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Why You May Want a Data-Driven Manufacturing Culture

By Tom Weber

March 22, 2021

Connected devices are everywhere today. The manufacturing community may not have transformed as quickly as others, but it is one more place you can find connected and smart devices. The key to thriving, though, is creating a data-driven manufacturing culture that takes full advantage of all available data.

Here are some reasons and benefits. In a data-driven manufacturing culture, the firm leverages the breadth of data available from new technologies such as the Industrial Internet of Things (IIoT), automation, artificial intelligence, or other digitization tools.

There are many advantages to a data-driven culture. First, decisions are made based on fact. Rather than relying on hunches or “how things have always been done,” a firm can use real-time information—often in conjunction with predictive forecasting and historical data. With data driving decisions, a firm can efficiently identify potential risks and new opportunities and achieve better results.

Added benefits include:

  • Reduced machine downtime from enabling predictive maintenance;
  • Increased production capacity;
  • Lower material consumption;
  • Greater receptiveness to consumer demand; and
  • Improved ability to customize products.

The challenge can be in creating the data-driven manufacturing culture.

How to Create a Data-Driven Manufacturing Culture

1. Identify Assets

In digital manufacturing, there are more assets available. On top of the factories or buildings and machinery and equipment, along with intangible assets such as patents, copyright, and licenses, there are now digital assets from industrial applications, digitally optimized processes (such as ERP, CRM), and edge and cloud computing.

To achieve the productivity and profitability gains possible in a data-driven manufacturing culture, the firm needs to clearly define all of its assets and put plans and processes into place to identify and dispense with data bottlenecks.


2. Break Down Silos

Sharing data across the manufacturing organization streamlines processes and helps ensure that every team at the firm is pulling in the same direction—and able to understand why.

Develop your capabilities (software and human) to gather, merge, manage, and analyze the big data stored throughout the manufacturing firm. If procurement and production, for instance, aren’t sharing data, you can’t improve their decision-making.

Don’t expect your humans to be able to get the most out of big data without the aid of advanced analytics. For instance, with artificial intelligence and analytics doing the heavy data lifting, a company might analyze profit-per-hour factoring in as many as 1,000 variables and 10,000 constraints to help manufacturers figure out what to buy, what to make, and how they should make it, to yield the most profit in each period.

Fun fact: The digital universe is doubling in size every two years. By this year, the data we create and copy annually was expected to reach 44 trillion gigabytes, according to IDC.

3. Train Humans Better

When a manufacturing firm adds more technology and demands greater interoperability, it creates a more complicated ecosystem. The humans already need to understand how to operate, troubleshoot, and monitor machines and the related technology. Now they also need to be trained on the process of data sharing and learn how the entire plant can function better by embracing this new interconnectedness. For example, valve manufacturer Richards Industrials achieved a 40% increase in productivity within six months of integrating its shop-floor management software.

By showing employees how to test and measure data, and helping them to understand its importance, you help get them invested in the data-driven culture.

4. Lead Intelligently

While demonstrating empathy for those who find change challenging and are nostalgic for the “old ways,” leadership needs to prioritize developing an understanding around the value of smart devices, data analysis, and digital transformation. Leaders must know that the results are only as good as the decision-makers themselves.

This also can’t be an IT-team-only initiative. Heads of every business unit need to understand the use of big data and educate their teams about the importance of effective data security and data management.

5. Encourage Experimentation

Data analysis should be directed at problem-solving, process improvement, and profit generation. Yet it can help to encourage people throughout the firm to experiment with the data. You may get a fresh perspective on processes or business challenges.

Establishing a data-driven culture as a priority can improve buy-in to the initiative while also leading to improved production rates, lower costs, reduced downtime, and greater employee satisfaction along the way.

PortraitTom Weber is president of WeberSource LLC and is AICC’s folding carton and rigid box technical advisor. Contact Tom directly at