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As businesses move from traditional approaches and embrace digitization and automation, large volumes of data are being generated as a result, and with the right approach and strategies, this data can be exploited as a source of economic value to the manufacturing industry.

Although challenging, the chief data officers (CDOs) and chief information  officers (CIOs) in organizations are mastering these new ways that have proven to be invaluable game changer and differentiators in the stiffly competitive world of manufacturing business.

With the deployment of an enterprise resource planning (ERP) system and other interconnections such as internet of things (IoT), manufacturers are not only more connected to their operations, products and customers, but also able to collect data for insights to improve efficiency, and also generate an income stream.

Simply defined, data monetization refers to the process of utilizing data to secure measurable economic benefits  such as improved profits due to reduced production costs and better customer satisfaction therefore more sales, and enhanced efficiency as a result of streamlined operations. The process can take a direct or external approach, which involves selling data to third parties (within the confines of the law) therefore securing an income, or, an indirect or internal approach, in which data gathered is used internally to improve operations, customer satisfaction, products and services, therefore, influencing the businesses’ value chain.

In the business world, data is the new oil. Moreover, as an intangible asset, its value can grow with the more insights drawn from it and the more ways it is used. For manufacturers, there are a number of ways they can pursue to monetize their data.

Harnessing existing data

Many manufacturers around the world are sitting on vast amounts of data that they have no use of, do not know how to use it, or do not even know of its existence, and with the current digital transformation, this data is only increasing. Often kept in silos in business applications such as ERPs, this data can be smartly exploited to draw meaningful insights. By employing data analytics, this existing data can be used to identify existing and unnoticed weak links, carry out corrective actions, and enhance profitability. For instance, analytics of such data could reveal a repetitive erroneous task by an operator or machine that has been leading to more faulty/defective products in the production line. A corrective measure is then effected, which leads to reduction in defective products, therefore enhancing profits. Moreover, existing data can be used to increase machine utilization and factory throughput by using such data to optimize production schedules through factory simulations.

Offering data driven products

Digitization and automation makes it possible and easy for manufacturers to gather data about their products. For instance, through IoT connection, manufacturers can monitor their sold products’ use and operational performance remotely; get notifications for such aspects as maintenance or breakdown. With such data, manufacturers can then pinpoint the products’ aspects that require improvements. Another viewpoint of this is using data to draw insights and make better product-related decisions. For example, manufacturers can use data from sales and marketing to gain insights on customer preferences, or data from service and support to develop products that are more serviceable. A manufacturer can then leverage the improved decision making to achieve a competitive advantage over competitors.

Additionally, manufacturers can collaborate with e-commerce platforms such as Amazon, Alibaba and Jumia to gain access to crucial data such as product demand and customer reviews, then use the data for product improvements or decision-making. Manufacturers can establish the available data from external sources, combine it with what they have internally to improve their products, thus maximizing their sales.

The ultimate benefit of offering data driven products is that it ensures that the manufacturer’s products are satisfying the target customers’ needs, which in turn means more sales, therefore more revenue.

Optimize operations through data

Data collected from internal sources about processes, applications and systems can be used to streamline operations, in turn reducing lead times, overheads, and enhancing efficiency, thus maximizing profits. Take for example, a manufacturer collecting and analyzing data on how long a product stays in the production line. From analysis, it is established that there are stages or actions involved that are unnecessary and thus can be bypassed. This would mean the product manufacturing cycle is shortened, thus saving time to manufacture more products, which also means overall reduction in production costs. This approach not only reduces product development costs but also improves customer experience by ensuring faster product innovation.

Getting it right

For effective data monetization by manufacturers, there are a few guidelines that need to be observed. First, manufacturers need to understand the role and value of data in their business. This involves establishing how valuable it can be, whether it is internally in streamlining operations, improving sales and cutting costs, or externally in improving customer satisfaction. With this understanding, manufacturers can better manage and smartly utilize their data.

The second guideline is organizing the manufacturer’s data house. Here, manufacturers need to establish where their data resides, the quality of data, and the kind of data they have regarding their products, customers, and business partners. Thirdly, infusing data monetization into business strategy. Through this, manufacturers can evaluate their strategic initiatives and goals from the perspective of how data can support them and then setting the right structures in place to monetize it. Fourthly, manufacturers have to communicate and educate the value of data to internal and external stakeholders, since data monetization may be a new concept to them. This will foster growth through encouraging brainstorming how data can improve manufacturing processes.

For proper monetization, manufacturers need to put up a well outlined plan. First, all data should be integrated. Here, cloud computing is crucial. All data storage, business applications and systems need to be integrated to a centralized cloud based data point for easy exchange and retrieval. Secondly, this data needs to be secured by implementing appropriate security measures such as restricted access and additional security layers to systems. Thirdly, employing data analytics to turn the data into insights. Fourthly, utilizing the insights effectively to streamline operations, improve products and processes, and enhance efficiency. With this kind of plan, manufacturers stand to rip enormously from their data.

While many manufacturers are used to pursuing success through established corporate strategies, harnessing data monetization comes with enormous benefits and potential to deliver value as an additional revenue source. Manufacturers therefore ought to be open to the endless opportunities presented by digital transformation.