Data Lakes for Packaging OEMs – How to Maximize Aftermarket Opportunities?

Packaging and processing companies are always looking for innovative ways to maximize aftermarket opportunities. One such innovation is the utilization of data lakes. A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. This approach is instrumental in creating a unified source of truth, which is crucial for deriving actionable insights and enhancing business operations. This blog will explore how data lakes for packaging equipment manufacturers can help in creating a single source of truth? And how it can unlock significant aftermarket potential. The primary reference source for this blog is the very well-researched Transforming Packaging Industry report done by PMMI.org

Current Data Management Challenges in the Packaging OEM Industry

Managing operational data in the packaging industry is a complex and varied process. Companies employ a wide range of methods, from manually entering data into spreadsheets and uploading them to the cloud, to leveraging advanced analytics. On-site data is often managed using systems like warehouse management systems (WMS), enterprise resource planning (ERP), and material requirements planning (MRP). Solutions such as SAP, Siemens, MVI, PowerBI, Microsoft SharePoint, MasterControl, DataBricks, and SolidWorks are commonly used for external data storage and analytics. Many companies also rely on external maintenance and support to ensure proper data storage and management. Interestingly, data management practices can differ even within the same organization. As one end-user noted in a recently done survey of the packaging industry manufacturers by pmmi.org, data is often “separately managed for each division.”

How is the Packaging Industry using its data?

What is the need of Data Lakes for the Packaging OEM industry?

One of the major insights from the PMMI report for the Packaging industry is that the industry understands the value of data management, but is only able to partially execute it most effectively. The report quotes one of the users saying “We are good at collecting, not so good at using,”. This is because of the absence of a Single source of truth when it comes to their Installed Base Data. Single Source of truth is a basic element to drive the Digital transformation. This is where Data lakes in the packaging industry come into the picture.

Source: PMMI Report on OEM_2024 Transforming Packaging And Processing Operations

Understanding Data Lakes

A data lake is a system or repository of data stored in its raw form, typically blobs or files. It includes a wide variety of data, such as customer information, equipment details, warranty records, maintenance contracts, and service records. Unlike traditional databases, data lakes are designed to handle high volumes of diverse data types. This flexibility is particularly beneficial for the packaging and processing industry, where data originates from multiple sources, including CRM, ERP, and Field Service Management systems. By integrating all this data into a single repository, what we call a “Single Source of Truth”, companies can perform comprehensive analyses and derive valuable insights to drive their aftermarket strategies.

Benefits of Data Lakes for Packaging and Processing OEM Industry

The adoption of data lakes enables organizations to create a Single Source of Truth. This offers numerous benefits for packaging and processing companies. Firstly, it enhances data accuracy and quality by consolidating information from disparate sources into a single, clean, de-duped dataset. This unified view is essential for identifying and capitalizing on aftermarket opportunities. Secondly, data lakes improve visibility into equipment performance and customer behavior, enabling proactive maintenance and targeted marketing efforts. Lastly, the streamlined data management processes reduce operational inefficiencies and support better decision-making across the organization.

Steps to Implement Data Lakes for Packaging OEM Industry for Aftermarket Opportunities

1. Assess Your Data Needs

Start by identifying the types of data you need to consolidate. This includes customer records, equipment details, warranty information, maintenance contracts, and service logs. Determine the sources of this data, such as CRM, ERP, and Field Service Management systems. Understanding your data requirements is crucial for designing an effective data lake that meets your business needs.

2. Choose the Right Technology

Selecting the right technology is vital for the success of your data lake. Consider solutions that offer robust data integration, storage, and analytics capabilities. Popular technologies in the industry include Hadoop, Amazon S3, and Microsoft Azure. These platforms provide scalable and flexible solutions that can handle the diverse data types and volumes typical of the packaging and processing industry.

3. Data Integration and Cleaning

Integrating data from multiple sources involves extracting, transforming, and loading (ETL) processes. This step is critical for ensuring data quality and accuracy. Employ data cleaning techniques to remove duplicates, correct errors, and standardize formats. Clean, de-duped data forms the foundation of a reliable data lake, enabling precise analysis and actionable insights.

4. Leverage Advanced Analytics

Once your data lake is set up, leverage advanced analytics to uncover aftermarket opportunities. Use predictive analytics and machine learning models to analyze customer behavior, predict equipment failures, and identify potential maintenance needs. These insights enable you to address issues and offer targeted aftermarket products and services proactively.

5. Ensure Data Security and Compliance

Data security and compliance are paramount when managing large volumes of sensitive information. Implement robust security measures to protect your data lake from unauthorized access and breaches. Adhere to industry regulations and best practices to ensure compliance and safeguard your data assets.

Maximizing aftermarket opportunities in the packaging and processing industry requires a strategic approach to data management. By implementing a data lake for the packaging OEM industry, companies can consolidate their data into a single, unified repository, enabling comprehensive analysis and actionable insights. This not only improves data accuracy and visibility but also supports proactive maintenance and targeted marketing efforts. As a result, companies can enhance their operational efficiency and drive significant growth in their aftermarket business.

Are you ready to transform your packaging and processing operations? Discover how Entytle’s Installed Base Intelligence Platform can help you create a Single Source of truth by implementing a data lake and unlocking new aftermarket opportunities. Contact us today for a consultation or demo and take the first step towards a data-driven future.