We have seen decades of enterprise software development and evolution, from basic materials requirements planning (MRP) to enterprise resource planning (ERP) and from on-premise to the cloud. In 2018, we are now seeing the next step — enterprise software integrated with data flows from the internet of things (IoT).
This movement is driving significant digital transformation in part because IoT data is driving new insights into how products and assets are performing in near real time. This insight, if leveraged, can drive new business opportunities and even new business models. As companies adopt more advanced use cases for IoT, more of them will be able to use data from connected devices not only for analysis but to trigger business processes and transactions in enterprise software, automating entire value streams through the enterprise.
Even in manufacturing, where sensor-enabled machines are now commonplace, we are at the early stages. In 1968, General Motors knew it was necessary to find a replacement technology for its costly, unreliable relay switch-driven automation. Richard Morley of Bedford Associates offered up a modular digital controller that relied on ladder logic — the first programmable logic controller (PLC). Even today, data from PLCs drive manufacturing, with data sent to the supervisory control and data acquisition (SCADA) system to monitor, schedule or control manufacturing processes. SCADA is perhaps the precursor of modern IoT. Next steps include extending the availability of data beyond SCADA, which has historically been used on the plant floor, and into the rest of the enterprise. Data capture will come not just from PLCs but from an array of flow sensors, humidity sensors, temperature sensors, vibration sensors and other devices that enable smart support of equipment deployed in the field.
Already, we are seeing an increased focus on the use of data from connected devices for decision support. A study from Telecoms and Computing Market Reports reveals that the global manufacturing analytics market will grow annually by 21.9% between now and 2022. But according to a primary research study conducted by IFS, access to IoT data is still primarily limited to the plant floor:
* 85% of respondents said they have sensors on equipment.
* Condition-based and predictive maintenance are far and away the most common use case for IoT data. But only 20% of respondents said they had integrated IoT data with enterprise asset management software used to manage equipment maintenance.
* Most respondents said access to their IoT data was limited to those using a process automation system or supervisory control and data acquisition (SCADA) system.
* Only 16% said it was accessible to ERP, the corporate system of record.
We are moving past IoT data being available and consumed on the plant floor, toward more comprehensive and higher-value use of data from connected devices to inform business-level decisions. Once IoT data is integrated with enterprise applications like ERP, it can also be used to automate not just manufacturing processes but transactions and business process.
Promising Early Applications
Most IoT-enterprise integration we see today is focused and purpose-driven. Smart companies are seeing the potential but picking their fights to drive immediate value.
* An international midwater drilling contractor started an automated data capture project to simply eliminate manual data entry, but as it gained confidence, the company started using features of its enterprise application to enable predictive maintenance on its offshore rigs.
* Companies in the medical equipment industry are embedding sensors in equipment sold to customers and using that data to automate the issuance of field service work orders based on metrics like duty cycles or operating conditions.
* Aerospace companies have integrated data from sensors on individual aircraft with systems used by the grounds crew. This diagnostic information can trigger activities in systems for maintenance to supply chain management to make the most of the time the aircraft spends on the ground.
As integration between IoT and the enterprise becomes more sophisticated, it will enable not just new insights and automated processes but entire new business models. It will enable, for instance, a product-as-a-service approach where a manufacturer or distributor can rely entirely on cost-per-use fees instead of upfront revenue from new product sales.
Challenges And Next Steps
Integrating data from IoT with the enterprise presents certain technological barriers that must be crossed.
To start with, SCADA and automation systems that track data from connected devices just think differently than enterprise software used to run a business. Automation systems collect continuous data — capturing running, speed, faults, temperature and other performance metrics every second or so, or even on a shorter increment. Enterprise software will need to boil that data down into defined events — time stamps, average operating temperatures or fault data. So an IoT discovery platform is generally required to turn data from connected devices into something enterprise software can use. The enterprise software itself must also have a defined method to port IoT data into the transactional database in a usable fashion.
The potential applications for IoT in an enterprise of any size are almost countless, which can make the starting point difficult. For that reason, it’s best to start with something simple, such as collecting machine runtime hours or production counts. An initial project should have modest objectives — and modest cost. Once you’ve started down the path and can see results, it becomes much easier to envision the next step in the journey. IoT projects can often be viewed as IT projects. But it’s wise to create a partnership between IT and leaders from the business side. In one project, IoT was used in partnership with the marketing deparmtent, and the marketing team was able to use the data to create a specialized marketing campaign backed by real data.
But digital transformation is not defined only by objects (by connected things) but by connected people. Software must include data from IoT, but it must be made accessible to people. And it must improve in its ability to capture insight — not just from things but from people through enhanced usability. This trinity of IoT, usability and mobility will define digital transformation for industry.
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