González, V; Alarcón, L F; Maturana, S; Mundaca, F and Bustamante, J (2010) Improving planning reliability and project performance using the reliable commitment model. Journal of Construction Engineering and Management, 136(10), pp. 1129-1139. ISSN 0733-9364
Abstract
Commitment planning reliability at an operational level is a key factor for improving project performance. In the last 15 years, the Last Planner System, a production planning and control system based on lean production principles, has improved commitment planning reliability in the construction industry. However, many construction decision makers continue to rely on their experience and intuition when planning their commitments, which hinders their reliability. The reliable commitment model (RCM) is proposed to improve commitment planning reliability at the operational level by using statistical models. RCM is an operational decision-making tool based on lean principles that supports short-term forecasting commitment planning using common-site information such as workers, buffers, and plans. RCM was tested in several case studies, demonstrating its production forecasting capabilities and its ability to help increase commitment planning reliability and improve project performance. RCM also supports workload and labor capacity matching decisions. RCM has the potential of becoming a useful production decision-making tool.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | commitment planning reliability; decision making; lean production; matching load-capacity; project performance; reliable commitment model; statistical models |
| Index terms: | commitment, production planning, lean production, workload, intuition, decision-making, last planner system, control system, becoming, forecasting, case study, statistical model, construction industry, project performance, buffer |
| Subjects: | management, manufacturing engineering, monitoring and control, financial risk, project management theory and practice, project controls, decision analysis, cognitive psychology, industry analysis, philosophical process, data collection methods, psychology, data science, prediction and forecasting, project delivery |
| Topics: | Cost Management, Business Strategy, Engineering Principles, Research Practice, Project Management, Risk Management, Human Resources, Time Control, Organizational Design |
| Descriptive scope: | 5 PCTEA |
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