Geospatial data will accelerate a new era of economic development by delivering hyper-local information about traditionally hard to understand places. The inability to answer questions like, “what does the local population look like?”, “how do they behave?”, and “what do they buy and prefer?”, has caused many companies to lose strategic bets across countless emerging markets. Until recently, the information required to understand these localized consumer concentrations simply wasn’t available. Instead, in an attempt to capture the growing opportunity, decisions have been based on anecdotes, gut instinct, or national statistics that mask massive sub-national and hyper-local differences.

For instance, Nestlé reorganized its Africa business in May 2018, which included shuttering its regional head office in Nairobi, citing unsustainable costs given existing sales volumes in the East and Central African regions. In 2015, Diageo, the global spirits giant, shifted growth investments from its vodka and whiskey business in Nigeria towards beer products with more mass market appeal after overestimating the size of the high-end alcohol market. In each of these cases, detailed consumer data could have allowed these companies to more precisely size markets, inform strategic investments, and expand in a calibrated way.

The efforts to secure market share are warranted. Emerging markets are the frontier for corporate growth. By 2050, Africa will have the largest youth population on the planet, and the consumer class on the continent has already reached 330 million, with regional household income of $1.6 trillion in 2017. Southeast Asia will rank as the world’s 5th largest economy by 2020, with a current collective GDP of $2.5 trillion. The sooner companies can secure a place within these economies, the better.

Contextual awareness is often the difference between success and failure for businesses. It’s also acutely difficult to acquire without spending decades pounding the pavement city by city and neighborhood by neighborhood. We all inherently know that consumers look differently across countries and towns. Moreover, moving just one kilometer or two within a city can dramatically shift the make-up of a specific community. Only by understanding these spatial dynamics can businesses make truly strategic decisions about where to focus scarce resources, whether it’s launching a brand campaign, opening a new store, optimizing distribution networks, or launching a new product or service. The businesses that do so will be ones that win the future.

Thanks to recent technological advancements, it’s now possible to obtain data that has long been the dream of consumer-facing companies. Plus, it can be done in a way that protects individual’s identities and personal information. Satellite imagery, household surveys, and cloud computing can now be used to reveal population characteristics in countries, cities, and neighborhoods, even down to the 1 square mile level. The days of being forced to make big business bets off highly aggregated market statistics are gone. The geospatial data revolution has officially begun.

Big Data Privacy An illustration photo shows letters composing the word "big data" in Paris, April 21, 2018. Photo: LIONEL BONAVENTURE/AFP/Getty Images

This means the ability to incorporate human-centric intelligence such as demographics, spending power, access to services, electrical grid connectivity, occupation and employment types, and media consumption patterns. These insights add an entirely new dimension to strategic planning and can answer questions like; “who exactly is my best customer?”, “where should we focus go-to-market resources?”, “what’s the best way to optimize sales performance?”, and “how can we monitor whether our teams and distributors are performing?”

Applications for this type of data are vast and span across sectors. Consider a scenario in which a bank wants to establish an agent network in areas where it doesn’t currently have a brick and mortar presence. Banks across emerging markets are rapidly moving their operations to low-cost, highly distributed agent-based models, which are complemented by digital banking services. For these institutions, the ability to zoom in on, and surface, prospective communities that have hot-spots of target, unbanked households can dramatically accelerate customer acquisition. Even more so when they can consider where the competition is already located; thereby identifying true white space to exploit.

Consider another example. Consumer goods companies are often looking to improve their sales performance in secondary markets where they traditionally have taken a passive, distributor-led approach. For them, it’s almost impossible to analyze whether these distributors are actually performing up to potential. Candidly, most companies are unable to independently track performance the moment their products leave the factory in their distributors’ trucks. It’s a massive and highly frustrating blind spot. Yet, by combining territory-based sales performance data with hyper-local consumer data, businesses can calculate and track their market penetration, identify latent demand, and then optimize their sales and distribution networks. We’ve seen companies increase sales by up to 5 times by taking this approach.

When it comes to making decisions, context is king. It increases the value of other information sources, and provides a framework to operate within. Granular data for fast growing markets is now available and actionable. Businesses that use geospatial data to formulate their vision, strategy, and planning will have a tremendous long-term advantage, and will be light years ahead of teams grappling with archaic intelligence.

Ben Leo is the CEO of Fraym, a geospatial data and analytics company.