Having made a significant investment in your CMMS, advances in Data analytics are prompting rethinks about the Master Data that underpins your ability to launch programs such as Asset performance management, Monitor Asset health and enhance Predictive Maintenance.
A consistent approach to Master Data increases the value of the data, ensuring your system is easy to use and removes ambiguity or lack of confidence in the critical analytics.
Organisations with a high level of governance, policies and procedures that ensure Master Data consistency obtain increased returns from their CMMS investment.
In the past, design decisions for CMMS were made based on the ease of entering the Data with a requirement to enter the least possible Data. The benefit of a CMMS relational Database is that both requirements can be easily met and increase analytical requirements with some forethought at the outset of the implementation.
The more regulated the business, the Process and Data governance will be subject to increased internal or industry body regulatory controls.
Governance over the CMMS defines the process for configuring and customizing the system to support business needs and processes. This control is often applied by the IT department on behalf of the business. However, the Business’ Master Data requires Governance as well and should be owned by the business not the IT team.
This article will address some of the common Master Data issues and how implementing Data governance will unlock the value of your CMMS data.
What is Master Data?
Master Data means different things to different organisations. Most users think of Assets, Inventory and Work templates but when you look deeper into a CMMS – there are many more discrete elements and decisions to manage Data for each record.
Examples of these include
- Auto numbering or intelligent numbering of a key record’s Data field
- Auto number seeding – future proof the system as records with 6 digits and 7 digits do not sort in number order in excel but by the first digit in a record. Predict the possible volume of records in a table and start with a 6 or 7 digit number from the beginning e.g. 1000000
- Governance and Naming conventions for all records such as Assets, Inventory, descriptions, names of workers, lists of values, use of text delimiters rather than comma
- Populating lists of values with values taken from industry standards
- The character length in lists of values is inconsistent
- Use of ‘free’ text fields instead of a validated list
- Prioritizing work order records; defining types of work
- Define units of measurement to be imperial or SI (Metric) or both. Keep the options consistent (Examples mm or MM, IN or INCH or “, PSI or kPa)
- Purchasing and inventory units and conversions (Buy a box of 10 but issue from stock as single item)
- Number of decimal points allowed in a numerical field
- Prefixing and suffixing key fields, especially related records such as follow on work orders or purchase ordered created from a contract
Implementing consistency in legacy master Data is challenging to implement, introducing technical and Data changes requiring users to adapt to the revised Data structures and conventions.
Why Govern Master Data?
From my experience, organisations are considering introducing governance over the Master Data in their CMMS, but the implementation is deemed too complex or too expensive.
A lack of governance has often arisen through:
- A legacy of multiple custodians “owning” the Data during their tenure as the CMMS custodian
- Changing business processes without considering Data implications
- Users entering data inconsistently when the system allows them to
Poor Data governance and Data quality show up in such ways as:
- Engineers spending months of effort locating Data from the CMMS and other systems to answer a question posed by industry regulators or respond to an industry incident
- Cannot account for the operating cost of maintaining Assets
- Cannot Identify all your Assets of the same type
- Multiple versions of the same report to support different departments
- To investigate an asset failure takes an extraordinary amount of time sifting through many data sources
- Work requests are poorly defined slowing the work management process, creating duplicates, or missing important work
- Reduced Planning and scheduling efficiency
- Users find the system unfriendly through having to type in multiple fields
- Users search for ways to bypass a data entry customization
- Work records are linked to the parent in the hierarchy and the Planner or Reliability Engineer are left to figure where the history should be stored
I’m certain most CMMS users will have a similar experience to share.
If you wish to introduce governance to your organisation, where do you start?
Ensure the value of the Master Data Governance is understood
Leadership support will be required and the long term value to the business must be understood and supported. Enhancing and maintaining Master Data comes at a cost requiring a strong business case.
Value comes in many forms, some are:
- Reduced cost of upgrades – minimizes system re-engineering or Data fixing
- Consistent analytics and reporting
- Users support the system
- Data field look up values easy to select
- Efficient system navigation and Data searching functions
Evaluate the existing Master Data issues
Confirm what Master Data means to your business and how it is deployed as this will generate focus on the important data in the CMMS.
Create a list of the Data elements which create most challenges. Users will gladly provide a list.
Create a road map for Data which requires conversion. This is the most challenging step as the volume of inaccurate legacy Data will have an impact on applying the new convention and you will need support from a Data team.
Expect that some Data cannot be changed, especially financial data and key table field values as they can be found in many related Data tables.
Traps and Pitfalls
I’d like to share a few experiences relating to lack of Master Data Governance
- Data field lengths are longer than the visible window in the User interface resulting in critical information at the end of the text string being hidden from view.
- System Data protection is configured, and users figure out a workaround in less than a day.
- Reserve text fields for descriptions only
There is no need to place all the critical information in a single text field, for example asset number; team name; type of work; work description.
- Define your Asset Breakdown structure for every asset type in your organisation, go as deep as you need to support your asset management goals.
- Asset and Location structure
If available in your system, use the functional location to describe where the asset is located – a well-constructed navigation hierarchy is strongly recommended.
Use the asset description to describe what it is – use industry naming standards as appropriate.
Implement Master Data Standards
Document your Master Data governance principles, spelling out clearly the many values, attributes and styles that support consistent application of Data standards and definitions
Define the rules (or Key Tenets) you expect all users of the system to follow, for example
- Focus on mandatory reporting Data
- Use list based fields instead of text
- Avoid using “OTHER” as a value in a controlled list
- Don’t force failure reports on inspections
- Work history to be reported against a specific component of an asset
Socialize the Master Data standards with key stakeholders. Your Master Data standards will generate some changes for everyone involved and so will take some time to be socialized, accepted, and authorized.
Communicate your Master Data conventions to all users and support them while they familiarize with the enhanced Data structure.
Change the data
Create an Implementation plan and educate users about the changes and the timelines.
One approach is to select and deliver simpler (low cost) changes first to demonstrate the value of governance.
Produce some short term metrics and demonstrate the changes are working, for example the removal of a few duplicated reports, the population of a Data field previously left empty.
Publicize improvements in Data quality across the business.
Protect this Data using a change management process that includes your governed data. I find this is vital, especially if there are many stakeholders and divisions in an organisation using the CMMS for diverse purposes.
After a few ‘quick wins’ , change your focus to the more challenging enhancements.
BPD Zenith has the team to support you
Some of the goals of investing in a CMMS are:
- Effective and Efficient implementation of Asset Management Plans
- Produce operational and regulatory reports consistently, reliably and with minimal human intervention
- Optimize the user interface supporting easy, accurate transactional Data entry
- Automate transactional capabilities to minimize user interaction
- Enhance the value of data using Asset performance management models
- Improve knowledge of Asset health and predict the capital replacement plans for Asset replacement at the end of life
- Introduce predictive maintenance based on inspection history
BPD Zenith is well positioned to support you to achieve these goals with people who
- Share your vision to optimize your CMMS investment and unlock the value of your data
- Have experience in Master Data management and governance
- Have implemented CMMS to support standards such as ISO55001 and industry specific standards
Rethink your approach to managing master data by understanding the value of master data governance, evaluating existing master data issues and implementing master data standards. The people at BPD Zenith are well positioned to support you through these steps.
To contact the people at BPD Zenith, click here.