May 31, 2021
RPA in real estate: an opportunity to explore
RPA Business Analyst
Nowadays, the typical archetype of a smiling real estate agent with extraordinary interpersonal skills, able to get rid of unsaleable properties, has become pretty common across the media. However, the success of this industry, the global market value of which in 2020 was estimated by Research and Markets at $2.7 trillion and looks set to reach $3,7 trillion by 2025, also lies in the work of administrators, marketers, and accountants.
Their efforts don't always have much to do with public relations, but rather with piles of paperwork higher than a five-floor manor. At least virtually, as most of these procedures are digitized and performed on a computer.
Anyway, the manual processing of documents and data is massive, depriving these professionals of precious time that would be more useful and motivating to devote to tasks with a greater strategic, social and creative component.
How to streamline and speed up these clerical operations while improving accuracy and saving money? A possible answer to this dilemma has come in recent years from various automation technologies, which aim to replace or support human operators with bots and virtual assistants in carrying out particularly tedious and time-consuming tasks. One of the foundations of this innovative and rapidly spreading approach is robotic process automation (RPA).
Let's start our analysis with a significant sore point. Real estate has traditionally shown a limited propensity for change, especially compared to other sectors. A good bunch of real estate companies still use spreadsheets when collecting and analyzing data for property evaluation, invoices, lease administration, and so on.
"The real estate industry is still in the infancy stages of technology innovation"
Co-founder and CEO of ShelterZoom Corp
This could be due to the fact that interpersonal relationships between agents and customers are still perceived as a crucial point. For example, according to estimates by the National Association of Realtors, 41% of sellers who turned to real estate agents found theirs through the recommendation of friends and family. Therefore, many professionals may be skeptical of delegating part of their duties to software.
However, this sector is no stranger to new solutions. These advances, which may be grouped into so-called “real estate technology”, encompass many different business aspects and processes, including the appraisal, leasing, marketing, and management of residential, commercial, and industrial facilities.
The first major innovation in this sense was the shift of residential listings from print to digital media. A further step forward involved innovative tools to make properties more accessible, such as Airbnb. What we are seeing now is the latest wave of this evolutionary process, related to the growing adoption of automation solutions, such as RPA.
RPA entails the deployment of software robots which are programmed to mimic typical human actions and fulfill a wide range of repetitive and high-volume duties. The business operations best suited to be automated with RPA in real estate are those involving huge amounts of data entry and processing operations. Among them, we can mention:
The results achievable by investing in robotic process automation consulting and leveraging RPA robots for the aforementioned processes might be truly remarkable in terms of money savings. According to Deloitte, 45% of the companies surveyed expected cost savings of 10 to 20%, while 27% of these agencies were even aiming for savings of 20 to 40%.
RPA in real estate also looks very promising with regards to potential time savings. According to our partner and business automation leader UiPath, one of the top Malaysian real estate companies, Sunway Group, reduced processing times by 30% across 35 high-value business operations with an RPA solution empowered by AI.
While physical operators can easily get distracted or frustrated after repeating yet another operation and, as a result, make mistakes, RPA robots are fast, tireless, and almost foolproof workers when carrying out straightforward tasks.
This technology is also highly scalable by increasing the deployment of bots in various business processes, and is relatively simple and inexpensive to implement. That's because RPA robots, unlike other more intrusive tools, can easily operate with legacy IT systems on the front-end, without the need to replace previous configurations.
This ease of integration and flexibility makes RPA solutions ideal when it comes to connecting multiple IT systems that would normally struggle to communicate with each other. Think of an email client and an ERP system used by a real estate company. To move data from one software to another, employees should manually extract the required information from incoming emails and upload it to the ERP. This activity can be automated by adopting a bot that will take care of bridging gaps between the two systems.
Does this mean that RPA robots are flawless? Obviously not. Especially in their "basic" version, these assistants are limited to dealing effectively with standardized, rule-based tasks and recurring scenarios because they follow pre-established instructions without asking too many questions.
To make bots smart, i.e. able to learn from experience, understand the context in which they operate, and face any exceptions to the rules, they need a little boost. Indeed, the most recent trend is to enhance RPA solutions with AI, machine learning, and cognitive technologies. The result of this teamwork is known as intelligent process automation (IPA), and while not necessarily implemented in all situations, it's becoming a standard choice for many companies.
The list of RPA use cases in real estate is quite long. We can aggregate some of the most common and significant ones in terms of potential ROI into three main categories.
Let's start our roundup of RPA use cases from the most distinctive aspect of the real estate sector, namely property and facility management. This highly process-centric aspect of the industry involves a wide range of repetitive and rule-based activities that can be improved in efficiency and accuracy by implementing RPA:
While not exclusive to this sector but common across all industries, the natural protagonists of RPA in real estate are probably the financial, tax and accounting processes. The key role that bots can play in back-office activities is determined by at least three factors.
First, the typical activities performed in these departments are generally repetitive, high volume, and well-structured. Therefore, easily manageable by RPA bots. Just think of the time and effort required of accountants to manually monitor the huge amount of invoices, payments, renewals, and lease contract changes.
Second, delegating these activities to bots with a zero-error rate significantly reduces one of the main business risks, namely the likelihood of fraud and human error.
Third, as a direct consequence of the previous point, the greater accuracy achieved by bots in managing administrative practices is an important catalyst for regulatory compliance, both in terms of personal data management and tax legislation.
Some of the accounting and financial activities worth automating are:
Management and accounting would be useless if real estate properties were not sold or rented. Marketing represents an important boost in this regard, and many of its processes can be automated with RPA, too:
RPA in real estate is a technology with an immense potential. However, like all great innovations, it also entails controversial implications and needs to be implemented wisely. Three factors should be taken into account by any company that is planning to deploy bots in its business workflows:
Forward-thinking companies should pay attention to these variables and consider the relative backwardness of the real estate sector as a potential asset. Because if it is true that this industry as a whole is a couple of steps behind the others in terms of automation, it also means that the innovation leaders will benefit more from the implementation compared to their competitors.
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