Financial Benefits Of CMMS Master Data Development Projects

Quality master data is often referred to as the foundation on which a plant’s maintenance and reliability program is built. In fact, it is nearly impossible for a plant to progress from bottom quartile performance to top quartile performance without investing in quality master data as one of its first steps. 

To demonstrate in detail the benefits of implementing quality master data, this document will compare two fictitious plants where “Plant 1” has done minimal master data development and “Plant 2” has fully developed, high-quality master data. These two plants are compared in more detail in the image below. 

Plant 1 – Without undergoing a Master Data initiative, the likely result achieved* is that:  

Plant 2 – Having completed a Master Data initiative, the result is that: 

*Based on what has been encountered at multiple client sites 

The following section provides a couple of case study examples that demonstrate some real-world benefits of developing quality master data.  

The sections that follow the case studies provide a more in-depth comparison of Plants 1 and 2 and will investigate each of the many effects of master data quality on plant operations. 

1. Case Studies

1.1 Hierarchy Case Study Example

Consider a real example from one of our clients where their hierarchy was only created down to the level of “Case Packer” (pictured below).  This Case Packer contains approximately 1000 wearable parts and performs the following functions: 

1. Box Erecting 
2. Conveying product and placing into boxes 
3. Box closing & sealing 
4. Conveying boxes out of case packer to the next processing equipment 

All work orders on any component within this Case Packer had to be assigned to the Case Packer itself because no further level of granularity existed.  

Additionally, all parts for any component of this system would have to exist on a single BOM. In this case, that would have resulted in a BOM containing 1,000 parts. 

The hierarchy developed for the Case Packer by Laurentide Controls as part of our master data project ended up consisting of 104 asset records, compared to the one record the client had created. While it is true that it is possible to create excess detail in an asset hierarchy, a ruleset defining the desired granularity was agreed upon with the client and then applied to the Case Packer. 

The Case Packer had been identified as a bad actor early in the plant’s life, but that comes as no surprise when only one asset existed instead of the 104 that should exist. Rolling up all the problems of 104 assets into one resulted in a long list of work orders being generated against that single asset.  

Identification of the Case Packer as a bad actor was of little value when it was unclear which of its sub-equipment was contributing most to equipment down-time. The appropriately detailed hierarchy (104 assets) would have showed much more quickly that the true bad actor within the Case Packer was a single sub-equipment shown here: 

Acting on the bad actor to improve equipment uptime is much easier with a detailed asset hierarchy that can provide more detailed information. Without it, the entire Case Packer work order history had to be meticulously reviewed and documented to determine specifically which components were being worked-on most often and for the longest periods of time. 

The master data project completed for this client accomplished everything needed to transform the Case Packer from one experiencing the pains of Plant 1 (described earlier) to one that resembles Plant 2. 

1.2 Duplicate Parts Inventory Case Study Example 

A client built a large new tissue plant in two phases. One tissue machine was built per phase. The two tissue machines were nearly identical and provided by the same OEM. 

The OEM provided a list of critical and recommended spare parts to keep in inventory for each tissue machine. The OEM claimed that the Phase 2 tissue machine’s parts list had already been de-duplicated, identifying which parts were also on the first machine built earlier and therefore already in stock, and which parts were new and needed to be purchased. 

It is likely that without Laurentide Controls’ assistance, the client would have done minimal additional verification and trusted the OEM’s duplicate check process of identifying the already created and purchased parts. 

Laurentide Controls was able to identify another $600,000 USD of duplicate parts overlooked by the OEM. The client agreed that without Laurentide Controls’ support, they would have trusted the OEM’s duplicate check process and spent this excess $600,000 USD to stock additional parts already in inventory in the right amounts. These savings were achieved with only a few days’ work. 

Additionally, had the extensive duplicate check not been performed, additional carrying costs would have been generated, meaning that these excess parts would have continual holding costs as well. 

2. Comparative Analysis of Fictitious Plants 1 & 2 

The following sections describe how implementing Master Data best practices as described for Plant 2 above (developing an asset hierarchy, parts, and BOM), impacts plant operations in a variety of ways. Particular attention will be paid to the effects on planned and unplanned downtime. 

2.1 Benefits of Establishing Standards 

One of the key reasons why so many plants’ current Master Data resembles that of Plant 1 described earlier in this document is because no standards have been developed to define how asset hierarchies, parts, and BOM should be developed and managed. Establishment of such standards must be the first step in any Master Data undertaking. 

In plants operating without standards, many well-intentioned people work in an individual and subjective fashion to make decisions about the items listed below, which results in wildly inconsistent and low-quality Master Data. Sometimes even a single person may make different decisions and perform the same task differently from one day to the next, so merely limiting who has permissions to create or modify Master Data is an inadequate alternative to developing complete standards. These standards contain the rules to be applied to an enterprise’s master data development and management, and determine, among other things: 

• What justifies something being assigned a record in an asset hierarchy vs. being a part? 
• How should asset numbers and descriptions be developed? 
• What additional information should be linked to an asset record (Tag number, drawing number, etc.)? 
• What fields must be filled in the CMMS for both assets and parts (ex. cost center, allow work order?,etc.)? 
• How should a part description be structured? 

• What are the minimum information requirements for parts to be created in the computer system? 

Where our clients already have established standards, this step consists of reviewing the documentation to ensure that it is complete, functional, and sufficiently versatile for all intended applications. Where issues are found or no standards exist, strategy session meetings are held with client stakeholders and led by Laurentide Controls to define these standards. 

These standards define the project rules to be applied and are used for the rest of the plant’s life or even more broadly at multiple sites. The direct financial benefit of establishing these standards is not quantified in this document. 

2.3 Benefits of a Complete, Accurate and Detailed Asset Hierarchy 

Impact on Work Management 

1. Work Identification  

In the above-described Plant 2, work identification is simple because work requests can be easily and clearly linked to the specific component requiring attention. This is because the component in question exists in the CMMS (or EAM or ERP) and has a clear and accurate identification number and description. Planners therefore clearly and quickly understand what asset is identified in the work request and can quickly move on to the next step in the planning process. 

In plant 1, on the other hand, often the specific component requiring attention does not exist as an asset in the CMMS (as described in the Case Packer case study above). Therefore, those submitting work requests must associate the request with a parent, grandparent, or other related asset that does exist in the CMMS. This slows down and creates confusion in the work identification process because the submitter must provide additional information in the request to more clearly identify where work is required. The submitter therefore wastes time since they could have moved on to another productive activity more quickly if the asset hierarchy were complete, accurate and detailed. The impact of this productive time lost (soft savings) is not quantified in this document. 

2. Work Planning 

Once the work request has been submitted, planners in Plant 1 must attempt to interpret the information provided by the submitter to create an accurate corresponding work order. Generally, this is done in a daily review meeting.  

The lack of definite asset hierarchy will slow down the daily review meeting process and may at times require additional follow-ups with submitters. Planners therefore waste time both trying to interpret requests and then trying to convey which components require attention to the tradespeople assigned the work orders.  

This inefficiency causes planners to use a portion of their time ineffectively; causing them to either plan fewer jobs in a given period of time, or, more likely, to spend less time planning each job that goes on schedule.  

Having less time to dedicate to the planning of each job on schedule will result in lower quality planning, where: 

• Work procedures are incomplete, lacking detail, or are altogether missing.  
• Parts needed for the job may not all be identified. 
• Non-stock parts needed for the job may not have been ordered, rendering the job impossible to complete at the scheduled time. 
• Any special tools needed may not have been reserved and may not be available.  

3. Work Execution 

Tradespeople who are then assigned work orders suffer the consequences of the planning quality issues explained above. Tradespeople in Plant 1 are likely to spend more time completing work than they would in Plant 2 due directly to issues stemming from the asset hierarchy. 

Time lost during the work execution would result in additional planned downtime since work cannot be completed as quickly. Laurentide Controls estimates that this time lost during work execution represents a 5% increase to the total plant planned downtime. 

In Plant 2, where this 5% of time is saved, the time saved can then be repurposed for preventive (PM) or predictive maintenance (PdM) activities, which would further positively impact equipment availability over time, providing even greater financial benefits. This added benefit is not quantified in this document. 

The diagram below is a simplified illustration of the work management process and the time losses resulting from an incomplete, or inaccurate asset hierarchy.

Impact on Continuous Improvement

Continuous improvement relies on the ability to review plant historical data to make informed decisions. Because of the issues with Plant 1’s asset hierarchy, Plant 1 is likely to experience the following problems that Plant 2 would not: 

1. Because Plant 1’s asset hierarchy is insufficiently detailed, Plant 1 will have a “bunched” work history, where work performed on several assets had to be assigned to the same asset in the CMMS since so many assets weren’t created in the system (as described in the case study portion of this document). Bad actor identification at Plant 1 would require a tedious review of all of these “bunched” work orders to identify which specific assets have required the most attention. 

2. Calculation of important continuous improvement key performance indicators (KPIs) such as Mean Time Between Failures (MTBF) is also very difficult for the same reason. 

Plant 1 is therefore likely to miss out on significant opportunities for improvement that would lead to a safer, less stressful, and more profitable plant. While Plant 2’s ability to leverage data towards continuous improvement is valuable, the benefits of the above are very difficult to quantify. For that reason, no % downtime reduction or dollar amount will be assigned to this part of the exercise.  

Impact on Criticality Assessment & Work Prioritization  

Asset criticality assessment is an essential step towards a reliable and safe plant. This assessment is an objective determination of how critical an asset is to different plant parameters such as Health & Safety, Environment, Operations, Quality, and Maintenance. 

By determining the criticality of all a plant’s assets, maintenance and reliability teams can see which equipment are highly critical and therefore demand significant attention, and which equipment are not at all critical and can receive only minimal attention or even be run to failure. Without the criticality assessment, it is impossible to effectively allocate limited resources. 

And without a quality asset hierarchy, it will be impossible to break down the plant equipment to the appropriate level of granularity to assign accurate criticality rankings to assets. Therefore, a quality asset hierarchy is a necessary pre-requisite to a criticality analysis, which itself is a pre-requisite to determining how to allocate limited resources for a maintenance strategy deployment. 

2.4 Benefits of a Complete and Accurate BOM (Bill of Material)

Impact on Work Management 

1. Planning efficiency and/or quality 

Having a complete and accurate BOM linked to parent assets in the complete and accurate hierarchy will facilitate assigning the needed parts to any job. It will also enable planners to more easily ensure that any needed part is in stock or ordered in time to arrive before the scheduled job is to be executed.  

The issue caused to planners by lack of BOM is fundamentally the same as the issue caused by the lack of a detailed and complete hierarchy, lost time. This lost time negatively impacts the quality of job planning in the same ways described in the hierarchy section earlier in the document and repeated here: 

• Work procedures are incomplete, lacking detail, or are altogether missing.  
• Parts needed for the job may not all be identified. 
• Non-stock parts needed for the job may not have been ordered, rendering the job impossible to complete at the scheduled time. 

• Any special tools needed may not have been reserved and may not be available.  

At Plant 1, the need to fill the weekly work schedule for tradespeople often requires that planners sacrifice the quality of planning to provide sufficient planned jobs to the schedule. Planners at Plant 2 who are working with quality BOMs will therefore be able to plan jobs that can be more efficiently executed than jobs planned in Plant 1.   

Additionally, planners at Plant 2 will much more quickly arrive to the capability of kitting parts and consumables for upcoming jobs. Kitting greatly saves time to tradespeople executing work, making the operation of the entire maintenance team more efficient. This added benefit is not quantified in this document. 

2. Planned work execution efficiency

The decreased planning quality described for Plant 1 in the previous section renders tradespeople less efficient in the work execution phase since they lose time working without detailed procedures and are left to find needed parts and special tools on their own.  

This loss in efficiency is estimated to slow the completion of planned work orders by at least 5%. This at least 5% increase increases planned downtime by 5%. 

3. Reactive Work Execution 

Tradespeople performing unplanned (reactive) work will be greatly affected by the quality of the master data available to them. A complete and detailed hierarchy with BOM will enable tradespeople to easily identify the correct parts needed for a job to be performed. This easy identification of correct parts is likely to cause reactive work to be completed at least 20% more quickly (MTTR – Mean Time to Repair). This effectively reduces overall unplanned downtime by 20% (source: Emerson: The Missing Tool for Maintenance and MRO Inventory Control, Nov 2018). 

Breakdown of a reactive maintenance task. Ref: LAI Reliability 

The diagram above shows that approximately 20% of a reactive maintenance activity is spent collecting tools and materials, and another 20% is due to travel. Reactive maintenance activities often generate excess travel as the different troubleshooting stages of the job can reveal needs for additional parts or tools.  

A complete and accurate BOM will reduce this back and forth by making the identification of correct parts much easier. It is therefore reasonable to assume that by reducing the time needed to identify and collect parts, as well as reducing back and forth travel, the time required to complete a repair is easily reduced by 20%. 

This 20% of time saved can be repurposed for preventive (PM) or predictive maintenance (PdM) activities, and in fact this is true for all time savings identified in this document. This benefit is not quantified in this document. 

In addition to the 20% of time saved in part identification, use of BOM also ensures that the correct part is used and not just a part that fits. The BOM therefore serves as a quality assurance tool. Use of the correct part will ensure the optimal functionality of plant equipment and eliminate the potential of causing early and potentially catastrophic failure that could occur from use of incorrect parts. Ensuring use of the correct parts therefore extends the interval between failures (Mean Time Between Failures – MTBF). Increasing the MTBF further increases equipment availability. This benefit is not quantified in this document.

2.5 Benefits of Quality Part (Item) Data & Inventory

Plant 1 has a parts library that is likely full of parts that are duplicated, obsolete, have incomplete ordering information, and/or have poor or inaccurate descriptions. This section describes the potential benefits of a parts library and inventory that resembles that of Plant 2 vs. Plant 1.  

“By properly managing your maintenance, repair and operations (MRO) inventory, you can save 10 to 30 percent of your annual inventory dollars.” – Reliable Plant 

1. Descriptions 

Because assets can often contain multiple different parts of the same class (ex. bearings); clear, consistent, and detailed part descriptions are beneficial to planners and tradespeople trying to correctly identify the part required for a job.  

Plant 1’s poor and incomplete descriptions contribute to time lost by both the planners (planned work) and tradespeople (unplanned work) trying to identify the correct part to use for a job. This can be true even with accurate BOMs, particularly where BOMs are large and complex. 

The confusion this causes can also lead to the occasional purchase of the wrong part. When this occurs, planned work must be delayed since the wrong part was ordered and sufficient time may not remain to get the correct part on hand.  

This issue can be particularly problematic if corrective work orders to replace worn or damaged parts must be delayed. Additional unplanned downtime may be produced if worn or damaged parts do not last until the revised scheduled time to execute the work order. The benefit of detailed and accurate part descriptions is not quantified in this document. 

2. Incomplete Ordering Data 

Often times not only are part descriptions incomplete or poor, but also manufacturer or vendor information needed to actually purchase a part may be missing or inaccurate. These parts are of very little value even on a BOM because additional effort is required to properly identify and purchase them. Both planners and tradespeople will therefore waste time trying to find the required information to identify and/or purchase needed parts. The benefit of complete vendor and/or manufacturer data is not quantified in this document. 

3. Duplicate Inventory 

Plant equipment is generally provided by many different vendors. Often, the de-duplication process used by our clients is inadequate to ensure that the same parts are not being purchased from multiple vendors. In fact, previous projects completed by Laurentide Controls have shown that duplicate parts are even frequently generated by the same vendor (as seen in the case studies section), leading our clients to create duplicate inventory. 

When building a new plant, new plant area, or adding a new production line, most plants will fall into the pitfalls of Plant 1 and create numerous duplicate parts. 

Duplicate inventory purchases are essentially wasted money spent to unknowingly stock parts already on the shelves. Since duplicated parts are created as individual unique parts and are not consolidated, it is often the case that a part can appear to be out of stock when in reality it is on another shelf in the stores room but identified with another part number. This can lead to further waste when parts are needed on an emergency basis and express shipping costs are incurred. 

Based on previously completed projects and industry benchmarks, Laurentide Controls estimates that completing a Master Data project will reduce inventory cost by 0.5% RAV. This is a one-time cost savings; however additional expenses will be tied to these parts and are detailed in the next section: carrying costs. 

When Master Data projects are performed on new plants or product lines, no historical part consumption data is available, and so it is impossible to achieve a fully optimized inventory. However, careful parts management and elimination of duplicates can achieve a much more optimized inventory than would be otherwise produced. 

The following Emerson benchmark data illustrates that the above % RAV savings claim is quite conservative since it only describes at most an industry standard half-quartile performance improvement. 

4. Carrying Costs 

Although it may seem like the total cost of a part must be its initial purchase price, this is unfortunately not so. Parts in inventory have a continual cost to the organization, these are called carrying costs. Carrying costs are approximately 20% of the purchase cost of a part, per year. These carrying costs are due to: 

• Use of space 

• Depreciation 
• Labor (stores room management) 
• Property taxes 
• Insurance 
• Utilities 

It is therefore crucial to optimize parts inventory to eliminate excess, duplicate, and obsolete parts. Carrying cost savings due to inventory deduplication can be calculated as follows: 

0.5% RAV X 0.2 = Annual Carrying Cost Savings (due to deduplication) 

2.6 Impact on Safety

All the above stated benefits of implementing a quality Master Data program had the aim to lead to a less reactive, more planned, and more profitable plant. It is important to note that less reactive, more planned plants are not only more profitable but are also safer.  

Many accidents in plants occur due to: 

• Unexpected catastrophic equipment failures that can harm someone in the vicinity if present. 
• When performing reactive maintenance – trying to get the equipment back up and running as quickly as possible.  
• Unplanned work is more improvised and is more likely to be performed without applying safe procedures. 

Therefore, by implementing quality master data, which leads to a less reactive plant for numerous reasons, we also make a safer plant. This benefit is not quantified in this document. 

3. Summary of Required Investment & Benefits 

3.1 Summary of Benefits: 

Measured One-Time Savings: 

• 0.5% RAV from unpurchased duplicate inventory 

Measured Annual Savings: 

• 10% less planned downtime 

• 5% due to asset hierarchy – clearer asset identification 
• 5% due to BOM – Needed parts can be identified on work order and even kitted. 

• 20% less unplanned downtime 

• 20% due to BOM 

• 0.1% RAV (0.5% RAV x 20%) from reduced item inventory carrying costs. 

Unmeasured: 

• Plant or corporate standards created defining rules and requirements for development and management of: 

• Asset hierarchy 

• Parts 
• BOM 

• Time saved generating work requests.  
• Time saved by tradespeople interpreting work orders. 
• Facilitated kitting 

• Elimination of work on incorrect machines – leads to failures. 
• Continuous improvement is much easier to implement.  

• Bad actor identification 
• MTBF calculation 
• RCFA 

• Tradespeople’s time saved can be re-purposed for PM/PdM 
• Use of correct parts (not just parts that fit) 
• Improved part descriptions – avoids confusion and time loss. 
• Parts contain all needed information to be orderable. 
• Safer plant 

3.2 Investment Required:

The investment required to transform a plant from one resembling Plant 1 to one resembling Plant 2 depends on the size of the plant or area being included in the scope. The larger the project, the lower the relative cost (per hierarchy asset, per part, etc.). Values here are calculated as a percentage of the replacement asset value (RAV) of all the equipment included in the scope. 

Project scope RAV <$50 million  à  Estimated project cost = 0.8-1% RAV 

Project scope RAV >$50 million  à  Estimated project cost = 0.35-0.8% RAV 

Real Example 1: Project executed on new production line with RAV $25 million. Project investment required was approximately $225,000 (0.9% RAV). 

Real Example 2: Project executed on new plant with RAV $500 million. Project investment required was approximately $1,700,000 (0.35% RAV). 

3.3 Return on Investment (ROI) Calculator

Benefits of optimized PM/PdM asset strategy: 

Optimization of asset maintenance strategies is a separate initiative from Master Data development, however the two are inextricably linked and are often grouped together in what Laurentide Controls calls a “Reliability Foundation” project. 

For one thing, all maintenance activities must be assigned to an asset in the hierarchy. Therefore, a complete and accurate hierarchy: 

• Clarifies which components require work (work identification) 
• Avoids confusion from trying to interpret planner’s instructions in the field  
• Allows accurate bad actor identification and analysis 

The objective of a asset strategy optimization is to: 

• Validate the maintenance activities that are complete, detailed, value added activities 
• Add new maintenance activities if required (some failure modes not adequately protected by existing activities) 
• Eliminate any redundant or no-value added activities 

The result is both the creation of new maintenance activities and the deletion of others. Overall, the net impact on the total amount of planned downtime is zero. 

However, the impact on unplanned downtime is significant. The optimized maintenance activities better protect components from preventable or detectable failures that would otherwise result in unplanned downtime. Overall, the estimated impact that implementing such a program can have is to reduce unplanned downtime by 25% (source: Emerson – could go as far as 50%). 

Quality master data management is crucial for improving plant performance. This document compares two fictitious plants, one with quality master data (Plant 2) and one without (Plant 1). Benefits include a 10% reduction in planned downtime, a 20% decrease in unplanned downtime, and cost savings of 0.1% of the Replacement Asset Value (RAV). Unquantified benefits include increased safety, continuous improvement, bad actor identification, and more. Investment costs vary based on project scope, ranging from 0.35% to 1% of RAV. Optimizing asset maintenance strategies complements this initiative by reducing unplanned downtime by 25%. This translates to greater equipment availability and increased profitability.