How Networks of Connected Devices Are Creating New Business Models and Revenue Streams

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How Networks of Connected Devices Are Creating New Business Models and Revenue Streams

Ethics in Technology · Chapter 14: Tomorrow's Technology: AI, Biotech, IoT, and the Connected FutureSection 14.6 · lesson 94 of 11614 min · free with a free account

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In this lesson

Servitization, recurring services, outcomes, and responsible use of device data.

  • Explain how services and outcomes extend a one-time product sale.
  • Compare subscriptions, outcome payments, data products, and maintenance services.
  • Follow sensor data through a predictive-maintenance process.
  • Analyze data rights, meaningful agreement, and effective anonymization.

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Transcript

Everything said in the video, section by section (1,694 words). Read along, or search it.

Tomorrow's Technology: AI, Biotech, IoT, and the Connected Future

Connected Devices, New Business Models

Connecting equipment can change what a company sells, extending its relationship beyond a single product transaction. Information about operation supports continuing services, measurable outcomes, and useful products made from device data. Servitization describes a move from products alone toward services and, in advanced arrangements, delivered outcomes. A customer may value reliable operation more than simply receiving ownership of a physical machine. We will compare four models: subscriptions, outcome payments, data monetization, and predictive maintenance as a service. Each charges for a different kind of value. Contracts can still combine several models. Connected sensors help the provider understand equipment in use, away from its own premises. Monitoring also supports earlier maintenance decisions that may reduce disruption from unexpected failures. Turning usage information into a separate data product creates additional questions about rights and customer understanding. Anonymization must reduce identification risk effectively, rather than merely remove an obvious name from each record. By the end, connect the revenue model with the ongoing performance and data duties it creates.

Servitization

Sell Continuing Value beyond the Physical Product

A traditional product sale primarily transfers a physical item in exchange for its purchase price. The customer often owns that equipment, while warranties and other terms affect the parties’ later responsibilities. Servitization extends the offer toward continuing services, and sometimes the outcome that the equipment delivers. An outcome-focused arrangement can charge for availability or output, rather than just the machine itself. The provider’s revenue then depends on the continuing relationship and the performance commitments in its contract. Specified maintenance or breakdown risks can move toward the provider, according to the agreed terms. Retaining ownership may help a provider manage the asset and the risks it has accepted. Ownership is a separate contractual choice. It is not automatically transferred in every service-based business model. Some services support equipment that remains owned and operated by the customer throughout the relationship. The broader shift concerns the value being offered, rather than one universal rule about asset ownership. Compare the contract’s service, payment, and risk provisions before assuming every servitized offer behaves identically.

Visibility and Risk

Connected Monitoring Helps Manage Equipment in Use

Connected sensors provide visibility into relevant usage and operating conditions while equipment is in service. The manufacturer or service provider can receive information without physically inspecting the equipment at every moment. That supports maintenance planning, assessment of performance, and a better understanding of the risks accepted. For an outcome agreement, reliable evidence helps determine whether the promised result was actually delivered. An aircraft-engine service illustrates the connection between successful operation and the provider’s revenue. Rolls-Royce describes TotalCare as maintenance paid for on a per-flying-hour basis. Its account identifies specified maintenance risks transferred to the provider, while customers retain operational control. That is different from assuming every engine-service customer gives up ownership of the physical asset. Connected monitoring makes many advanced arrangements more manageable. IoT is not a universal requirement for services. Contracts still define availability, maintenance responsibilities, exclusions, and the method for measuring performance. Visibility helps manage a promise; it does not replace the organizational work needed to fulfill it.

Four Revenue Models

Different Offers Charge for Different Kinds of Value

A subscription model charges a recurring fee for continued access to a product, content, or features. A connected fitness bike’s monthly classes illustrate a service that can accompany the physical equipment. An outcome-based model instead ties payment to a measurable result, such as agreed hours of machinery uptime. Data monetization packages collected information for sale or licensing as a product in its own right. A protected crop-yield dataset supplied to agricultural researchers illustrates that distinct use of connected equipment information. Predictive maintenance as a service charges for ongoing monitoring and support that anticipates equipment problems. An elevator-monitoring offer can help organize repairs before a likely issue creates an unplanned interruption. These models may overlap: maintenance can use subscription billing, and outcome commitments may include monitoring. Overlap does not erase the difference between access, performance, a data product, and maintenance support. Not every data license must produce recurring revenue. Its payment terms determine the actual pattern. Identify what value is sold and what event makes payment due under the particular arrangement.

Access versus Results

A Recurring Fee Is Different from a Measured Outcome

A subscription payment follows continuing access over an agreed period, such as a monthly membership. The customer obtains the specified features or content according to the terms of that access. In the fitness-bike example, the monthly service includes classes rather than a guarantee of fitness improvement. Physical equipment ownership is a separate question: a customer may own the bike or use a rental package. An outcome agreement instead identifies a result that the equipment or service must deliver. For machinery, an agreed unit could be a successful operating hour, measured under defined conditions. The contract needs a clear measurement method and a meaningful explanation of the promised performance. The contract also needs to allocate consequences. What happens when the agreed performance is not achieved? Access charges and outcome charges can coexist, making the complete terms more informative than the marketing label. The essential distinction is what triggers payment: continued availability of access or an agreed measurable result. Explain that trigger before deciding how much performance risk each party has actually accepted.

Predictive Maintenance

From Sensor Readings to a Proactive Service Decision

Predictive maintenance uses equipment information to anticipate potential problems and support proactive service decisions. The diagram begins with collecting sensor readings, such as temperature, vibration, or patterns of usage. Analysis then compares those readings with expected operating patterns, looking for changes that warrant attention. The next stage estimates the risk of a problem, rather than knowing a future failure with certainty. A component or machine may be flagged for review when its measurements suggest an emerging issue. An appropriate service decision can then arrange inspection, repair, or another intervention before major disruption. The original reading becomes valuable through that interpretation and the timely physical response it enables. Predictions can be inaccurate. Some faults may occur without a useful prior warning. A service offer should therefore aim to reduce avoidable disruption, rather than promise that failure becomes impossible. The detailed implementation can vary by equipment and industry, even when the broad stages look similar. Monitoring, analysis, judgment, and action must work together for the maintenance service to deliver useful value.

The Economic Value

Avoiding Unplanned Downtime Can Be Worth Paying For

Unexpected breakdowns can cost more than repairing a failed component, because normal operation also stops. Lost operating time may disrupt production, building use, travel, or the activities dependent on the equipment. Planned intervention gives the organization more opportunity to arrange people, parts, and access in advance. That can reduce the additional disruption associated with a sudden failure. The customer is therefore paying for improved operation, rather than merely a continuous stream of measurements. A monitoring subscription supplies value when its warnings lead to appropriate and timely service decisions. However, savings depend on prediction quality, service effectiveness, and the actual cost of downtime. Monitoring itself costs money. Unnecessary interventions can consume resources or interrupt otherwise useful operation. Compare those costs with the losses a well-designed service can realistically help avoid. An inexpensive reading becomes a business service through reliable interpretation and a useful response. The economic case needs evidence about the complete process, rather than assuming every forecast guarantees a saving.

Data as a Product

Clarify Rights and Uses before Selling Device Information

Data monetization treats device information as a product that can be packaged, sold, or licensed. Crop-yield information from farm equipment could support agricultural research, subject to appropriate rights and protections. Before offering it, clarify what the manufacturer, customer, and analyst may collect, use, retain, and license. Different parties can have different interests and permissions. One simple ownership claim does not settle every question. Contracts should explain those responsibilities clearly and remain consistent with applicable law and privacy duties. Customer understanding also matters, especially when information collected for operation is proposed for another purpose. Meaningful agreement requires explaining the collection, intended uses, recipients, and relevant choices in understandable terms. A long agreement clicked without understanding does not by itself demonstrate responsible communication. Privacy protection must address whether the product identifies people or reveals confidential customer information. That assessment concerns the actual released information and its context, rather than its commercial label. Responsible monetization therefore begins with rights, purpose, and protection before treating the data as revenue.

Effective Anonymization

Removing Direct Identifiers Is Only Part of the Work

Anonymization aims to make people unidentifiable within the relevant context of the data’s use or release. Removing names and account details can help, but those direct identifiers are not the only identifying information. Location patterns or unusual combinations of attributes can sometimes link a record with other available information. A dataset may therefore remain identifiable even when no row contains an obvious personal name. Assess the information itself, the recipients, and the additional information reasonably available to them. Suitable transformations and release controls can reduce the risk, while preserving the usefulness needed for the intended purpose. The effectiveness of that approach must be evaluated, rather than assumed from a statement that names were deleted. Review matters when information or uses change. Those changes can affect the practical ability to identify people. In a crop-data product, also consider confidential information about farms or customers alongside personal identification risk. Calling a dataset anonymous is a conclusion that needs support, rather than a technique applied merely by labeling. Useful data and effective protection must be designed together before a responsible sale or license.

Review and Apply

Explain the Model, the Risk, and the Data Responsibilities

For the first review question, explain why asset control can help a provider manage accepted performance risks. Then qualify the ownership claim, because service arrangements do not all require the provider to retain equipment. For the second, explain how connected visibility supports remote monitoring and the management of ongoing commitments. That is especially useful in advanced connected models, without making sensors a universal precondition for all services. For the third, distinguish a recurring access fee from payment triggered by an agreed measurable result. For the fourth, connect planned intervention with avoided disruption, repair planning, and the cost of lost operating time. The savings are potential benefits that depend on the quality and costs of the actual service. For the fifth, explain why a data product needs effective protection against identification and unwanted disclosure. Removing direct identifiers alone may leave revealing links. Those links can still identify people or expose customer information. Across the models, inspect what is promised, how payment works, and which risks or permissions are allocated. Continuing value requires continuing duties for performance, clear terms, responsible data use, and effective privacy protection.

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Universities that work with NCCRS

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FAQ

Questions students ask us

About How Networks of Connected Devices Are Creating New Business Models and Revenue Streams

What is servitization?
Servitization is a shift from selling products alone toward selling ongoing services and, in advanced cases, guaranteed outcomes. Instead of just buying a machine, a customer may pay for reliable operation or availability. Rolls-Royce's TotalCare, for example, charges airlines for engine maintenance per flying hour, with specified maintenance risks moving to the provider. Connected sensors make such deals easier to manage by showing how equipment performs, but ownership terms vary by contract.
What is the difference between a subscription model and an outcome-based model?
A subscription charges a recurring fee for continued access, while an outcome-based model charges for a measurable result. A connected fitness bike's monthly class membership is a subscription; it guarantees access, not fitness results. An outcome deal might pay for each agreed hour of machinery uptime, so the contract must define how performance is measured and what happens if it falls short. The key difference is what triggers payment.
What is predictive maintenance as a service?
Predictive maintenance as a service is a paid offering that monitors equipment with sensors and analytics to spot likely problems before they cause breakdowns. Readings such as temperature and vibration are compared with normal patterns, risk is estimated, and inspection or repair is scheduled in advance, for example on elevators. It can reduce costly unplanned downtime, but predictions can be wrong and some failures give no warning, so savings depend on prediction quality and response.
Is anonymized IoT data really anonymous?
Not necessarily, because removing names and account numbers does not remove every way to identify people. Location patterns or unusual combinations of attributes can be matched with other available data; researcher Latanya Sweeney estimated that ZIP code, birth date, and sex alone uniquely identify about 87 percent of Americans. Before selling or licensing device data, companies should assess re-identification risk for the actual recipients, clarify data rights, and explain uses to customers in understandable terms.

About the Ethics in Technology course

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Ethics in Technology (Computer Science 195) carries a NCCRS credit recommendation for 3 semester credits. ACE and NCCRS have over 2,100 cooperating colleges that will consider accepting credits; the final decision is with the universities.
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