Entering The Era of Data Economy and What It Means for Companies
In today’s digital era, data has emerged as a new type of strategic asset which can be sold and exchanged. Data can now be easily generated from various sources which are mainly categorized into two: IoT devices (sensors/wearables, mobile phones, embedded chips, attached sensors/wearables, gyroscopes, etc.) and traditional big data sources (business applications, social media, websites, open sources, financial transactions, surveys, censuses, and digitized hard copies). All the generated data can be potentially utilized for various purposes, from product development and customer experience improvement to monetization. As its economic value keeps increasing, companies collect, analyze, organize, exchange, and sell data — participating in what is called the data economy where data is becoming a key measure of whether a company will remain relevant through the digital revolution.
The Data Economy Framework
Companies from various industries may contribute to the data economy, from telecommunications, retail, manufacture, fitness, automotive, insurance, healthcare, banking, finance, media, pharmaceuticals, travel, and hospitality to government. As published in their report about the rise of the data economy, IBM developed The Data Economy Framework to characterize companies, their roles, capabilities, and overall trends in how they act in the data economy. According to the report, the future marketplace contains Data Producers, Data Custodians, Data Aggregators, Platform Owners, Insight Providers, and Data Presenters. In this framework, Data Producers and Data Presenters are in a position of strength. The strength of Data Producers comes from collecting, accessing, and controlling large amounts of exclusive data. Meanwhile, Data Presenters are in a position of strength due to customer loyalty and content as they provide strong user interfaces, interactive experiences, and data discovery capabilities.
In The Data Economy Framework, the roles of companies are illustrated as a stack of layers from Data Producers at the bottom to Data Presenters at the top. Companies may move in multiple directions within the framework as their strategy: across the layer, up or down the stack, and compress or expand the stack. As they move across a layer, companies gain a bigger portion of the layer by adding material and content to their current capabilities, for example, a company that makes fitness trackers adds sleep monitoring to their abilities to monitor steps and heart rate. When companies move up or down the stack, they take on a new role and capabilities of another layer of the framework, up or down, to gain advantages such as more audience and better customer engagement. GPS device companies in the transportation industry provide an example of this by moving up the stack from Data Producers and Aggregators to Insight Providers. These companies moved from collecting and aggregating data from multiple sources to providing insights, optimizing transportation routes, and improving fuel efficiency. Compressing the stack typically means jumping from Data Presenters layer to Data Producers and continuing to build out data offerings. By performing this movement, companies may use platform ownership to get more data or use the supremacy of data producing to become a Platform Owner. Google and Amazon are two companies that do this.
Data is The New Oil
In 2017, The Economist stated that, “The world’s most valuable resource is no longer oil, but data”. Participating and taking a role in the data economy is essential for companies not only to grow their presence and potential value but also stay relevant in the long run. Even when directly participating within the framework is not feasible, companies might find other methods to move aligned with the framework such as creating and monetizing industry specific data taxonomies. All in all, to succeed in the digital revolution, companies will need to evaluate their organization’s structure, go-to-market approach, and overall corporate identity in the lens of the new data economy.