Case Study in PropTech: helping real estate developers & Investors

This Case Study by Prabhat PropTech elaborates adoption of latest technologies such as SaaS platforms ERP and CRM employing Data Science and Business Analytics- by real estate developers to successfully operate their business in a complex environment.

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Proptech Revolution in Indian Real Estate

1. What is Proptech?

Proptech refers to the integration of technology into real estate processes, transforming how properties are bought, sold, managed, and experienced.

#Proptech includes different technologies like artificial intelligence (AI), big data analytics, virtual reality (VR), and blockchain.

2. Benefits of PropTech for Mid-Size Developers:

Streamlined Operations: automate repetitive tasks, allowing developers to focus on strategic decisions and client relationships1.

Cost Savings: By digitizing processes, mid-size developers can reduce resource expenses and enhance efficiency.

Pre-Sales and Lead Management: Online channels facilitate pre-sales processes, lead management, and unit bookings, improving overall productivity2.

Market Insights: Advanced data analytics and AI provide valuable market insights, helping developers make informed decisions based on property prices, demand-supply dynamics, and consumer preferences.

Smart Buildings : optimize energy efficiency, security, and comfort in buildings, benefiting both developers and occupants.

Property Management Solutions: Proptech streamlines property management, enhancing tenant experiences and maximizing returns on investment.

Consider Indian real estate sector that is witnessing rapid proptech adoption. Notable companies like #NoBroker and #Livspace leverage technology to revolutionize property transactions and management.

The Confederation of Real Estate Developers’ Association of India (CREDAI) launched a $100 million proptech fund, Spyre Proptech Venture Fund, to support startups in this space.

The market is expected to grow at 9.6% from 2021 to 2025, reaching $100 billion by 2030.

4. Future Prospects:

PropTech has immense potential to create transparency, efficiency, and customer-centricity in the Indian real estate market, driving business forward3.

As technology evolves, real estate tech firms will continue to maximize their impact.

In summary, proptech empowers mid-size developers by optimizing processes, providing insights, and enhancing overall efficiency. Its growth trajectory in India is promising, making it a pivotal force in shaping the future of real estate

Case Introduction:

Real estate developers face the triple challenge of

(a) trust deficit among potential buyers,

(b) unusually high inventory levels in residential projects

(c) uncertain regulatory framework relating to taxation and project approvals.

Decision making becomes stressful when developers have to meet various conflicting goals.

Business Analytics and Data Science tools are being employed to decide optimum course of business actions, after evaluating probability of success in various business scenarios.

This case study focuses on mid-size residential apartment project(s), located within developing cities of Maharashtra.

Business Case: A mid size real estate developer

Abhijeet is a young and dynamic second generation real estate developer. He is leading their family owned real estate business as his father’s health had deteriorated recently.

Abhijeet boasts of an engineering degree followed by MBA in operations management. He had acquired the ‘tricks of the trade’ from his father, having worked for over 7 years in their family business. However, Abhijeet is struggling to find shores amid the severe strain faced by residential realty sector post year 2013.

Abhijeet relies on experience of his engineering team for completion of ongoing residential real estate projects. These projects often run behind schedule leading to cost overrun. Controlling quality of work done by small contractors while meeting project cost and schedule remains challenging.

Oversupply in national as well local residential real estate market has impacted demand from buyers affecting all of his projects. Abhijeet had to offer higher commission to real estate agents whom he relies on to bring buyers. Expensive promotional campaigns involving online and offline adverts, were proving ineffective.

Presently his biggest worry is to kick-start launch of three new residential real estate projects, which were postponed since 2016 due to slowdown in the sector. He need to rework the project proposals; amid rising cost of financing, lack of interest among investors and increased compliance requirement from RERA and GST.

During a business conference, Abhijeet became aware of the vast potential that Business Analytics and Data Science tools offer. He approached Growth Pattern Consulting, a B2B consultant specializing in business analytics. Growth Pattern Consulting assigned a team to evaluate the business of Abhijeet. They offered to implement ‘business analytics framework’ and resolve his business issues within two months.

Value Discovery:

· Real estate market has been termed complicated and volatile by industry experts.

· For all stakeholders – including developers, lenders, buyers and affected local communities – the decision making process is fairly complex with high risk of making a wrong choice.

· Real Estate transactions involve very high per unit cost. Often buyer is investing their lifetime savings in real estate.

· Developers struggle to reach potential buyers or investors.

· Conventional strategies for customer acquisition are unable to meet the sales target.

· Companies in the sector are stressed to improve operational efficiency and customer experience.

· Home-buyers and renters are dependent on brokers for their real estate transactions.

Methodology:

Real Estate Analytics is a scientific process of transforming industry data into valuable insight – for making decisions with higher accuracy. Analytics makes use of information from different sources, application of digital technologies coupled with statistical analysis and mathematical modeling – to gain improved insight about business operations.

Different types of analytics methods i.e. descriptive analytics, predictive analytics and prescriptive analytics may be employed depending on customer requirement and complexity of the problems involved.

Prabhat PropTech recommended their proprietary 7-stage ‘business case solution’ technique to address the issues faced by Abhijit in his business operations. After initial assessment, issues faced by Abhijeet were categorized as follows:

· Project Completion: Control work quality, cost escalation while improving profitability for ongoing projects.

· Customer Acquisition: Sale of ready possession or under construction units at competitive pricing and in line with sale targets.

· Re-assessment of New projects: detailed evaluation and conceptual design, based on change in market dynamics, policy changes and compliance under RERA/GST.

Each of the above issues were appropriately analysed with due consideration of industry benchmarks, past and present industry trends, regulatory changes, legal compliance, project financing, target consumer segment, competition, demand/supply/inventory levels, price sensitivity, trust deficit among potential buyers, etc.

Prabhat PropTech developed data based Real Estate Model for each project location, based on detailed market research and organising industry information from numerous sources. Each of the analytics model involved over 300 parameters covering apartment and building design, buyer preferences, socio-economic developments, market dynamics, locality and neighborhood, accessibility, security, amenities as well as financial modelling for developer and potential buyers. These models are further customized for individual project depending on specific business case(s), as applicable.

Once the model is validated and met expectation of customer, it is used to evaluate various business operation scenarios. Individual scenario outcome is further studied by engaging the customer’s team and industry experts.

Using advanced optimisation techniques, most probable business scenario is identified. These findings were then used as basis for deciding future course of action.

Conclusion:

Based on rigorous analysis carried out by Growth Pattern Consulting, Abhijeet was confident of the recommended course of actions as summarized below:

1. Abhijeet adopted appropriate technology, to improve his business processes to match industry benchmarks, helping avoid delays in ongoing projects, improve work quality and project financing.

2. He was assured of improved returns from sale of units from his ready possession and ongoing projects. This included improved sales targets, customer segmentation, focus on target buyers and strategies for engagement with the buyers.

3. Regarding proposed/future projects, he readily accepted the ‘optimised conceptual design’ including the project location(s), composition and carpet areas of 1/2/3 bhk units, staggering of the project development, focus on different consumer segment and rework financing of the project(s).

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