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The Data Pile-Up Problem: How to Capture and Monetize Enterprise IoT

By Special Guest
Rick Veague, CTO, North America, IFS
June 11, 2018

Data streams from connected devices have the potential to deliver new insights that can in turn be used to drive new products and services, and ultimately new revenue streams, for companies that deliver services, sell products or maintain capital assets. However, according to a recent IoT study by Capgemini, 60% of enterprises lack the analytic capability to actually use this data– think of this as the “data pile-up” problem. We’re seeing too much IoT data ending up in silos and not fully utilized, which is an unfortunate sign that companies are neglecting a wealth of knowledge that could revolutionize their business models.

By breaking down these data silos, and creating a flow from data acquisition, through analysis and finally to action, companies can learn what useful knowledge can be extracted from IoT data, and can use this untapped resource to develop a more efficient, competitive organization.

What can IoT-ERP Integration bring to the table?
The first step is understanding how to leverage IoT data to improve product or service offerings. Of course, this process varies by industry and business model, but consider how an asset-intensive service operation can benefit from the predictive maintenance insights generated from IoT data. Already, on the plant floor, this data is often used to drive condition-based maintenance and even preventive or predictive maintenance. Driving IoT data to asset performance management or EAM software can help monitor which asset items or components are working properly and provide a 360-degree view of asset readiness and operational capacity.

An industrial manufacturer can capture data from equipment sold to their customer and transform that data into insights that can help them sell and deliver on aftermarket service contracts, or even move to a business model that involves selling throughput, capacity or duty cycles, resulting in a “product as a service” business model.

Setting objectives, while keeping an open mind
Setting initial objectives on what to achieve will provide a sense of where to start when analyzing specific patterns or pockets of data. For example, you might already know temperature or rotational speed is worth measuring in your goal to assess which components are bad actors and negatively affect total throughput. You may have a handful of customers who want more proactive service, and would be receptive to an annual maintenance contract where service is driven by real-time condition monitoring.

However, it’s equally important to be open to modifying objectives as insights picked up along the way could influence what’s being measured. Perhaps when monitoring temperature or speed, it becomes evident vibration patterns also affect system productivity. At this point, the need to track this variable over time is apparent considering its impact on performance.

Having well-defined ideas on what you are going to achieve with IoT data is necessary, but keeping an open mind and modifying end goals as new trends are uncovered along the way is also part of the process. You’ll probably be surprised at what you find!

Using IoT to drive digital transformation
In many industrial organizations, information from connected devices provides windows into equipment health, asset status and other valuable system components, mostly on the plant floor. However, a recent IFS survey of 200 IoT decision makers at North American industrial companies reported only 16 percent consume IoT data in enterprise resource planning (ERP) software, where business-level actions are taken. Collecting data, or collecting and analyzing data, is useless if the insights gained are not acted on.

This disconnect suggests the next level of digitization will be dependent on integrating IoT with ERP, enterprise asset management (EAM) or field service management (FSM) systems. In the context of strategic business data and processes, IoT data streams can trigger operational processes, provide real-time insight into performance against goals and create value to customers. Consider the following examples:

In the instance of ERP, industrial automation technology provider Rockwell Automation used IoT in assisting customers with connecting their 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.

On the EAM front, 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. This meant that technicians only needed to visit the trap when the battery was low. The data flowing from these connected devices has also enabled Anticimex to optimize where additional traps should be deployed, by predicting infestation patterns.

The IoT benefit to FSM is obvious due to the distance between the equipment being serviced and the service organization. Real-time insights on 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 the customer to give them insights into their operation and equipment they may need to consider replacing, deepening the relationship with their service provider.

If you can operationalize, you can monetize
IoT is projected to have an annual impact of $11.1 trillion by 2025 according to McKinsey Global Institute, and opportunities for new revenue and greater profits are there for organizations who can marry these data stores with their operations and business intelligence systems.

When products and services are better connected, there’s more opportunities to operationalize the data yielded from it. Begin assessing what trends or workflows could be monitored and be open to modifying these objectives based on initial findings. You can monetize data if you can operationalize it, and cutting down costs and time while increasing productivity maximizes profitability.

About the author: As 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, Veague regularly speaks on IFS solutions and IT strategies at tradeshows and industry events throughout the country.




Edited by Ken Briodagh


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