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IoT Will Drive the “Golden Rule” for Data as a Service (DaaS) or Data Broker Opportunities

By David Yockelson | March 22, 2016 | 0 Comments

Non-Tech to Tech ProvidersiotDigital BusinessDaaS

Many years ago, I read a clever joke within a cartoon strip (it was the “Wizard of Id’ for those interested). Set on a dirt path near the king’s castle, two peasants were sneering as the king’s carriage passed. The king saw this and said to them, “Remember the Golden Rule!” One peasant asked what that was, and the other said, “Whoever has the gold makes the rules.”

Translating from medieval England to the present, one can definitely see similarities with respect to the Internet of Things (IoT) and data that is and will be generated by the billions of sensors that will be omnipresent in the “things” we own, buy, visit, live in, drive, watch, etc. There will be multitudes of data generated by these things, but it is what an organization does with the data via rules – or algorithms and ultimately products and services it creates – that will enable entry into new markets, creation of new sources of revenue or simply significant cost savings through better planning and management of assets.

Collecting and then creating solutions from data is nothing new. Organizations that range from Nielsen, to Thomson Reuters, to Acxiom, to Google (data related to searching, browsing, navigating, etc.; I’m not even talking about data potentially from Nest) and many others have generated significant businesses and revenues from gathering data, applying rules to determine its import and value and selling it back to other organizations for their organization to consume. Just this week, energy and transportation data behemoth and solution provider IHS acquired financial data and solution provider Markit for nearly $6B, a 5X+ multiple of its current revenues (arguably as a hedge against declining revenues in IHS’ energy business), creating a $13B data and solution provider across at least three major industries.

So there’s clearly money in collecting and providing data plus algorithms or rules to manipulate that data for large numbers of customers. Consider that the past crop of data as a service providers – we can certainly recognize them as DaaS providers – or data brokers, in Gartner’s lingo – even if they weren’t strictly digital or always selling their data and solutions via the web – have collected data resulting from transactions, customers (anonymized or not depending upon the situation or desired solution) or via brute force creation. With IoT, data will be generated by everything all the time (I exaggerate, but I’m sure you appreciate the potential scale), and winners will be those that are best able to harness that data, make sense of it, build rules governing its usage and its value and sell it back to the masses as it were. Last year, for example, IBM acquired The Weather Company (TWC). While terms were not disclosed, the prior owners of TWC had paid roughly $3.5B for it seven years prior, and one can only assume what multiple IBM paid for its assets. And what DID IBM acquire? Not only the links to huge numbers of sensors that drive data into TWC’s applications (and ultimately to Watson’s), but the applications that understand how to ingest and make sense of the data, all the better to be able to create rules to make the data meaningful for organizations within insurance, energy, transportation, government, etc., or anyone whose livelihood might depend upon knowing various aspects of weather. Hey, North Face — it’s going to be unseasonably cold for the next three weeks in Arizona – how about targeting some ads to Facebook “friends” in the region?

Through TWC, IBM owns the data generated by a wide variety of (and I’ll use the term very generally) sensors located around and above the world, and it also owns the infrastructure capable of receiving and massaging all that data to make it useful. Don’t be mistaken – that is a huge part of the magic here, and it’s clearly not something many – if any – others can replicate (though don’t worry, Microsoft has already launched competitive campaigns regarding weather data). But weather and its aspects are only one type of data that can be captured, and while I’d bet that IBM plans on leveraging its acquired infrastructure for other “thing” data, there’s plenty more out there and many other entities that are vying for “data cowboy” roles in the Wild West of IoT. Some of these will be “pay for play;” interesting startup Terbine is positioning itself as a clearing house for a wide variety of IoT or senor data, offering to capture it, clean it, manage it and even broker or sell it for you in its marketplace if you don’t want to fund the infrastructure to do so. Mozilla, with what it calls Project SensorWeb, is taking its open source message to IoT and attempting to drive crowdsourced data (about air quality at first) from contributors’ devices that are tuned to sniff out a particular variety of pollution. Alphabet, the parent company of Google (and Nest), has a daughter company called Sidewalk Labs that recently created a partnership with the US Department of Transportation to build an analytics platform able to collect data via WiFi and provide traffic, public transportation, parking and other “urban applications” as it calls them to make our cities even smarter. There are numerous gateways and connectors to hook in all sorts of home and commercial devices to capture the data streaming from them, and the more intelligent purveyors of those gateways and connectors are either providing their own algorithmic and analytical capabilities or partnering to delivery them.

The moral of the story is that organizations should seize the opportunity to grab all the gold (data) and create the rules (algorithms and analytics) they can, both to benefit businesses and scenarios they are already focused upon but also to potentially create new data brokerage businesses. These new offerings may be adjuncts to their core competencies, enabling them to reap the benefits that the IoT revolution is bringing. There are packaged providers, there are evolving marketplaces, there are crowdsourced collections, and there are many basic building blocks an erstwhile organization can implement to capture, manage, slide, dice and provide data brokerage offerings. As GE has already proved through the acquisitions, investments and development that formed Predix, traditional non-tech focused organizations can pivot to becoming tech providers pretty quickly, opening up new avenues for revenue and profit.

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