One way to attack your asset management challenges is to approach them from a data perspective. There are two types of data that drive great EAM system information. Master data and Transactional data.
- Master data, the static data structures in the system (e.g., equipment master, codes, etc.), form the building blocks of the EAM/CMMS system.
- Transactional data (e.g., work orders, MRO material usage, etc.) is created by the system and helps drive system reporting and analysis.
Fixing both of these data types can have a significant and positive impact to the operation.
Good data can help improve equipment availability, reduce cost, and drive down health, safety and environmental risks. In asset management, data rules the roost. Without good data we are making decisions in the dark. It’s like playing darts with a blindfold on. Each time you throw the dart you don’t know what you are going to hit. Asset management acts the same way.
Working with the airline industry you learn quickly that they are all about good asset management data. What is done to those airplanes is meticulously tracked and monitored. Airlines realize high quality asset management data is super critical to their survival. Lives depend upon it. Airlines are not unique. All asset-intensive organizations, organizations that rely on their assets for their success, like the airlines, should have this same commitment to quality data.
“Every work order is gold”, “no sku left behind”, “no bill of material left undeveloped”, etc. should be the mottos of every asset management operation.
How’s your asset management data? Ask yourself these questions. See how you fare in asset management data 101.
- Do you have developed bills of material for your critical assets?
- Have you identified all of your critical spares?
- Have you identified all of the facility’s maintainable assets?
- Do you have good spare parts usage, lead time and cost information?
- Have you classified your equipment?
- Are your work order codes distinctive and do they adhere to a consistent scheme?
- Have you developed problem-failure codes for your critical asset classes?
- Is your MRO procurement data tied to your work order data?
- Are maintenance costs driven down to the asset management activity?
- Is your work order data complete, accurate and timely?
- Is your MRO material master data clean and classified?
Asking these questions can get you thinking about your data. Fixing your data will go a long way to fixing your asset management challenges.
When improving your EAM data, what are the right steps to take?
- Step 1: Develop a data model. Set your data standards. Like Stephen Covey would say, start with the end in mind.
- Step 2: Compare your data model against your current state. Identify the gap between where you are and where you want to be.
- Step 3: Build an implementation plan to close the gap. This plan would include the tasks, resources, and timelines required to comply with your data model.
- Step 4: Implement the plan. Execute the tasks and begin closing gaps.
- Step 5: Monitor results. Evaluate outcomes and adjust / improve as needed.
I know it sounds like a lot of work, but the payoff is worth it. If you do a little bit each day and start your journey right by establishing an asset management data model, then you will have ½ of the journey already completed. You will know what your data “should” look like now it is just a matter of getting your data there.
Data is king in EAM. With it we are in a better place to make better decisions. Without it we are shooting from the hip and not sure what we are going to hit. One thing is for sure. You will never have consistent value creation without good quality asset management data.
Since 1997, we have been helping organizations create rich and actionable EAM data. Contact us at email@example.com so we can help you solve your EAM data challenges or get a free demo of the EAM Master Data LibraryTM to start improving your asset management data today.