If the value derived from internet of things data is so beneficial, why aren't more companies using the data to its full potential?
In a study conducted by Forrester Research and commissioned by Xively, researchers found 51% of companies focused on manufacturing or developing IoT devices were collecting data for future use, yet only one-third were using the data for anything at present.
While this statistic is low -- even if it is an improvement from McKinsey's oft-cited statistic that only 1% of all IoT data collected is ever used -- it proves there is a wide gap between the potential of IoT and companies' ability to seize that potential.
"It's a concrete example of how there's opportunity in IoT, but if you approach it the wrong way, you're going to be putting a lot of work and exercise into something that's not going to have a really good payoff," said Ryan Lester, director of IoT strategy at Xively.
Internet of things data: Goals versus reality
Ryan Lesterdirector of IoT strategy, Xively
When asked about their motives for creating connected products, survey respondents said competitive differentiation, new product features and expanding revenue were top business drivers. They also cited four key use cases of connected product data: integration with existing systems; profiling and segmenting customers; providing feedback to improve product features; and providing insight to internal teams, partners and suppliers.
However, despite the well-defined goals, the majority of the 232 companies polled weren't using the internet of things data as planned, which can lead to a great deal of data waste -- and wasted opportunity.
Of those using the data, 34% claimed it was to profile or segment customers, 33% to provide data-driven insights to stakeholders and partners, and 32% to personalize customer interactions.
Why the gap?
"Everyone is drowning in data," said Mike Gualtieri, principal analyst at Forrester. "The ability of devices to connect and generate data far outpaces the ability of organizations to analyze it."
Bruce Sinclair, president of Iot-Inc., attributed the gap to not having a clear plan for internet of things data. "A value plan qualifies and quantifies the value you will be creating with your product," Sinclair said. "Once done, you will know the information you need to create, and from there, you will know the data you need to capture. It's a romantic notion to think that you can collect data, and then go back to it later and analytically mine it for gold. You need a plan upfront."
A lack of talent also holds many companies back from prospering from the insight of IoT device data. "If they are capturing data without at least getting advice, they are wasting time and money," Sinclair said. "The data will just pile up."
Preventing IoT data waste
One of the survey respondents said, "In the next 10 years, [IoT] will focus around who owns the data. The market will be shaped in this way. We will start to see an expected value from all data we are collecting."
Mike Gualtieriprincipal analyst at Forrester
However, to get there, a few things have to change.
"Company leadership must insist on a business plan before building their project," Sinclair said. "Don't let a vendor drive your decision of what data to collect. This needs to be a top-down process, not one that starts with the sensors and what data they can capture."
In addition to knowing how you are going to use the data to begin with, companies must also think of how other departments may be able to leverage the collected information in future use cases. But this leads to several questions, Lester said, including how to make the data available to others and integrate it into siloed teams' tools.
"You don't know how you're going to want to use the data down the road, so looking for platforms that offer predefined integration into other tools you're using today -- ERP, CRM [customer relationship management], billing programs, etc. -- having those customer integrations and APIs that allow you to get the data out and put it into others tools, that's really important," Lester said.
Gualtieri noted the specialized skills and platforms needed to properly analyze internet of things data aren't always available in-house. "Advanced analytics such as machine learning shows the most promise to enable a system of connected devices to learn over time, but it requires data science and machine learning tools," he said. Finding vendors and services that support a perishable insight framework, embed analytics to automate real-time decisions and support human decision making are critical to making sure collected data pays off for the collecting companies, Gualtieri said.
Sinclair agreed. "Companies must have the talent to transform the data into value," he said. "If it does not have it in-house initially, the company needs to find it externally."
An appliance manufacturer that responded to the survey shared the sentiment. "The future of the IoT world depends on where you draw the partnership line. We can't and don't need to do everything ourselves."
Looking at IoT data and analytics
Why IoT is more than just connected devices
A guide to enterprise IoT project success