While IoT can play a key role in the journey to become a resilient organization, manufacturers often face challenges in bringing these initiatives to life. These challenges can be both technology and/or business-related. In addition, there is the fact that the IoT technology ecosystem includes a complex mix of hardware, software, connectivity and services vendors – and each vendor may play several roles at once. It can be very difficult to navigate which technology components an organization should buy from which vendor, and then, to figure out how those components will work together. These multi-vendor solutions can also be very difficult to scale, unless integrations have been done between products – and both vendors are committed to the relationship for the long term.
In IDC’s latest worldwide IoT survey, manufacturers cited cost as the number one challenge holding back or slowing IoT projects within their organizations.
For manufacturers, costs can include the need to instrument brownfield equipment with sensors, as well as broader infrastructure upgrades required to handle the volume of data these sensors will emit. New software may need to be purchased to enable real-time analytics in the cloud and at the edge. In addition, there can be ongoing connectivity charges associated with sending data over wireless networks. Manufacturers will also often engage with services firms to help them integrate various IoT technology components, as well as to integrate their IoT data with existing backend systems, such as ERP and EAM.
Another challenge manufacturers face with IoT projects is the issue of skills gaps. In general, manufacturers are facing talent shortages and an aging out of the workforce. In a recent IDC survey, in fact, close to 45% of industrial companies said they were currently understaffed. The three areas they were understaffed in were IT, engineering, and operations – groups critical to carrying out IoT initiatives. Most industries, including manufacturers, are also struggling to find – and pay for – data science talent. Many are relying on third parties for this function due to the scarcity and cost of having these resources in house. However, data scientists cannot work alone; they have to work with plant engineers who understand operational processes in depth to build the right algorithms for complex machinery. In addition, IT is required to provide the foundation and scale for the project.
Although operational technology (OT) and information technology (IT) used to live within separate groups organizationally, as OT data increasingly gets integrated with IT systems, the people aspect must also be integrated. It is a change management exercise that most industrial organizations will be going through in the near future, if they haven’t already.
While change is never easy, this process is necessary to ensure the right organizational structure is in place to support the charter to become a resilient organization.
Security is another concern with IoT projects. Operational technology environments have often depended on air gapping – or completely isolating the OT system from other systems (including other internal networks and external networks) – to prevent malicious actors getting access to these networks. However, an IoT strategy inherently requires manufacturers to send data that once lived only within the realm of the OT network to other networks, including the Internet and/or other internal company networks. Thus, manufacturers must now take a more IT-like approach to security that includes multiple layers of defense. Everything must be protected, from the device, to the network, to the data, to the application. This requires a strong level of visibility into what is connected to the network, the status of those things, where those things are emitting their data, and who gets access to that data.