As digital transformation reshapes the business landscape across nearly every vertical market, the Internet of Things (IoT) has matured from simple novelties to becoming integral for innovating CIOs and decision makers to achieve their overarching business objectives.
As with all technical investments, IoT solutions must have a clear value proposition and a compelling return on investment. While the value proposition may be fairly straightforward to articulate, creating a solution that justifies that investment can prove to be a much greater challenge.
Connecting the dots
Consistent and accurate data is the fundamental building block IoT solutions require to achieve intended business outcomes. Getting that data across the entire IoT ecosystem requires a broad mix of technology components, including devices used to collect data, communications channels, and platforms used to manage the devices. In addition, other elements to consider are the means used to store and analyze the data, as well as methods used to encrypt and secure it end-to-end.
Once the data has been ingested, tools and applications activate the data and provide actionable information for consumers. The reality is that all this infrastructure comes at a cost, which is the principal impediment that prohibits a strong return on investment. Challenges in accurate data collection, secure communications and reliable platforms can often hinder companies from scaling IoT solutions to production, ultimately stranding them in pilot purgatory.
Old form, new function
To overcome these challenges, IoT technologists are driven to find more efficient methods that reduce the total cost to deploy solutions at scale. One important area of focus is finding new and innovative ways to collect data. In some instances, IoT solutions can easily include thousands of managed devices, resulting in challenges to collect data in a secure and efficient manner. In other instances, collecting operational and environmental data was not a feature of the original design of the systems. This is the case in legacy environments deployed prior to the advancement of the technologies that enable IoT.
In such cases, the environment must be retrofitted with additional sensors to collect and transmit actionable data. An example of this might be operational technology (OT) environments that utilize Industrial Control Systems (ICS) such as manufacturing, energy and utilities, as well as for environmental controls for any physical plant which typifies the OT/IT convergence.
As with any infrastructure, updating OT environments and enabling them to become “connected” brings both massive opportunities and significant challenges. The ability to continuously monitor equipment using an IoT solution now allows decision makers to refine processes more quickly and accurately, resulting in more efficient and profitable operations.
For example, manufacturers can more precisely monitor the quality of their products and make adjustments in the production process in a timely manner, resulting in improved financial performance through better margins by reducing waste and lowering production costs. In more advanced use cases, devices can not only be monitored, but can also be controlled and configured either manually by technicians or even as an automated response based on predefined event management rules.
While there are many welcomed benefits stemming from connected solutions, IoT brings significant security risks as well. By connecting devices and equipment at an enterprise scale, businesses vastly increase the attack surface malicious actors seek to exploit and to gain access to sensitive data, resulting in either physical or digital damage, or both. These threats necessitate an enhanced cybersecurity strategy to mitigate risks.
Traditional monitoring and security infrastructure required agents to be deployed. However, this resulted in performance overhead and management issues. Passive data collection solutions have proven to be better alternatives as they incur less overhead in system performance and licensing costs than active data collection methods.
While intrusion detection and other SIM technology has long-existed (that can passively collect and monitor the communications channels that interconnect the infrastructure) they have traditionally had a one-dimensional purpose to detect and mitigate security threats. New methods are being developed to improve the value propositions of cybersecurity solutions, specifically in OT environments.
Something from nothing
ICS deployments in these environments exchange significant amounts of data between devices and the Primary Logic Controllers (PLCs). Unfortunately, there are few industry-standard protocols and many systems communicate via proprietary protocols. Advanced cybersecurity technologies are now able to decode these proprietary protocols to extract the control data to detect anomalies and provide alerts when necessary to protect critical infrastructure. This ability to capture data from these sources is significant as it was previously not accessible or didn’t exist until recently.
Cutting-edge techniques are also now being developed to realize even more compelling outcomes. The same decoded control data can be leveraged as valuable input to business intelligence platforms. The data can be stored in a repository, and then advanced data analytics methods can be employed to transform the data for high-value activities such as predictive maintenance. The data that has always existed is now being used to gain back lost revenue and even generate new revenue opportunities with results varying by industry.
Reducing downtime in a manufacturing context translates to increased levels of production and subsequent revenue. Improving the availability of infrastructure in the energy and utilities sector yields higher production and the reduction of wasted resources. The common thread is improved outcomes including higher customer satisfaction and greater profits.
Brian Russell, IoT Solution Architect at Atos North America (opens in new tab)