Real Estate Investment, Asset Management
Article | May 25, 2023
While many workers plan, at least according to recent surveys, to continue spending at least part of each week working from home, a shorter commute still seems to be holding increasing appeal. The National Association of Home Builders (NAHB ) says its first quarter Home Building Geography Index (HBGI) indicates not only a pandemic driven shift in construction to low density, low cost markets, but a rapid expansion in areas with the shortest commutes.
Litic Murali, writing in NAHB's Eye on Housing blog, says workplaces are moving toward hybrid home/office work models which could affect 30 to 40 percent of the American workforce. This will give renters and buyers increased market power over their travel times and the ability to reduce both housing and transportation costs.
The nationwide average commute is 26 minutes. Those counties in the bottom quintile (lowest 20 percent) have a commute time of 18 minutes or less while the commute in the highest quintile is 28 minutes. The data show that 36.2 percent of the U.S. population resides in the counties in that top slice.
The HBGI indicates that the top two quintiles with the longest commutes together had 63.6 percent of single family building. However, growth was strongest in that bottom quintile with a four-quarter moving average annual growth of 22.2 percent.
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Real Estate Technology
Article | July 25, 2022
It has already been approximately one month since the COVID-19 pandemic thrust the commercial real estate industry in Canada into chaos. Landlords and tenants alike continue to face a litany of issues not previously seen in modern times. Many tenants are fighting for their continued survival, with some jurisdictions in Canada reporting that as many as half of the businesses closed will not re-open once this crisis is over. Landlords are grappling with how to keep their projects viable with so many vacancies looming and cash flow becoming increasingly restricted. How the industry addresses and emerges from the recent events will determine not only the immediate future, but also the long-term evolution of our industry.So how do commercial landlords and tenants proceed in these uncertain times? Below are some key considerations for both landlords and tenants alike.
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Real Estate Investment, Asset Management
Article | May 5, 2023
Real estate is always an attractive avenue for keen investors. The prospects of property appreciation and their potential returns keep luring people every now and then.Investment in residential property in India is always on the boom. However, the commercial real estate investing trend is also witnessing a rise. This is because commercial properties for medical care centres, hotels and shopping malls present bright investment opportunities. They provide huge returns on investment in short time. This is because of the high profits involved.
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Real Estate Advice, Asset Management
Article | May 9, 2023
Explore the latest trends, tools, and strategies for optimizing data-driven real estate asset management services and achieving long-term success with a comprehensive guide to improving business ROIs.
Contents
1 Importance of Data-driven Model for Real Estate Asset Management
2 Seven Steps to Measure Data-driven Asset Management
2.1 Defining the Purpose and Scope
2.2 Identifying the KPI
2.3 Determining the Sources
2.4 Collecting and Cleaning Data
2.5 Data Analysis
2.6 Performance Evaluation
2.7 Continuous Monitoring
3 Effectiveness Metrics for Data-Driven Asset Management
3.1 Occupancy Rate
3.2 Operating Expense Ratio
3.3 Tenant Retention Rate
4 Conclusion
1. Importance of Data-driven Model for Real Estate Asset Management
As real estate technology continues to develop and become more cost-effective for both new and existing business structures, and as collaboration platforms, sensors, and smart devices continue to advance, the amount of data produced by commercial real estate assets is growing exponentially. This data can give real estate market participants like investors, asset managers, property managers, and tenants a competitive advantage and help them avoid disruption if they develop data-driven services and new business models centered on the specific needs of users, owners, or the property itself. However, only a concerted effort by all real estate stakeholders including builders, investors, owners, tenants, and service providers towards data-driven real estate asset management can optimize data to generate insights that improve performance and profitability.
The significance of data-driven models in real estate asset management is growing as the models enable more informed decision-making and more efficient operations by collecting and analyzing data from various sources. Real estate asset managers can gain a greater understanding of the performance of their assets and make more informed management decisions. This can result in increased efficiency, profitability, and tenant satisfaction.
2. Seven Steps to Measure Data-driven Asset Management
Measuring the effectiveness of data-driven real estate asset management services enables businesses to evaluate their current strategies and identify areas for improvement in the services they offer By following these steps to measure asset performance, processes, and activities, businesses can gain insights and make data-driven decisions to optimize performance and maximize returns.
2.1 Defining the Purpose and Scope
The process of measuring data-driven real estate asset management services begins with a clear definition of the purpose and scope of the measurement. It involves conducting a comprehensive review of the business goals as well as identifying specific objectives and purposes for the strategies to develop a well-defined purpose and scope for measuring the effectiveness of asset management services. It helps to ensure that the real estate asset management services are aligned with the broader business strategy.
2.2 Identifying the KPIs
Defining the purpose and scope of data-driven asset management is followed by identifying KPIs to measure success. It requires a clear understanding of critical areas of asset management and selecting quantifiable measures to define success factors and track progress. Choosing the right KPIs provides valuable insights into asset performance, enabling real estate executives and managers to make informed, data-driven decisions to optimize performance and maximize returns.
2.3 Determining the Sources
Identifying the data type, including financial, property, market, and tenant, is essential to determine the sources for evaluating data-driven asset management services. After establishing the data requirements, the sources, such as internal systems and databases, third-party data providers, and publicly accessible data sources, are determined with data compliance and security as the determining factor. Determining sources ensures that the asset management data is trustworthy, current, and accurate, which impacts subsequent decision-making. This step provides the groundwork for data-driven decision-making.
2.4 Collecting and Cleaning Data
Data collection and cleansing are essential for measuring data-driven asset management services. The collected data must be precise, exhaustive, and dependable for subsequent analysis and decision-making. The step involves validating the data for completeness and accuracy, eliminating errors, inconsistencies, and duplicates, and standardizing the data across all sources. The process identifies improvement opportunities, optimizing real estate asset management services for maximum efficiency and profitability.
2.5 Data Analysis
Data analysis plays a critical role in measuring data-driven asset management services. After finalizing the data collection and cleaning step, the data is analyzed using various techniques such as statistical analysis, predictive modeling, and data visualization. These techniques help to identify trends, patterns, and relationships that provide insights into asset performance. Data analysis provides a more profound understanding of the performance of real estate assets, leading to improved efficiency, increased profitability, and enhanced tenant satisfaction.
2.6 Performance Evaluation
Evaluation of data performance to comprehend improvements in the data-driven asset management services starts once the data is analyzed. The performance evaluation step involves comparing actual results to the established KPIs to determine whether the goals are being met or whether there are areas for improvement. It aids in identifying deviations from predetermined objectives and prompts and taking required corrective actions to realign with the business strategy. In addition, this step facilitates identifying improvement opportunities and ensures that real estate asset management services are optimized for maximum efficiency and profitability.
2.7 Continuous Monitoring
Measurement of data-driven real estate asset management services ends with continuous monitoring. To ensure asset management strategies are working, continuously tracking and evaluating KPIs from earlier steps while identifying underperformance and improvement opportunities is involved in the last stage. Operation managers can make data-driven choices, identify risks and opportunities, and optimize asset management strategies for efficiency and profitability by monitoring real estate asset performance. In addition, it ensures that real estate asset management services remain effective over time and can adapt to market changes to maintain a competitive edge.
3. Effectiveness Metrics for Data-Driven Asset Management
Effectiveness metrics for data-driven asset management services are the KPIs used to measure the success of data-driven strategies. These metrics help real estate executives and managers evaluate the performance of their assets and make data-driven decisions for maximum efficiency and profitability.
3.1 Occupancy Rate
The occupancy rate is an essential metric in data-driven real estate asset management. This metric indicates the proportion of a property's rental units that are occupied at present. A higher occupancy rate suggests the property performs well, as more tenants occupy the units. Therefore, this metric can be used by real estate businesses to gauge the efficacy of their digital asset management strategies.
3.2 Operating Expense Ratio
The operating expense ratio is used to evaluate a property's operational efficiency for data-driven asset management. It is calculated by dividing the operating expenses incurred by the property by the total rental income generated. It helps measure the proportion of income consumed by the expenses, such as maintenance costs, utilities, and commercial property management fees. A lower operating expense ratio indicates better cost control and efficient use of resources, resulting in increased profitability for the real estate asset.
3.3 Tenant Retention Rate
In real estate asset management, the tenant retention rate is an essential metric that measures the proportion of tenants who choose to renew their lease agreements. It is an essential indicator of tenant satisfaction and the quality of property management services. A higher tenant retention rate indicates that tenants are satisfied with the property and management, resulting in a stable tenant base, lower vacancy rates, and decreased costs associated with tenant turnover.
4. Conclusion
The significance of utilizing data-driven models for real estate asset management is rising due to digital real estate asset management, technological advancements, and the expansion of collaboration platforms, sensors, and intelligent devices. To gain a competitive edge and avoid disruption, stakeholders in the real estate industry must prioritize the development of data-driven services and innovative business models that cater to the unique needs of users, owners, and the property itself. In addition, the use of data-driven models can also lead to more efficient and informed decision-making, reducing costs along with increasing profits and improving real estate portfolio management.
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