Optimize Manufacturing Operations with Data and AI

June 20, 2024
manufacturing employee going through data

Key Takeaways

  • When manufacturers align their business goals with their data, they gain valuable insight that keeps them agile and at the forefront of their industry.
  • Becoming data-driven consists of three critical components: capturing the data, analyzing the data, and turning the data into actionable insights.
  • When leveraged effectively, data can help manufacturers qualify suppliers, improve production processes, monitor equipment, and increase customer satisfaction.

Manufacturing companies take in massive amounts of data every day, from equipment performance to customer reviews. When measured and leveraged effectively, this information can be a powerful tool to optimize manufacturing operations; however, many manufacturers lack the resources to easily access and analyze their data.

In short, better data drives better business decisions. Creating an environment that allows you to collect, analyze, and turn data into actionable insight requires a digital-first focus.

Capturing the Data

Examples of data that can be collected and analyzed by manufacturers include:

  • Production Data: Quantity and quality of output, scrap and rework rates
  • Machine and Equipment Data: Uptime and downtime, maintenance schedules, performance
  • Supply Chain Data: Supplier performance, lead times, delivery times
  • Inventory Data: Inventory levels, turnover rates, stockouts
  • Financial Data: Revenue, cost of goods sold, gross profit margins, operating expenses

You can collect all the data in the world, but to gain actionable insight from your data, you must identify the most valuable key performance indicators (KPIs) for your manufacturing company. These KPIs will differ between departments and may include:

  • Finance: net operating profit, liquidity ratio, return on asset reports
  • Human Resources: turnover, compensation, time to fill positions
  • Production: cycle time, production yield, customer return rate

At the end of the day, your KPIs should be driven by your strategic objectives. For this reason, company leadership must be at the helm any time there is a data and technology initiative.

Analyzing the Data

Disparate systems create data silos. By pulling and centralizing data into a data warehouse, all the information you collect, including sales, accounting, and inventory data, is synthesized into a single source of truth that every department can access. This eliminates data silos and results in more accurate reporting.

Data analysis then takes the information from your data warehouse and uses computational algorithms, including artificial intelligence (AI), to identify problems. Visualizations of the data help you understand the current state of your organization and lead your team to action.

  • Generative AI has transformed manufacturing operations, reducing costs through automation and predictive maintenance, increasing operational efficiency, and enhancing quality control in real-time.

Using the Data

After collecting your data and organizing it into something everyone can understand, it’s time to turn insight into action. Consider a consumer goods manufacturer operating in a highly competitive landscape. They want to increase production capacity and reduce production costs as part of their strategic operating plan for the upcoming year.

By looking at production data such as OEE, machine downtime, cycle time, and production yield, leaders can identify bottlenecks that slow production down and limit capacity. They can dive into supply chain data such as performance, lead times, delivery times, and material cost to explore ways to increase efficiency in their processes. With the help of AI, they can use predictive analytics and what-if scenarios to gain insight into different courses of action.

These actions may include:

  • Investing in new equipment that is faster and more efficient.
  • Optimizing their supply chain by standardizing their processes, diversifying their network, and negotiating a better price with suppliers.
  • Automating tedious and manual processes so employees can engage in higher-value work.
  • Reducing waste and increasing recyclables.
  • Changing their Electronic Data Interchange (EDI) from a price-per-document model to a license-based model.

Becoming a Data-Driven Manufacturer

When manufacturers align their business goals with their data, they gain valuable insight that keeps them agile and at the forefront of their industry. But becoming data-driven starts with strategy. It’s time review your data strategy if:

  • Your organization has no defined data strategy.
  • It has been more than five years since you updated your data strategy or reviewed your data points for vulnerabilities.
  • There has been a change in leadership at your organization, particularly in financial, operating, or technology roles.
  • You have merger and acquisition activity at your organization.
  • You are looking to make investments in technology and analytics.

Your data strategy must be unique to your business. Eide Bailly’s experienced data professionals can help define your key goals and objectives, organize your data for actionable insight, and take your manufacturing business to the next level.

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About the Author(s)

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Adam Hanel

Adam leverages his experience with systems and network management specifically related to business office functions to help clients identify and implement the changes necessary to achieve their goals.