Geospatial data analytics, location analytics, or spatial business intelligence (BI) are interchangeable terms that relate to enriching data with a spatial or location component. The data your company retains about employees, facilities, customers, and transactions generally have a physical space associated with them.
Enhancing data with spatial components allows governments and companies to gain deep insights that add the “where” element to data about their citizens, clients, opportunities, project successes, and business growth.
What Is Geospatial Data?
Geospatial data combines location, such as a region, street, or census block with information in a database. Examples can include purchasing habits by zip code combined with census block data such as age, average household income, race or ethnicity, educational attainment, or traffic patterns.
Data can be either static or real-time. The internet of things (IoT), including location sensors, mobile devices, and social media, provides additional information.
Examples of Geospatial Data
The potential in geospatial data comes from understanding the range of relevant information that an organization can gather and use to help make decisions.
Demographics
Demographic and social data includes indicators such as age, race, household income, educational attainment, and more.
Businesses and governments can use this information to determine where to locate new facilities and store fronts or to focus marketing efforts. Educational attainment, meanwhile, can be an indicator of availability for desired employee characteristics in a local labor pool. Companies can use household income data to help determine the location of facilities so they exist in a neighborhood with residents likely to use their services.
Environment
Environmental data is vast and various.
Current projects track real-time global carbon emissions and predict how the change in sea level could affect coast lines. Power utility companies use vegetation data to prioritize power line maintenance. Developers and government planning agencies use data on precipitation, plant and animal habitats to determine how and where sustainable growth may best to protect endangered species. Renewable energy development depends on solar insolation and wind speed data to determine project feasibility.
Time
Businesses and governments continuously collect data on their clients, business, and citizens: participants of welfare programs; the quantity of business license applications per day, month, year; client churn; or even how long a car parked at a mall.
Using trends in data is commonplace in today’s business intelligence (BI). Adding a spatial component to timeseries data creates three-dimensional information. Decision makers know the subject in each transaction, the time, the place, and if similar events occurred in the same area. A water utility company can track the date, size, material type, and crew for infrastructure installation or service calls. Minimizing travel time for crew dispatch can enhance productivity.
What Is a Geospatial Information System (GIS)?
A geographic information system (GIS) analyzes and displays geographically referenced information—for example, Google Maps. It’s a tool spatial data science uses to combine data such as demographics, household income, and utility infrastructure with dissimilar data (e.g., clinical facilities).
This combination of static and real-time data—through spatial BI—fosters an entirely new way for business to grow.
How Industries Use GIS
Many industries use GIS in spatial BI. If your business relies on data, you may augment your data with a spatial component. Designers intended GIS for land management; and organizations continue to leverage those tools to understand how rising sea levels will impact nearly 40% of earth’s population within about 60 miles of ocean coastlines.
Examples of GIS in Use
- Utility developers use spatial BI to determine maintenance schedules for infrastructure.
- Real estate investment companies use spatial BI to site their next profitable investment or to identify trends in neighborhoods and regions.
- Location intelligence, used to monitor IoT, changes the way we shop, travel, and consume advertising.
How Can Geospatial Analytics Benefit Your Business?
If your business uses a database, geospatial analytics or spatial BI could enrich your customers’ experience in the virtual and physical world.
Spatial BI can:
- Simplify complex relationships through visualizations
- Enhance predictive analytics and forecasting
- Refine marketing efforts
Specifically, these analytics can empower holistic planning, prediction, and problem solving by providing unique insights that reveal relationships, patterns, and trends previously hidden in one- or two-dimensional datasets.
These new findings can enrich customer experiences, prevent forest fires, track the spread of disease, optimize supply chains in real-time, and inform businesses investing in environmental, social, and governance (ESG) initiatives.
Top Six Applications for Spatial BI
Geospatial analytics spans a broad range of industries and has nearly limitless applications to help your organization compete and succeed according to its potential.
The following industries rely on geospatial data for everyday operations:
- Utilities
- Health care
- Real estate
- Financial services
- Supply chain optimization
- Business marketing
Utilities
Utilities use spatial analytics in a broad set of contexts—from monitoring vegetation growth around infrastructure, to planning maintenance and system upgrades, to determining cost of servicing new developments in their territory, to natural disaster planning and mitigation efforts.
The utility industry uses population density to estimate the cost of providing services and to monitor vegetation growth that may damage infrastructure.
Health Care
Spatial analytics can track the spread of disease, identify locations for rural pop-up health care events, and design community health communications programs. Both insurers and providers in the health care industry can lower costs and improve services by adding spatial components to their analyses.
Real Estate
From retail commercial spaces to single-family and multifamily home developers, hyper-local data can help drive profit by enabling retailers to select the most profitable site and develop vibrant mixed-use work-live spaces. Spatial analytics can inform businesses of important neighborhood demographics, distances to desirable schools, proximity to public transportation, and more.
The short-term rental industry has enhanced their customer experiences, for both the host and traveler, by providing hosts with the capability to map and share with guests their favorite local spots. This enables the traveler to experience a local’s favorites, plan day trips and sightseeing with ease. Short-term rental companies can then use the location data to create regionally focused experiences.
Financial Services
Banks and creditors predict customer behavior by obtaining insights from card usage history augmented with location intelligence. The migration of many financial services offerings to digital platforms has made the optimization of service offerings more important than ever in selecting the best brick and mortar locations.
Supply Chain Optimization
Location intelligence provides organizations with transparent real-time data related to orders, inventory, and delivery bottlenecks, allowing decision makers to mitigate potential disruptions to the supply chain.
Corporations with ESG initiatives can use location intelligence to identify environmental pollution, shortages of natural resource and raw materials, and geopolitical considerations. Manufactures may use drive time and drive distance for logistics planning.
Business Marketing
Spatial analytics in marketing lets companies be more precise in advertising and promotion strategies. The spatial component allows marketers to personalize customer experiences through location-based push notification, segmentation based on location, targeted digital advertising, and personalized recommendations for consumers.
What Are the Challenges with Geospatial Data?
Leveraging geospatial data requires advanced technical skillsets and knowledge base—for appropriate application of spatial analytic techniques, effective implementation, and maintenance of specialized platforms.
Mid-market businesses and governments ready to enhance their operations through the incorporation of geospatial analytics, location intelligence, or spatial BI can save time and money when they seek professional advice through planning, implementation, and management of their successful digital transformation.
A geospatial specialist can help:
- Plan during the initial stages
- Implement a spatial database
- Select appropriate techniques and analytics system
- Understand how and when to leverage location intelligence
- Manage, store, and analyze large amounts of data
- Perform deep analyses
- Provide actionable insights
We’re Here to Help
To understand how you can apply geospatial data analytics to your business needs as well as information about data analytics services, contact your Moss Adams professional.