I want to set the scene that may seem odd at first, but it will help explain this post as we go along. Transport yourself back to a bustling school cafeteria at lunchtime. The room hums with chatter as students gather around their tables, each unpacking their lunch. Some have crisp apple slices and hearty sandwiches, others have warm rice bowls or fresh salads, each meal distinct, carefully packed, and satisfying on its own.

At first, everyone enjoys what they have, but then, glances start darting across the table. One student eyes the golden crackers on their friend’s tray, another notices the perfectly seasoned chicken across from them. Curiosity turns to envy, and soon, hands start reaching. A piece of sandwich is swapped for a spoonful of rice, a bite of pasta is traded for a handful of chips.

Before long, the once well-balanced lunches become a chaotic blend of mismatched flavors. The crisp freshness of the salad is now mixed with soggy fries, the warm rice is speckled with peanut butter from a hastily grabbed snack. By the time lunch is over, no one quite recognizes what they’re eating anymore. Each meal, once thoughtfully prepared and independently satisfying, has turned into an unidentifiable mix of everything else—less distinct, less enjoyable, and not quite what anyone wanted in the first place.

And this, in many ways, is exactly what’s happening in the geospatial industry.

The geospatial industry is stuck in a cycle of self-competition, constantly fighting over the same set of functionalities and use cases (or in this case the analogy lunch items) instead of expanding into new areas and industries.

Companies are so focused on outdoing each other that they fail to realize the real challenge isn’t beating competitors – it’s making geospatial a core part of the broader data ecosystem.

For years, I’ve watched this unfold while working with companies across the geospatial spectrum. The expectation in this industry is that a single company or platform must do everything: data ingestion, storage, analytics, visualization, and even distribution. This has created an environment where every company feels the pressure to be an all-in-one solution, leading to fragmentation, redundancy, and, unfortunately, stagnation.

Our industry has an uncanny ability to create new technical innovations and tools to support our work, but this tends to stay trapped inside the walls of geospatial since we focus on creating a complete solution rather than expanding to bring this to new areas.

This post is the first in a series where I’ll explore the key challenges and opportunities facing the geospatial industry today. These challenges became clear to me as I developed the Modern Geospatial Data Stack, a framework that rethinks how geospatial technology should be structured and integrated with broader data workflows. As I built this framework, I started to notice a fundamental gap between the way modern data systems evolve and how geospatial technology continues to operate in silos.

In this series, we’ll explore:

• Better Together: Why Geospatial Companies Must Work Together or Fail Apart (You are here)
• The Single Biggest Gap in the Geospatial Data Stack
• Why Geospatial Data Engineering Sucks—and How to Fix It
• Stop Using Data Warehouses for Geospatial (At Least in This Way)

The goal of this first post is simple: a call to action for collaboration instead of competition. The geospatial industry needs to stop competing internally and start focusing on its role within the broader data landscape. If we fail to do this, we risk keeping geospatial on the fringes rather than making it an integral part of modern analytics and decision-making.

The Root of the Problem: A Zero-Sum Mindset

One of the biggest misconceptions in the geospatial industry is the belief that success is a zero-sum game—that for one company to win, another must lose. I have seen it in many different applications and solutions but given that the biggest player (Esri) in our space is an all-in-one platform in their technology and go-to-market approach, we shouldn’t be surprised.

For years, geospatial companies have built their platforms under the assumption that they must provide everything—data storage, analytics, visualization, and even applications—within a single product. The industry has fostered an expectation that a geospatial solution must be a complete platform rather than a modular part of a larger stack. This has resulted in companies spending more time competing over existing customers rather than expanding geospatial’s reach into new industries and applications.

Too often, companies equate winning business with taking customers from competitors instead of expanding the overall market. This creates an environment where many prioritize feature parity over true innovation. Instead of focusing on what they do best, companies feel compelled to stretch beyond their expertise, adding capabilities outside their core strengths to stay competitive.

Compare this to the Modern Data Stack, where different tools seamlessly integrate to form a best-of-breed workflow. Companies in the modern data stack don’t try to do everything; they specialize and interconnect. Meanwhile, in geospatial, companies still behave as if every feature must exist within their own walls.

Why This Hurts Everyone

This mindset is limiting geospatial’s growth. Instead of working together to educate new markets and demonstrate the value of location-based data, companies spend time undercutting each other. Meanwhile, industries outside of GIS remain unaware of the true potential of geospatial because they’re not being engaged in a way that fits into their existing workflows.

If geospatial is ever going to achieve its full impact, companies must stop treating each other as adversaries in a fight for limited resources. Instead, we must expand the pie, showing businesses and industries that geospatial isn’t just a niche toolset—it’s an essential part of modern data-driven decision-making.

Fragmentation Limits Growth

When every geospatial company tries to do everything, they dilute their core strengths. Instead of focusing on what they do best – be that geospatial storage, analytics, or visualization—they spread themselves too thin, leading to:

• Inferior products that attempt to cover too much ground without excelling in any one area.
• Inefficient duplication of effort, where companies develop features that already exist elsewhere instead of integrating with existing solutions.
• Lack of interoperability, as companies prioritize their own ecosystem over creating open, modular tools that work across the broader data landscape.

This prevents the industry from developing a strong, interoperable stack like what we see in the Modern Data Stack, where different tools integrate seamlessly to provide best-in-class solutions.

Another consequence of the fragmented geospatial landscape is that potential users don’t fully understand what geospatial can do for them. Rather than educating new industries about the value of spatial insights, companies waste resources fighting over the same small pool of GIS users.

• Business leaders and data teams outside of GIS often struggle to see how geospatial fits into their workflows, leading to limited adoption.
• Competing, overlapping solutions create friction in decision-making, making it difficult for potential users to choose the right tool.
• Customers are left in confusion and unsure where to begin, sometimes seeing geospatial as not worth it thus never making use of geospatial data.

The result? Slow adoption beyond traditional GIS fields, which prevents geospatial from becoming a standard part of modern analytics.

Missed Opportunities

The biggest loss in all of this? Geospatial remains a niche industry instead of integrating into the broader data ecosystem. Rather than embedding geospatial intelligence into the core of business decision-making, companies remain hyper-focused on their GIS competitors, ignoring:

• Strategic partnerships with modern data platforms where spatial data could provide enormous value.
• Interoperability with mainstream analytics and BI tools, making it easier for companies to use location-based insights alongside their other data.
• New industry applications that could benefit from geospatial insights but don’t yet understand its potential.

To move forward, geospatial companies need to shift their mindset—from trying to own the entire workflow to seamlessly integrating into modern data stacks. The industry’s future depends on making spatial data accessible, scalable, and easy to use outside of traditional GIS circles.

Expanding Geospatial Beyond GIS

The biggest opportunity in geospatial isn’t stealing market share from competitors; it’s making spatial intelligence indispensable across industries. The problem is, many industries still don’t fully understand the value of geospatial data—or how to incorporate it into their existing workflows. Instead of fighting for dominance within GIS, companies should be asking:

• How can geospatial fit into financial modeling?
• How can location intelligence improve supply chain management?
• How can climate and environmental data be integrated seamlessly into mainstream analytics?

The reality is, most data-driven industries could benefit from geospatial insights—but they won’t adopt them unless geospatial integrates with the tools they already use.

Learning from the Modern Data Stack

Look at how companies in the Modern Data Stack operate. No one tries to do everything. They don’t position themselves as end-to-end platforms that replace all other tools. Instead, they integrate seamlessly into existing workflows and make the pie bigger by enabling other companies to do more with data.

Geospatial needs to follow this same path:

• Interoperability should be the default, not an afterthought. Geospatial data should flow effortlessly into analytics tools, BI platforms, and data warehouses.
• Geospatial tools should focus on specific problems, not try and be the end all be all for everything with a lat/long (or pixel, or array).
• Stop selling “GIS.” Don’t make spatial special. Most industries don’t want to join the geospatial revolution, they need actionable insights that fit within their existing systems.

What to Do Instead: A Blueprint for a Collaborative Geospatial Future

The geospatial industry doesn’t need more competition—it needs collaboration. The way forward isn’t about creating all-in-one solutions that attempt to do everything. Instead, success lies in specialization, interoperability, education, and strategic growth. Here’s how we can build a more integrated and impactful geospatial future.

Specialization Over Consolidation

It’s okay for companies to focus on doing a few things really well rather than trying to be everything to everyone. Some of the biggest breakthroughs in the broader data ecosystem have come from specialized tools that solve one problem exceptionally well rather than trying to replace an entire workflow.

• Be the best at one thing. Instead of adding features to match competitors, focus on mastering your niche.
• Create complementary solutions, not competing ones. A strong ecosystem thrives when companies recognize how their tools fit into a larger workflow rather than trying to own every step of the process.

Interoperability as a Standard

The geospatial ecosystem should be built on tools that work well together, not walled gardens that force users into proprietary ecosystems.

• Adopt open standards. Support widely accepted formats like GeoParquet and Cloud-Optimized GeoTIFFs to make it easier to share and use geospatial data.
• Make integration seamless. Ensure tools, data, and connectors work with existing data platforms so that spatial data can flow into modern analytics tools without friction.
• Encourage ecosystem development. Companies should make it easy for developers and data teams to extend their solutions, fostering an open innovation environment.

Educate the Market Instead of Competing Over It

Many industries don’t even realize they need geospatial. Instead of fighting over the same few customers, companies should be expanding awareness and demonstrating value in new areas.

• Show how geospatial fits into business intelligence, finance, climate modeling, and logistics. The biggest opportunities lie outside the traditional GIS space.
• Speak the language of other industries. Instead of selling “GIS,” try speaking location intelligence, spatial analytics, and data-driven decision-making. Or better yet, talk about the value drivers they care about (want a case study – check out how Placer.ai does this really well)
• Create resources that lower the barrier to entry. Training, case studies, and developer-friendly documentation can help non-geospatial users incorporate geospatial into their workflows.

Let Innovation Happen First, Then Let Consolidation Follow Naturally

Instead of every company trying to be an end-to-end solution, the industry should allow best-of-breed solutions to emerge and integrate naturally.

• Encourage solutions and innovations. Find one specific problem and focus on that. Then collaborate with and connect to other platforms.
• Focus on solving real-world problems before merging technologies. Consolidation should be the result of success, not the starting strategy.
• Learn from the Modern Data Stack. This ecosystem thrives because they integrate seamlessly into existing workflows rather than trying to replace everything at once.

The biggest challenge facing the geospatial industry isn’t competition—it’s a lack of mainstream adoption. We spend too much time competing over the same core use cases when we should be focused on expanding geospatial’s role in the broader data ecosystem.

To do so we must prioritize:

• Collaboration over competition. Instead of trying to own every part of the geospatial pipeline, we need to integrate and work together to create a more seamless user experience.
• Specialization, not generalization. The most successful tools are those that do one thing exceptionally well rather than trying to be an all-in-one solution.
• Integration with mainstream data workflows. The future of geospatial lies in embedding spatial capabilities into the analytics and decision-making tools that businesses already use.

The companies that embrace these principles will be the ones that define the next era of geospatial, making it more accessible, scalable, and impactful than ever before.

This post is just the beginning of a much-needed conversation about the future of geospatial. In the next post, we’ll dive into one of the biggest gaps in the geospatial data stack—and why no one is fixing it.

Stay tuned.