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The Geospatial Edge: Issue 8, Winter 2024

The Geospatial Edge is Esri Canada’s periodic newsletter for managers and professionals tasked with growing their organizations’ geospatial capabilities. In this issue, Matt Lewin goes over three key activities you can undertake in 2024 to help boost the growth of your geospatial program.

Now that we're well into 2024, it's time to leave behind the holiday season and start planning for the upcoming year. What are your top priorities for your GIS program this year?

I'm hearing from many of you that growth is top of mind this year, particularly doing more with GIS and growing the profile of your programs. It's somewhat surprising, given all the doom talk about an impending inflation-driven recession. But still, "maximizing our investment" and "being more innovative" are terms I hear a lot.

If your focus is on growth, here's a rundown of three key activities to prioritize in 2024 (and every year).

1. Figure out which parts of your business can benefit from GIS

IS is a potent tool with applications to many business functions. However, its vast range of capabilities can sometimes make it seem overwhelming. At Esri, for instance, we have literally hundreds of pre-built solution templates for virtually every industry. So, where do you start? Like many things, I suggest starting with value, i.e. where would a geospatial solution, whether pre-built or newly invented, create the most value?

One approach I like is concentrating on three types of use cases that Jordan Levine from MIT has identified as particularly suitable to data-driven technologies (like GIS):

Use cases that support senior management-level metrics. You can't go wrong with this one, but delivering means understanding the key performance indicators (KPIs) that senior executives need to track and measure to make important business decisions. For example, a retail company may want to track the sales performance of its stores. By integrating GIS into the sales tracking system, the company can analyze the sales data based on the geographical location of the stores. This can provide valuable insights into the performance of each store based on its location, enabling senior executives to make informed decisions about expansion plans, marketing strategies and product mix.

Business processes that can be enhanced by spatial analytics. This involves identifying areas where spatial analysis can provide insights to improve business processes and decision making. For example, a logistics company may want to optimize its delivery routes. Using GIS to analyze traffic patterns, road conditions and delivery locations, the company can optimize the routes to minimize the distance travelled, reduce fuel consumption and increase delivery efficiency. This can result in significant cost savings and improved customer satisfaction.

Compliance-related activities that are necessary to perform. This involves understanding the regulations and policies that govern your industry and ensuring that your GIS program is designed to comply with them. For instance, a healthcare organization may want to use GIS to analyze patient data to identify disease clusters and track the spread of infectious diseases. However, the organization must ensure that patient privacy is protected and that the data is used in compliance with local health regulations.

There are countless useful applications of GIS, but you can't do it all. Prioritize those that deliver visible and significant value.

2. Scale your capabilities

Identifying a batch of high-value GIS solutions is one thing, but eventually, you have to deliver on them... and at scale, too! For this, you'll need a GIS strategy that looks across people, processes, technology, data and governance and aligns the demand for GIS solutions with the realities and constraints of supporting such an environment. A well-crafted strategy will ensure your program has adequate funding and resource allocation and that your personnel and technology investments are well-utilized and positioned to accommodate growing and changing demands.

Here are six factors critical for scaling up:

Leadership engagement. Strong support from the organization's leadership is crucial for the growth of a GIS program. Leaders need to understand the value of your geospatial solutions and commit to integrating them with the organization's strategic goals. This commitment often translates into advocating for the program, facilitating cross-departmental cooperation and ensuring that GIS initiatives align with the overall vision and objectives of the organization.

Funding commitment. Adequate and sustained funding is essential for a growing GIS program. This includes investments in technology, human resources and training. Securing long-term funding commitments ensures the program can develop without interruption and adapt to changing technological landscapes.

Data governance. Effective data governance is essential for managing GIS data assets. This involves establishing policies and standards for data accuracy, accessibility, security and compliance. Proper data governance ensures that GIS data is reliable, up to date and used responsibly, which is critical for the integrity and growth of the program.

Cross-functional teams. A GIS program benefits significantly from the collaboration of cross-functional teams that bring together diverse skills and perspectives. These teams can include GIS specialists, IT professionals, data analysts and end users from various departments. Collaborative efforts help ensure that the GIS solutions developed are comprehensive, user friendly and aligned with the needs of different stakeholders.

Scalable architecture. As the GIS program grows, its technological infrastructure needs to scale accordingly. This means adopting a GIS architecture that can handle increasing amounts of data, more complex analyses and a growing number of users. Scalable architecture involves using cloud services, efficient data storage solutions and robust processing capabilities.

Embedding GIS in the culture. For a GIS program to flourish, it must be embedded into the organizational culture. This means promoting a culture where GIS is normalized and encouraged across all levels of the organization. It involves training staff, promoting GIS-based decision making and integrating GIS into everyday business processes.

3. Prepare for a changing industry

GIS is a constantly evolving technology. Over the years, we've seen it progress from a basic mapping and data management tool to a system for spatially informed decision making with integration hooks into virtually every corporate system you can name. Much of this growth has ridden on the backs of other technology phenomena, such as mobile devices and cloud computing.

The latest technology changing the game is machine learning and generative AI. The capabilities of traditional, predictive machine learning algorithms, along with generative AI toolsets, are greatly influencing the growth and direction of geospatial technology. The table below breaks down the impact generative AI is having across various GIS capabilities.

Generative AI and Geospatial Technology

Generative AI has the potential to accelerate outcomes at every stage of the geospatial data life cycle, shifting human involvement toward data-driven interpretation, decision making and innovation

Geospatial Data Life Cycle Stages
Acquisition & Collection
Validation & Management
Discovery & Access
Desired outcomes Acquire best-fit geospatial data from relevant and trusted sources Ensure the quality, structure and integrity of geospatial data Enable timely and relevant access to curated geospatial content and maps
Current technologies (not exhaustive) GPS/GNSS/EOS
UAV/Drone tech
In-situ sensors, AVL
Survey stations
Social media
Field data collection
Spatial ETL
Spatial virtualization
Native geodatabases
QA/Data reviewers
Geodata exchanges
Data marketplaces
Spatial search
Geo-enrichment services
Generative AI-driven enhancements Enhance data resolution, coverage area and attribute richness at source

Gen-AI advancements:
Data augmentation
Image super-resolution
Semantic segmentation
Data fusion
Enhance quality assessment, error detection & integration of diverse datasets

Gen-AI advancements:
Auto QA assessment
Anomaly detection
Attribute gap filling
Enhance metadata generation and personalize data curation and data search recommendations

Gen-AI advancements:
Auto metadata gen
Intelligent search
Auto curation
Impact on human operators Shift from data compilation work toward data fit assessment and value-add product dev Shift from manual data QA and integration work to data exploration and modelling work Shift from manual content wrangling to creative curation tailored individual or community preferences
Geospatial Data Life Cycle Stages
Analysis & Modelling
Mapping & Visualization
Sharing & Collaboration
Desired outcomes Understand spatial phenomena, interpret spatial relationships, predict patterns, and model geo-scenarios Visually represent spatial and temporal relationships in 2D/3D/4D Communicate and share geospatial content and stimulate feedback from users and stakeholders
Current technologies (not exhaustive) Geostatistics
Intelligent routing
Temporal analysis
2D/3D spatial analysis
Map prod software Integrated Dashboards Plotters
3D Printers
Federated geo-hubs
Open data sites
Story maps
Generative AI-driven enhancements Enhance pattern recognition, feature extraction & simulation through AI determined variable selection

Gen-AI advancements:
Complex feature detect
Synthetic data sim.
Uncertainty quantification
Enhance map production speed and consistency, and provide contextual or personalized visuals

Gen-AI advancements:
High-quality map gen
Map style transfer
Contextualized visuals
Real-time visuals
Enhance data privacy and accessibility, accelerate sharing through standardization and automate feedback

Gen-AI advancements:
Data anonymization
Collab. data fusion
Chat assistance
Impact on human operators Shift from focus on the process of analysis to novel interpretations of the products of analysis Shift from map production work to novel, creative visual representation work Shift from content production to novel narrative forms involving geospatial data

View “Generative AI and Geospatial Technology” as an image file.

Managers can prepare for the impact of machine learning and gen-AI by doing the following:

Invest in AI and machine learning talent. Organizations should hire or train professionals skilled in AI and machine learning, especially those with expertise in applying these technologies in geospatial contexts. Building a team with strong AI skills will be crucial for leveraging the advantages of generative AI within a geospatial context. And since AI is a rapidly evolving field, companies should focus on continuous learning and employee training programs. This ensures that the workforce stays up to date with the latest AI technologies and practices and can implement these in geospatial projects effectively.

Collaboration and partnerships: Engaging in collaborations and partnerships with tech firms, academic institutions and other organizations can provide access to advanced AI resources and expertise. These collaborations can also help stay abreast of emerging trends and innovations in the AI and geospatial fields.

Innovation and R&D investments: Managers should allocate resources to research and development (R&D) in generative AI and its applications in geospatial technology. This could involve developing new AI-driven geospatial tools, improving existing products or exploring innovative use cases.

By taking these proactive steps, managers responsible for GIS programs can effectively prepare for the transformative impact of generative AI, capitalizing on its benefits while responsibly managing its challenges.

Let’s talk

I’d love to know about how you’re approaching growth in 2024. If you have an interesting story, send me an email or connect with me on LinkedIn. I’d like to hear about your experiences! 

All the best,


The Geospatial Edge is a periodic newsletter about geospatial strategy and location intelligence by Esri Canada’s director of management consulting, Matt Lewin. This blog post is a copy of the issue that was sent to subscribers in February 2024. If you want to receive The Geospatial Edge right to your inbox along with related messages from Esri Canada, visit our Communication Preference Centre and select “GIS Strategy” as an area of interest.

About the Author

Matthew Lewin is the Director of Strategic Advisory Services for Esri Canada. His efforts are focused on helping management teams optimize and transform their business through GIS and location-based strategies. As a seasoned consultant, Matthew has provided organizations in the public and private sectors with practical strategies that enable GIS as an enterprise business capability. At the intersection of business and technology is where Matthew’s interests lie, and he thrives on helping organizations bridge the gap to achieve their most challenging GIS ambitions.

Profile Photo of Matthew Lewin