The $371 Billion Opportunity for “Data Smart” Manufacturers

By: Sanjay Ravi, Worldwide Managing Director for Discrete Manufacturing: High Tech & Electronics, Automotive, Aerospace, and Industrial Industries at Microsoft

The most recent quarterly report from the Manufacturers Alliance for Productivity and Innovation (MAPI), a leading indicator for the manufacturing sector, showed that manufacturing in the U.S will grow faster than the overall U.S economy in 2014 and 2015. Worldwide, projections for the health of the sector vary depending on regional economic trends and policies. Japan’s recent increase in national sales tax, for example, is causing a contraction in manufacturing activity and J.P. Morgan’s global manufacturing PMI report showed a slowdown in other countries in Asia as well. Against this backdrop of variability in the manufacturing sector, one thing remains consistent. Forward-thinking manufacturing organizations are not only finding new ways to automate and create efficiency, they are also focusing on new opportunities for revenue growth. And at the center of their quest for transforming their organizations is data.

Microsoft recently sponsored an IDC study (results in infographic below) to look at companies globally to better understand what actions by “data smart” manufacturing organizations yield the most impactful outcomes—both in terms of growth and efficiency. The research surfaced an eye-popping number of $371 Billion—the potential net value of what we refer to as the “data dividend” over a four year period for the manufacturing sector if companies become data smart and perform some combination of the following four actions: a) bring together even as few as 3-4 discrete data sources, b) use modern analytics tools to glean insights from data, c) surface those insights in a consumable fashion to the right decision makers across the company and d) ensure that insights from data are shared in a timely manner. Manufacturing organizations that take all four of these steps potentially stand to realize a 60 percent greater return on their data assets. The research also revealed that productivity and operations are two areas with the largest data dividend gains.

Big numbers around big opportunities are an abstraction until you see how businesses are making it real. At Microsoft, we’ve been seeing for some time now how our manufacturing customers are making trends such as big data and the Internet of Things actionable for their business today. From smart factories that build a car body every 77 seconds, to heavy equipment manufacturers using the cloud to analyze data for predictive maintenance, to ISVs building new revenue opportunities off the data flood from smart meters, our customers’ “data-smart” strategies are yielding early but impressive returns across the high-value areas identified in the IDC study (employee productivity, operational efficiency, product innovation and better customer engagement models). In doing so, they’re already part of a small but growing band of global data leaders in the manufacturing sector looking to tap the $371 billion data dividend opportunity. 

It’s easy to develop a case of analysis paralysis when it comes to big data—Where to start? What data to collect? Who really needs it? How to deliver insight in a consumable way to the non-data scientists, the business decision makers in your manufacturing organization? For one manufacturing plant, the pressing business issue might be predictive maintenance of their expensive capital assets, for another it might be building smarter supply chains, and for yet another, the driving need to use data might stem from improving efficiencies in their automated production lines. Whatever your business imperative, the right data—big, small, or any other kind—surfaced at the right time and with the right decision maker to drive impactful action is your ticket to a piece of the $371 billion data dividend opportunity that our IDC study identified. Unsure where to start? See how Microsoft’s big data and analytics solutions are helping other customers here.


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