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Customer Story

Malnove Packages Its Data to Get A Better View into Its Packaging Business

Company Overview

Malnove is a privately owned, family run, manufacturer of custom folding carton solutions serving the U.S., Caribbean, Mexico, and Canada from strategically located regional facilities.

Problem: Reliance on Manual, Outdated Reporting

Malnove lacked an up-to-date, standardized approach to reporting and analytics particularly around its manufacturing processes. The company was relying on outdated methods and tools—such as pasting daily scorecards on the wall on the manufacturing plant floor—for consolidating and distributing information. As a result, Malnove was unable to analyze and make decisions based on key metrics such as: the volume of manufacturing output, the status of safety incidents, trends around labor rate and overtime work, maintenance issues, and causes of manufacturing downtime.

Malnove wanted to automate reporting and enhance its analytics abilities so it could make informed decisions in order to maximize output and increase efficiency of its manufacturing processes.

Solution: Analytics Provide Views that Show the Full Picture of Operations

Analytics8 conducted a strategic data and analytics assessment, which included interviews with business users to identify their daily processes and understand how they were currently utilizing their data. From that assessment, we developed a solution including a data warehouse to consolidate disparate source data into a centralized repository that is optimized for enterprise reporting.

From there, we worked with key stakeholders including executives and plant managers to understand their needs and developed a comprehensive manufacturing analytics solution using Power BI that enables more timely and user-friendly access to information. The analytics solution we developed includes a suite of dashboards such as:

  • A manufacturing overview dashboard that provides an executive-level glimpse into six of the most important KPIs including sales per day, sheets per day, total labor rate, spoilage, and days since last safety incident.
  • A manufacturing productivity dashboard that provides a huge step forward for Malnove in terms of modernization and rapid decision making. It replaces a previously manual, paper-based process that involved posting a scorecard on the wall of the plant. The modernized manufacturing productivity scorecard allows for analysis of 12+ key performance indicators across the four departments involved in the printing process.
  • A plant performance and machine performance Power BI dashboard that allows executives and plant managers to monitor and analyze across metrics such as downtime percentage, runtime percentage, and run speed at the plant level.

Results: Better Information Leads to Better Decision Making and Increased Efficiencies

Instead of manually consolidating data from disparate systems and generating manual or physical reporting, the solution allows Malnove to focus on making better decisions and maximizing output and efficiency of its manufacturing processes. The analytics solution we developed allows Malnove to:

  • Better understand the health of the business and easily identify anomalies, outliers, and potential issues so it can escalate them quickly and take action. With the ability to quickly see issues and act on them, Malnove has realized increases in output, revenue, safety, customer satisfaction, and decreased labor costs.
  • Improve manufacturing productivity by getting insights into sheets per day, labor rate, run rate, and printing spoilage. By analyzing these metrics, the company was able to decrease manufacturing downtime and reduce the cost of printing waste, in turn increasing manufacturing output and customer satisfaction.
  • Measure plant and machine performance by analyzing trends over time and dig deeper into the individual machine level. This allows the company to proactively identify machine maintenance issues before they become real problems.

Armed with the new dashboards, Malnove can focus its attention on increased productivity, better decide which plants to allocate resources toward, and proactively address concerns that can cause downtime.

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