With emerging technologies putting vast amounts of data at your fingertips, the discipline of asset management has become more valuable than ever. Data and intelligence will be collected in new ways in the future, and asset managers must be able to turn that data into a competitive advantage.
For some, the proliferation of digital information might seem like a mixed blessing. Data-driven insight certainly guides process changes and decision making. But the data must be collected appropriately and analyzed in the real-world context of today’s industry challenges.
That raises the question: Is it possible to have too much asset data?
As Cody Gray, Director of Product and Design for ManagerPlus, recently said on the Asset Champion Podcast, you don’t want to get lost in the data and lose sight of why you’re collecting it in the first place.
“Data needs to be translated into some sort of actionable knowledge that we can consume and act upon,” Gray said.
Knowing the importance of asset data, how can you ensure data integrity and that you’re maximizing the benefits of an asset strategy that’s backed by your own unique dataset?
Why you need asset management data
According to Gartner, business intelligence and analytics are the most important technology capabilities that differentiate asset-intensive businesses and help them achieve their mission.
Gathering the information necessary to oversee hundreds or thousands of physical resources may seem like a formidable task. However, collecting the data in a methodical way using an enterprise asset management (EAM) platform makes the process intuitive for asset managers as well as maintenance teams.
Asset data in an EAM system can provide a snapshot of a business’ fleet vehicles, construction equipment, manufacturing equipment, and facilities assets, no matter where those assets are located. In fact, Gartner also notes that today’s trends point toward smaller and smaller businesses opting for more sophisticated EAM systems that are cloud-based, rather than homegrown or on-premises platforms.
Data in your EAM is the foundation for measurement, improvement, and decision making. In other words, having an honest perspective on where you stand today is essential to your future profitability, efficiency, and reliability. But simply collecting asset data isn’t enough — you must also understand what it means.
EAM platforms help translate data into actionable business strategies. The right software simplifies tasks like asset and inventory tracking, work order management, budgeting, and maintenance scheduling. Advanced capabilities also provide real-time notifications, intelligent reporting, dashboards, and custom analytics that:
Offer visibility into day-to-day operations
Prevent delays or overlooked work orders
Resolve incidents before they impact operations
Enable collaboration between departments
Identify risks, and more.
However, to make smart decisions, organizations must also verify the quality of their asset data to be sure they can have confidence in the road ahead.
How to ensure data integrity
Asset management software is most effective when it leverages information across an entire organization from a single source of truth. From executives to accounting to end-users, everyone benefits when records are complete and correct.
The following initiatives will help protect asset data integrity:
Permissions – Not everyone needs full access to the asset database. Set permissions on the individual-user level to limit who can make entries or alterations. Be aware of any regulations that might require audit trails documenting changes to your records. Also, create mandatory fields in your EAM to encourage record completeness.
Training – Users who need access to your asset information (maintenance technicians, inventory staff, etc.) should know how to use the EAM platform the way it was intended. Comprehensive training will go a long way to keep your data in order.
Digitization – If your information is digital, you can find, sort and analyze it. But that’s just the start. Digitization also ensures security when your data is stored on a cloud-based EAM platform. With a digital environment, you can also create digital twins — which are essentially digital replicas of the real thing that can be used for modeling your asset management strategy. Those twins can allow you to test theories without compromising the live dataset.
Document history – Some equipment just naturally produces an abundance of data. With documented history or version control, staff will know they’re looking at the most up-to-date resources such as vehicle manuals, maintenance schedules, or asset history.
Regular backups – Backups enable administrators to roll the system back to a prior point in time, or to recover information if it becomes compromised or corrupted. Again, a cloud-based EAM offers the advantage of storing your asset data with automatic backups so you never have to copy your data to physical device such as an external hard drive. Look-backs can also allow managers to follow audit trails for greater accountability.
Asset managers must always build their EAM to capture the collective institutional memory across the enterprise for today and for the future. But different tactics are needed to address the integrity of historic information already recorded.
How to clean up your asset management data
Asset information can be a bit messy because your business goals change over time, because your assets change, and because you’re always refining your strategy for the sake of improvement. That being said, a relatively clean database makes your job easier and the business insight gained from your EAM that much more accurate.
Analyzing a small amount of clean data is more effective than drawing on a bigger dataset full of outliers. Aim to keep your data as healthy as your assets.
Some of the tasks required to clean up data include:
Standardization – Establish naming conventions, abbreviations, classifications, and formatting requirements for data entry. Figure out which fields are essential to capture (and which aren’t).
De-duplication – There may be exact duplicates in your system, or worse, near-duplicates. These repeat files can skew your reporting analysis. Develop a process that will allow your teams to alert you to possible duplicates they come across so you can vet them and combine data where appropriate.
Corrections – It seems overly simple, but check for spelling mistakes, inconsistencies, and incomplete records. EAM software that produces custom reports will speed the process of locating those errors.
After cleaning up the asset data, it’s time for an audit. Are the details in the system the same as what you see in reality? Don’t be surprised to find undocumented fixes, incorrect locations, or spare parts that aren’t being tracked. A few simple reviews can get you started with your own data audit.
Check entries against what’s actually on the shop floor to find out whether there’s more work to do. If your EAM captures images, consider adding a process that allows your technicians to record their completed work by snapping a picture with their smartphones.
If there are underused entry fields, find out why. Are the fields unnecessary or simply misunderstood? You might need to train your teams to use the entries correctly, or perhaps consider removing them if they don’t serve a purpose.
Check permission settings in your EAM to ensure active employees have the level of access they need. You might find that some former users still exist on your roster who need to be deleted.
Cleaning up data goes a long way in improving your perspective on your valuable assets. EAM software can help you leverage that perspective for new efficiencies and cost savings.
Business intelligence gained from EAM data
To answer the original question: Yes, there is such a thing as too much data when it’s purely data for data’s sake. What changes that value proposition is the alignment of the data with business goals. It’s about connecting the dots.
For example, merely recording fleet maintenance tasks won’t reduce downtime. Rather, deciphering the patterns of upkeep as they relate to reliability will help you see the opportunities to improve. Those improvements will likely lead to a new preventive maintenance strategy that will in fact reduce downtime.
Always think about your business requirements first and then determine the data collection requirements — not the other way around. By putting more thought behind your input sources that feed your analytics, you’re more likely to capture exactly what’s needed.
In other words, it’s about quality rather than quantity.
Asset-intensive organizations typically adopt EAM solutions to gain big-picture efficiencies. With such business intelligence, your data can help you quantify:
Investments – Find out where you’re losing money and where you’re getting value.
Key performance indicators (KPIs) – KPIs might be the bottom-line bellwether for your business or simply the everyday questions leadership often asks you. An EAM platform will provide the answers to those questions, backed by data.
Big decisions – EAM data can help you identify areas for business expansion or investment in new assets.
Cost savings – EAM data can demonstrate opportunities to improve productivity, for example, or identify overspending on inventory.
One of the most straightforward secrets to success is putting your data to work for you. As Gray said, don’t get lost in the data. Use it as a tool for mapping the road ahead.
ManagerPlus Lightning is at the forefront of the asset management software industry, providing powerful, cloud-based capabilities that transform data into intelligence. Request apersonalized demo of ManagerPlus Lightning today.
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