Unlocking the Value of Manufacturing Usage Data Management to Propel Your Company’s Digital Transformation

Introduction

Many manufacturers are still just in the initial phases of their digital transformation. But the increased availability and affordability of sensors, radio technologies, and IoT platforms means that the pace of digitalization in production industries is steadily accelerating.

To take the next steps forward in digitalization, the frontrunners in manufacturing realize that they need more robust solutions to manage their data. To find value from the massive amounts of data that they’re already collecting today, and to keep scaling up, most major manufacturers will require a purpose-built solution for service usage data management.

In this article, we’ll provide a brief overview of the value of manufacturing usage data management in the digital transformation of your business. We also share strategies for you can capture that value through better usage data management.

What Is Manufacturing Usage Data? 

Quite simply, usage data tells you how your products are being used and/or how your services are consumed. For most manufacturers, that involves three basic categories of data: 

1. Product usage data
This is data related to tracking how customers use physical products, which is the key to offering servitization or outcome-based billing models. This data also provides insight into how machines perform in real-world conditions, which can be applied to build continuously better products.

2. Software usage data
This is about understanding how customers interact with software solutions, insight which can be used to drive Agile development. To support interoperability, OEMs also need to understand how their software interacts with other platforms in the customer’s IT architecture.

3. Production systems usage data
This is about understanding how machines and digital solutions are performing on your own factory floor. In-house system usage data can be applied to support Lean production processes and the evolution to predictive maintenance (PdM).

The Value of Managing Your Manufacturing Usage Data Efficiently

Transforming to new business models such as servitization means that across an entire organization, the objectives and KPIs for each business area also transform. In a data-driven business, everyone is dependent on clean, accessible data. 

Delivering that clean data is the job of the CIO and IT department. With a purpose-built solution for usage data management, their job becomes a lot easier, and the importance of their work becomes more evident. 

With clean usage data, each department in a manufacturing business can become more efficient and more innovative.  

Faster Innovation Cycles 

CIOs across industries are under pressure to speed up innovation. In today’s tight economy, that pressure is only increasing, but automating the collection and processing of usage data can help make things easier in a number of ways. 

First, automated data management frees up time for data scientists and IT teams to create more value, rather than performing manual tasks. Automation also eliminates the human error that comes with manual work. 

To become more agile, R&D teams need to be able to take control of usage data. Then, the value of clean usage will be evident in the development of physical products, software offerings, and bundled solution packages. 

59% of CIOs say that digital initiatives take too long to complete, and 52% say they take too long to realize value.

Gartner, 2022 CIO survey

Flexible Service Monetization 

As outcome-based billing models develop over time, it will be crucial for manufacturers to have the flexibility to customize price models that fit the customer’s needs. Doing so requires granular visibility of usage data generated by machines and digital services. 

A key challenge in monetizing services in new ways is how you incorporate new charging metrics into the billing landscape. With a system in place to capture, verify, aggregate, bind, and enrich usage data before it reaches the billing system, manufacturers have greater flexibility to design price models, as well as accurate data to create customer invoices. 

Easier Partner Settlements 

Succeeding in the world of IoT and connected products requires most manufacturers to build a partner ecosystem. Rather than try to build a complete solution themselves, most OEMs work with an array of specialist partners. 

Depending on the customer-facing package, a basic IoT solution ecosystem might include sensor and control system integrators, software vendors, connectivity providers, and maintenance service providers. 

As the scale and complexity of ecosystems grow, making sure all those players are paid accurately becomes more challenging. With a purpose-built solution for usage data, you can automate revenue sharing and settlement processes, and establish a strong audit trail to ensure partners are being paid and invoiced correctly. 

Minimized Revenue Leakage 

In the old world of manufacturing, billing for machines and related service packages was relatively easy. The customer either paid the invoice or they didn’t. 

But as OEMs add outcome-based or usage-based billing models to their offering portfolio, things get a lot trickier. You need to be sure that all the usage data related to both physical and digital products is tracked and billed for accurately. 

When you lose data about how customers use your services, or process the data incorrectly, the result is revenue leakage and compromised growth. You’ll need a solution to automatically capture usage data, bind it to customer accounts, along with validation and error-correction capabilities, so your customers get accurate bills. That means you have dependable revenue assurance and faster growth. 

Agile Service Personalization 

Businesses are increasingly interested in paying for outcomes rather than buying assets. As their customers demand greater flexibility in terms of purchasing, pricing and service agreements, manufacturers have to personalize offerings in order to stay competitive. 

By leveraging usage data, businesses can better understand service consumption, and thus better understand the needs of customers. That insight plays a crucial role in the design and pricing of machines, software, and bundled services. 

Clean usage data helps to verify that SLAs are being met and supports account managers in upselling and cross-selling relevant services. With a foundation of robust usage data management, OEMs can increase the lifetime value of customers and strengthen net revenue retention. 

Reduced Legacy Systems 

Manufacturers have a reputation for having slow-to-evolve business systems. Unfortunately, the old adage of “if it ain’t broke, why fix it?” just doesn’t hold up anymore. 

The organizational data silos, homegrown solutions, and overlapping systems that can build up over time create significant risk as systems are upgraded to adhere to evolving business requirements. 

But digitalization doesn’t have to mean a complete “rip and replace” of the IT infrastructure. By adding a purpose-built solution for usage data management, OEMs can minimize in-house development and manual processes, while getting more value out of existing systems. 

Increased Operational Efficiency 

We’ve already discussed how better usage data management can help improve efficiency for the IT team and other business areas. For manufacturers, clean data is also essential to increasing production capacity. 

In the quest to minimize production equipment downtime caused by machine failures or planned maintenance, manufacturers of all sorts are working to implement data-driven preventive maintenance, and eventually, PdM programs. 

To work properly, machine learning and maintenance software systems that support that mission need clean data from the machines on the factory floor. But production facilities have a mix of old and new machines, and mixed fleets from various suppliers that all use various systems and data formats. 

With better usage data management, the various formats of machine condition data can be normalized and contextualized, enabling PdM systems to work properly, and thus increase both efficiency of maintenance and supply chain teams, as well as supporting production uptime. 

Conclusion 

The manufacturing industry’s digital transformation is accelerating, driven by the availability and lowering cost of IoT technologies.

To augment and have full control of the transformation’s value, manufacturers must adopt robust solutions for managing their data effectively.  

Clean usage data brings numerous benefits, from faster innovation cycles through automation to flexible service monetization. It simplifies partner settlements, minimizes revenue leakage, enables agile and personalized offerings, reduced legacy systems, and increased operational efficiency.  

Ready to create more value from  your usage data?

CMO @ DigitalRoute

Behdad has extensive experience in Telecom and IT, as well as banking/financial sector, automotive, and utilities through cross-industry initiatives.

He is an entrepreneurial person with a strong result orientation. He displays the ability to see the bigger picture, and a good eye for finding uniqueness in people.