Integrated Cleaning Operations Analytics Dashboard : A Data-Driven Approach to Performance, Cost and Customer Satisfaction Optimization for Crystal Clear Cleaning (Orex Oy)
Mallawa Arachchige, Ruchirani Rangathara Gunawardana (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025122038741
https://urn.fi/URN:NBN:fi:amk-2025122038741
Tiivistelmä
The main goal of this thesis is to develop a centralized data analytics dashboard for Crystal Clear Cleaning which is a subsidiary of Orex Oy, to configure operational performance, cost efficiency, and customer satisfaction. The company handles its cleaning schedules, cleaning supply usage, payment information, the team member allocations and customer feedback via separate manual records mainly in excel sheets which limit the ability to obtain real time information and make data driven decisions
The aim of the project was to design and implement an integrated Power BI dashboard that integrates these fragmented data sources into one platform, enabling managers to monitor key performance indicators (KPIs) interactively and identify improvement areas promptly. The theoretical framework of the thesis is mainly focused on data driven decision making, service operations analytics, and predictive forecasting modelling.
The development process of this thesis followed a practice-based approach, requiring data collection from existing data records, cleaning and transforming datasets in Excel in correct and power BI friendly data format, and visualizing them with Power BI data visualization tool. The dashboards will depict performance analysis, profit analysis, and few predictive forecasting modelling visualizations, and client satisfaction analysis.
The result of this thesis is a prototype analytics dashboard which gives Crystal Clear Cleaning real time transparency, enhances operations and helps data driven management. The implementation shows how digital analytics tools can develop efficiency in service sector, customer satisfaction, and overall operational sustainability in the cleaning industry.
Key words Power BI Dashboard, Operational Analytics, Predictive Analytics, Time Series Forecasting, Cleaning Operations, Customer Satisfaction
The aim of the project was to design and implement an integrated Power BI dashboard that integrates these fragmented data sources into one platform, enabling managers to monitor key performance indicators (KPIs) interactively and identify improvement areas promptly. The theoretical framework of the thesis is mainly focused on data driven decision making, service operations analytics, and predictive forecasting modelling.
The development process of this thesis followed a practice-based approach, requiring data collection from existing data records, cleaning and transforming datasets in Excel in correct and power BI friendly data format, and visualizing them with Power BI data visualization tool. The dashboards will depict performance analysis, profit analysis, and few predictive forecasting modelling visualizations, and client satisfaction analysis.
The result of this thesis is a prototype analytics dashboard which gives Crystal Clear Cleaning real time transparency, enhances operations and helps data driven management. The implementation shows how digital analytics tools can develop efficiency in service sector, customer satisfaction, and overall operational sustainability in the cleaning industry.
Key words Power BI Dashboard, Operational Analytics, Predictive Analytics, Time Series Forecasting, Cleaning Operations, Customer Satisfaction