April 30, 2026
Operational efficiency and performance in the real estate sector: DMAIC method
Jéssica Carvalho das Chagas; Vagner Ferreira
Summary prepared by the ResumeAI tool, an artificial intelligence solution developed by the Pecege Institute focused on synthesis and writing.
Property management in the contemporary scenario is outlined by reduced financial margins, high operational costs, and a rigorous demand for regulatory compliance, factors that make operational efficiency a substantial element for organizational survival. In markets where competitiveness is fierce, operational efficiency ceases to be just a differentiator and becomes a basic necessity for sustenance (Slack et al., 2020). In the real estate sector, specifically in condominium administration, companies face the challenge of dealing with margins that, although secure, are considerably lower when compared to other activities in the segment (Buildium, 2023). This reality is aggravated by a dense administrative burden and the need for extreme service customization, as the market is highly capillary and each client has unique specificities. To balance the delivery of high-quality services with the necessary profitability, the adoption of rigorous performance measurement methods becomes fundamental to support sustainable growth. The absence of structured models for this measurement severely impairs the ability to identify failures and optimize processes, which invariably results in inefficiencies and uncontrolled cost increases (Werkema, 2012).
The implementation of data-driven measurement systems is a central pillar for improving organizational performance, as it allows strategic decision-making to abandon empiricism and be based on concrete evidence (Jacobs, 2021). In the context of companies experiencing exponential growth, as is the case with organizations with almost two decades of operation that position themselves with personalized services, internal complexity tends to increase, making standardization of activities difficult. Manual control and inspection methods, which may be effective in small structures, become unviable and obsolete as the operation scales. Therefore, the development of a performance measurement model not only accompanies operational expansion but ensures that service quality is not diluted by the increase in workload. The theoretical foundation for such a structure is supported by Lean Six Sigma, which combines the waste elimination philosophy of lean manufacturing with statistical rigor for variability reduction (Werkema, 2012). Lean Thinking guides the organization to specify value from the customer’s perspective, identify the value stream, create continuous flow, establish pull production, and relentlessly pursue perfection (Womack; Jones, 1998).
The pursuit of continuous improvement is reinforced by the Kaizen philosophy, which establishes that no day should pass without some form of improvement being made in the organization (Ohno, 1997). This approach, originating from the Toyota production system, demonstrates that it is possible to increase productivity and quality without the immediate need for large financial investments, provided there is focus, discipline, and cooperation among teams (Imai, 1994). Companies that adopt Kaizen seek to eliminate the causes of undesirable results and constantly improve routines, introducing new levels of control that stabilize processes (Campos, 1992). Complementarily, the use of tools such as the five whys technique allows for deep and systematic analysis to find the root cause of detected problems, preventing solutions from attacking only superficial symptoms (Ohno, 1997). The stabilization of these processes is guaranteed by standardized work, which ensures that activities are performed within defined time intervals and in pre-established sequences, reducing variability and creating an environment conducive to critical analysis and the resolution of recurring problems (Nishida, 2000; Womack, 2010).
To structure an effective performance measurement model, the Define, Measure, Analyze, Improve, and Control (DMAIC) methodology serves as a structured guide that highlights the progress achieved in relation to established objectives (George, 2002). In the definition phase, the project scope is validated and the relevance of the problem is analyzed from different perspectives, using tools such as the problem map to identify causes, consequences, and impacts (Júnior, 2013). The “How Might We” technique assists in formulating questions that frame challenges in a way that stimulates solution-oriented ideation, ensuring clarity and focus on objectives (Rosala, 2021). Subsequent measurement determines the problem focus through initial data collection, while analysis investigates priority causes and validates the root cause of critical processes (Werkema, 2012). The improvement stage proposes and implements solutions evaluated by prioritization matrices that relate execution effort to expected impact, allowing management to focus on interventions that generate quick and sustainable results (Moura, 1989). Finally, the control phase ensures that achieved goals are maintained over time through standardization and continuous performance monitoring.
The methodology adopted for the development of this study is characterized as a descriptive research with a quantitative approach, focused on describing the characteristics of a specific population and establishing relationships between operational variables (Gil, 2019). The main method consisted of a case study applied to a company in the real estate sector, here named Company X, which manages over 200 developments nationwide and has a staff of over 600 employees. Participatory research was the chosen design, involving the definition of a conceptual framework, collaborative planning of the problem situation, data collection and analysis, and report generation to test the theories of the theoretical framework. The process began with an exhaustive literature review on operational efficiency, process control, and performance management, using authors such as Werkema, Paladini, Womack, and Slack to support the model to be developed.
Secondary data collection was carried out through the organization’s enterprise resource planning system, i9, which allows for online management of developments. Each building manager enters updated information and documents into the platform, which are compiled into reports on the quantity of mandatory documents, monthly management reports, and current contracts. The analysis period covered the months of January to April 2025. In addition to systematic data collection, direct observation was used at the “gemba,” the place where operations occur. Three developments with distinct profiles, defined in conjunction with the operations directorate, were visited to observe the practical execution of processes and identify bottlenecks that would not be visible solely through numerical data. This immersion allowed for the validation of hypotheses raised during brainstorming sessions held with senior management in October 2024, where operational challenges and the lack of clear metrics for monitoring internal processes were discussed.
Data analysis followed a descriptive nature, using information extracted via Application Programming Interface (API) and organized into electronic spreadsheets. Operational compliance was calculated as the ratio between the number of compliant items and the total number of items evaluated in each development, generating specific percentage indicators. To obtain a global indicator representative of the company, a weighted average of individual results was applied, using the volume of items evaluated in each case as the weight. This methodological choice ensured that developments with a higher administrative load had a proportional influence on the consolidation of results. Based on these indicators, dashboards were developed in the Microsoft Power Automate system to facilitate data interpretation and ensure transparency to stakeholders. The use of pattern recognition techniques allowed for the transformation of observable characteristics into consistent numerical values, supporting continuous improvement as advocated by quality management literature (Paladini, 2024).
The performance measurement model was structured around three critical requirements that reflect the organization’s strategic priorities: the regularity of mandatory documentation, the regularity of contracts, and the timely delivery of the Monthly Management Report (RGM). The mandatory documentation comprises 19 essential items for the legal and safe operation of the ventures, whose validity and accessibility reduce the risk of penalties and reinforce customer trust. Contract management focuses on the registration and updating of all legal instruments related to service provision, avoiding operational interruptions. The RGM is the main channel of transparency with the client, and must be entered into the system within the agreed timeframe and with high-quality information. The percentage performance of each venture was defined by the arithmetic mean of the conformity of these three pillars, composing an overall ranking disclosed to the entire organization to encourage healthy competition and alignment with strategic objectives (Attadia; Martins, 2003).
The initial results obtained in January 2025 revealed a scenario with significant opportunities for improvement, showing an average global performance of 64%. The breakdown by indicator showed that mandatory documentation conformity (CDOC) was only 44%, while contract regularity (CONT) reached 57% and the delivery of management reports (CRGM) presented the best initial index, with 81%. Qualitative analysis carried out in the “gemba” and brainstorming sessions identified priority problems, such as the absence of RGM preparation in some units, irregular documents or documents not entered into the system, unregistered contracts, and a generalized lack of knowledge of the processes by those responsible. Furthermore, a lack of manager follow-up on the quality of deliveries and the absence of standardized procedures were noted, which generated frequent customer complaints about lack of transparency and bottlenecks in supplier payments due to contractual irregularities.
Given this diagnosis, the work team, composed of the performance executive, a technical coordinator, and a systems analyst, developed an action plan focused on resolving the root causes. The first intervention consisted of defining an organizational knowledge management policy, establishing guidelines for standardization, registration, and systematic training. A channel was created on the intranet for the dissemination of process standards with mandatory read confirmation by users. Personalized training sessions were conducted to equip teams with the new standards, consolidating a culture of continuous improvement according to the organization’s specific needs. For critical processes, system manuals and specific process standards were created for mandatory documentation, RGM, and contract management, the latter including a direct link to the payment module to prevent the settlement of supplier invoices with irregular contracts.
The implementation of these actions led to significant progress in conformity indices over the analyzed period. The Monthly Management Report (CRGM) delivery indicator showed the most pronounced evolution, jumping from 44.1% in January to 89% in April 2025, representing a gain of 45 percentage points. This advance is particularly relevant as it directly impacts the final customer’s perception of value, who began to receive information about their assets’ performance in a more agile and structured manner. The regularity of mandatory documentation (CDOC) also showed consistent progress, starting from 57.2% and reaching 83.9% in April, an increase of approximately 27 percentage points. This improvement significantly enhances the legal and operational security of the managed ventures, reducing the company’s exposure to regulatory risks and fines.
The contract management indicator (CONT), which already presented a higher initial level of 81.1%, showed greater stability and reached 95.9% at the end of the period, an increase of 15 percentage points. The consolidation of this index at near-perfect levels ensures that almost all third-party relationships are duly formalized and monitored, optimizing financial flow and the continuity of building services. The monthly disclosure of these results through the performance ranking on the intranet ensured absolute transparency and promoted formal recognition of the best-performing teams. This structured feedback process is essential for maintaining employee engagement and aligning individual efforts with the organization’s macro objectives. The use of automated dashboards allowed regional managers to track the evolution of their portfolios in real-time, facilitating quick interventions in units that showed deviations.
The discussion of the results in light of the literature confirms that the transformation of observable characteristics into numerical indicators is the path to a consistent quality assessment (Paladini, 2024). The developed model not only measured performance but also served as a strategic tool for the marketing and sales teams, who began to use compliance data as proof of management effectiveness in commercial proposals. The transparency generated by the measurement system strengthened customer trust, who now have full visibility over the regularity of their assets. However, the research also revealed limitations, such as the need for even more automated integration between systems to reduce the burden of manual data entry and the importance of structuring recognition processes that include financial benefits linked to achieving performance goals.
For future research, it is suggested to cross-reference operational performance data with customer retention indicators (churn rate) and satisfaction levels (NPS), in order to quantify the direct financial impact of operational efficiency on customer base loyalty. The study of the feasibility of implementing artificial intelligence algorithms for automatic document auditing is also recommended, which could further elevate compliance levels and reduce administrative effort. The culture of continuous improvement established during the project must be fueled by constant cycles of indicator review, ensuring that the model remains aligned with the changes in the real estate market and new regulatory requirements that may arise. The definitive incorporation of the model into Empresa X’s routines demonstrates that data-driven management is a point of no return for organizations seeking excellence and competitiveness.
It is concluded that the objective was achieved, as the performance measurement model developed provided rigorous control and unprecedented visibility over the levels of efficiency and quality in the operational processes of the analyzed company. The application of the DMAIC methodology allowed for the identification of historical bottlenecks and the implementation of structured solutions that resulted in significant increases in the compliance rates of documents, contracts, and management reports in just four months. The transition from manual methods to a data-based monitoring system and automated dashboards consolidated a culture of continuous improvement and transparency, strengthening the organization’s reputation with its stakeholders and clients. The model proved to be a vital strategic tool, capable of reducing operational risks, optimizing costs, and serving as a competitive differentiator in the real estate market, although there are still opportunities for full automation of indicators and the structuring of financial incentive policies linked to performance.
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