21 October 2021


The State of Data Science in Manufacturing in 2021

Earlier this year, we published Accelerate Your Data-Driven Transformation, a commissioned study conducted by Forrester Consulting on behalf of RapidMiner. The study explored the impact that data science initiatives like advanced analytics, machine learning, and artificial intelligence have had on organizations in a variety of industries. The study surveyed business executives tasked with leading their organization’s digital transformation to find out how they’ve thought about data science in the past, what’s happening now, and what they expect in the future.

Although the aggregate results across industries are interesting—especially the observation that getting more models into production earlier results in greater ROI long-term (see page 4 of the study)—the manufacturing leaders that we surveyed had some unique perspectives.

Because manufacturing has seen an increased use of data science tools as part of the Industry 4.0 revolution, it’s not surprising that manufacturers have a different take on the impact that data science is having on their industry. If you’re in manufacturing, the results below can help you better understand how your industry leaders—and your potential competitors—are thinking about data science initiatives like advanced analytics, artificial intelligence, and machine learning.

If you’d like to compare the manufacturing numbers that we discuss below to the results across all industries—and discover additional insights about how to deliver successful results through your data science initiatives—you can download the full study here: Accelerate Your Data-Driven Transformation.

Let’s dive in and look at places where manufacturers stood out from other industries on some of the key issues explored in this study.

Data Science is a Powerful Driver of Competitiveness and Investment in Manufacturing

A clear trend across all industries, but especially in manufacturing, was that respondents viewed data science as both critical for the competitiveness of their organization and as a primary investment area (see page 3 of the study). And in manufacturing, there has been substantial growth in both how important data science is to competitiveness, as well as the amount of investment in data science.

2-3 years ago, only 47% of manufacturing respondents said that data science initiatives were among the most important factors in the competitiveness of their organization. Today, 83% put these technologies in that category, and that percentage grows to 87% when respondents were asked to look 2-3 years down the road.

And manufacturers are putting their money where their mouth is. Only 2% of manufacturing respondents said that AI, ML, and AA initiatives were their single most important investment area 2-3 years ago, whereas today, 24% think it’s the most important investment area. In the next 2-3 years, the majority (56%) expect it be their most important investment area.

The Industry 4.0 movement is clearly convincing manufacturers of the importance of AI and ML for long-term competitiveness, and this sentiment is only going to grow in the coming years.

Data Science Initiatives Deliver ROI for Manufacturers

One trend we saw across all of the industries surveyed is that those who adopted AI and ML earlier are seeing greater ROI today, and expect that ROI to grow to even greater levels in 2-3 years (see page 4 of the study for details). Given that manufacturers have only recently started investing in AI and ML, we wondered what manufacturers would think about the potential ROI from advanced analytics, machine learning, and data science initiatives.

It’s clear that, 2-3 years ago, those in manufacturing weren’t expecting data science and machine learning to do much for their bottom line. Back then, only 2% of manufacturers expected a 5x-10x ROI on their investment in AI and ML, and 9% expected less than 1x ROI. Compare that to respondents from financial services, where 14% expected 5x-10x ROI just a few years ago.

Today, manufacturers’ expectations for value have caught up to other industries, with all respondents expecting at least 1x-2x ROI, and with 33% expecting 5x-10x ROI—a number that’s comparable to the average across all survey responses.

When looking to the future, however, manufacturers are again underestimating the impact that data science could have when compared to the expectations in other industries. Only 7% of manufacturers surveyed thought that their data science initiatives would have >10x ROI in the next 2-3 years—compare that to 22% for financial services, and 15% across all industries.

In some ways, this might reflect realistic expectations driven by relatively late investments. As we saw in the study, earlier adoption of data science leads to greater ROI today and greater ROI expectations in the future. Because manufacturers started relatively late, it’s possible that their estimates are in line with reality. However, with the accelerating pace of Industry 4.0 technology adoption, as well as the speed with which data science tools are maturing, it’s certainly possible that manufacturers are going to see far greater ROI in the near future than they’re estimating.

Model Operations Key for Manufacturers

One additional place where manufacturers stood out from other industries was in terms of model operations.

In financial services, when asked about how valuable various features of data science platforms would be for their organization, 56% of respondents in financial services said that model deployment and monitoring capabilities would be very valuable, while 31% said extremely valuable. Compare that to manufacturing, where the situation is reversed: 29% said ModelOps capabilities would be very valuable and 47% said extremely valuable.

From these responses, it appears that manufacturers, despite starting to invest in data science initiatives relatively late, have quickly come to understand the importance of effective ModelOps solutions as part of an overall data science program. They’re putting more emphasis on that feature when it comes to thinking about possible tools and platforms than those in some other industries.

Wrapping up

It’s clear from the above that data science is having a profound impact on the manufacturing industry. The responses from executives give a sense of how manufacturing leaders are thinking about data science initiatives today, and what they expect in the next 2-3 years.

If you’d like to take a look at the full study across all industries, you can download your copy of  Accelerate Your Data-Driven Transformation today.

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