Location, location, location (data)

thoughts on geo for businesses and apps, in honor of Geography Awareness Week

I spend a lot of time thinking about what smartphones and cheap sensors enable — and one of the most critical capabilities they introduce is knowing where a user is, much of the time. This enabled first obvious things: navigation, advertising, and then less obvious things: new social/comms apps, on-demand transportation, event and venue recommendations, other predictive/contextual services, but most uses are still yet to come.

(For one, the holy grail of linking online and offline behavior for advertising attribution is still in its infancy.)

How we think of “location” will also continue to change — the resolution of the data will keep increasing, and we will enrich it with indoor location, 3D models, aerial/drone/underwater/satellite imagery, Lidar, thermal, weather and other datasets about our environment.

The wider analogy to be drawn here is between the online and physical worlds: how users traverse the web/apps (links clicked, words typed, mouse hovers) are indicative of profile, interests, lifestyle, work. Traversal in the physical world (where someone goes, how long they dwell, who they are with, what objects they interact with) reveals a new wealth of information about users.

There are obviously privacy implications to all this, but considering location data is being collected from smartphones at a rate of 10,000+ times per month already, and being an optimist/venture capitalist, I’ll focus on the potential utility for those consumers and businesses who opt-in (given careful controls around that data).

We announced an investment in Rhumbix recently, and it was partially because of this belief in operational use of geo data collection, especially from smartphones.

Construction is a ~$10T industry, and to boil it down to VC-simple terms, it is an industry with some very big problems.

As an industry, it is the largest consumer of the world’s resources/energy and the biggest contributor to its waste. Macro cycles aside, for the forseeable future, worldwide population growth, urbanization, and increasing wealth look likely to drive increased secular demand for building.

At the same time, it is the only industry that has become less productive over time. We build everything as if it is unique, have unacceptable worker injury/fatality rates, collect sparse data on usage of machines, materials and labor (mostly manually), face a growing skills shortage, and have broken communication paradigms.

Today, an owner can’t answer with any level of accuracy, “How long, and how much money, will it take to build this structure?”

A contractor can’t answer, “What should I change, real-time, in the management of my jobsite to do this more efficiently and safely? What level of confidence do I have in that decision?”

A worker can’t answer, “What work have I done today? What skills am I building? What will I get paid? What is happening with my team or others on the jobsite I should know about? Is there a more efficient way to do this task?”

All this is not a criticism of the people that work in the industry — the tools aren’t there for data collection, analysis, and workflow. But this changes when every jobsite has cellular and wifi coverage, and every worker has a smartphone, which, equipped with the right app, can put the power to collect data, retrieve analysis, and communicate, in every pocket.

Construction will not be the only industry that faces a leapfrog moment. The government, utilities, energy, logistics, insurance, mining, consumer finance and agriculture are all industries that all already use geo data operationally — but the tooling for them to integrate the mass of new location data streaming off smartphones, cars, and other cheap sensors mostly doesn’t exist yet. “Geographic Information Systems” (GIS) systems have traditionally been janky, complex software, the domain of a few highly trained analysts in a back room doing offline processing.

The contracting firm that gets better with every job, the trucking company that has trained more fuel-efficient driver habits, the port with real-time asset-tracking and monitoring for suspicious activity, the insurance company that prices based on actual driver risk, the retailer that understands its in-store customer behavior — these companies will have unfair advantages.

Time to look at some latlongs.