Performance Indicators to Optimize Continuous Flow in Home Remodeling Industry
Keski-Loppi, Kasperi (2018-07-11)
Performance Indicators to Optimize Continuous Flow in Home Remodeling Industry
Keski-Loppi, Kasperi
(11.07.2018)
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Turun yliopisto
Tiivistelmä
Construction industry – including home remodeling industry – is known to be inefficient. To increase efficiency and competitiveness in the industry, construction companies have started to implement Lean processes. One of these processes, Continuous Flow, has shown promising results in terms of efficiency. However, the industry seems to lack core mechanisms to measure their production performance real-time. This research introduces some already proposed indicators in the context of home remodeling industry. The goal of this research was to resolve how some of these indicators could be implemented in practice, what their technical implementation could be like, and what do they require from the data collection standpoint.
This research took a constructive approach by creating a proof-of-concept IT solution that was used for three weeks in a real world remodeling project. The IT solution collected data for data aggregation and aggregated the collected data to create some of the proposed indicators.
It was concluded that the selected indicators may work in optimizing Continuous Flow. However, reliable indicators require consistent data collection that produce consistent data points. It was concluded through interviews that the data collection did not succeed in terms of consistency. After excluding invalid data points, the indicators did produce results that indicated production performance. Further research is needed to gain more understanding of other indicators.
This research took a constructive approach by creating a proof-of-concept IT solution that was used for three weeks in a real world remodeling project. The IT solution collected data for data aggregation and aggregated the collected data to create some of the proposed indicators.
It was concluded that the selected indicators may work in optimizing Continuous Flow. However, reliable indicators require consistent data collection that produce consistent data points. It was concluded through interviews that the data collection did not succeed in terms of consistency. After excluding invalid data points, the indicators did produce results that indicated production performance. Further research is needed to gain more understanding of other indicators.