Operationalizing IoT Data to Drive Revenue in the Enterprise

By Rick Veague

Digesting data and devising a way to collect, analyze and operationalize insights can result in profitability.

Connected devices can generate valuable data streams that provide a wealth of knowledge which enterprises can employ to enhance product and service solutions. This potential for enterprises to successfully transform their business models and increase profitability isn't being tapped to the extent that it can be. Sixty percent do not possess the analytic capabilities they need to leverage this data, according to an IoT study conducted by Capgemini. Unfortunately, most of these data streams pile up in silos and are forgotten about, but digesting this data and devising a way to collect, analyze and operationalize these insights will result in profitability, if done right.

Understanding the Potential of IoT Data
Operationalizing data from connected devices begins with knowing what it can do for your company. Take the example of how asset-intensive service operations can take advantage of predictive maintenance insights generated from data streams. Already, on the plant floor, IoT data is used to drive condition-based maintenance and even preventive or predictive maintenance. Driving IoT data to asset performance management or EAM software can help companies track which components are operating correctly and capture a comprehensive snapshot of asset readiness and operational capacity.

For instance, an industrial manufacturer can take data from the equipment sold to its customer and convert it into a resource to help sell and deliver on aftermarket service contracts. In other words, data insights can fully transform a product-centric business model into a service-forward product-as-a-service model.

Modifying Your Monitoring Along the Way
It's important to go in with some direction on which patterns of data you're interested in analyzing. It might be clear that factors like temperature or rotational speed could be worth tracking in your pursuit to determine which factors negatively affect total throughput. There might be customers demanding more proactive service, and who would welcome an annual maintenance contract by which service is driven by real-time condition monitoring.

As monitoring progresses, making note of other factors affecting the process being studied could provide valuable observations worth adjusting your initial objectives around if it impacts productivity. For example, you might find that vibration patterns appear to accompany the temperature and speed factors in affecting total throughput, making it clear that this should be monitored as well. By and large, setting concrete objectives regarding what to achieve with IoT data is important, but reworking along the way will ensure no trend is forgotten.

Integrating Data With the Digital Transformation Ingredients
Despite IoT data capturing an extended view of equipment health, asset status and other system components, a recent IFS survey of 200 IoT decision makers at North American industrial companies found only 16 percent consume IoT data in enterprise resource planning (ERP) software. There's no point in compiling and analyzing data without having plans to do something with it. Thus, integrating IoT with ERP, enterprise asset management (EAM) or field service management (FSM) systems is needed to progress to the next stage of digital transformation. Below are examples of each:

• ERP: Industrial automation technology provider Rockwell Automation used the IoT in assisting customers with connecting its equipment to the cloud. As a result, these customers were more empowered to analyze their operational data, which ultimately improved decision support for both operational technology and IT users.

• EAM: IoT data was used to digitize pest-control services for a company called Anticimex. The service provider retrieved IoT data from thousands of smart traps to inform predictive maintenance and enable proactive system management. The data flowing from these connected devices has also enabled Anticimex to optimize where additional traps should be deployed, by predicting infestation patterns. In one year, the IoT solution generated nearly 10,000 automated work orders, boosted sales by 100 percent and increased customer satisfaction significantly.

• FSM: The IoT benefit to field service management is obvious, due to the distance between the equipment being serviced and the service organization. Real-time insights into faults, duty cycles and operating conditions can trigger the issuance of a work order, streamlining service provision. IoT data can also be made available to customers to give them insights into their operation and equipment they may need to consider replacing, deepening the relationship with their service provider.

Turning Data Streams into Revenue Streams
According to McKinsey Global Institute, the IoT has a projected annual impact of $11.1 trillion by 2025. Companies that leverage the IoT data they already possess to revolutionize their operations and business-intelligence systems will be able to measure and track value in new ways, enabling them to maximize revenue streams.

Where to Start
The amount of data and opportunities are daunting, and it is easy to experience paralysis by analysis as an executive team sets out to make the most of this data. Start by understanding the value of IoT data and the specific processes that might be worth monitoring—starting, perhaps, with one or two processes that could deliver a rapid return on investment. Keep an open mind about the trends you're uncovering and tailor goals as necessary to ensure data streams are being analyzed and operationalized in the ways that will deliver the greatest value to your product and service offerings.

As the chief technology officer of IFS in North America, Rick Veague has overall responsibility for the product and industry solutions offered to IFS customers and partners in the United States and Canada. As a well-respected panelist and speaker, Rick regularly speaks on IFS solutions and IT strategies at trade shows and industry events throughout the country.

Rick joined IFS in 1999, and has held various pre- and post-sales positions developing, marketing and delivering high-value business applications, including ERP, FSM, EAM and MRO solutions. He holds a degree in computer science and mathematics from Knox College.