Type “Big Data” on Google, and you get over 730 million results. No doubt, businesses are getting excited over the notion of big data — there’s been so much focus on it and the soaring volumes of data — but let’s not forget data variety, the small, wide and thick data, which are key enablers to business transformation as well.
Now, we’ve geospatial, or locational, data which is making it possible for organisations to add the context of timing and location to data, with maps that show changes over time and exactly where those changes are taking place.
There’s a huge opportunity to exploit that data to create competitive advantage. And that’s what the power of location really is: location is an intrinsic component of nearly all data about physical objects. Every physical entity exists somewhere in space and time and, consequently, there is often something to be learned by analysing those locations in conjunction with other data sets, to arrive at insights to make better, more actionable business decisions.
Location data has information linking people, objects or behaviours with the “when and where” they occupy. Location analytics takes this data and creates geographic models and visualisations and can show historical changes and current trends.
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Unlike traditional business analytics, which tends to present results in spreadsheets, pie charts and bar graphs, maps allow businesses to see the underlying proximity relationships in their data, which has benefits for every industry — from enterprise asset management to every manner of planning, governance, services, infrastructure, and applications.
Increasingly, organisations are using location-based data, generally collected from satellites and drones, and analytics to do just that in a number of ways, from reducing costs through augmenting address verification to improving customer experiences with in-store location technology.
Location intelligence has moved into the mainstream enterprise technology landscapes, as business intelligence platforms, like IBM Cognos, package location analytics and data as part of its offerings. Location intelligence vendors are differentiating themselves on the strength of the geo-enriched data products they offer, and the breadth, depth and quality of each. Locale, a location analytics platform, converts raw lat-long data across all databases and formats into meaningful insights so that decision-makers can make very precise, data-driven decisions about their ground operations.
Spatial mapping and analysis software is becoming more user-friendly, moving into the realm of everyday users.
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Mapping data is especially helpful for businesses seeking maps and data that suit their specific purposes. For example, on-demand companies such as food delivery companies and eCommerce companies require highly specific details of a locality within a town, and that data can be used to increase user acquisition and conversion.
Acquiring users in locations where there is already demand helps these companies to reduce customer acquisition cost. Hence, in choosing the next location where they want to expand, a good question to ask is: what are the locations that already have a latent demand in terms of app installs, searches, orders placed?
Demand mapping lets an on-demand business overlay its search data and install data that it can use to analyse the spatial and time-wise trends for different areas. Businesses can use these insights to identify which areas are untapped for different categories.
There are many ways industries can take advantage of geospatial data analysis, especially, including in the logistics and supply chain industry where understanding the location of raw materials, products, or assets combined with the ability to better predict logistic disruptions globally is critical to business resilience.
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Use cases
Insurance: Accurately geocoding location data can be the difference between a property being improperly designated inside or outside a flood zone. That’s a difference that could come down to a few hundred feet but have huge cost implications, either because the insurer undercharges on a policy and is exposed to greater risk than it had estimated, or because it overcharges a customer and subsequently loses that business to a more accurately priced competitor. Also, an insurer can better project risk and alert policyholders before issues occur increasing efficiency.
Financial services: Geo-enriching customer profiles and accounts is increasingly being used in the financial sector, where regulations designed to prevent fraud and money laundering require institutions to properly understand the links between different accounts and identify potentially fraudulent behaviour. This can be done by locating customers and transactions, incidents and areas of risk, and identifying geographic relationships between accounts. A lender can also improve its credit risk scoring methodology and reduce bad loan placements.
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Retail: Retailers that use interior Bluetooth Low Energy Beacons, RFID or Wi-Fi in combination with a mobile loyalty app may be able to analyse customer shopping behaviour in-store, and as a result, optimise store layout or inventory. The data could also be used to automate in-store mobile offers relevant to the customer’s past shopping history or the department the customer is visiting. This kind of customer engagement at the point of purchase can increase purchases and store loyalty when offers are served at the right time. In sales and marketing, having a better understanding of demand signals through geo-tagged information helps to optimise limited resources and grow market reach cost-effectively.
Last year, in managing COVID-19 and the broader disruption of the global pandemic, mobility information became instrumental. As cities and governments turned to geospatial data in response to COVID-19, we saw innovative thinking around what is possible when combining geospatial data with other data. With the increasing focus on sustainability, geospatial data is proving to unlock several sustainability initiatives, such as sourcing.
As breakthroughs in data collection and processing continue to surge, enterprises have an opportunity to establish a competitive advantage. First steps toward tapping into the power of geospatial data include examining legacy operational processes for inefficiencies created by siloed data sources, like maps, address databases and sensors that could be combined into streamlined workflows. A business’s ability to fuse geospatial data with other data and collaborate across their business and throughout their value chain globally will prove to be a key differentiator.
And those enterprises that harness the powerful flood of information will find themselves occupying the high ground.
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