TY - JOUR
T1 - Analysis of manual data collection in maintenance context
AU - Mahlamäki, Katrine
AU - Nieminen, Marko
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Purpose: The purpose of this paper is to identify details of technological, organizational and people (TOP) factors affecting maintenance technicians’ use of computerized maintenance management systems (CMMS) in manual collection of asset data. Design/methodology/approach: In addition to TOP factor details, results from six case studies in Finland, India and the Caribbean are presented. Interviews and observations clarify the role of TOP factors in CMMS use in industrial maintenance. Findings: In total, 17 detailed TOP factors are identified and criteria for analyzing CMMS contexts with them are defined. Analyzing the cases with these factors reveals that technicians who collect good quality data have received good training and instructions for the CMMS, are competent, and understand how manually collected data benefits them in their own work. However, even these sites struggle with the usability of the CMMS. Research limitations/implications: The 17 TOP factors and the criteria for CMMS evaluation extend understanding on context and usability in manual data collection. Case study method does not imply the relative importance of the TOP factors, which calls for future research using quantitative methods. Practical implications: Management can use the criteria to analyze the context of manual data collection for improvements, e.g., in CMMS usability. Originality/value: Insights from industrial environments and a new way of studying contextual factors of CMMS use are presented. The results extend a data quality research framework with details to manual data collection and define the TOP factors in CMMS context.
AB - Purpose: The purpose of this paper is to identify details of technological, organizational and people (TOP) factors affecting maintenance technicians’ use of computerized maintenance management systems (CMMS) in manual collection of asset data. Design/methodology/approach: In addition to TOP factor details, results from six case studies in Finland, India and the Caribbean are presented. Interviews and observations clarify the role of TOP factors in CMMS use in industrial maintenance. Findings: In total, 17 detailed TOP factors are identified and criteria for analyzing CMMS contexts with them are defined. Analyzing the cases with these factors reveals that technicians who collect good quality data have received good training and instructions for the CMMS, are competent, and understand how manually collected data benefits them in their own work. However, even these sites struggle with the usability of the CMMS. Research limitations/implications: The 17 TOP factors and the criteria for CMMS evaluation extend understanding on context and usability in manual data collection. Case study method does not imply the relative importance of the TOP factors, which calls for future research using quantitative methods. Practical implications: Management can use the criteria to analyze the context of manual data collection for improvements, e.g., in CMMS usability. Originality/value: Insights from industrial environments and a new way of studying contextual factors of CMMS use are presented. The results extend a data quality research framework with details to manual data collection and define the TOP factors in CMMS context.
KW - Data quality
KW - Human factors
KW - Industrial maintenance
UR - https://www.scopus.com/pages/publications/85063008175
U2 - 10.1108/JQME-12-2017-0091
DO - 10.1108/JQME-12-2017-0091
M3 - Article
AN - SCOPUS:85063008175
SN - 1355-2511
JO - Journal of Quality in Maintenance Engineering
JF - Journal of Quality in Maintenance Engineering
ER -