What do project managers need to know about GIS?
TL;DR: Project managers don't need to become GIS specialists, but they do need to interpret GIS outputs — orthomosaics, elevation models, point clouds — read how current they are, and know who owns keeping them accurate. Most project delays and rework trace back to a team working from an outdated or misread site record, not a lack of GIS training.
Key takeaways
- According to Autodesk and FMI's Construction Disconnected report, construction workers spend approximately 35% of their time — nearly two full working days per week — searching for project information or resolving conflicts caused by outdated data.
- A separate Autodesk and FMI study estimated that bad data cost the global construction industry $1.85 trillion in 2020.
- PMI's 2025 Pulse of the Profession found that project professionals with high business acumen — including the ability to interpret data like GIS outputs — post a 27% lower project failure rate than their peers.
- According to IBM's Institute for Business Value, 77% of respondents say data silos hinder their organization's ability to perform real-time analytics and make data-driven decisions.
- A project manager's job with GIS data isn't to become a GIS analyst — it's to know what a dataset represents, how current it is, and who's accountable for keeping it that way.
What is GIS, and why does a non-specialist need to understand it?
GIS (Geographic Information System) is technology for capturing, storing, and displaying data that's tied to a physical location. For a construction, infrastructure, or operations project manager, that mostly shows up as maps, aerial surveys, and elevation models rather than software you operate yourself.
You don't need to run GIS software to make good decisions from GIS outputs, but you do need to know what you're looking at. A project manager who can't tell the difference between a live site survey and a six-month-old reference map will make decisions on the wrong information — and won't know it until the discrepancy shows up as a clash, a delay, or a dispute over whose numbers were right.
This is different from most other project inputs. A budget spreadsheet or a schedule is self-explanatory: the numbers speak for themselves. A GIS dataset carries hidden context — when it was captured, at what accuracy, and whether it's still current — that isn't visible just by looking at the map. Reading that context is the actual skill a PM needs, not GIS analysis itself.
What GIS outputs will you actually see as a project manager?
Most project managers encounter five recurring GIS output types: orthomosaics, digital elevation models, point clouds, contour maps, and vector layers like site boundaries or utility lines. Knowing what each one shows — and doesn't show — is more useful than knowing how any of them are produced.
Orthomosaics are large, geometrically corrected aerial photographs, usually stitched together from drone imagery. They look like a photo of the site from above, and they're the easiest output for a non-specialist to read at a glance — but they only show what's visible from the air on the day they were captured.
Digital elevation models (DEMs) represent the height of the ground surface as a grid of values rather than a picture. They're what earthworks, drainage, and cut-and-fill calculations are based on. A DEM looks abstract compared to an orthomosaic, but it's often the more decision-critical dataset, because it's what volume and grading numbers come from.
Point clouds are dense collections of 3D points, typically from drone photogrammetry or LiDAR, used for detailed as-built records and clash detection. They require more processing power to view than the other formats, which is why they're often shared as a rendered 3D model rather than raw data.
Contour maps translate elevation data into lines a non-specialist can read quickly — useful for a fast visual check of slope and drainage without opening a full 3D model.
Vector layers — site boundaries, utility lines, easements, inspection points — are the data type most likely to be wrong if nobody owns updating them, because they change slowly and get forgotten between capture dates.
Why does understanding GIS data actually matter for project outcomes?
Understanding GIS data matters because most of the cost tied to "bad data" in construction and infrastructure projects isn't a specialist failing to do their job — it's a decision-maker acting on a version of the site record that was already out of date. Autodesk and FMI's Construction Disconnected report found that construction workers spend approximately 35% of their time on non-productive activities, including searching for project information and resolving conflicts caused by miscommunication or outdated data.
That figure includes plenty of situations that have nothing to do with GIS specifically, but site data is a disproportionate contributor: a physical site changes daily, so a survey that was accurate three weeks ago can be meaningfully wrong today. A project manager who treats a survey as a one-time deliverable rather than something to be reissued as the site changes is building decisions on ground that's already moved.
A separate Autodesk and FMI study put a bigger number on the same problem, estimating that bad data cost the global construction industry $1.85 trillion in 2020. PMI's 2025 Pulse of the Profession offers a more direct link to project management skill specifically: professionals who scored high on business acumen — a category that includes reading and acting on operational data — recorded a 27% lower project failure rate than their peers, and tracked an average of 9.1 success factors per project compared to 6.3 for everyone else. Interpreting GIS data well is one part of that broader acumen, not a separate specialist skill sitting outside it.
What mistakes do project managers commonly make with GIS data?
The most common mistake is treating a GIS output as a fixed reference rather than a snapshot with an expiry date — using the site survey from kickoff to make a decision in month four without checking whether a newer one exists. The second most common is mistaking a PDF or PNG export of a map for the underlying dataset, which loses the metadata (capture date, accuracy, coordinate system) that tells you whether the export can be trusted for the decision at hand.
A third mistake is letting GIS jargon become a reason to disengage from the data entirely — deferring every question to "the surveyor" or "the GIS team" instead of asking directly what a dataset shows and when it was captured. That's a reasonable instinct when the tooling genuinely requires specialist software, but it becomes a liability when nobody on the project side is checking whether the data being handed up the chain is current.
The fourth is not assigning clear ownership for keeping site data current. IBM's Institute for Business Value found that 77% of respondents say data silos hinder their organization's ability to perform real-time analytics and make data-driven decisions, and 83% believe silos undermine innovation. On a project team, a silo usually isn't a technical failure — it's a survey sitting in one person's inbox because nobody was named responsible for distributing it.
How does GIS data fit into a typical project lifecycle?
GIS data plays a different role at each project stage: it informs decisions during planning, tracks change during execution, and becomes the record of what was actually built at handover. Knowing which role a dataset is playing at a given moment tells you how much scrutiny it needs.
During planning and feasibility, GIS data — existing terrain models, aerial imagery, utility layers — shapes decisions like site selection, access routes, and early risk identification. Errors here are usually about completeness: a utility layer that's missing a line because it was never digitized, not because it changed.
During execution, GIS data shifts to a monitoring role — comparing a current drone survey against the baseline or against last month's survey to check progress, verify quantities, or catch a deviation from the design before it becomes expensive to fix. This is where currency matters most, because the whole point is measuring change, and a stale comparison point makes the comparison meaningless.
At handover, GIS data becomes the as-built record — the version of the site that gets handed to the client, operator, or asset manager as the reference going forward. A common failure here is publishing the handover based on the last survey taken, rather than confirming it reflects the final built condition.
What should you look for in a platform to work with GIS data?
The right platform for a project manager is one where you can open and understand a GIS dataset without installing specialist software or waiting on someone else to interpret it for you — because if every question about site data requires a request to the GIS team, the data isn't actually helping you make faster decisions.
For project managers who need to view and act on drone surveys, elevation models, and site records rather than analyze them in depth, a browser-based geospatial collaboration platform is usually a better fit than a full desktop GIS package built for specialists. Birdi, for example, lets a project manager open an orthomosaic or DEM directly in a browser, compare it against an earlier survey of the same area, and comment on a specific location for a colleague to resolve — without either person needing GIS training. Mirvac, one of Australia's largest construction groups, reported saving 32 hours per site per month on progress reporting after moving to this kind of shared, browser-based workflow. Project managers who need deep spatial analysis — complex terrain modeling, custom coordinate transformations, advanced feature editing — will still need a GIS specialist and dedicated GIS software; a collaboration platform is built for acting on outputs, not producing specialist analysis.
Whichever platform you use, the habits matter more than the software: check the capture date before trusting a dataset, know who's responsible for reissuing it, and ask directly when something looks out of date rather than assuming someone else has already checked.
Frequently asked questions
Do project managers need formal GIS training?
No. A project manager needs to know how to read common GIS outputs — orthomosaics, elevation models, point clouds — and how to judge whether a dataset is current, not how to produce or analyze that data. Formal GIS training is valuable for the specialists producing the data, but a PM's job is interpretation and governance, not analysis.
What's the difference between GIS and CAD?
GIS manages data tied to real-world geographic location, such as aerial surveys, elevation models, and utility layers, and is typically used to understand existing site conditions. CAD (computer-aided design) is used to create precise design drawings, such as building plans or engineering layouts. Many projects use both: GIS to understand the site as it is, and CAD to design what will be built on it.
What file formats will I encounter as a project manager working with GIS data?
Common formats include GeoTIFF (orthomosaics and elevation models), LAS or LAZ (point clouds), and shapefiles or GeoJSON (boundaries, utility lines, and other vector data). You generally don't need to open these files directly — most platforms display them visually — but recognizing the format helps you understand what type of data you're dealing with.
How do I know if a GIS dataset is current?
Check the capture date attached to the dataset, not just the date it was shared with you — a survey can sit unreviewed for weeks before it reaches a project manager. If a platform shows multiple versions of the same area, confirm which one is marked as current rather than assuming the most recently uploaded file is the most recently captured one.
Can non-GIS specialists use GIS software directly?
Traditional desktop GIS software has a steep learning curve and is generally not built for occasional or non-specialist use. Browser-based platforms designed for viewing and collaborating on GIS outputs — rather than producing or editing them — are built specifically so non-specialists can work with the data without that training investment.
Sources
- Autodesk and FMI. "Construction Disconnected: The High Cost of Poor Data and Miscommunication." Autodesk Digital Builder, 2018. https://www.autodesk.com/blogs/construction/construction-disconnected-fmi-report/
- Autodesk and FMI. "Study from Autodesk and FMI Finds Better Data Strategies Could Save the Global Construction Industry $1.85 Trillion." Autodesk, 2021. https://investors.autodesk.com/news-releases/news-release-details/study-autodesk-and-fmi-finds-better-data-strategies-could-save
- Project Management Institute. "Pulse of the Profession 2025." PMI, 2025. https://www.pmi.org/-/media/pmi/documents/public/pdf/learning/thought-leadership/pulse/pulse_of_the_profession_2025-1.pdf
- IBM. "What Are Data Silos?" IBM Think, 2025. https://www.ibm.com/think/topics/data-silos