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Taking a collective intelligence approach to IoT

I’m a believer in the power of collective intelligence to increase operational efficiency, accuracy and sustainability. Enterprise outcomes exponentially improve when people, technology and data connect to deliver a fully informed approach to conducting business. Emerging, rapidly democratizing technologies like artificial intelligence, machine learning and the internet of things help global businesses to complete the collective intelligence picture. Individually, these technologies have massive potential to change fundamental approaches to work and the way we manage processes. Together, they can solve even greater business challenges. A first step towards doing this is to put IoT to work in a way that mobilizes data sets created and shared by customers, vendors and companies.

When it comes to IoT, industries have been talking about the technology’s potential to shake up global markets for decades. Security concerns, unrealistic expectations connected to hype and a general lack of know-how continue to keep IoT’s complete democratization from happening. Yet, there are a few simple steps companies can begin to take a collective intelligence approach to deploying IoT.

Understanding real-world applications of IoT

At its core, IoT is simply the interconnection, through the web, of computing devices embedded in everyday objects that enables them to send and receive data. Once IoT is connected to the relevant data sources, the technology sets to work making sense of the collected information to ensure it’s more valuable than any individual input. For example, a field service engineer that uses an app connected to a combine harvester in the field can see when the machine needs fixing before the customer realizes it. He can proactively service customer needs by checking the app regularly between maintenance visits. Similarly, a commercial HVAC worker can look at trends from IoT-driven data that illustrates maintenance records and conduct preventative service before a problem even arises.

Understanding the ways data-enabled IoT can transform enterprise will open a wealth of solutions for service-oriented businesses looking to improve operational efficiency and improve the customer experience.

Taking stock of sensors and connecting them to data streams

Understanding real-world applications of IoT is merely the first step. The key now is for businesses to determine how many of their everyday assets (service vans or trucks, on-site products like air conditioners or combines, proprietary structures like solar panels or wind turbines) have computing devices embedded in them. The next step is to connect them to contemporary data streams flowing through proprietary computers, phones and other internet-enabled devices, creating a link between previously offline objects and central business operations. Importantly, companies need to bring the world’s offline assets online in a secure, data-focused way that benefits businesses, customers and entire supply chains. The reason? Commercial assets that stream data can efficiently present performance and maintenance information to the right audiences.

A report from McKinsey found that IoT-ready sensors already reside on traditionally offline equipment, machines, fleets of transport vehicles and tools in use by industries across the board. Further, analysts pointed out one case in which an oil rig had over 30,000 sensors, but only 1% of them were activated for mission-critical work. It is important for data-oriented companies to take a proactive approach to identifying what sensors and data sets are available — and how they can improve services once connected.

Deciding who owns the data

The final frontier for companies looking to take a collective intelligence approach to making IoT work for business is to agree on who owns specific IoT-linked data. Is the data owned by a public sector entity, specific industry council or standards organization, a group of private companies or an individual vendor? Answering this question as it applies to individual contexts is an important step because it will determine who has the right to economically exploit the technology, especially if the data itself were to become a managed service. Determining the answer could simply boil down a company’s business model; for example, if a vehicle by which data was gathered was owned or leased by the company. Or, if a particular enterprise was pulling from public records or another public source of data.

Undoubtedly, the debate surrounding data ownership will only increase as IoT becomes increasingly powered by individual data sets created by manufacturers and other vendors. Failure to agree on who owns the data could result in businesses finding themselves in serious regulatory trouble. However, the very threat of regulatory consequence could be the external pressure needed for stakeholders to reach agreement.

The shared future of IoT

While we are not there yet when it comes to fully leveraging data-powered IoT technologies, one thing is clear: The information gleaned from IoT-linked assets has the potential to connect companies’ front and back offices to boost workplace efficiency and inform the entire organization’s subsequent activity. Once an IoT-linked platform is in place, everyone — from field workers, office staff and the C-suite — shares a stake in what the data means for their specific jobs and the company’s ability to achieve business success. Understanding the power behind real-word applications of IoT, taking stock of available sensors and data sets, and deciding who owns the data are all important steps toward driving IoT-connected data applications forward in the industry.

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

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