The way we realize value has changed considerably since the industrial era, when growth was measured by the number of machines shipped, and delivery equaled revenue. Where once it was about product design, it’s now about what runs inside the product: software, analytics, optimization logic, and AI models.

Today, capabilities are often enabled, updated, or disabled remotely. As such, two identical machines may offer vastly different value simply based on the software applications they contain and the ways in which those applications are used and evolve in the field. This trend has increased efficiency over time, provided predictive insights, and enabled adaptive behavior.

This is a new paradigm riddled with ingrained conflict. Manufacturers of industrial products are no longer simply making products; they are running de facto software businesses within the entities that design and produce physical products.

The goal has now shifted from one-time monetization to continuous software monetization through customer-tailored features. However, there is no software monetization without control.

Static Revenue Models vs. Dynamic Software Value

Traditional commercial revenue was designed to be stable. It was based on the assumption that once a product was sold, the transaction was complete. This meant that each transaction would have a fixed configuration and would use only one delivery point.

Commercial revenue methodologies were tied to manufacturing and logistics. As a result, revenue flowed in predictable patterns. However, unlike traditional commercial revenue methodologies, software-defined revenue does not follow the same rules.

When a feature is deployed, it evolves. Features are activated dynamically across multiple machines, sites, and production lines. Operational demand dictates the usage of the software, not when a purchase is made. By creating offers that meet customer needs, revenue can increase, and new revenue streams can be opened up without any extra R&D investment, simply by turning on existing capabilities.

The resulting tension is seen as an "execution" problem. However, in reality, it is a structural issue. Conventional monetization models are unable to keep pace with the continuous delivery of software-defined value. The gap between creating value and governing revenue is not due to a lack of creative pricing and sales discipline, but to a fundamental misalignment.

Where Industrial Software Revenue Erodes in Practice

The results of this mismatch show up in how we do business every day.

We turn on features temporarily to test or commission them, and they remain on.  We duplicate our software across all our machines or production lines; however, we do not have an entitlement process in place to support this.  We use our software and other digital assets beyond what was agreed upon contractually, and yet we have neither the ability to see when this happens nor a way to enforce it.

These types of issues are called revenue leaks. However, using this term may mislead people. In nearly all industrial markets, the problem is not "bad behavior." The problem is complexity. The way we design and implement distributed systems, deploy at the edge (in proximity to where data originates), and manage long-term asset life cycles creates a situation in which software use moves away from commercial agreements, merely because we don't have a governing system to prevent it.

Revenue degradation does not occur due to neglect, but rather due to a lack of enforceable governance across software, devices, and their use.

Monetization Is Not Pricing, It Is a Control System

The way we need to think about this must change.

Monetization is often treated as a commercial exercise. Price lists, SKUs, contracts, and discount structures all matter, but they are not enough on their own. In reality, robust monetization systems reduce SKU complexity by replacing old, rigid product definitions with governed access.

Software Monetization through licensing and entitlements is a de facto control system. It governs what is protected (even in offline field environments), including who can access which capabilities, under what conditions, and with what visibility over time.

Without enforceable controls across software, devices, and usage, monetization will remain a “pie-in-the-sky” dream rather than operational. Pricing defines intent, while control determines reality.

Why Hardware-Era Controls Fail in Software-Defined Industrial Environments

Legacy controls were built for static products, so they can’t help but fail in environments where product value is constantly changing.

Static license models can't enforce features that are enabled or disabled at different times, and manual processes don’t work under subscription, usage-based, and hybrid models. Local-only control also fails to provide the level of transparency needed to manage global ecosystems of factories, regions, and partners.

Perhaps more important than the direct impact on revenue is that these gaps create additional risks beyond just the financial ones. As manufacturing moves to software-defined systems (such as smart machines), a monetization gap develops between application security and app licensing.

When an organization’s IP, access rights, and usage limits aren’t consistently enforced across users, both the business's revenue and risk position will suffer.

Control systems have to evolve, just like software architectures, deployment models, and threats evolve. Until this happens, there will be a gap between the logic governing business revenue generation and the reality of business operations.

What Control with Licensing and Entitlements Enables

The future state is not defined by tools or platforms, but by capability.

Modern monetization systems help industrial companies stand out through software, not by creating more versions of their hardware. They make it easier to offer subscription, usage-based, or mixed models without rebuilding core products. This means offerings can change after deployment without adding operational complexity or disrupting customers.

These systems are designed with industrial constraints in mind: edge deployments, intermittent connectivity, and safety-critical or regulated environments where uptime and compliance are non-negotiable.

Control is often seen as a blocker, but in practice, it is the enabler. When access, usage, and entitlement are governed systematically, flexibility increases. Agility improves. Scale becomes manageable rather than chaotic.

Security, Compliance, and Monetization Are Now Intertwined

Industrial monetization has changed along with its risks.

With software-based creation of revenue-generating value come risks such as intellectual property theft of algorithms and models, unauthorized use of features, and regulatory or export compliance breaches.

Rather than anomalies, these should be seen as fundamental risks in today’s globally connected industrial environments.

Revenue protection and risk management cannot be viewed as separate entities anymore. Trust, auditability, and resilience have become non-negotiable in monetization strategies. Monetization will be undermined if entities treat security and compliance as secondary.

Access Control Is What Turns Industrial Software into a Revenue Engine

Industrial software can deliver ongoing value, but this cannot happen until control has been established, either by protecting revenue from loss (revenue retention) or by driving the growth of new revenue streams.

To do this effectively, a mindset shift must happen within executive ranks. Don’t ask how you can sell better products or machines; ask how you can design, enforce, and evolve monetization systems that span your software, hardware, and lifecycle.

The next generation’s industry leaders will be those companies that treat their monetization capabilities as part of their infrastructure: intentionally developed, consistently enforced, and evolving with the same discipline as the systems they create.

Kirsten Doyle has been in the technology journalism and editing space for nearly 24 years, during which time she has developed a great love for all aspects of technology, as well as words themselves. Her experience spans B2B tech, with a lot of focus on cybersecurity, cloud, enterprise, digital transformation, and data centre. Her specialties are in news, thought leadership, features, white papers, and PR writing, and she is an experienced editor for both print and online publications. She is also a regular writer at Bora.