The deployment of the Internet of Things is becoming synonymous with maturity for many industries. An organisation gaining visibility into their physical assets to understand asset utilisation, health and location is progress, however the pursuit of data should not be the objective. The true power comes in the action that can be taken, driven by the data and the business process automation that can enable new levels of agility for a business.

Process automation can conjure up many meanings depending on who you’re talking to, but typically it falls into 5 categories; the automation of physical processes, the automation of back-office tasks and business process, automated reporting, automated exchange of data within a value chain such as supply chain, and automated alerting if a physical response is required by a person.

Automating Physical Assets

The most prominent examples here are likely related to both smart manufacturing and smart buildings. Let’s look at Smart Manufacturing for example. With the arrival of Industry 4.0, IIoT (Industrial IoT) speaks to the ability to collect data from machines and other manufacturing systems to both optimise production output and reduce downtime. As an example, customer order data can be used to optimise the production line settings required for the forthcoming task, reducing the need for human intervention. In addition to this, IoT sensors can be used to help manage inventory or leveraged in conjunction with machine learning to predict machine part failure and ensure maintenance can be handled without impacting the entire production line.

Automation of Back-office Tasks

In this instance we refer to IoT data triggering a back-office task or process, which is further enhanced when RPA (Robotic Process Automation) can automate the task itself. This might be IoT data related to inventory triggering a purchase order to a supplier or ordering a part for a failing field asset when a failure is detected or predicted.

Automated Reporting

A typical example of this might be for food standards compliance where refrigeration must sit within certain tolerances for different food products. Historically, this might be a paper reporting exercise performed by a person taking a reading and recording it. Now this can be recorded in real-time using IoT sensors and automating alerting if thresholds are exceeded to ensure compliance and reduce food waste.

Automated Data Exchange

Typically, we see this in supply chain, where data relating to the location of goods, as well as inventory levels are shared with the extended chain of stakeholder related to product to enable complete transparency. This transparency enables better supply chain planning, reduced disruption and more efficient B2B process interactions between the various parties involved.

Triggering Human Intervention

We often see this with systems that relate to situational awareness and public safety. With the introduction of AI and Computer Vision, big brother is not only watching, but increasing his understanding of what he is seeing. AI powered cameras are now able to detect suspicious packages, potentially violent situations and crowding where it creates risk (such as we’ve seen in the recent pandemic). These events then trigger alerts where people are called to the scene to deal with the situation at hand.

In Summary

There is an evolution of a sensory digital fabric casting eyes on every aspect of the assets we use and the spaces we occupy. Also, with the advent of AI, systems can not only sense but they understand this data in context to take action and augment the day to day ways we operate in industry. Bill Gates was quoted as saying “Automation applied to an inefficient operation will magnify inefficiency”, so it is critical that organisations pay keen attention to the processes they implement and the interconnections between those processes before striving for higher levels of automation.

IoT (or IIoT) and process automation is now a business imperative that cannot be ignored.