ERP Systems Under Pressure as Internet of Things (IoT) Piles on the Data, Survey Finds

As the industrial internet of things (IoT) integration grows more complex and the cost of broad-based IoT integration and monitoring continues to fall, businesses are becoming aware of the limitations of their enterprise software in making use of IoT data, a survey finds.

IoT involves the monitoring of all aspects of manufacturing or a business by imbedding monitors in things like components, production lines or fleets of vehicles, so it’s easy to see how they would create a flood of data.

IFS North America, a business software provider who commissioned the study with researcher IEN and analyzed the results, asked 200 IoT decision makers across a range of industries how well their software facilitated IoT data integration in 2017 and 2018. The results show a decline in confidence.

Only 52% thought their software worked somewhat or very well in 2018, compared with 60% who thought so in 2017.

Some 46% thought their software performed poorly or was an impediment to integration in 2018, compared with just 40% the year before.

These “digital transformation laggards” — as the study calls companies who said their ERP  software wasn’t up to the task — are at risk of serious disruption to their businesses by enterprises moving quicker to leverage IoT technology, said Antony Bourne, president of IFS Industries.

“If industrial companies do not embrace digital transformation, chances are that their business will be the one that’s disrupted by faster movers,” Bourne said. “IoT helps companies transform their businesses, making them more efficient, helping them explore new revenue sources and fundamentally changing business processes.”

Digital transformation is a broadly used term, but in this context the IFS Study defines it as the growing use of digital technology that change the way we live and conduct commerce, opening up new ways for businesses to create new revenue opportunities, reduce costs, enhance the customer experience and potentially launch new business models.

As software is updated and IoT data volumes continue to grow, data centers will have their own hurdles to face over networking and connectivity.

Aside from this study, a recent Network World article discussed some of the challenges and changes that IoT brings beyond the factory floor. The flood of IoT data is requiring a shift from human decision-making to artificial intelligence linked to machine learning programs that can replace manual controls, the article said.

In the study, IFS’ chief product officer, Christian Pedersen, said “in some ways it can be a scary picture because there is so little human involvement and in some cases … none at all.”

“Data from IoT used to focus on collecting datapoints for analytics that would be acted on,” Pedersen said. “Now the data is triggering events directly in the business, in automation engines and in AI engines. … They can combine data from multiple sensors and generate entirely new intelligence and even send actions out to other, different devices and sensors. That is when we start getting to true automation.”

Advanced Monitoring and Automation

The IFS study found that process automation and monitoring operational efficiency are the most common uses of industrial IoT.

In 2017, 49% of businesses used IoT monitoring for process automation and 54% for operational efficiency; in 2018, those figures increased to 55% for process automation and 65% for operational efficiency.

These gains represent a shift away from a focus on using IoT for cost reduction via condition-based maintenance and similar applications prior to 2018 toward more concrete transformations in operations and the more sophisticated data collection requirements that come with them, the study said.

IFS found that between 2017 and 2018, the percentage of respondents that did not monitor their equipment fell threefold, from 15% to just 5%.

Respondents also increased the complexity of existing monitoring practices. Just 40% said they monitored full work cells or production lines compared to individual components or machines in 2017. In 2018, that figure had jumped to more than 56%.

Bourne notes that this large increase may be the result of some organizations completing pilot projects, seeing what works, and taking expansion and integration steps into larger parts of their business.

Control and Execution Systems

The IFS survey also noted a shift in business systems being used to control and consume IoT data.

Respondents using a Manufacturing Execution System (MES), fell 10%, while those employing a Supervisory Control and Data Acquisition systems increased by 10%. MES is used to help plan and execute process command for industrial machines, while SCADA uses a network of controllers, sensors and user interfaces to create a high level of control for operators at a large plant.

As IoT integration expands and the data required to successfully automate more industrial and business processes becomes more available, SCADA systems begin to both encroach on the functionality of MES and absorb the latter’s role in sending relevant data to ERP systems.

Technology consultant Ajay Kaushik published a helpful article on LinkedIn further discussing the interaction and roles of these vital control systems.