Recent IFS research shows the industrial internet of things (IIoT) is still considered a cost-containment strategy rather than a revenue driver. Despite rising IoT adoption for asset management and equipment monitoring, most industrial organizations have yet to make strides toward enabling IoT data to fully power digital transformation.
IoT technologies have thrived in the manufacturing industry for some time. Rudimentary solutions such as networked programmable logic controllers (PLCs) and data from supervisory control and data acquisition (SCADA) systems have been used to automate and optimize plant floor processes. Although steps have been made, it’s not uncommon for even established manufacturing companies to struggle with deploying IoT deeper into their business landscapes.
A company’s ability to achieve an autonomous manufacturing environment relies on data from connected devices flowing in and triggering actions effectively, including maintenance work, customer orders, and inventory re-orders. Such events and transactions can transform and “lean out” a business, by allowing it to shorten timelines, enhance the customer experience and open doors to new product and service lines.
Real transformation necessitates visionary leadership, combined with the technology and skill sets to execute on that vision. Treating IoT as a cost-saving strategy isn’t a fitting approach in these disruptive times.
Take the construction sector. It’s experiencing the highest and most immediate ROI potential in terms of increased safety. Yet IoT continues to be used as a cost-avoidance mechanism by many constructors.
Digital transformation is a future-proofing, creative process. Companies should aim to generate a fresh business model from it, not just gradually improve their rudimentary systems. Every industry and company must evaluate where IoT will drive a measurable return.
Large companies may fund huge systems-integration projects between IoT, SCADA and enterprise software, with the goal of achieving enterprise-wide benefits from IoT. A recent study by Bain & Co. reveals that prospective IoT adopters believe vendors have failed to limit the most significant barriers to IoT adoption. These include security concerns, the challenge of integrating with existing IT and operational technology systems, and unclear returns on investment.
Customers have extended their expectations of when such use cases will reach scale in their organizations, and are planning less-extensive IoT implementations by 2020 than were foreseen in 2016. They are further hindered by the fact that commercial off-the-shelf solutions, which connect data from multiple devices to the enterprise, have generally been slow to come to market.
Other barriers include the logistical and technical challenge of enabling IoT and enterprise resource planning (ERP) systems to talk to each other. IoT typically creates data in a continuous stream. A sensor may send a record of conditions in a piece of equipment or component to a plant historian or SCADA system at any given time. ERP, on the other hand, requires descriptive data on specific business events, such as an exception to ideal operational conditions, or duty cycle of a piece of equipment.
The reason why it’s difficult to consolidate these systems is rooted in the broad range of PLC and SCADA systems and their relationship with ERP, resulting in a substantial gap between connected devices and the transactional software used to run a business. In this environment, IoT can quickly become too complex, with systems integrators mapping multiple systems together.
To overcome this divide and help companies adopt transformational business models built around IoT data, ERP software will increasingly need to provide flexible solutions to knit together various information streams and present an overall picture of operational performance.
When considering the future of IoT, two types of future investment strategies stand out. The first focuses on enabling more thorough and strategic data collection; the second on making more complete use of that data. Data collected on a customer’s equipment might at first enable a company to identify issues, but in the future it could drive an automated field-service supply chain where the equipment sends its own work orders when required.
In time, these sensors will support servitized business models, enabling companies to charge customers for productivity and outcomes — duty cycles, products manufactured and hours of operation — instead of a discrete product.
When collected and acted upon efficiently, data enables companies to stay agile, improve the customer experience and leapfrog competitors. Achieving productivity and ROI gains from IoT will come down to a company’s ambition to take the strategy beyond a mechanism for cost prevention. To reap these benefits, decision-makers must demonstrate visionary leadership and ensure their enterprise solutions are future-ready.
Rick Veague is chief technical officer for North America with IFS.