In an age where every organization is essentially a data organization, the emphasis often shifts towards accumulating more data, overshadowing the importance of its quality. Yet, many organizations find themselves overwhelmed with a plethora of unwanted data—duplicates, outdated files, irrelevant documents, corrupted files, mislabelled data, the list goes on.
While data is vital to an organization, the costs associated with managing and storing it can significantly impact asset-heavy and critical infrastructure sectors. The volume of data being handled by such sectors is on the rise, driven by the growth of unstructured data, such as video, image files, geospatial, etc. The World Economic Forum’s research shows that 2020 saw over 44 Zettabytes (ZB) of data collected globally—that's 44 trillion Gigabytes—and it's estimated that by 2025, unstructured data will make up 80% of all data globally.
The realm of data storage has seen cloud solutions as a prominent player due to its perceived cost-effectiveness and security features. However, the financial aspect of such storage can become a concern as costs escalate from hidden charges such as egress fees when data is retrieved from the cloud.
The challenge of managing and retrieving data efficiently becomes a pressing concern, especially when considering the costs involved in handling irrelevant or incorrect data. These costs become particularly noticeable when data needs to be retrieved periodically, where every piece of irrelevant data retrieved is considered money wasted. For many, tackling the problem of irrelevant data can seem insurmountable. Generic Document Management Systems (DMSs) like SharePoint offer basic data management features, but often fall short in providing the tools necessary for cleaning up engineering drawings and other specialized data types. This inadequacy results in a silent yet relentless drain on resources, time, and ultimately, the bottom line.
The Complexity and Cost of Unwanted Data
Data is often considered an asset, but it's an asset with a carrying cost. Although the cost of data storage has generally decreased over the years, the sheer volume of data has been increasing at an unprecedented rate, making the overall cost anything but negligible. According to a study, the global data storage market, already valued at USD 217.02 billion in 2022, is expected to reach USD 777.98 billion by 2030. While these figures might seem distant, the financial ramifications of poorly managed data are immediate and often hidden.
Case Study: Greg Kodweis, Director of Infrastructure Management at Las Vegas Valley Water District, noted, "We went from 464,000 drawings down to 351,000 by removing direct duplicates—a 24% reduction." This is not just a reduction in the number of files; it's a significant cost saving when considering the man-hours required to manage these files and the operational risks associated with using outdated or incorrect information.
Operational inefficiency due to poor data management manifests in various forms—time wasted in searching for files, delays in project timelines, and even regulatory fines for non-compliance. As Rob Trout, Digital Transformation Leader at WestSide, pointed out, "Reduced search time for information is the biggest contributor. By bringing that down from hours to seconds, we’re saving 12.5% in engineering time and costs."
In sectors like utilities and mining, the complexity is compounded by the need for real-time data for monitoring and decision-making. Given that these sectors often operate in highly regulated environments, the cost of an error due to poor data quality can be astronomical, ranging from financial penalties to operational shutdowns.
Case Study: Bruce Bonney, Facilities Maintenance Manager at Children’s Health Queensland, emphasised, "We have 45,000 drawings and more than 20 contractors to manage. It allows us to respond a lot quicker to issues that we have in the hospital, especially the more difficult to find issues."
The Limits of Generic DMSs
On the surface, generic Document Management Systems (DMSs) like SharePoint appear to offer a comprehensive solution for data management. They provide features for storing, organising, and sharing files, seemingly making them a one-stop solution for all document-related needs. However, the reality is far from this perception, especially when it comes to managing specialized data such as engineering drawings.
The first major pitfall of generic DMSs is the lack of robust version control. In fields like engineering and utilities, where precision and accuracy are paramount, even a minor versioning error can lead to catastrophic outcomes. The absence of specialized version control features means that multiple versions of the same drawing can exist simultaneously, leading to confusion and costly errors.
Lack of Data Clean-Up Functionality
Perhaps one of the most glaring omissions in generic DMSs is the lack of automated data clean-up features. At the scale at which asset-heavy industries operate, manual clean-up is not just cumbersome; it's practically impossible. The absence of automated clean-up functionality leaves organizations with a growing pile of redundant, outdated, and trivial data, which not only consumes storage space but also administrative resources. Managing engineering drawings is a complex task that demands more than what generic DMSs can offer. These drawings often come with layers of metadata, are linked to various versions, and are critical to operations. A small error in managing these could result in significant operational setbacks, emphasizing the need for specialized DMSs equipped to handle such complexities.
Insight: During a recent project with MP Materials, we significantly streamlined their data, reducing the file count from 250,000 to 25,000—a whopping 90% reduction. This extensive data clean-up was achieved using specialised tools capable of identifying undesired files, such as duplicates, which would be impracticable to address through a manual, human-driven process as necessitated by a generic Document Management System (DMS) like SharePoint.
Industries such as utilities and mining operate under stringent regulatory frameworks, where compliance isn't merely a checkbox but a critical operational necessity. Generic DMSs often fall short in providing essential features for compliance tracking, especially for specialized documents like engineering drawings. They may lack robust audit trail capabilities, comprehensive revision logging, custom workflows, user and artifact reporting, and stringent data security measures. These gaps could potentially hinder traceability, accountability, and ultimately, the compliance of the organization. As Kai Eberspaecher, COO at Bengal Energy, aptly pointed out, "With RedEye, I don’t need to look through 16 different systems. In terms of compliance, that is pretty important to us." This level of centralized compliance management is especially crucial for adhering to regulatory mandates, something that may pose a challenge in generic DMSs like SharePoint.
Generic DMSs’ like SharePoint are designed more for project-based access, which might not be suitable for handling sensitive or regulated documents. While their focus is to provide access to documents and files, they cannot restrict access based on specific roles. A specialised EDMS on the other hand will typically feature sophisticated access controls to limit document access, ensuring total control of who can access your information.
EDMS: The Tailored Solution for Engineering
The Missing Puzzle Piece
In contrast to generic DMSs, specialized systems like RedEye are designed to handle the complexities of specific industries. They offer robust version control, data clean-up, and compliance tracking features that are essential for managing specialized data like engineering drawings and reducing costs associated with unwanted data.
Designed for Complexity
In fields like engineering, the stakes are high. A single error in an engineering drawing can result in operational delays, cost overruns, and even safety risks. Engineering drawings are not mere files; they are intricate digital assets often linked with metadata, annotations, and version histories. Specialized systems like RedEye appreciate this complexity and offer features like metadata management, layer control, and stringent versioning to ensure that your engineering drawings are not just stored, but managed with the precision they demand.
The practical benefits of employing a specialized EDMS like RedEye are substantial. For instance, the ability to quickly retrieve accurate, up-to-date engineering drawings can significantly reduce operational downtime. By enhancing version control and simplifying compliance, RedEye directly contributes to improving operational efficiency and reducing costs. The robust version control and data clean-up features discussed earlier facilitate these real-world benefits, ensuring that the data management process is streamlined and error-free.
Case Study: WestSide reports substantial operational cost savings since implementing RedEye. According to Rob Trout, Digital Transformation Leader at WestSide, their digital transformation project with RedEye and the associated business process changes are resulting in an estimated 16% saving from their engineering budget every year.
Testimonial: Nick Skobelkin of Snowy Hydro said, "RedEye came along at just the right time. We had some old systems in place for the best part of 20 years. We had a huge drawing collection which is a critical cornerstone for pretty much all of our technical staff. The turnaround time for that drawing to be visible for the rest of our Snowy population is very important."
Our advanced data clean-up tools take the guesswork out of eliminating unwanted files, providing organizations with efficiencies that go beyond storage costs. For instance, Ok Tedi used RedEye to process more than 900,000 digital files in their legacy drawing library. Mark Kelly, Senior Draftsman at Ok Tedi, noted, "We took advantage of RedEye’s bulk data management tools to automatically remove duplicate files, quickly add metadata, and 'fold' multiple versions into single identifiable drawing”.
The Tidal Wave of Data
As digital realms continue to expand, the influx of data is nothing short of a tidal wave. The surge in unstructured data, constituting 80% of all data by 2025, represents a significant challenge and an opportunity. The challenge lies in effectively managing this deluge to extract actionable insights, while the opportunity resides in harnessing this data to drive innovation and operational excellence. As organizations navigate through this digital transformation, the capacity to adeptly manage data will become a distinguishing factor between industry leaders and laggards.
The advent of Artificial Intelligence (AI) and Machine Learning (ML) heralds a new era in data management. These technologies not only promise to automate mundane tasks but also offer the potential to uncover patterns and insights that were previously elusive. However, the efficacy of these technologies hinges on the quality and organization of the data fed into them.
The marriage of AI and big data paves the way for predictive analytics, enabling organizations to anticipate issues before they escalate, optimize operations, and make data-driven decisions in real-time.
Data Governance and Quality
Emerging technologies will also play a pivotal role in enhancing data governance and quality. Real-time data quality checks and advanced data governance frameworks will become indispensable as organizations strive to maintain data integrity amidst the burgeoning data volumes.
Preparing for the Future
The rapid evolution of data management technologies necessitates that organizations remain agile and forward-thinking. Adopting a proactive approach to data management, embracing emerging technologies, and investing in specialized Engineering Information solutions like RedEye, can equip organizations to ride the wave of digital transformation successfully. By fostering a culture of continuous learning and innovation, organizations can stay ahead of the curve, ensuring they are well-positioned to leverage the potential of future data management trends to their advantage.
The exponential growth of data presents both an opportunity and a challenge. On the one hand, data can provide invaluable insights that drive innovation and efficiency. On the other hand, the management of this data, especially unwanted or redundant data, can have a profound impact on an organization's bottom line. While generic DMSs like SharePoint offer basic data management features, they are inadequate for specialized needs, particularly for managing complex engineering drawings.
As industries increasingly rely on complex and voluminous data, the need for specialized solutions like RedEye becomes not just preferable but essential. With features tailored to the unique demands of asset-heavy and critical infrastructure sectors, RedEye offers a solution that can significantly reduce costs and improve operational efficiency.
It's time to tackle the issue of unwanted data before it becomes an impossible problem. The future is not just about collecting more data but managing it more effectively. And that begins with choosing the right EDMS for your specific needs.