Over half of enterprises are already Internet of Things within the workplace, citing business value in optimising operations and reducing risk.
Despite the recent rise of connected technologies, 65 per cent of organisations currently collect data from equipment, devices or other connected endpoints and use that data for a business purpose.
Findings from 451 Research’s inaugural Voice of the Enterprise : Internet of Things (IoT) study reports that datacentre equipment (51 per cent) is currently the most common source of IoT data, followed by camera/surveillance equipment (34 per cent), datacentre facilities equipment (33 per cent) and smartphones/end-user devices (29 per cent).
In addition, industry plays a big role with 49 per cent of manufacturing organisations gathering data from factory equipment and 49 per cent of healthcare organisations gathering data from medical devices.
“The term, ’Internet of Things‘, has proliferated rapidly and taken on different meanings depending on the audience,” 451 Research Research Director, Dan Harrington, said.
“As is reflected in our survey data, these connected endpoint scenarios are both old and new.
"They vary immensely from traditional use cases such as IP connected cameras, building automation, warehouse automation and telematics to emerging industrial use cases such as crop monitoring and remote patient monitoring.
“Organisations are both enhancing their already connected endpoints with greater capabilities as well as connecting new objects with sensors and circuitry to derive net new value for the business.”
Harrington said business value derived from these deployments include reducing risk (66 per cent) followed by optimising operations (63 per cent), developing new or enhance existing products or services (33 per cent) and enhancing customer targeting (21 per cent).
According to Harrington, this also varies by industry with manufacturing and utilities mostly focused on optimising operations, while reducing risk is more critical for those in finance and public sector.
Types of data gathered
“The volume of data being gathered and stored by these endpoints is immense,” said Harrington, who broke these types of data down into three major categories, machine sensing (data gathered from machines), biological sensing (data gathered from humans and animals) and environmental sensing (data gathered from the environment).
Respondents noted that the majority of the data today is gathered from machines for business use (71.5 per cent), while data gathered from humans and animals (8.5 per cent) and the environment (20 per cent) represents a smaller, but growing portion of the overall data.
With regards to IoT deployments, 46 per cent said security concerns were an impediment while nearly a third cited lack of internal skill sets (32 per cent), while a lack of IT capacity (29 per cent) and lack of perceived ROI/benefits (29 per cent) were also cited.
“The elephant in the room is, of course, security,” one respondent stated. “I’m getting a lot of push back on my security requirements for all of these IoT projects. I'm not budging, and fortunately I have the blessing of my CIO not to budge.”
Harrington said most organisations (61 per cent) manage IoT initiatives without the help of external consulting or professional services, but this could change.
“There is a clear need for external expertise to help convince organisations of the business value of IoT as well as to fill internal skill set gaps in areas like security, big data and network infrastructure,” Harrington added.
“As these projects mature, many organisations will find themselves looking to outside consulting and professional services firms for these capabilities.”
IoT - Established and emerging
“IoT is both old and new,” Harrington said.
Equal amounts of innovation and value will be found in both connecting new assets as well as enhancing already connected endpoints with increased functionality through more capable sensors producing robust data to be analysed with big data tools and machine learning software.
“While there are numerous examples of ‘old’ IoT, it does feel very much like early days,” Harrington added.
“We are just now beginning to understand the value of the data being produced and how best to put it to use.
"In order for IoT to evolve as a key digital transformation enabler, enterprises and vendors of key solutions must address security concerns, set standards for connectivity, and lower both the cost and complexity of deploying these environments.
“This complexity includes not only the deployment of the physical hardware itself, but also the backend analytics and software platforms, and the business justification tools used to realise the value of the data being gathered.”