A computerized maintenance management system (CMMS) is only as good as the data in it. Even the best CMMS cannot fix underlying issues caused by inaccurate or insufficient maintenance data. Therefore, it is crucial to closely vet any data prior to importation. This article outlines data preparation best practices to help you organize and improve your maintenance data, giving you a greater chance of success with your new CMMS.
Data Collection Best Practices
Maintenance data exists in various formats and locations, ranging from hand-written notes on a desk, to paper work orders in a file cabinet, and data stored in spreadsheets or other computerized systems. The goal of data collection is to gather all relevant maintenance data and put it in a format where it can be easily organized, edited, and formatted for later importation.
Determine What Data to Collect
Depending on your goals for the CMMS, not all maintenance data will or should be imported. Having too little information available hampers use of the system, but too much data is overwhelming. Think about your maintenance management goals and what information is required to achieve them.
For example, some organizations choose not to track MRO inventory, so information about parts is omitted. Obviously, is a minimum amount of data required for effective maintenance tracking, but not all information will be relevant. Only collecting the data you need will be a big timesaver.
Select the Data Collection Tool
As mentioned earlier, maintenance data will ultimately need to exist in a format that makes importation easy. Most CMMS software importation tools use some form of a spreadsheet or text file format. Microsoft Excel® is the most commonly used tool for data collection, though other tools may be used.
Determine How Much Data to Collect
Collecting data on tens, hundreds, or even thousands of assets all at once is a painstaking effort. Instead, be more systematic about which assets will be entered first and how much information you need to gather for each.
Start by collecting the most important data on the assets most critical to the operation of the business. Non-essential, “nice to have” information can be added at a later time. Once critical assets are entered in the system, repeat the data preparation and importation process for less-critical assets.
Data Cleaning Best Practices
As the saying goes, “garbage in, garbage out.” What this translates to is that if flawed data is entered into a system, expect poor-quality results. Your maintenance data is a valuable asset, so it’s important to ensure that the data is “clean” and error free.
Clean Your Data
Data cleaning, also referred to as data scrubbing or data cleansing, is the process of ensuring data is correct, consistent, and usable by fixing or removing data that is inaccurate, corrupted, incorrectly formatted, duplicated, or incomplete. Do the following to clean your maintenance data after it has been collected:
- Remove any obsolete, outdated, or unused information
- Rename any records, if necessary
- Eliminate duplicated information
- Standardize record or asset naming conventions
- Remove extra blank spaces that may cause improper sorting
- Check spelling, correct typos, and ensure consistent capitalization
- Fill in missing data
- Verify that data, such as numbers and dates, are in the correct format as required by the CMMS
- Verify that data meets the character limits
Expand Your Dataset
During the course of the data cleansing process, you may encounter missing information or the need for additional information. Now is a good time to add any extra data to the dataset, if necessary. If you discover missing information after data importation, it can be entered manually.
Data File Preparation
With your data collected and cleaned, the dataset is almost ready for importation. You must first map data to the correct fields in the CMMS database. This is accomplished by: a) copying and pasting data into a pre-defined import template or b) renaming and formatting spreadsheet columns according to the vendor’s requirements.
Each CMMS has its own preconditions regarding incoming data, such as what data is required and in what format the import file should exist. Work with your CMMS vendor if you have any confusion about terminology, the structure of the import file, or other formatting requirements.
Before you import data, take the opportunity to review the dataset for any errors one last time. Once maintenance data is in the system, it may not be easy or quick to clear out. Minor errors can be corrected after importation, however.
Looking Ahead: Avoiding “Dirty Data”
Your data preparation and cleansing efforts will all be for naught if larger changes regarding data entry do not take place. The last thing you want is for workers to continue using poor data entry practices with the new system.
The implementation of a CMMS is the perfect opportunity to review and/or create new data entry policies. Standardization rules go a long way toward preventing “dirty” or flawed data. The best way to standardize data is to develop an asset naming convention that sets guidelines for how records should be named in the system.
Configuration options, such as the ability to require field values, helps avoid incomplete records from being created. In some systems, administrators can even control what type of data a field will accept. Discuss configuration options with the vendor during product setup.
Finally, train you employees on any new policies or procedures for using the system. If bad habits aren’t broken, you’ll be back to square one in no time.
Transfer Your Maintenance Data to FTMaintenance
FTMaintenance includes data importation tools that make it easy to enter clean, well-formatted maintenance data. Data importation templates allow you to map your data to FTMaintenance fields. The easy-to-use Data Import Utility transfers your data in seconds. If needed, FasTrak also offers CMMS data importation services to assist companies that do not have the time or resources to perform their own data importation. Contact us to learn more.