Real Estate Technology, Asset Management
Article | May 30, 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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Real Estate Investment, Asset Management
Article | May 5, 2023
If you are intending to invest in real estate and are looking for methods of growing your real estate business successfully to earn a large income as soon as possible, I’m here to give you some quick and simple tips, that are essential when it comes to managing a business and achieving success.
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Real Estate Technology, Asset Management
Article | June 15, 2023
Today’s housing market is full of unprecedented opportunities. High buyer demand paired with record-low housing inventory is creating the ultimate sellers’ market, which means it’s a fantastic time to sell your house. However, that doesn’t mean sellers are guaranteed success no matter what. There are still some key things to know so you can avoid costly mistakes and win big when you make a move.
When inventory is low, like it is in the current market, it’s common to think buyers will pay whatever we ask when setting a listing price. Believe it or not, that’s not always true. Even in a sellers’ market, listing your house for the right price will maximize the number of buyers that see your house. This creates the best environment for bidding wars, which in turn are more likely to increase the final sale price. A real estate professional is the best person to help you set the best price for your house so you can achieve your financial goals.
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Real Estate Technology
Article | December 9, 2021
The construction industry, whether operating at the building level, infrastructure level, or city level, has undergone significant changes over the past decade, and the pace of change has only intensified in the past year. Opaque operating models are giving way to digitalization and transparency in every aspect of the industry, leading to better accountability of the business stakeholder ecosystem and better experience and quality of life for the end customers.
The value realization for the sector is coming in three different ways, each with its set of technologies, tools, systems, and processes that lead to specific value maximization.
1. Connected Stakeholder Ecosystems
Every stakeholder and their interactions and service provision to building and construction has been digitalized and automated.
Architects, urban planners, designers have long been using tools and technologies. The use of 3D modeling and visualization, AR/VR platforms, and drone mapping are creating intuitive means to fast-track the design iteration process and reduce errors. Innovation has been happening in building materials and technologies for smart logistics and inventory management, which is digitalizing the procure to pay cycles and reducing the cost and sustainability footprint of the industry. Infratech is being included into civil construction, and information, communication, and operational tech hardware and software solutions are being integrated at the design stage itself.
The industry uses the services of a network of internal and external third party providers and managers. The combination of mobile and enterprise applications, connectivity, and internet of things devices and variables is connecting these people together. Unified frameworks and digital and AI/ML tools allow seamless construction, management, and optimization of built spaces. The sales process is becoming highly digital with the use of customer relationship management platforms, channel management applications, and digital sales aids that blend AR/VR, 3D visualization, audio, video, and digital.
The governance and financial mechanisms have evolved as well. Government bodies have digitalized and permissions, access rights, and payment mechanisms are increasingly digital. Regulators are moving towards real time sensor based monitoring and centralized digital reporting on effluents and emissions, aiming to improve sustainability metrics. An array of digital and cloud financial management tools, systems, and dashboards allow every aspect of the financial flow to and from entities to be managed, monitored, and optimized.
The users, in both the customer and citizen persona, have become digitally savvy and experiential. The connected and sentient building, infrastructure, and city ecosystem increasingly allows for connected living where many services can already be accessed digitally.
2. Connected Lifecycle Management
The construction industry is using digital and automation technologies at every stage of projects – from design to monetization of building, infrastructure, or city systems. Ingredient technologies such as internet of things, artificial intelligence, block chain, distributed computing, edge and mesh intelligence, cloud computing, big data analytics, and data visualization are allowing the industry to plan better and act predictively.
The Design phase, in addition to using design and planning tools and technologies, is increasingly adopting concepts of wellness, biophilia, and blue-green integrations to blend technology and architecture.
The Build phase has significantly transformed through innovative construction materials and methods, as well as digital, cloud, and sensor based solutions to monitor staff, progress, audits, and errors in construction. The entire land records management system in the country has been digitalized, and plans are underway to use drone based mapping to catalogue all assets and sites at a national level.
The Sell phase is using technologies and platforms that have disintermediated some ecosystem partners and aggregated others, increasing the flow of information, communication, validations, and transactions. From marketing to site visits to legal documentation and commercial transactions, every step has been digitally transformed through a combination of AR/VR, AI/ML, digital, and cloud technologies.
The Operate phase is seeing newer models of maintenance and management of assets over the long term. Tech enabled metering and monitoring allows for discretization of pay per use type of commercial arrangements, which can be digitally contracted and managed. This allows multi-stakeholder and multi-user assets to operate seamlessly. Multiple automation and real time monitoring systems and solutions – whether fully integrated or point solutions, are enhancing visibility and improving efficiency of operational performance.
The Experience phase ensures an interplay of operational and service related systems and technologies allow the users to better access services at building, infrastructure, or city level. There is a lot of emphasis on enhancing customer experience by reducing wait times, improving service levels, creating areas and systems for interaction and engagement, and delivering a better quality of work or life to the end user.
The Monetization phase is increasingly at the top of mind of administrators, owners, and operators of construction assets. Long return on investment cycles and complex modes of deployment of public and private capital predicate focus on easing the flow of money and identifying multiple modes of monetization to ensure that projects can succeed. Value added services through retail, advertising, data, or service based use cases are allowing for recurring revenues to be generated. Many of these services can be digitally conceptualized, delivered, and managed.
3. Connected Systems and Services
Buildings and infrastructure spaces are increasingly envisioning themselves as an interconnected system of functions, utilities and services, all managed centrally and digitally through a building level control room or an infrastructure or city level integrated control and command center.
The set of technologies first adopted for smart cities - such as networking and connectivity; smart management of water, waste, lighting, power, sewage, air quality and emissions; smart access to services and retail; interconnected mobility, parking, and traffic management; and managing request-response systems and on-demand servicing and issues management - are increasingly becoming important for buildings and infrastructure projects. Transport hubs are reimagining themselves as microcities. Road assets are creating logistics hubs and multiple digital monetization channels. Buildings are transforming into mixed use spaces that are accessed and managed digitally. On-demand, surge, discounted pricing mechanisms rely on complex algorithms and predictive forecasts.
Multiple indices and standard comparative metrics are being considered by users, governments, regulators, and financiers of patient long-term capital. At the building level, Green ratings and Well Building standards are being measured and reported, and creating methods of differentiating premium and non-premium buildings. Global Infrastructure rankings rate countries in the quality and density and access of road, transport, utilities, and other major infrastructure systems and projects. Ease of Living Index and Sustainable Development Goals create the benchmarks to measure and monitor the performance and impact of city systems. Increasingly, gamification through Swachh Survekshan, Municipal Performance Index, and other city, state, and national level assessments is creating awareness and improving service levels. The indices themselves rely on a set on technology inclusion within projects and technology systems to aid performance measurement.
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