Contributing writer Jorge Izquierdo is the VP of market development for PMMI, The Association for Packaging and Processing Technologies.

In an era dominated by digital transformation, the packaging and processing industries increasingly rely on big data to streamline operations and enhance efficiency. Central to this revolution is the concept of the “data lake” — a vast, dynamic repository that stores and secures colossal amounts of raw data. PMMI’s recent white paper, Transforming Packaging and Processing Operations, offers a deep dive into the challenges and opportunities associated with data lakes, revealing how industry leaders leverage this resource to gain a competitive edge. 

Understanding the data lake 

A data lake serves as a central point where businesses can store unstructured data across various sources until needed. One of the unique features of data lakes — and this distinguishes them from data warehouses — is that they are not schema-in. This means they can take in raw data in its native format without changing any of the data attributes from the source. They only apply schema to the data on the actionable side of the data lake once it has been processed for analytics, making it schema-out. Data warehouses, on the other hand, are schema-in, meaning the data must be structured before coming in. 

Data lakes are helping manufacturers solve concrete problems. With the schema-out structure of data lakes, manufacturers organize what information they need when they need it. This flexibility makes it an invaluable tool for machine learning, analytics and real-time reporting, helping companies react swiftly to market changes and internal demands. On the other hand, manufacturers must define their data needs with a schema-in structure before using it. And in most cases, they only end up using a fraction of the data. 

The packaging and processing industry is increasingly seeing the potential value of data as an asset. It is being used to measure and enhance business performance and operations, with applications including: 

– Measuring performance and downtime

– Developing and tracking KPIs 

– Driving operational improvements 

– Performance opportunities 

– Analyzing equipment 

– Processing performance vs. expectations 

– Tracking quality and production metrics 

– Analyzing business operations 

– Driving, planning, safety, BOMs, specs and operations improvements

For example, a quality problem — whether it is food contamination or a delivery that doesn’t meet specifications — can mean a dreaded slog through uncontextualized (or even paper) data to find out what happened. Moving to a data lake turns this process into a much simpler query that can be done in minutes. Proactively creating traceability reports means that manufacturers can quickly identify the underlying issue and pinpoint just the affected units, keeping products on the shelves and ultimately protecting consumers and the bottom line. 

Finally, predictive maintenance is often considered the pinnacle of data-driven manufacturing. According to another report by PMMI, Trends in Remote Monitoring, the ability to use predictive maintenance was seen as either somewhat or very important by 83% of end-users. Reduced machine downtime is a major factor in end-users specifically investing in predictive and preventive maintenance, with 92% of end-users citing machine downtime as a very or somewhat important factor. Data is the foundation and requires a combination of people, process and technology expertise. Without enough data and the right data architecture, it will remain elusive. 

Data lakes are the foundation to process and analyze immense amounts of sensor data in real time and then visualize it to enable pattern recognition. This opens the door to testing and training machine learning models on historical sensor data to identify the precursors to machine failure. As manufacturers and their technology partners fine-tune these models, they become increasingly adept at predicting machine failure far enough in advance to perform necessary maintenance to prevent failure. 

However, the Transforming Packaging and Processing Operations white paper shows that while data lakes are widely acknowledged for their potential, many companies in the packaging and processing sectors are not fully tapping into this potential. End-users and OEMs alike admit there is significant room for improvement in how they utilize data to enhance operational efficiencies and drive business growth. 

Challenges in data management 

One of the primary challenges in managing a data lake is ensuring the quality and consistency of the collected data. PMMI’s findings indicate that data management practices vary widely, from manual data entry to sophisticated AI-driven analytics platforms. This inconsistency can lead to data reliability and usefulness issues, potentially turning a data lake into a “data swamp.” 

Security is another critical concern. As companies move more of their operations to the cloud, they must protect data against breaches and theft. According to the PMMI white paper, data governance and security challenges emphasize the need for robust strategies to manage and protect the vast amounts of data collected and stored in data lakes. This includes concerns about interoperability and sharing data across different platforms and stakeholders while ensuring data security and privacy.  

One end-user participant in PMMI’s research pointed to the importance of storing data in the cloud so that it can be shared across organizations and noted, “The more data you have, the more value you’ll create at the data lake.” and “The more people who have access to the data, the more that value can actually be realized.” 

However, security and confidentiality concerns can prevent data from being shared and fully leveraged. These are often the most common threats within IT teams in factories and can lead to tension between IT and OT teams. The white paper suggests that action is needed to bring IT and OT leaders together and to involve IT specialists more in discussions about data analytics. Although the technology to leverage data offers “tremendous economic benefits,” very real risks can be “profoundly expensive to the organizations if any of these security vulnerabilities get exploited.” 

Leveraging AI and advanced analytics 

AI and machine learning are playing increasingly critical roles in navigating the complex data landscapes of the packaging and processing sectors. The rise of artificial intelligence and advanced analytics has transformed the potential of data lakes. These technologies allow companies to predict trends, automate decision-making processes, and optimize operations in ways previously unimaginable. For instance, as previously noted, AI-driven predictive maintenance can anticipate equipment failures before they occur, minimizing downtime and maintenance costs.  

The integration of AI extends beyond maintenance. It’s also transforming operational processes by enabling the analysis of vast data sets to identify inefficiencies and optimize production lines. AI’s potential to offer predictive insights can lead to significant improvements in both productivity and operational reliability. 

The Transforming Packaging and Processing Operations white paper underscores the varying degrees of AI integration across the industry, with some companies at the forefront of innovation and others just beginning to explore the possibilities. However, the common thread is a clear recognition of the need to invest in these technologies to stay competitive. 

Collaborative efforts and industry standardization 

PMMI’s white paper stresses the importance of collaboration and standardization to maximize the benefits of data lakes. By sharing data and analytics tools, companies can gain insights that would be unattainable in isolation. Standardizing data formats and analytics processes can also facilitate a more seamless integration of new technologies across the industry. 

The PMMI white paper highlighted several collaborative initiatives, such as the Vision 2030 series and the OpX Leadership Network, which are focused on developing industry guidelines and best practices. These efforts are essential in fostering a more integrated and efficient data management and utilization approach. 

Future directions and Pack Expo International 

Looking forward, the report suggests that embracing data-driven strategies will be crucial for the packaging and processing industries. Pack Expo International, set for Nov. 3-6 in Chicago, offers numerous resources, such as Innovation Stage presentations and networking opportunities, to aid in this transition. These gatherings allow industry leaders to share best practices, explore new technologies, and form partnerships that can help them navigate the complexities of data management. 

With seven pavilions and six stages devoted to learning from industry experts and thought leaders from around the world, Pack Expo International is the premiere opportunity to gain knowledge about data lakes and how this technology is impacting manufacturing operations.  

The show presents critical opportunities to see the latest technology and trends from more than 2,500 exhibitors on the show floor. Show attendees can reconnect with suppliers and meet new ones, face-to-face. Forge new connections with guests at Pack gives Back, the Packaging & Processing Women’s Leadership Breakfast, and the Young Professionals Network networking events. Meet packaging and processing professionals from nearly all the top CPG and life sciences companies and people from companies of all sizes from more than 40 vertical industries. Connect with peers in a relaxed environment at one of the many lounges located on the show floor.  

As the packaging and processing industries continue to evolve, the role of data lakes will become increasingly central. By addressing the challenges of data management, harnessing the power of AI, and fostering industry-wide collaboration, companies can unlock the full potential of their data to drive innovation and efficiency. The insights from PMMI’s report and the resources provided at PACK EXPO International are invaluable tools in this ongoing journey, helping businesses stay afloat in the vast data lake and thrive in these turbulent digital waters. 

Dive into the innovation epicenter and discover answers to your packaging and processing challenges at Pack Expo International. The most expansive and all-encompassing packaging and processing industry event in 2024, more than 45,000 attendees from consumer-packaged goods and life sciences companies worldwide will converge, searching for innovation, connection, and insight. For more information or to register, visit the Pack Expo International website.