"Despite generally high levels of economic confidence, U.S. middle market manufacturing leaders are dealing with high inflation and continue to worry about a potential recession… Only half of manufacturers believe they are fully prepared to respond to new disruptions arising from these economic circumstances" (National Center for the Middle Market and Chubb, 2023, pg. 9).

Mixed Economic Indicators for Manufacturing

Q1 2023’s manufacturing economic indicators continue to send mixed signals.

Despite stable industrial production, steady hiring (Manufacturer’s Alliance, 2023), and 58% of mid-market companies projecting year-over-year growth in 2023 (National Center for the Middle Market et al, 2023), manufacturers contend with a contractionary PMI® (47.8% as of Feb 2023, Trading Economics, 2023), rising production costs, raw materials inventories, and a stubbornly elevated CPI.

In an uncertain, complex time, data visibility becomes a critical means of oversight and control. Data intelligence provides leaders with the insight they need to mitigate risks and control costs, while simultaneously aligning teams to the value creation plan, increasing employee retention, and boosting overall company valuation

Despite these noted benefits, there is a sizeable gap between companies’ data investments and their ability to establish data cultures. NewVantage’s 2023 Big Data and AI Executive Survey shows that while 93.9% of organizations are increasing their data investments, only 20.6% have a data culture (NewVantage, 2023).

Why the gap?

It comes down to the execution of their data strategy.

Over the past 12 years, we’ve worked extensively with mid-market manufacturers to develop their data infrastructure and reporting. Below, we’ve shared a few case studies, sample metrics, and dashboard examples that demonstrate how manufacturers leverage data for operational excellence, effectively closing the execution gap and supporting a data culture.

Jump to a report example:

Case Study #1 - Manufacturing Operations Reporting Portfolio

This manufacturer ($150+M) services multiple industries through a wide range of product lines. With seven separate manufacturing and finishing facilities, they are a logistically complex operation. They engaged Blue Margin to:

  • Move KPI metric tracking across plants, business units, geography, and transactional systems out of spreadsheets
  • Align executive team, managers, and operators on strategic priorities
  • Operationalize and track priorities rather than make ad-hoc adjustments
  • Surface and track the metrics, ratios, and initiatives critical to the bottom line.

In support of these goals, we created the following portfolio of reports:

Manufacturing Business Unit Summary Report

Management wanted a unified approach to monitor and compare performance by business unit and plant. This report compares key metrics of bookings, shipments and on-time delivery (OTD) across time for each business unit. 

Business Unity Summary-1

Labor Utilization

Companies that regularly track employee labor hours and output produce insights that inform process improvements and HR decisions, such as job changes or additional training. Within a healthy organizational culture, tracking employee utilization fosters accountability and productivity, driving bottom-line growth. (For more information on data’s impact on team culture, listen to our interview with an organizational change expert or this podcast on how we embraced data transparency at Blue Margin.)

In this report, Employee Utilization is shown by various dimensions with detail down to the employee level.

Employee Utilization

Production Efficiency

Visibility into the performance of individual machines and facilities enables manufacturing leaders to quickly identify concerning trends and prevent costly delays by reallocating resources and/or adjusting production strategies to meet changing demand.

This Production Efficiency report shows a calendar view of production efficiency and highlights top- and bottom-performing facilities.

Production Efficiency-1

Sales Rep Scorecard

For a comprehensive view into sales performance, manufacturers need to see details on their sales pipeline, quote cycle, quotes won/lost, and performance by individual sales reps. Quote cycle data helps inform process adjustments to increase conversion rates (and ultimately revenue) while insight into individual sales reps’ quotes won/lost and revenue generation surfaces opportunities to recognize top performers or provide targeted coaching to increase overall team productivity.

This Sales Rep Scorecard visualizes metrics for expected revenue, total quotes, quotes won/lost, and quote summaries by business unit, plant, market, industry, territory, rep, and customer.

Sales Rep Scorecard-1

Case Study #2 - Material Margin Analysis 

A North American manufacturer ($180+ MM) with four US-based plants and warehouses in the midst of rapid expansion needed a unified business intelligence solution. Their key data source was Oracle E-Business Suite, and they faced the following issues:

  • No real-time view of commodity material costs and impact against material margin and gross profitability.
  • No insight into margins at the part level and uncertainty of when/how to adjust pricing.
  • Their P&L couldn’t offer timely visibility to assess current performance versus prior periods.

Material Margin Analysis

The Material Margin Analysis report displays historical trends for material margins, analysis of changed costs based on CDI index, and the ability to filter large data sets by date ranges, markets, customers, parts, and material types.

Additionally, the margin analysis price calculator allows for a what-if analysis of impact on margins. Users change prices using sliders to observe impacts on GP or MM.

MMA Price Calculator

Case Study #3 - Shop Loading 

During a design project, a North American ($100M) circuit board manufacturer identified shop loading as an area of immediate opportunity for BI reporting. Increased visibility would allow leaders to closely monitor their production process, identify and resolve bottlenecks, and improve yields.

Blue Margin engaged with their IT team and warehouse leadership to wireframe and rapidly develop a report that improved visibility into shop load by different priority categories.​

With better visibility, production schedules could be adjusted to minimize downtime, reduce material waste, and maximize output. Additionally, analyzing shop load by priority category allowed them to prioritize orders, manage short-term fluctuations in demand, and better allocate resources.

Shop Loading-1

Business Intelligence for Middle Market Manufacturers

Manufacturers looking accelerate value creation and digital transformation don’t have to (and shouldn’t) jump straight to prescriptive analytics for results. BI lays the foundation for advanced ML and AI opportunities, and as the examples above illustrate, allows for deeper insight into operations, the analysis of vast amounts of data, identification of trends in customer behavior, optimization of pricing models, and streamlined production.

Ultimately, by leveraging business intelligence for growth strategies, manufacturers get a leg up in today's increasingly competitive market. 

For Further Reading

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Katie Johnson and Suzanne Rains

Written by Katie Johnson and Suzanne Rains

Katie Johnson is Blue Margin’s marketing manager. With a degree in human development, Katie is a student of the connection between data insights and the people who use them. She has a gift for making complex ideas accessible and brings her aptitude for process design to every conversation. Suzanne Rains is a communications specialist at Blue Margin Inc. With a MA in Human Resources and BAs in Marketing and Management, Suzanne unites an understanding of human nature and a keen interest in industry research to author thought leadership articles for today’s business leaders.