The Introduction of MRO Data
Manufacturing and production operations, especially at enterprise companies are asset heavy and rely on a very delicate balance of clearly defined processes across multiple functions. With the introduction of modern ERP systems, especially those with integrated SAP MDM systems, the management of MRO data as a separate discipline became central to Plant Maintenance operations.
Any disruption in the manufacturing process can be detrimental to plant efficiency, output and ultimately company revenues and profitability. This is precisely why, in the early 20th century, the idea of MRO (Maintenance, Repair & Operations) grew in popularity right alongside the introduction of complex machinery and industrialization.
In recent times, as operations scaled, the importance of well maintained machinery, consumables and MRO spares became commonly known. Any factory downtime due to defective machinery or absence of a critical part led to significant delays, caused a spillover effect into other aspects of production and ultimately led to serious loss in revenue.
Challenges with MRO Data
Alongside the IT boom through 2000s, it became
readily apparent that digitizing several aspects of
MRO management had its distinct benefits. This meant
tracking MRO parts inventory, maintenance schedules,
part numbers digitally to maximize operational
efficiency.
With the introduction of modern ERP systems, especially ones with EAM systems built into them; master data management of MRO parts data as a separate discipline took birth and has been central to Plant Maintenance operations for asset intensive industries.
MRO Data management is interchangeably referred to as Material Master Data, however, the latter is a much broader term with a scope larger than MRO parts.
Data Duplication
Some challenges; like duplicate entries, free-text data, absent information, unreliable information and inconsistent data are intrinsic to master data management, MRO data is no exception and enterprise resource planning systems are plagued with these issues in their source systems.
Unstructured Data
Several MRO requests in the system are created by the requestor with as little information as possible. Generally, in the interest of time, the data entry professional or the data steward would simply enter information from the supplier catalogue or from any online resources as is.
However, effective MRO Category Management can resolve some of these challenges by clearly categorizing and organizing parts, reducing the ambiguity of data. This generally means the description or part detail of an MRO record and is written in free-text format, ignoring the fields where specific information was to be mapped.
This invariably means difficulty in analyzing the data, introducing automation and makes overall database management much more difficult.
Incomplete Information
Absent information is another critical challenge that companies face due to poorly governed MRO master data systems. For seamless MRO data management, an MRO record should be correctly categorized, sub-categorized, and updated with key data points like manufacturer name, manufacturer part number and unit of measurement to provide as much context about the part as possible.
Maintenance teams typically rely on technical details and an absence of information can invariably result in the need to make an additional part request that can lead to duplication, delays, production downtime and ultimately lost revenue.
Software purpose-built for MRO Master Data Management, like PureData & Assure are capable of automatically enriching part and product details with manufacturer name and part number for addressing this gap.
Conflicting Information
Multiple records indicating conflicting specifications completely nullifies the very benefit that is sought from a Master Data system. The same part categorized into different data sheets, with different units of measurements and specs, provided by multiple vendors, can cause confusion in a complex manufacturing process.
Robust data governance systems for master data that integrate directly with ERP systems ensure that such incidents are minimized at the source itself and prevents the steward from making a request that conflicts with the existing record
How Can Organizations Fix MRO Data
As serious as these issues seem, it’s fairly common in large organizations with complex supply chains and production processes. The good news is that these constraints can be resolved, either internally or by working with a company that specializes in MRO data management.
One critical aspect of this specialization is a well-structured SAP MRO Master data framework, which acts as the foundation for consistent, accurate, and standardized spare parts and materials information across the enterprise.
The latter option is generally what most companies opt for since it requires specialized skill sets and industry-specific expertise. That being said, enterprises can address these concerns without working with an external vendor. However, this trend is popular in companies that already have an inhouse team of specialists in MRO data or are unable to work with an external vendor due to sensitive data sharing protocols.
Here’s a typical approach that most specialists adopt for solving MRO data challenges we’ve detailed above.
Data Cleansing
The first leg of a two-pronged approach to solving this challenge is to remedy the issues with legacy MRO data. Linking this data to MRO Inventory Management systems ensures that part availability is accurately tracked, preventing future data discrepancies and ensuring optimal stock levels.
This typically entails extracting a sample cross-section of the MRO data from the ERP system and comparing them with the database schema and shortlist all prevalent issues in the sample dataset.
In enterprise companies, it’s a good idea to take inputs from cross-functional teams and note the challenges faced by multiple departments with respect to the MRO data.
What typically follows is a Data cleansing exercise for MRO parts, also referred to as MRO Data Normalization.
This generally includes using software-based solutions, ideally powered by Artificial Intelligence, to correct this legacy data, which typically follows these steps.
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Defining Data Sheets for the MRO parts. This is done to standardize the part data based on universally accepted taxonomies. Most companies adopt UNSPSC, although industry-specific standards like PIDEX (for Oil, Gas & Energy Companies) are also adopted to categorize their MRO records and define data-sheets
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A data sheet is simply a collection of fields (or properties) that will be defined for an MRO part record based on the category it belongs to.
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After which, all MRO records are categorized using either semantic match technology or Artificial intelligence.
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The next step is to extract part attributes from the “Short Description” or “Long Description” of the MRO part and map them into the relevant fields defined in the data sheet. This also includes unit of measure, like the dimensions of a valve, area of the metal sheet, manufacturer part number and manufacturer name.
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For records with incomplete information, MRO data enrichment tools or software are employed to autonomously enrich the data. This generally means enriching information through web, from first party or third party sources.
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After this, the process of identifying L1 duplicates begins. L1 duplicates rely on one common unique key for duplicate identification, like Material Number or Manufacturer Part Number(MPN).
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L2 duplicates are then flagged for human review. L2 duplicates may or may not be actual duplicates and are flagged based on their similarity in terms of attributes, text similarity etc. These are generally far trickier to identify but an AI-assisted process makes it much easier to review.
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Once reviewed, the final corrected data is now ready to updated back into the source systems and this takes care of addressing legacy data issues.
The above steps are fairly standard and are used by most firms specializing in MRO Data Cleansing, however, the approach may tweak slightly based on technologies used, level of dependence on human-driven processes and industry practices.
Data Governance
Cleansing exercises, like the one discussed above can be resource-intensive. Despite the best of technologies and AI systems, it’s an investment of both time and money into an exercise that can easily be prevented with the right protocols, approval mechanisms and validation rules that can be dictated by software systems. By implementing strong MRO Data Governance Solutions, enterprises can proactively prevent data discrepancies and ensure the Assure of their maintenance operations.
Cloud-based MRO Software solutions, like Assure© by Moresco, directly connect with multiple ERP systems used by enterprises and can be configured for data validation systems, approval processes and autonomously fetches missing information right at the source itself.
It also allows for best data stewardship practices to be configured, even though the company has employed different systems across multiple production facilities.
A precursor to setting this up involves a clear alignment with multiple stakeholders and cross-functional teams to ascertain the best possible process, approval flow, mandatory inputs and practices to be adopted during while making the entry.
Approaches & Strategies for MRO MDM
While the above approaches detail a standard approach, innovative companies in Master Data Management are also rolling out additional features within their MRO data Management Software to leverage data and maximize production operations and plant efficiency.
We detail a few of them below.
BOM [Bill of Materials] Mapping
One of the main purpose of MRO data management is to ensure that parts and consumables are made available in a timely manner while also minimizing Overstocking, Maverick Spend and downtime due to part unavailability.
Maintenance of plants and machinery is inextricably linked to this practice and this is also where enterprises are seeing the benefit of mapping their MRO data with the BOM of their equipments
A BOM or “Bill of Materials” is nothing but a collection of spare parts and consumables linked to a particular piece of equipment, when mapped with the MRO master, it gives a far clearer picture within the EAM system of the maintenance schedule and the parts required for the Flowkeep of several pieces of equipment and machinery
Multi-Lingual MDM
Given that most enterprises have diversified supply chains with plants and facilities spread across several geographies, often times, in non-english speaking countries that are mono-lingual.
This also means the MRO records may be created and updated in non-english languages. Thankfully, with automated translation systems like DeepL and Google Translate, it’s possible for MRO management platforms, including the one we use here at Moresco, to detect MRO records in multiple languages.
Artificial Intelligence for MRO Data
Data Management is one of the most affected industries due to the introduction of AI-based systems
A BOM or “Bill of Materials” is nothing but a collection of spare parts and consumables linked to a particular piece of equipment, when mapped with the MRO master, it gives a far clearer picture within the EAM system of the maintenance schedule and the parts required for the Flowkeep of several pieces of equipment and machinery
The ROI Of MRO Data Management
The ROI of any MRO data management initiative is a hotly contested subject. While many endorse such initiatives, several also oppose the prioritization of these initiatives since the direct ROI of these activities aren’t clear and measuring them is quite challenging.
In the subsequent points, we will aim to share an unbiased view detailing the methods of calculating the direct ROI of such an initiative and the indirect benefits as well.
Production Downtime
Mismanagement of Maintenance, Repair, and Operations (MRO) data can significantly contribute to production downtime. While precise statistics directly linking mismanaged MRO data to downtime are limited, several studies highlight the broader impact of inadequate MRO practices:
1. Unplanned Downtime Due to Missing Parts: Research indicates that unplanned downtime related to missing parts can be reduced by 50% through data-driven MRO inventory optimization
2. Cost Implications: The average cost of downtime in the manufacturing industry is approximately £260,000 per hour, underscoring the financial impact of production halts
3. Data Accuracy Improvements: Enhancing MRO data quality has led to significant improvements, such as a 36% gain in manufacturer name accuracy and a 16% increase in manufacturer part number accuracy, resulting in reduced downtime and operational costs.
These findings emphasize the critical role of accurate and optimized MRO data in minimizing production downtime and associated costs
Analytics & Decision Making
When MRO Master Data is combined with other multi-domain master data disciplines, procurement and production planning teams can readily gain insights into plant-level spends, especially specific to production and maintenance planning.
For instance; An employee master data can provide an accurate picture into human resource spends specific to maintenance and Flowkeep in a specific plant, that can help ascertain the overall spend into maintenance and MRO for a specific plant
Procurement Planning
Procurement planning teams can seriously benefit from a clear view of their MRO parts data and can plan inventory stocking and ensure seamless demand planning through accurately maintained MRO data.
Inventory overstocking costs can be minimized with accurate insights into equipment maintenance requirements and availability of MRO parts at any given point in time.
