format and phrasing often demand extensive manual work, something difficult to automate using traditional rules-based systems. Fortunately, with 30 years of experience, Verimatrix has accumulated a large database of previous RFP responses and legal contracts, ideal for training an an AI . By training an LLM solely on our historical data, we reduce external noise and mitigate the risk of AI hallucinations. Today, when an RFP arrives, our AI drafts a response in seconds. Though the accuracy is around 90-95%, a manual review is still necessary to ensure precision. Nonetheless, this approach saves considerable time for our engineers and legal teams. It's a practical use of AI to address real-world business tasks. AI doesn’t always mean radical transformation, sometimes, it's just about working smarter and saving valuable time. #AIinBusiness #SmartAutomation #WorkSmarter #EfficiencyBoost #RealWorldAI #Verimatrix