Killing Your Data Vampires
Data is the lifeblood of our organization.
How many times have you heard someone say this?
Have you said it yourself?
There’s no denying that data is the key to insight—and in a dogged effort to reap every bit of innovation and efficiency from their data, many leaders focus on amassing as much data as they can. The global data storage market, valued at USD 217.02 billion in 2022, is expected to reach USD 777.98 billion by 2030.
That’s partly because we have so many tools that can grab and record every bit of activity—in and out of our systems. But quantity isn’t the same thing as quality. Even the most zealous data collector can admit that when casting a wide net, they bring in as much garbage as gold.
The problem? That garbage can cost them more than they realize, and their current systems may contain poor data.
The High Cost of Data Hoarding
Consider Colin, who leads a critical infrastructure organization with systems that exhaustively collect data. Over time, those systems fill up with worthless data—outdated information, corrupted files, duplicate records, and mislabeled data. Much of this data is unstructured, such as video, image files, and geospatial data. Colin’s organization isn’t alone in this; according to the World Economic Forum, unstructured data is estimated to make up 80% of all data globally by 2025.
None of that data is useful for managing assets or developing growth strategies, yet the company pays to manage and store it.
Colin isn’t too worried about this. He assumes his data storage cloud solution is both advanced enough and cost-effective enough that it’s not an issue. Then, he retrieves some data from the cloud and is hit with surprisingly high egress fees. He’s irritated to realize he just paid a hefty sum to retrieve mounds of irrelevant data.
Colin forms a task force to study the company’s data management systems and processes. They realize their problems go beyond fees. The teams spend too much time searching for files, struggling to use the old interface. Costs run over budget, and workers feel their safety is sometimes compromised. Employee morale is low. Projects have hit delays, and—to Colin’s mortification—the company has paid steep regulatory fines for non-compliance due to data issues.
He realizes his systems are full of data vampires, silently draining the company’s resources, time, and profits.
The Limitations of Old Document Management Systems
Here’s why this is so destructive for Colin and his organization. They operate in highly regulated process manufacturing environments and need real-time data to monitor their infrastructure and make intelligent decisions on the fly. Even a simple error can unleash disastrous costs, from financial penalties to operational closures.
The task force digs into the performance of their Document Management System (DMS.) As expected, it has features for storing, organizing, and sharing files. But they find that it falls short in four areas:
1. Data access. Their DMS is built on old technology. It lacks a modern interface with quick and easy ways to find the correct data. The lack of robust version control and concurrent engineering has led to versioning errors that caused severe mistakes. Their engineering drawings are intricate digital assets often linked with metadata, annotations, version histories, and other documents, but the DMS can’t handle that level of complexity.
2. Clean-up. They need to automate data clean-up, as manually cleaning their ever-growing pile of redundant and outdated data is too burdensome. However, the DMS does not have such automation.
3. Compliance. The organization operates under stringent regulatory frameworks, and compliance is a critical operational necessity. However, their current DMS offers very limited capabilities. What they need are robust audit trail capabilities, comprehensive revision logging, custom workflows, and user and artifact reporting. Without those features, the team can’t count on traceability, accountability, and true compliance.
4. Security. Colin is especially annoyed by the system assigning access to team members by project. This gives too many people access to sensitive or regulated documents, increasing the organization’s risk surface. He would prefer a system that restricts access based on specific roles.
In short, Colin’s DMS simply cannot handle the complexity of managing engineering drawings and other specialized data for a fast-paced critical infrastructure organization.
Engineering Document Management System (EDMS) /EDMS: Tailored to Engineering
Colin begins looking for a system to reduce expenses while unlocking new efficiencies. He wants tools to identify duplicates and other junk files and a cloud-based system that can reduce infrastructure costs. By working with Kinsmen Group, he finds RedEye, an Engineering Document Management System (EDMS).
Here’s how RedEye and Kinsmen Group changed everything for their organization.
Kinsmen Group can easily handle organizational complexity. Kinsmen AI handles automated data clean-up, and compliance tracking features make it easier to manage specialized data. Metadata management, layer control, and stringent versioning give the team new speed and control over their information.
Efficiency goes up, and costs go down. Teams can retrieve accurate, up-to-date engineering drawings whenever they need them, boosting productivity and reducing downtime. Robust version control features help them minimize costly errors, and because RedEye is cloud-based, they can also reduce their spending on physical infrastructure maintenance.
Smarter technology unlocks new competitive advantages. Artificial Intelligence (AI) and Machine Learning (ML) automate mundane tasks to workers’ delight; new insights and predictive analytics help them spot improvement areas, anticipate issues before they escalate, and optimize their operations. Data governance and quality, always a headache before, are now optimized through data quality checks and advanced data governance frameworks—helping them take their data integrity to another level.
RedEye Results
In the first few months of working with Kinsmen Group, Colin’s team dedupes their engineering documents by 20% while radically reducing their manual work cleaning and managing files. Colin can now assign document access by role, tightening up their security posture. The teams love their new freedom from manual work and being able to access the information they need, when they need it. They also appreciate how much easier it is to meet regulatory mandates.
Colin is thrilled with the cost savings and convenience of using cloud-based systems like RedEye. Eliminating needless spending on storing and managing redundant data has freed up the budget for new projects and improved the organization’s bottom line.
Best of all, Colin is now getting the rewards he always wanted from his data: innovation and efficiency. By finding the insights in his data, he and his team guide the organization into strategies that benefit all facilities and departments – and take their operations to a more agile and profitable level.
