MLC Research

MLC Research

Survey: Data Mastery is Slow to Mature but Essential

Manufacturers show some progress with data mastery efforts, but much opportunity for growth exists.   

When MLC last fielded its Data Mastery survey in 2021, senior content director Penelope Brown wrote of the results, “Manufacturing data mastery is in its tween years for most enterprises – certainly past its infancy, but still awkward and gawky and not quite fully formed.

If data mastery was a tween then, the effort is on the final stages before becoming a teenager now. Like a tween, there has been some maturation but also some regression in how companies are accessing and using data and analytics. Likewise, companies can see dramatic development in specific areas of data utilization, but each organization seems to mature at its own pace while encountering a wide array of challenges and pursuing various desired outcomes and focus areas.

Why is progress slow? To further the tween metaphor: perhaps it is growing pains. More than one-third of respondents tell us that the volume of data they’re collecting has at least doubled. Nearly 20% say the amount of data has at least tripled. Before this exponential growth came into play, companies were already dealing with an uphill climb to verify and analyze data. Given this rapid growth – like in tween years – there’s bound to be some awkwardness and slower progress.

Still, it is clear from the 2023 MLC Data Mastery and Analytics survey that mastering manufacturing data will be essential to future competitiveness. Presently, 91.1% of respondents report that data has allowed for more accurate or timely decisions, both of which are essential to overcome the pressures that businesses face now and those they will face as their data mastery skills continue to mature.

Read on for key findings and selected graphs from the 2023 Data Mastery and Analytics survey.

Part 1: Data Strategy and Governance


The majority of respondents have a formal data plan and guidelines in place, but there has been little change since the last time we fielded this survey in 2021. Currently, 56.5% of respondents say they have a corporate-wide plan, strategy, or formal guidelines for how data is collected and organized. This number sat at 55% in 2021.

Q: Does your company have a corporate-wide plan, strategy, or formal guidelines for how data is collected and organized across the enterprise, including manufacturing operations? (select one)

For those with a formal corporate-wide data strategy, nearly all (90.5%) see at least some alignment to overall business strategy, but only 52.4% say it aligns entirely or very closely.

Q: If your company has a corporate-wide plan, strategy, or formal guideline for how data is collected and organized, how closely do you feel this data strategy is aligned to your company’s overall business strategy? (select one)


Measuring data’s value is still elusive to many organizations. However, there’s been increases in assigning monetary value and measuring revenues of data-driven services in the past two years. In fact, 22.6% of respondents now say they measure the value of data in monetary terms compared to 4% in 2021. Meanwhile, 12.1% say they measure data’s value by revenues of data-driven services compared to 3% in 2021.

Q: How do you measure the value of the data in your organization? (select all that apply)


Manufacturers see a slight positive shift in their ability to collect the right data the business needs. In 2021, 16% of survey respondents ranked their company as highly able to collect the right data. In the latest survey, that number has climbed over 20%. On the low end of the spectrum there was only minimal change moving from 26% in 2021 to 26.8% in 2023.

Q: How would you rank your company’s ability to collect the right data the business needs from your manufacturing operations? (select one)


Part 2: Data Collection, Use, and Analysis 


The ability to analyze manufacturing operations data is an opportunity for growth. Just over half of respondents report their company is moderately able to analyze the data, while 30.4% say they have low competency.

Q: How would you rank your company’s ability to analyze the data from your manufacturing operations? (select one)


Shop floor systems and ERPs remain the primary data sources. In fact, shop floor systems use increased from 79% in 2021 to 88.4% in 2023, while ERP systems increased from 77% in 2021 to 83.9% in 2023. Quality control systems, equipment maintenance systems, supply chain systems, and robotics systems saw similar increases since the previous survey, but product development systems fell 16 percentage points to 22.3%.

Q: What are the primary systems that generate your manufacturing data today? (select all that apply)


The survey revealed that there is considerable room for growth in real-time data collection. Less than half of respondents report their company’s data is comprised of 51% or more real-time or near real time data.

Q: What proportion of the data you collect today is real-time or near real time, not batch or historical? (select one)


In the past two years, companies are collecting more manufacturing data. Eighty percent report they’ve seen at least some increase in the amount of data collected. Meanwhile, more than one-third of respondents say the amount of data has at least doubled in that time.

Q: What has been the percentage increase in the amount of manufacturing data you are now collecting compared to two years ago? (select one)


Looking ahead at the operational focus for data projects in two years, respondents foresee a varying shift from manufacture, quality, maintenance, inventory, logistics, and assembly to process control, supply chain, track and trace, inspection, security/data protection, and tooling.

Q: What are your primary areas of operational focus for data projects today and what do you expect the primary focus will be in 2 years’ time? (select top three)  


Microsoft Excel remains the reigning champion of data analysis tools. In 2021, 71% of survey respondents reported that Excel was in their data analysis toolkit. That number rose slightly in 2023 to 72.3%. Statistical analysis programs of standard BI systems jumped from 47% in 2021 to 60.7% in 2023. This moved it from the fourth most used tool in 2021 to second place this year. Meanwhile, manufacturers are increasingly outsourcing analytics, with 24.1% utilizing external analytics partners this year compared to 14% in 2021. Somewhat surprising, the use of AI systems has decreased from 48% (when taking in-house, cloud and external AI partners in aggregate) to 41% in 2023.

Q: What systems do you use to analyze the manufacturing data you collect? (select all that apply)

Respondents’ companies are evenly split when asked about verifying the accuracy and quality of raw data. About 46% report they have a process while approximately 45% say they do not. In the 2021 survey, for comparison, 49% reported they had a process while 46% reported they did not.

Q: Does your company have a process to verify the accuracy and/or quality of the raw data before decisions are made on it? (select one)  


Part 3: Outcomes and Challenges


Increased data access has resulted in a variety of operational improvements. Leading the charge are cost reductions, productivity improvements, efficiency, quality, and uptime – all of which were cited as an improvement seen by 50% or more of survey respondents.

Q: In what ways has increased access to manufacturing data helped you to improve your manufacturing operations? (select all that apply)


Cost reductions are the primary motivator for new manufacturing data projects now, and this is expected to remain constant in two years. In fact, 65% of 2021 survey respondents anticipated that reduced costs would be a key business outcome objective this time around – a number that tracks closely with the 67.6% that listed reduced costs on this year’s survey. While reduce costs is anticipated to lead the charge again in 2025, the number is anticipated to decrease by 10 percentage points in that time. The biggest upward movers by 2025 are expected to be improved production speed, integrated processes, improved supplier network effectiveness, improved security, and monetizing data.

Q: What are your key business outcome objectives for embarking on new manufacturing data projects today and what do you expect the outcome objectives will be in 2 years’ time? (select top three)  


Data improves accuracy and speed of decisions. Half report that decisions have been more accurate and 40% point to more timely decisions. Only 6.3% of respondents report that there has been no change in their company’s decision-making because of data availability, while less than 2% of respondents, respectively, cite slower or worse decisions as the most prevalent way that data has affected their decisions.

Q: What is the most prevalent way that data has affected your company’s decision-making? (select one)


Survey respondents report that many challenges or obstacles are hindering their company from making more data-driven decisions. The leading challenges – each cited by 39-49% of respondents – are extracting data from legacy systems, lack of skills to analyze data effectively, and integration of data from different sources.

Q: What are the most important challenges or obstacles hindering your organization from making more data-driven decisions? (select top three)


Three out of four respondents report that data mastery is essential to their business competitiveness in the future. This 75%/25% split remains consistent with responses to the 2021 survey.

Q: Looking forward, how important will mastering manufacturing data become to your competitiveness as a future business? (select one)


About the author:

Jeff Puma is Content Director for the Manufacturing Leadership Council

Survey development was led by the MLC editorial team with input from the MLC’s Board of Governors.

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