Why Consulting Proposals Take So Long (and What to Reuse)

13 November, 20269 min read

Jan Beránek

Consulting proposals take so long because every pitch rebuilds research the firm has already done. Keep your method and source-checked public facts from every engagement, and the next proposal starts ahead.

One big reason consulting proposals take so long: each one rebuilds research the firm has already done. In a boutique, a proposal often follows an intro coffee and a chemistry meeting, and a partner writes it on top of client work. The experience from the last ten similar projects is there, but it sits in old decks, so the partner researches the prospect's market again from scratch – against the clock, and unpaid.

My take is that a bigger archive doesn't fix this. What fixes it is keeping two things from every engagement: the firm's method as its best people actually ran it, and the public, source-checked, dated facts that research produced. Pitch research is external by nature – the prospect isn't a client yet – so it can start from what the firm already knows without touching anything confidential. The payoff is sharper proposals with less unpaid partner time, and room to answer the ones the firm now lets go.

The hidden cost of pitching

In a pyramid firm, proposal research could go to whoever was between engagements. A boutique has no research bench, so the research lands on the partner who will lead the work, in the evenings, on top of billable days. Some proposals never get written at all, because the partner who would write them is busy delivering.

Formal tenders are the part of this anyone measures. Loopio's 2026 benchmark of dedicated RFP response teams puts a single RFP at 33 hours and nine contributors on average, all of it before anything is won, and those organizations respond to only 55% of the RFPs they receive (Loopio, 2026). Management consulting submits more RFPs than any other industry, 229 a year (Loopio, 2026). That's the big-firm end of the market, but the shape is familiar to a boutique.

On partner calls we hear the same story from firms that have started to change this: a good response that used to take three weeks and five people now takes one week and one person. The time that frees up goes back to client work, and to the proposals the firm used to let go.

Why proposals rebuild the same research

I call it selective amnesia when I see it in large companies: one project with consultants, another a month later, and the two don't know about each other. Consultancies have the same thing with their own pitches. Past work lives in decks built for one client's story, with the reusable part tangled up with that client's part. Its facts carry no date and often no source, so a market figure from last year can't go into a proposal without being checked again. And the people who knew why a slide said what it said have often moved on.

Generic AI fills the blank page faster, but it doesn't solve the checking. A pitch is exactly the kind of question where AI answers go wrong: one sector, this year, this prospect's competitors. Not super surprising that partners end up re-checking every number. As I put it on a partner call in November: "If what's in the answer is not supported by the source, it's hallucinated – we cannot use it."

The general case is in Research Knowledge Management: Stop Starting From Zero.

What to reuse across proposals, and what stays behind

The rule I keep for our own work is that every good run should leave behind something reusable. For a proposal, two things qualify. The first is the method: the questions your best people ask, the sources they trust, the order of steps, and what "good" looks like at each one. The second is the public facts your research produced about sectors, markets, competitors and regulation, each kept with its source and the date it was checked, so the next team can re-check a fact instead of finding it again. We run our own research that way: "We break it down into individual facts. Those facts we save for reuse." And every stored fact has been checked: "If it's here, it means that some agent somewhere on the platform had to verify this information."

One thing stays behind: anything a client gave you in confidence, such as interviews, internal data and documents. It belongs to that engagement, it has no place in the knowledge you reuse, and pitch research doesn't need it.

What	Examples	Carries into the next pitch?	How to keep it
Your method	Questions, lenses, trusted sources, order of steps, the quality bar	Yes – it applies to any prospect	Encode it once so it runs the same way every time
Public facts	Market, sector, competitor and regulatory facts from public sources	Yes, with source and date	Store each fact with its source and the date it was checked
Judgment notes	Which questions mattered, where the method had to change	Yes, as changes to the method	Fold them back into the method after each engagement
Client-confidential material	Interviews, client data, internal documents	No	Leave it with the engagement it came from

What pitch preparation looks like when it runs on your method

A prospect is, by definition, someone you hold no private material on. Everything a pitch needs is public: their market, competitors, announcements and regulators. Many firms assume the edge has to be proprietary or licensed data – on that November call it was the partner's first question. My answer was public sources, structured and verified. Two examples:

Pursuits at an architecture and engineering firm. For a $250M+ North American architecture and engineering firm, a regional market assessment used to be a multi-week, analyst-led deliverable. It now runs in 35 minutes to an hour, and feeds the firm's calls on which markets to grow into and which pursuits to chase (FifthRow proof). On a live request for proposal, the system answered a repositioning question in about an hour, and that run became a reusable template. The firm's own analysts built most of its systems in-house, and the firm met all eight success criteria it set itself.

Pitch and deal work across a practice. In the design and innovation practice of a $30B+ global IT services and consulting group, pitch and deal preparation is used by 15 consultants across a consulting and venture team, and the practice's own delivery leads put the productivity gain on research at 3 to 5 times (FifthRow proof).

Where a firm encodes its own method, FifthRow's Large Consulting Model runs it inside the tools the team already uses: Copilot, ChatGPT and Claude. Every answer is fact-checked before your team sees it, and a judge agent reads every output. We do not train on, resell, or package your data, and the platform pairs security and privacy controls with European hosting (FifthRow).

What doesn't change

The partner still decides whether to bid, frames the prospect's problem and owns the relationship. The architecture and engineering firm kept a human decision point between every stage (FifthRow proof). And the method that runs is the firm's own: your team encodes it, from your own playbook, in your own account. The research a proposal needs comes from public sources, not from anything a prospect told you over coffee.

What moves is the bottleneck. When research stops being the slow part, the slow part is the partner – which proposals to write, and what to argue in them that a competitor can't.

Frequently asked questions

How long does it take to write a consulting proposal?

For formal tenders, Loopio's 2026 benchmark of dedicated response teams puts a single RFP at 33 hours and nine contributors on average, before anything is won (Loopio, 2026). A boutique proposal after a chemistry meeting is smaller, and it often sits with one partner. The part you can cut is the research that repeats from pitch to pitch. The argument for why your firm should win takes as long as it takes.

What can you reuse across consulting proposals, and what should you redo?

Reuse your method and the public facts that carry a source and a date, re-checked before they go into the proposal. Redo the read on this prospect and the argument you make to them. Client-confidential material is never reused.

Where does AI help with consulting proposals, and where does it add review work?

It helps when it runs your own method on public evidence and checks every source first. It adds review work when it hands a partner a fluent draft with unchecked citations. For a checklist on the checking part, see How to Verify AI Research.

How should a consultancy research a prospect before a pitch?

Run a lighter version of your own discovery steps on public evidence about the prospect: market, competitors, announcements, regulators. Then put a standing monitor on the accounts you pursue, so the research is current when the request for proposal arrives.

Two ways to work with FifthRow

We spent fifteen years in the consulting chair, much of it as U+, the corporate venture builder FifthRow grew out of. There are two ways to work with us. Start with a license for your own delivery: your method encoded once and run by your team inside the assistant they already use. Or partner in delivery and co-own the work with us. Either way, you keep the client and the last mile. More on both at fifthrow.com/consultants.