According to a recent CIO article, the global data analytics market will grow to $549.7 billion by 2028. As this growth occurs,, enterprises should be prepared for a few key industry trends, including: 

Supply Chain Visibility 

You don’t have to closely follow the logistics industry to be aware of the recent global supply chain challenges. With ships waiting for weeks at a time to enter ports, containers piled up awaiting shipment at distribution centers, and shelves often empty in retail locations, it’s clear that the supply chain is under enormous pressure. It’s also evident that companies need greater visibility into the multiple levels of their supply chains to successfully navigate these challenges. Throughout 2022 and beyond, expect organizations to tap artificial intelligence (AI) and machine learning (ML) for supply chain analytics, enabling them to predict price indices, identify areas of weakness, and get ahead of potential supply and demand issues. 

Assigning Real Value to Data

When chief data officers are able to monetize or productize their data in some way, they are significantly more successful in their role. The CIO piece cites a Gartner® study that found chief data officers (CDOs) were 3.5 times more likely to achieve success when they met data monetization goals, compared to 1.7 times more likely when they demonstrated return on investment (ROI) on their BI or analytics investments. 

What’s more, the study also suggested that organizations that commercialize their data are more valued by investors, with the value of a company’s data becoming a key part of merger and acquisition (M&A) activity. Assigning value to data isn’t just about driving revenue or selling the data. iit’s also about determining how to incorporate data into existing products or services as well as whether and how to leverage it internally to generate positive business outcomes for the organization. 

Sustainability is Key 

According to a 2020 report, awareness of environmental, social and governance (ESG) issues are on the rise with 88 percent of publicly traded companies having an ESG strategy in place. There are numerous ways in which AI and analytics can help companies in their sustainability efforts, including the use of simulation and digital twins. In a manufacturing setting, for example, digital twins can monitor operations, identify potential waste, and allow the company to use that wase product elsewhere in its factory. You can read more about how analytics and related technologies can aid in ESG initiatives in this previous APEX of Innovation post.

For more on the above three trends and how they will impact the data analytics industry in the coming years, head over to CIO.