The Journey to Maintenance Excellence:Master Data (Part II)

Data Gathering

Data gathering is a crucial part of CMMS/EAM implementation. In this process, data is gathered on each piece of equipment. PM and safety procedures, parts information, vendor information, and employee information also need to be defined and implemented in the CMMS/EAM. Maintenance operations often attempt this with their existing manpower; however, in most cases they are already short on manpower, so this is not a feasible alternative. Data gathering is a massive undertaking, and in some cases gathering and entering the data yourself could take four to five years to complete. A major reason 80% of CMMS implementations nationwide have failed in the past is a lack of expertise and sufficient manpower for data gathering and entry. If your operation requires data gathering, you should consider hiring an experienced outside firm.

Data Cleansing

Before existing data can be transferred to a new CMMS/EAM, it needs to be cleansed so that corrupt data is not transferred to the new system. In existing systems, data often gets corrupt after five to ten years and also needs to be cleansed. In this process, the data is carefully reviewed for accuracy, spelling errors are corrected, and letter casing is uniformly converted to upper case. The data is normalized following a specific style guide so that manufacturer/supplier names, attribute values, abbreviations, units of measurement, etc., are consistent. Noun/modifiers are assigned to parts in order to aid in identification and part grouping. Duplicates are identified using a mixture of software, database queries, and manual inspection and are then removed. Descriptions are then rearranged to follow a consistent order.

Data Classification

The data-classification process, which involves categorizing data to increase its usefulness and efficiency, is crucial for an effective CMMS/EAM implementation. Depending on the needs of the maintenance operation, the data is classified to a variety of popular, global-standard schema (such as eCl@ss, UNSPSC, MESC, SMD, NAICS, NIGP, etc.) or to in-house/proprietary schema. Specific configuration requirements of the CMMS/EAM, such as field name, character limitation, and type, will have to be considered when determining formatting.

Data Enrichment

During the data-enrichment process, all possible critical information is collected in order to improve the quality and usefulness of the data. Data will likely have to be collected from a variety of sources. Web research can be conducted and information can be sourced from the manufacturer websites. If web research does not yield any results, the suppliers can be directly contacted (by email, phone, or fax) for additional data. A manual plant walk-down, in which data is collected from various sources within the plant (such as stores, item master, purchase orders/requisitions, codification rules, tags, nameplates, catalogs, etc.), may also be required. During the plant walk-down, technical data such as measurements are also gathered.

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Kris Bagadia is a world-renowned CMMS/EAM expert. He is the founder and CEO of PEAK Industrial Solutions, LLC, a firm specializing in maintenance consulting, training and computerized maintenance management system (CMMS) implementation. He has helped a wide variety of clients ranging from universities to hospitals to manufacturing plants to turn their maintenance into profit centers through comprehensive maintenance efficiency assessments (audits). He has helped dozens of clients save money, reduce downtime, and convert from reactive to proactive maintenance. Visit for more information.
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