Craig Stanley
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Anchoring in estimates

The first number mentioned pulls every later estimate towards it. How anchoring distorts project, budget and AI-benefit estimates, and what to do about it.

10 October 2026 · 2 min read · Craig Stanley
In short, explained

If someone says a number first, everyone else's guess ends up close to it, even if the first number was silly.

Anchoring is when the first number you hear drags your own estimate towards it. In meetings, whoever speaks first sets the anchor. Get people to write their estimates down before anyone shares one.

Anchoring biases estimates towards an initial value, even an irrelevant one. Use independent estimation before discussion, reference-class data instead of inside-view anchors, and treat vendor benefit claims as anchors to be tested.

Where it shows up at work

  • Project estimates: the sponsor says "this should take about a month" and every estimate clusters around four weeks.
  • Budgets: last year's figure becomes the starting point, whatever has changed.
  • AI benefits: a vendor case study claims a large time saving, and the internal business case quietly starts from that figure.

Why it's hard to avoid

Anchoring works even when people know the anchor is irrelevant. In classic experiments, numbers produced at random still pulled people's estimates towards them. Knowing about the bias reduces it a little but doesn't remove it.

What helps

Estimate alone first. Ask everyone to write their estimate down before discussion. Then reveal them together. The spread is useful information in itself.

Start from a reference class. Instead of asking "how long will this take?", ask "how long did the last five similar projects take?" Start from that and adjust.

Name the anchor. When a number has been put on the table, say where it came from and ask whether it applies here. Vendor figures in particular should be labelled with their source and date, as everywhere on this site.

Read next

A question to take awayWhich repeated decision would you trust a cheap model to score first, with a person checking the close calls?

About me

Craig Stanley

Microsoft AI consultant and technical architect, based in Whitley Bay. Over the last few years I've delivered Microsoft 365 Copilot, Copilot Studio agents, Azure AI Foundry work and governance for UK public sector and financial services organisations.

What interests me is the decision underneath the tool: what it costs, what it risks, and whether a small, transparent model can make it better. I write the methods up here and on Substack so anyone can use them.

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