Creating the right price point in a government bid isn’t just about hitting a target budget—it’s about outsmarting the competition without even seeing their cards. Because bidding is blind, we rely on multiple estimation models to position our bid where it stands the best chance of winning.
We do this not just to be competitive, but to optimise both value and profitability. Let’s walk through how we use Top Down, Bottom Up, Parametric and other estimation techniques as part of our Position to Win (PTW) approach.
Why Estimation Models Matter in Public Sector Bidding
In UK procurement, tenders are typically assessed using MEAT (Most Economically Advantageous Tender) scoring. That means your bid is judged on both price and quality—but you never see what others are bidding. This creates a high-stakes strategic challenge that’s very different from normal pricing.
To succeed, we model our way through it. Each method helps us answer a different piece of the puzzle:
- What’s the client’s budget?
- How will competitors price?
- What level of quality will be expected?
- Where should we pitch our price to balance value and margin?
By combining different estimation approaches, we can simulate potential outcomes and land our bid at the ideal point on the MEAT matrix.
01.Top-Down Estimation
This method starts with a high-level benchmark—usually the client’s published budget or previous contract values. We look at award notices, FOI requests, and portals like Contracts Finder to estimate what the buyer can pay.
We then work backwards from there, setting a ceiling price and trimming costs until we find a delivery model that fits beneath it. It’s fast and helps anchor our commercial strategy in reality.
02.Bottom-Up Estimation
This approach flips the logic. Instead of starting from the budget, we start from first principles—every labour hour, license, sub-cost, and delivery element. We build the full cost model from scratch.
Bottom-up is essential when pricing complex services, or when we’re entering a market we haven’t delivered in before. It gives us clarity on our true delivery costs, which means we never bid below margin.
03.Parametric Estimation
This is where things get clever. Parametric estimation uses mathematical formulas to estimate prices based on known inputs—like number of users, volume of transactions, or geographic spread.
We use past internal data and public award data to build price-per-unit estimates. It's especially powerful in high-volume or tech-heavy bids where scaling impacts cost.
04.Comparative Competitor Modelling
Because we never see what our competitors are pricing, we model them. Using a mix of public data, industry intel, and buyer behaviour, we build hypothetical competitor profiles:
- Cost Base: What are their likely overheads?
- Aggression: Are they aggressive on price or quality?
- Win History: Have they won similar bids recently?
- Strategy: Are they trying to break into a new framework?
This isn’t about guesswork—it’s about building evidence-based scenarios so we can position accordingly.
05.Game Theory & Strategic Trade-Offs
When we price a bid, we think in terms of trade-offs. What does scoring 95% on quality mean for our price? Where is the point of diminishing returns?
We use PTW to model different price/quality pairings and forecast potential outcomes. It’s game theory in action—predicting what others might do, and responding with our best possible move. Instead of aiming for “cheap” or “perfect,” we aim for “optimal”—the sweet spot where we score high enough on both price and quality to win.
Using 3-Point Models and PERT for Accuracy
Across all estimation methods, we use three-point modelling to capture a range of possible outcomes: Best Case, Most Likely, and Worst Case. This helps us factor in uncertainty, risk, and delivery volatility.
Where appropriate, we also apply PERT (Program Evaluation and Review Technique) to smooth the estimates into weighted averages. This adds nuance and realism to our estimates, moving beyond single-point pricing and giving us more informed control over bid strategy.
Creating a Price Landing Zone
Once all our estimates are built—top-down, bottom-up, parametric, competitor-based—we consolidate them into what we call a Landing Zone. This is the price range where we believe we can:
- Deliver profitably
- Score highly on quality
- Outperform the likely competitive field
We then simulate non-price scoring (quality, social value, implementation plans, etc.) to identify the ideal point within that zone that gives us the strongest overall MEAT score.
Summary
Estimation isn’t just a finance exercise—it’s a Position to Win strategy. By combining multiple modeling techniques, we bring clarity and control to one of the most uncertain parts of public sector bidding.
The Stratify Edge: We constantly arm ourselves with the latest techniques from Data Science, Big Data, Web Scraping & First Class Intelligence practices to leverage large volumes of data and give statistical significance to our Position to Win strategies.