I've been in the room when the CFO asks: "We're spending $730K annually on ESRI. Can we cut that to $24K with open source?" The answer that follows usually triggers what I call the "scam alert" reaction.
Because yes, you can eliminate ESRI licence fees. But no, your true annual cost won't be $24K. There's a hidden line item that most migration pitches conveniently omit: the Engineering Tax.
After leading geospatial migrations at enterprise reinsurance scale and consulting on dozens more, I can tell you this: organisations that treat migration as a pure cost-cutting exercise almost always fail. Those that treat it as a strategic platform modernisation, and price it honestly, succeed.
This article is the TCO analysis I wish someone had shown me before my first migration. It includes the costs vendors don't mention, the timelines they underestimate, and the honest answer to "when does this actually make sense?" If you haven't already, you might also want to check whether your current licenses are even being used efficiently.
Why "$730K vs $24K" Triggers Your BS Detector
You've probably seen the pitch. It goes like this:
THE VENDOR PITCH (INCOMPLETE)
CURRENT STATE
$730K/year
ESRI licences, maintenance, support
AFTER MIGRATION
$24K/year
Cloud infrastructure costs only
What's missing: Who maintains your open-source stack? Who fixes bugs? Who keeps Python libraries compatible? Who trains your team? Who builds integrations?
Here's the uncomfortable truth: open source isn't free. It's just a different cost structure. Instead of paying ESRI $730K to maintain their platform, you're paying engineers to maintain yours.
I call this the Engineering Tax—and for a mid-size organisation, it typically runs £120K-£180K annually in engineering time. Not because open source is bad. Because all software needs maintenance.
What Does a 5-Year ESRI Migration Actually Cost?
A realistic 5-year comparison shows £2.88M for ESRI vs £1.35M for open source (53% savings)—not the 97% vendors claim. The difference is the "Engineering Tax": open source requires £120-180K annually in developer time for maintenance, updates, and integrations that ESRI provides bundled. Let's model the same organisation properly. This is a real scenario from a European utility with 50 GIS users, automating risk assessment workflows.
5-YEAR TOTAL COST OF OWNERSHIP (TCO)
Mid-size organisation: 50 GIS users, automating repetitive workflows, cloud migration in progress
ESRI PATH
OPEN SOURCE MIGRATION PATH
YEAR 1 (MIGRATION YEAR)
↑ 48% MORE than staying with ESRI
YEAR 2-5 (STEADY STATE)
* 1 senior engineer @ 50% time maintaining stack, updating libraries, supporting team
Savings hit in Year 3. ROI becomes positive in Year 2.5 approximately.
Key insight: If someone promises immediate savings, they're lying. Migration is a 3-5 year strategic investment. The ROI is real, but you must survive Year 1.
Understanding the Engineering Tax
"But wait—you said QGIS is free!" Yes, the licence is free. But someone needs to:
Maintain library compatibility
GeoPandas 0.14 breaks your scripts when Pandas updates. Someone fixes that. (See our ArcPy to GeoPandas guide for what this transition involves.)
Troubleshoot platform issues
"Why is Rasterio failing on Windows?" Your team needs an answer, not a GitHub thread.
Build integrations
Connecting QGIS → Databricks → Power BI isn't plug-and-play. Someone architects that.
Support end users
ESRI has a support desk. You need to build yours (or designate someone internal).
Keep documentation current
Your custom workflows need docs. They need updating when libraries change.
REALISTIC ENGINEERING TAX ESTIMATES
These are fully-loaded costs (salary + benefits + overhead) for maintaining an open-source geospatial stack. Not unique to GIS—this is what internal platform teams cost.
The key question isn't "Can we eliminate this cost?" It's "Is £180K in engineering time better value than £575K in ESRI licences?"
For organisations doing repetitive, automatable workflows at scale, the answer is usually yes. You're not just saving £395K annually—you're building a platform your team actually controls.
When ESRI is Actually the Right Choice
I've consulted on migrations that shouldn't have happened. Here's when staying with ESRI makes more sense:
Low ESRI Spend (<£150K/year)
If your annual ESRI cost is below £150K, the ROI timeline extends beyond 5 years. Migration becomes a bet on future growth, not current economics.
Desktop-Heavy Workflows (No Automation Potential)
If 90% of work is manual cartography, ad-hoc analysis, or one-off projects with no repetitive pattern, you're not automating. QGIS can replace ArcGIS Pro here, but savings are minimal.
Highly Specialised ESRI Extensions
ArcGIS Maritime, Defence Mapping, or Aviation-specific tools with no open-source equivalent. If these are mission-critical, you're locked in.
No Technical Capability (and No Budget to Build It)
Open source requires technical literacy. If your team has no Python skills and no appetite to learn, the productivity dip might never recover.
Contractual ESRI Requirements
Government contracts sometimes mandate ESRI for interoperability. Check your contracts before planning migration.
There's no shame in staying with ESRI if it's the right technical and economic choice. The shame is in paying for unused licences or running manual workflows that should be automated.
The Migration Decision Framework
Here's the framework I use when advising organisations on ESRI migration. Score each factor honestly.
| Factor | Threshold | Your Score |
|---|---|---|
| Annual ESRI spend | > £400K = MIGRATE | ___ |
| Repetitive workflows | > 40% time = MIGRATE | ___ |
| Cloud infrastructure adoption | AWS/Azure/GCP = MIGRATE | ___ |
| Technical team capability | Python skills = MIGRATE | ___ |
| Executive sponsorship | 3-year commitment = MIGRATE | ___ |
| Workflow automation potential | High = MIGRATE | ___ |
Decision rule: If you score "MIGRATE" on 4+ factors, migration likely makes sense. If 2 or fewer, stay with ESRI and focus on workflow optimisation instead.
The Hybrid Approach (What Most Organisations Actually Do)
Binary thinking ("all ESRI or all open source") is how migration projects fail. The organisations that succeed use a hybrid model:
Open Source For
- →Automated pipelines and workflows
- →Cloud-native data processing (Databricks, Snowflake)
- →API integrations and web services
- →Large-scale batch processing
- →Data science and analytics workflows
Keep ESRI For
- →Specialist extension-dependent work
- →Complex cartographic production
- →Ad-hoc exploratory analysis
- →Teams not ready for Python transition
- →Contractually required deliverables
Real Example: European Infrastructure Firm
Reduced ESRI licences from 85 to 12 over 18 months. Savings: £420K annually.
Hybrid isn't compromise—it's pragmatism. Use the best tool for each job, not the same tool for all jobs.
Migration Risk Factors (What Kills Projects)
After watching migration projects succeed and fail, these are the risk factors that predict failure:
Expecting Year 1 Savings
If leadership expects immediate cost reduction, reset expectations now. Year 1 costs more. Kill this expectation or kill the project.
No Executive Sponsorship
Migration requires budget, patience, and air cover when things get difficult. Without a sponsor at director level or above, you'll get defunded at the first hiccup.
Underestimating Training Time
"We'll learn Python as we go" is code for "we'll be 40% less productive for 18 months." Budget proper training or accept the productivity hit.
Big-Bang Migration
Shutting down ESRI on Friday and going open source on Monday is organisational suicide. Phased migration over 12-18 months minimum.
Ignoring Change Management
"If we build it, they'll use it" fails. People resist change. You need champions, training, documentation, and patience.
No Engineering Tax Budget
If you budget £0 for ongoing platform maintenance, your stack will rot. Libraries break, integrations fail, users get frustrated, and you're back to ESRI within 2 years.
The Real ROI: It's Not Just Cost Savings
If migration were purely about cutting costs, the TCO analysis might not justify it for many organisations. But the real value comes from what becomes possible:
Workflow Automation at Scale
Processes that took 3-4 weeks run in 30 minutes. This isn't a 10% improvement—it's unlocking work that was previously impossible.
Cloud Platform Integration
Geospatial data joins your data lake. Analysts query spatial data in Databricks alongside business data. GIS stops being a silo.
Team Autonomy
Your team controls the stack. Need a new feature? Build it. Library breaks? Fix it. No vendor roadmap dictating what's possible.
Modern Data Science Integration
Data scientists can use geospatial data without learning ESRI tools. Geospatial becomes another data type, not a specialised silo.
The cost savings are real. But the strategic value is in what your team can build when they're not constrained by desktop GIS tools designed for a pre-cloud era.
The Bottom Line
ESRI migration is not a cost-cutting exercise. It's a platform modernisation project with a 3-5 year payback period.
If you're spending £500K+ annually on ESRI and running repetitive workflows that should be automated, migration likely makes sense—if you price it honestly and commit to the full journey.
If you're spending <£150K annually, have no automation potential, or lack technical capability, stay with ESRI and optimise what you have.
If you're somewhere in between, consider the hybrid approach: migrate automated workflows to open source, keep ESRI for specialised use cases.
The Question to Ask Your CFO
"Would you rather spend £575K annually on vendor licences, or £179K annually on a platform we control—if we're willing to invest £853K in Year 1 to make the transition?"
If the answer is "yes, if the ROI is proven," you're ready for migration. If the answer is "we need savings in Year 1," you're not.
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