Data is a critical component of digital transformation in the manufacturing industry. In fact, it is at the heart of all digital initiatives. However, data alone is not a value driver. It must be put to use for organizations to realize the full benefits. With massive volumes of information available at the stroke of a button, businesses may gain significant insights and create transforming experiences for their consumers and growth. Many manufacturers are failing to maximize the potential of data enrichment, resulting in missed chances to develop, optimize, or manage risk.

In general, industrial operations collect data (often manually), but many do not understand how to use it to impact the supply chain or cannot easily access it since it is locked in antiquated systems. Accessing data alone is insufficient; enterprises must also be able to monetize it. With the correct combination of technology and innovative thinking, this is an attainable objective.

3 Ways Manufacturers Can Monetize Data

1. Create new revenue models

Manufacturers can satisfy customers in new and innovative ways. With the rise of the subscription economy, there is an opportunity to expand beyond products but also include a service. Organizations can create subscription-based analytics products and with the data collected from IoT devices monitor and use trends, patterns, and insights about their usage. This strategy creates a subscription-based revenue stream, while the physical good itself is often a one-time purchase.

For example, a refrigerator manufacturer can install an IoT sensor in each of its units to check uptime and product temperature. When any of these criteria change, the gadget can send an alert message to the ERP system, prompting technicians to address the issue. Predictive maintenance is one of the most useful applications for data in manufacturing. This can help improve customer maintenance and service, create chances for services, and upsell. Combining and enriching data on price, inventory, and consumer behavior enables the company to generate educated forecasts using predictive analytics.

2. Share data for partnership and growth

Data partnerships and collaboration have the ability to alter value in the manufacturing sector. Monetization is not a direct result of this strategy, but rather a means of establishing alliances and increasing market share. Data can also promote cross-sector collaboration.

An example could be a collaboration between an electronics manufacturer that manufactures vehicle alarm tracking systems and the automobile rental business. The car rental business can use manufacturer data to monitor how drivers treat the vehicles and their speed. The manufacturer may then monetize both their devices and their data by working with other industry sectors.

3. Get onboard with eCommerce

Manufacturers have long avoided online sales. Some typical comments included feeling that it was ‘too difficult’ and ‘too high-risk’. During the pandemic, however, many organizations were forced to reconsider their views. With supply chain disruptions and physical shop closures, several businesses found themselves discounted from their primary outlets. Manufacturers have recognized the importance of integrating sales and inventory management across online and offline operations.

The beauty of eCommerce is the amount of information you can harvest not only from your own eCommerce site but in integrating with existing platforms. Manufacturers can leverage existing eCommerce platforms such as Amazon to sell products directly to consumers online with APIs, or software intermediaries that allow application programs to interact with each other and share data. APIs are integrated into an ERP system for manufacturers to gain first-hand information on what customers are buying. By analyzing this information, manufacturers can gain a host of critical insights.

The first step for those looking to benefit on data monetization prospects is to convert raw data into information. Data, whether from the client’s system of records, internal, external, or public sources, is frequently divergent, in many formats, and complex and inconsistent. Unfortunately, typical procedures, such as hand manipulation of Excel spreadsheets, are time-consuming and error-prone. Companies that automate data gathering and validation using an ERP system will be able to generate income faster.

How Does Data Monetization Work in the Manufacturing Industry?

The “Internet of Things” (IoT) is growing rapidly as the cost and size of sensors and communication technology decrease. In its 2017 Internet of Things (IoT) and Industrial Internet of Things (IIoT) forecast, Bain predicts that by 2020, annual revenues for IoT vendors selling hardware, software, and comprehensive solutions will exceed $470 billion, while General Electric expects investment in the Industrial Internet of Things (IIoT) to exceed $60 trillion by 2025. By 2025, the return on investment will be $13 trillion.

These connected items provide new potential for functionality, increased product use, and capabilities that go beyond traditional product boundaries, affecting industry structure and the nature of competition.

The new wave of the Industrial Internet of Things (IIoT) will pose a fundamental challenge to many businesses: “What business am I in?” Connectivity and intelligence provide a completely new set of functionalities and capabilities, which can be classified into four categories: monitoring, control, optimization, and autonomous.

Monitoring

Connected products enables manufacturers with comprehensive monitoring of a product’s usage, condition and external environment with the help of embedded devices like sensors along with other external data sources.

Read Also: How to Monetize Your Mobile App Data

The connected products are a huge source of 2.5 quintillion bytes of data created every day, can help companies raise a new set of strategy related to how value is created and captured, how the enormous amount of new and sensitive data they generate can be utilized and managed, how relationships with traditional business partners be redefined by helping them improve their offering by tracking and analysis.

For example, if you manufacturing and selling heavy equipment that can break and subsequently need maintenance and servicing, you’ve struck gold. Now you can offer preventative maintenance services, monitoring services and value-added services that you previously couldn’t, creating entirely new business line.

Control

Connected products can now be controlled through remote commands or algorithms built into the device or reside in the product cloud, these algorithms written as rules can direct the product to respond to specified changes in its condition or environment.

For example, in case of a liquid bulk third-party terminalling business, connected tanks can provide real time visibility into the functioning of the equipment’s – such as which tank is being heated or mixed or which pumps are being used to load or unload a truck or railcar. Now with connectivity and intelligence enabled the administrator can not only see real-time functioning of the pumps, mixers, but also the levels and the temperature of the tanks. The administrator can also take the external temperature from a weather station and use that to predict when a particular tank is going to reach a given set point, allowing them to shift activities accordingly.

Optimization

The rich flow of monitoring data from connected products, coupled with the capacity to control various product functions, operations, can help companies to optimize product performance in numerous ways.

Continuing our earlier example, on a liquid bulk third-party terminalling business, the collected monitoring data can help the business “Learn” models for activities to schedule them so as to smoothen peak-demand graph (reducing electricity bill).

Also in case of a heavy equipment manufacturer, real-time monitoring of data on product condition can enable firms to optimize service by offering preventative maintenance when failure is imminent and accomplishing repairs remotely, thereby reducing product downtime and the need to dispatch repair personnel.

Autonomy

With monitoring, control and optimization capabilities combined together can help businesses achieve a previously unattainable level of autonomy. At the simplest level is autonomous product operation like, a tank that uses sensors and software to monitor the pressure, is able to learn about the environment, self-diagnose the optimize pressure required and turn the value on/off accordingly.

Autonomy not only reduces the need for operators but also improves safety in hazardous environmental conditions and facilitates operation from remote locations.

Data Monetization Market Analysis

• Market Growth and Size: The market is witnessing robust growth, driven by the increasing importance of data-driven decision-making across various industries. The growing volume of data generated and the need for businesses to derive value from their data assets are also offering a favorable market outlook.
• Technological Advancements: Rapid technological innovations, such as artificial intelligence (AI) and machine learning (ML), are playing a pivotal role in enabling more efficient data monetization strategies. These technologies help in extracting actionable insights from data, enhancing its value.
• Industry Applications: Data monetization finds applications across diverse industries, including finance, healthcare, retail, and telecommunications. It allows businesses to unlock the potential of their data for better decision-making and revenue generation.
• Geographical Trends: North America leads the market, driven by its advanced technological infrastructure. However, Asia Pacific is emerging as a fast-growing market, driven by the adoption of advanced analytics.
• Competitive Landscape: Key players in the market are innovating to offer comprehensive solutions and stay ahead in the competitive landscape. They are investing in advanced analytics, AI, and machine learning (ML) technologies to provide more powerful insights from data, enabling businesses to make better decisions.
• Challenges and Opportunities: While the market faces challenges, such as data security concerns, data quality issues, and the need for skilled data professionals, it also encounters opportunities in leveraging untapped data sources and expanding into emerging markets.
• Future Outlook: The future of the data monetization market looks promising, with the increasing demand for tailored data monetization solutions for specific industries, such as healthcare, finance, and retail. These specialized solutions will address industry-specific challenges and opportunities.

Data Monetization Market Trends

Growing volume of data

Organizations generate massive volumes of data through their operations, customer interactions, and digital touchpoints. This data includes both structured and unstructured information, providing useful insights that may be used to make strategic decisions and generate money. As firms collect more data, they become more motivated to find methods to extract value from it.

Data monetization allows you to not only use this data for internal purposes, but also to generate additional cash by sharing or selling it to other businesses. The development of Internet of Things (IoT) devices, social media interactions, e-commerce transactions, and digital services all contribute considerably to the data explosion. This trend is expected to continue as technology becomes more integrated into daily life, further catalyzing the demand for data monetization solutions and strategies.

Need for data-driven decision-making

The increasing need for data-driven decision-making is bolstering the growth of the market. In the competitive business landscape, organizations recognize that data is an asset that can guide strategic choices, optimize processes, and improve overall performance. Data-driven decision-making empowers businesses to base their strategies and actions on factual insights.

This approach enhances the accuracy and effectiveness of decision-making processes, leading to better outcomes in areas, such as product development, marketing campaigns, and resource allocation. As businesses are seeking to gain a competitive edge and remain agile in fast-paced markets, the demand for data-driven insights is growing. Data monetization enables organizations to leverage their data assets to gain actionable insights, identify trends, and make informed decisions in real-time.

Technological advancements

Rapid progress in data processing, storage, and analytics technologies is opening new possibilities for organizations to extract value from their data assets. The advent of artificial intelligence (AI) and machine learning (ML) is revolutionizing data analysis. These technologies enable businesses to uncover hidden insights, predict future trends, and automate decision-making processes, which enhance the monetization potential of data.

Big data platforms and cloud computing are making it more feasible for organizations to store and manage vast amounts of data cost-effectively. This scalability allows businesses to accumulate and leverage data on a larger scale, driving the need for data monetization strategies.

Increasing awareness of data value

The growing awareness among the masses about the value of data is offering a favorable market outlook. Organizations across various industries are increasingly recognizing that data is not just a byproduct of their operations but an asset with the potential to generate revenue and insights.

This awareness stems from success stories where companies are monetizing their data, either through direct sales or by using it to enhance their products and services. Additionally, educational efforts, industry reports, and conferences focused on data monetization are contributing to spreading awareness.