https://doi.org/10.24928/2024/0118

Unveiling the Hidden High Variability in Processes With Stable and Good PPC Results

Omar A. Samaniego1

1Engr., Master, NEC-ECC PMA, VDC, PMP®, PMI-RMP®, Risk Management Program Director, Universidad Peruana de Ciencias Aplicadas, Quality Consulting Solutions Director, author and independent researcher, [email protected], [email protected], https://orcid.org/0000-0003-4352-2610

Abstract

Despite high and stable Percentage of Plan Completed (PPC) values obtained in projects where Last Planner® System (LPS) was implemented, construction processes often conceal variability, undermining true completion. Likewise, LPS metrics rely on a deterministic approach for measuring the performance of processes without contrasting them with non-deterministic variables, which can provide a new perspective and new room for improvement. This is why, this paper introduces four new metrics – Percentage of Plan Completed+ (PPC+), Percentage of Plan Completed++ (PPC++), Percentage of Plan Completed+ based on random scheme (PPC+r), Rate of Waste (Rw), and Rate of Planning Assessment (Rpa) – to unveil hidden variability around activity daily schedule, rework, excess capacity, and planning. Further, utilizing statistical modeling to define the pioneering stochastic indicator Rpa, the study presents an important leap from traditional LPS deterministic metrics. Thus, by also conducting one survey among LPS practitioners on PPC conception and usage, it illuminates how seemingly stable estimated PPC values can misrepresent process performance. These metrics offer a transparent brand-new assessment way, revealing new opportunities for improvement aligned with lean principles. The study also provides foundation and directions for further research on hidden variability which can propel the current LPS approach.

Keywords

Lean construction, Last Planner® System, PPC, metrics, stochastic indicator.

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Reference

Samaniego, O. A. 2024. Unveiling the Hidden High Variability in Processes With Stable and Good PPC Results, Proceedings of the 32nd Annual Conference of the International Group for Lean Construction (IGLC 32) , 316-327. doi.org/10.24928/2024/0118

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