For many organizations, location is more important than ever for key decision-making. And multiple technology trends are making the insights of geospatial analytics increasingly accessible and valuable.
Location-aware devices and services have exposed billions around the world to how technology can support “spatial thinking.” Whether searching on Google, navigating to an address on smartphones, ordering a shared ride, or tracking a food delivery, many people use spatial-aware technology routinely. Products such as Tile’s beacon trackers or Apple’s recently released AirTag accessories suggest a future in which people will know the location of anything they want at any time.1
And organizations are moving to analyze location data for a wide range of critical insights, with major implications. Geospatial analytics can be an important source of innovation, helping solve problems across talent, operations, marketing, risk, and beyond. It may even be instrumental in organizationwide transformation, changing how everyday business and operations are conducted, though minding ethical boundaries will be crucial in taking advantage of this technology’s potential.
Data analytics aims to provide answers to critical questions about who, what, when, and why: Who are my best customers and who is most likely to churn? What are my best-selling products? When will this machine need service in the future? Why did my revenue change from last quarter?
The power of geospatial analytics lies in answering where questions: Where are our customers interacting with us? Where are our assets and staff deployed? Where do we have exposure to supply chain or regulatory risk? Beyond telling us where things are, analyzing data through the lens of location can help answer where they should be: Where should we build new store or office locations? Where should we direct more marketing spend? Where should we acquire new talent based on local market conditions? Lowe’s, for instance, optimized new store locations by identifying trade areas with a favorable demographic profile.7
Three factors appear to be driving this trend: The volume and diversity of location data is exploding, the cost of acquiring and analyzing it is declining, and clever applications that create value for businesses and their customers are emerging. A leading Indian bank, for example, cut the traditional credit decisioning process for farmers to just a few days—compared to the industry average of 15 days or more—by analyzing satellite imagery instead of manually inspecting farmland.8 A more novel example: using real-time tracking of drone flights to measure flight risk and lower premiums for insuring enterprise drone fleets.9
Spatial thinking increasingly plays a pivotal role in tackling big, complex challenges such as addressing climate change, managing COVID-19 risks, and supporting a hybrid workforce. It can help answer questions such as: Where should we deploy resources to mitigate climate risk? Where is there greater risk of exposure to COVID-19 for staff or customers? Where should we consolidate our office footprint as we shift to a hybrid workforce model?
The volume and diversity of location data is exploding, the cost of acquiring and analyzing it is declining, and clever applications that create value for businesses and their customers are emerging.
Geospatial analytics—the practice of analyzing data with a spatial dimension—typically requires multiple steps: collecting geospatial data from varied sources such as surveys and sensors, turning data into multiple layers of spatial representations, and analyzing it to find useful patterns to inform operational or strategic decisions.10 Performing each step may call for specialized skills and assets such as remote sensing and image processing tools for data collection and classification, specialized geospatial analysis skills (including cartography) to analyze spatial information in context and guide decisions, and specific programming languages to generate insights.11 Leading adopters generally use geographic information systems (GIS)—specialized software systems purpose-made for storing, managing, analyzing, and visualizing geospatial data; see figure 1 for a list of typical GIS components.12 The global GIS market is expected to reach US$13.6 billion in 2027, up from US$6.4 billion last year.13
Many organizations haven’t yet experimented with geospatial analytics, but adoption is growing fast. In the past, government organizations were typically the main producers of geospatial data; they were able to afford the high costs of acquiring it—from sources such as aerial and satellite imagery or manually collected survey data—along with the requisite highly specialized talent skilled in drawing insights from it. By next year, though, 36% of large and mid-sized organizations are expected to have deployed location intelligence software, up from 10% in 2019.14 And private-sector efforts to acquire geospatial data are proliferating.
The geospatial technology industry has experienced rapid growth and change since hyperscalers such as Google, Microsoft, and Apple entered the market. Beginning with the release of consumer and professional offerings in the early 2000s, awareness of the power of geospatial data and analytics has continued to expand around the world.15 At the same time, the cost of sensors and devices that collect geospatial data is falling rapidly—Bluetooth tags with integrated power-harvesting are expected to drop in price by two-thirds—with corresponding proliferation and ever more data. By 2025, projections suggest 40% of connected IoT devices will be capable of sharing their location, up from 10% in 2020.16 Even the sky-high costs of launching a satellite have fallen sharply over the past decade on a per-kilogram basis,17 meaning more data-collecting satellite launches over the next few years.18 The expansion of 5G networks, too, will aid collection of greater volumes of geospatial data, with faster speeds and improved accuracy; a defense organization is now developing a prototype of a 5G-connected warehouse that will make it possible to continuously and precisely track the location of its assets and inventory.19
Artificial intelligence (AI) and machine learning (ML) has supercharged organizations’ ability to analyze vast quantities of geospatial data. AI and many of its subdomains, including ML and computer vision, automate information extraction to more quickly deliver real-time geospatial insights, such as helping to safely deploy firefighters during rescue operations20 or enabling autonomous or remote navigation for drones or vehicles.
Many new tools and solutions that make use of geospatial analytics are coming to market, especially industry-specific solutions that embed geospatial capabilities. And venture capital (VC) is pouring into this space, supporting the growth in new geospatial solutions, tools, and data sources. US-based startups offering geospatial capabilities raised US$2.5 billion in VC funding in 2020, about 25% more than in 2019. That trend continued this year, as VC investment topped US$1.8 billion by early May.21
Meanwhile, market-leading GIS and geospatial technology vendors (including Esri, Hexagon, and Descartes Labs) are modernizing their tools by launching their software offerings on the cloud for flexible storage and processing power to handle growing data volumes.22 And major enterprise software vendors are adding geospatial functionality to their core products. Cloud hyperscalers have launched geospatial data and analytics offerings, including services for embedding maps, geofencing, and other location-based features into clients’ web and mobile applications.23 SAP, Salesforce, Oracle, and others are integrating more geospatial capabilities through new partnerships,24 investments,25 and offerings.26 This will allow many more organizations to begin experimenting with geospatial analytics, including building custom geospatial applications on vendors’ platforms.
With the volume and variety of geospatial data growing, and new tools making it easier to work with, new applications have emerged. Location data aided COVID-19 contact-tracing programs all over the world27 as well as social distancing programs in organizations’ facilities.28 A California-based interior-design firm is using location data to support its shift to a hybrid workforce model: A mobile app allows employees to view real-time and projected office occupancy and book open desks, with indoor wayfinding to help them navigate office floors, facilitating better space planning and social distancing adherence.29 (See figure 2 for examples of geospatial use cases across industries.)
Proliferating IoT devices are boosting opportunities in emerging areas such as indoor mapping and tracking and location-based products. A California hospital shrank operating-room turnaround times, improved patient satisfaction, and saved US$1 million in annual costs with real-time patient tracking with RFID.30 Wearable technology can power products that remotely monitor the precise location and vital signs of first responders to increase their safety on the job.31
Geospatial analysis of satellite imagery and other data sources can be vital to mitigating climate risk. A joint US-EU program is using satellites to more accurately measure the rate that sea levels are rising around the globe, while also capturing atmospheric data to augment climate change models and weather forecasts.32
Such emerging applications are expected to fuel further demand for geospatial analytics. In the United States, the Biden administration has proposed investing US$50 billion in infrastructure resilience to mitigate climate risk.33 Geospatial analytics can help direct such investments toward high-risk areas to maximize their impact. Another example: California-based startup Pachama recently raised US$15 million to verify forest restoration projects for climate offsets with satellite imagery. It counts Microsoft, SoftBank, and Shopify among its enterprise customers.34
With the technology becoming more accessible, organizations are ramping up use of established geospatial analytics applications. Examples include Novartis analyzing local talent pools for office site selection,35 parcel delivery provider SEUR optimizing its supply chain network,36 the Rwandan government working to improve land management practices,37 and an American power utility reducing costs in managing risk from vegetation along its powerlines.38
As new geospatial data sources and use cases emerge, organizations should respond by reviewing strategy and operations through the lens of spatial thinking. Using the following approach, leaders should look for opportunities where geospatial insights can provide a competitive edge or produce significant operational advantages:
By now, many leaders recognize the role of analytics and data mastery in unlocking business value and achieving their organizations' digital ambitions. Increasingly, this means mastering the use of geospatial analytics and spatial thinking. For some organizations, this could be transformative—even becoming a launching pad for entirely new businesses.
The internet has freed people from being tied to a specific location. Education, work, and entertainment are available anywhere there is a network connection. And yet location matters now more than ever. Leaders’ best thinking should include spatial thinking.
With decades of industry-leading analytics and executive advisory experience, the Deloitte Geospatial Analytics practice helps government and commercial clients around the globe leverage the power of location to gain critical insights for improving their mission outcomes. Our dedicated team of analysts, software developers, data scientists, and strategists couple innovative data-driven approaches with cutting-edge geospatial solutions to deliver results—where it matters.