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Press Kit

Approved bios, downloadable photos, current talk titles, booking details and figures you can quote with sources. Use anything on this page without asking. For interviews and comment, email andreas@leed.dk.

Bios

Copy either bio and use it as it stands.

Short bio (about 50 words)

Andreas Bang Leed researches how to choose the right projects and make the best use of public resources, including how to measure and value nature. He co-authored How to Measure Anything in Project Management (Wiley, 2025), is a researcher at Aarhus University and has advised clients in more than 25 countries.

Full bio (about 150 words)

Andreas Bang Leed is a researcher in economics at Aarhus University, where he teaches a master's course on cost-benefit analysis in the public sector. His research concerns how to choose the right projects and make the best use of public resources. One strand examines how noise in cost and benefit estimates affects which projects are selected and how the selected projects perform against those estimates. Another estimates how the ecological quality of nearby nature is reflected in Danish house prices, so that nature can enter cost-benefit analysis.

He co-authored How to Measure Anything in Project Management (Wiley, 2025), which tests popular project management methods against the evidence and offers tools for forecasting and decision making. He has advised governments, multilateral organisations and consultancies in more than 25 countries on projects from nuclear energy and transport to artificial intelligence and biodiversity. For the Hong Kong Development Bureau he helped build an AI early-warning system that monitors its public-works portfolio.

Photos

Cleared for press and event use. The download links give the full-resolution files.

Andreas Bang Leed, square headshot in jacket and tie
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Andreas Bang Leed, seated portrait in a light blue shirt
Portrait, casual · 960 × 1440 px
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Andreas Bang Leed, studio portrait in a navy suit and tie
Portrait, suit · 1024 × 1536 px
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Andreas Bang Leed speaking on stage with a headset microphone
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Talks

Current talk titles. Each is described on the Speaking page.

  • Why Projects Fail, and How to Fix Them
  • How to Measure Anything in Project Management
  • AI for Project Oversight
  • Net-Zero Projects & the Cost of Carbon
  • Tipping Points & Tail Risk for Long-Lived Assets
  • Biodiversity & Ecosystem Valuation

Emcee introduction (about 40 words)

Our next speaker is Andreas Leed, co-author of How to Measure Anything in Project Management and a researcher in economics at Aarhus University. He studies how to choose the right projects and how to measure and value nature. Please welcome Andreas.

Booking

The practical details for booking me.

Formats
Keynote, workshop, panel and podcast.
Typical lengths
Keynotes run 30 to 60 minutes plus Q&A. Workshops run from 90 minutes to a full day. Panels and podcasts follow your format.
Languages
English and Danish.
Travel
I travel internationally and also run virtual sessions.
Notice
As much notice as you can give is appreciated. Late requests are still worth sending.
Enquiries
Use the speaking enquiry form. I read each enquiry myself.

Numbers you can quote

Each entry below gives a figure from my published work, a public analysis or my current research, with a source you can cite. A “Does not show” line under the source states the limits of the figure. Where a result is preliminary, the entry says so.

Across the cost reference classes, the median project ends about 1.1 times its estimate

The median roadway ends at 1.13 times its estimate, and the median IT project lands on target at 1.00. The tails carry the risk. The distribution has a heavy right tail, and a few projects run past three and a half times.

Source: the reference classes in Hubbard, Budzier & Leed (2025), How to Measure Anything in Project Management, Wiley.

Does not show: a single overrun rate for all projects. Medians differ by project type and by the stage at which the estimate is made.

UK rail projects need a 60% cost uplift to be 80% confident of no overrun

At the Full Business Case stage, the recommended uplift on rail capital costs is 60% at 80% confidence and 19% at the median. The analysis behind the guidance draws on a database including 2,522 new-build rail, road, bridge and tunnel projects.

Source: Budzier & Leed (2021), Updating the Evidence Behind the Optimism Bias Uplifts for Transport Appraisals, Oxford Global Projects for the UK Department for Transport.

Does not show: one uplift for everything. Figures vary by project type and rise sharply at earlier stages, to 121% for rail at Strategic Outline.

Clean-energy projects run 84% over budget on average

Across a dataset of more than 1,100 clean-energy and decarbonisation projects, the mean capital-cost overrun is 84% and schedules run 51% long. The cost figures rest on the 482 projects in the dataset with cost data. For projects completed since 2000 the mean cost overrun is 36%.

Source: Greig, Techau, Leed & Budzier (2025), Maintaining capital discipline in the rush to net-zero energy systems, iScience 28(4), 112241.

Does not show: that each technology performs alike. Excluding nuclear, the full-sample cost overrun falls to 17%, and solar PV lands closest to estimate.

More than 200 capital projects monitored by Hong Kong's AI early-warning system

The Project Supervision System, which I helped build, flags public-works projects drifting towards cost overrun or delay early enough to act. It was trained on 849 completed projects spanning HKD 460 billion of outturn cost.

Source: Flyvbjerg, Budzier, Agard & Leed (2022), AI in Action, Hong Kong Development Bureau (PSGO). Portfolio size per the Hong Kong Development Bureau.

80% of the Hong Kong system's cost forecasts land within ±10%

The current models reach 91% accuracy on cost overruns and 88% on schedule overruns, using how a project is spending in flight rather than plans alone.

Source: AI-PSS-3, Oxford Global Projects for the Hong Kong Development Bureau, presented at Machine Learning Week Europe 2024.

Does not show: general forecasting accuracy. The figures are cross-validated performance on Hong Kong's own portfolio.

Selection can account for roughly 25 to 50% of observed cost overruns

Across most infrastructure categories, ranking projects on noisy estimates and funding the best-looking ones can produce overruns in the funded projects even when no single estimate is biased. The central reading is near a third.

Source: Leed (2026), Noise, Selection, and the Illusion of Bias, SSRN Working Paper No. 6429358. The version on SSRN is an earlier draft.

Does not show: that optimism bias is gone. Selection explains only part of observed overruns. For dams, the category with the largest overruns, the central estimate of the share explained by selection is about 12%. Where funding decisions are not purely benefit-cost driven the effect is smaller.

One bioscore point of nearby ecological quality is associated with about 2.8 percent higher house prices

The bioscore, from the national Biodiversitetskort map, is an index of ecological quality scored 0 to 19 and averaged within 1 kilometre of each home. When homes of the same type within the same parish are compared across around 850,000 Danish sales, one additional point is associated with about 2.8 percent higher prices, or DKK 57,500 at the median sale price of DKK 2 million. Homes of the same type in the same parish typically differ by about half a point. One standard deviation of that within-parish variation, 0.56 points, is associated with about 1.6 percent higher prices, or DKK 32,000. Without any adjustment, one point is associated with about 10 percent higher prices across the country. Around seventy percent of that raw association disappears once other housing and location characteristics are held constant and homes are compared in this way. I read that reduction mostly as a matter of who chooses to live near nature.

Source: My current research at Aarhus University, a working paper in progress titled The Price of Biodiversity: Hedonic Evidence from Danish Housing Markets.

Does not show: a causal effect or a price for any particular place. These are preliminary associations from an unpublished paper and may change before release.

Nuclear waste storage needed a 202% cost uplift to be 80% sure

A reference-class forecast over 216 comparable past projects found that the lowest official Swiss contingency gave its estimate barely 30% certainty. At the median the required uplift is 67%.

Source: Budzier, Flyvbjerg, Garavaglia & Leed (2018), Quantitative Cost and Schedule Risk Analysis of Nuclear Waste Storage, SSRN Working Paper No. 3303410.

Does not show: a forecast for other countries' programmes. It is a Swiss case, and the reference class pools nuclear and underground mining projects.

Cost overruns analysed across 88 stadium projects

The analysis behind Danish coverage of stadium economics, including the planned Aarhus stadium.

Source: coverage in Jyllands-Posten (November 2024) and TV2 Østjylland (December 2024), both linked from the Speaking page.

Does not show: a headline overrun percentage. Ask me for the underlying figures before quoting a magnitude.

For interviewers

Suggested questions by theme, and the topics I can comment on at short notice.

Megaprojects and cost overruns

  • How often do large projects run over budget, and by how much?
  • How do Danish megaprojects compare with the rest of Europe?
  • Which project management methods have been shown to improve estimates and outcomes, and which are taken on trust?

Measurement

  • What does it mean to measure anything in a project?
  • What is wrong with risk matrices?
  • How does calibration training change expert judgement?

AI and public oversight

  • How does Hong Kong's early-warning system spot a project in trouble?
  • Where does AI help public-project oversight today, and where should it wait?

Noise and selection

  • How does the way projects are chosen affect how they perform against their estimates?
  • What should change in how governments approve projects?

Pricing nature

  • What do Danish homebuyers pay for the ecological quality of nearby nature?
  • Why does most of the raw price gap reflect who lives where?
  • How should biodiversity enter cost-benefit analysis?

At short notice I can comment on the cost of large projects, the evidence on which methods improve estimates and outcomes, stadium economics, AI in public-project oversight and the price of nature.

Email andreas@leed.dk. If you are working to a deadline, include the date in your message so that I can prioritise it.