By Kalyan Vaidyanathan, CEO & Co-founder, Nadhi Information Technologies.
Adoption of emerging technologies such as artificial intelligence (AI), machine learning (ML), data analytics remains low in the Indian real estate sector as compared to peer sectors like financial services, retail, travel & hospitality, and manufacturing among others. Within real estate, there has been the uptake of analytics on some functions like marketing and sales, and material pricing, but there has not been a wide application on project delivery and operations. Of late, things are changing, albeit slowly. Some of the recent policy changes like the implementation of RERA have put a greater need for the industry players to look at time and cost performance and improve their delivery efficiency. COVID has also seriously impacted the industry, impacting cashflows, working capital further accentuating the need to look at other technology enablers to improve the efficiency of project delivery. All of these business needs have created the need for looking at data and gaining insights. Fortunately, the technology environment has evolved to be more conducive to provide a platform and options and solutions in the hands of forward-looking players in the sector. The emergence of inexpensive cloud computing and the evolution of technology frameworks that can analyze data of all forms has led the industry players to look at analytics, AI, and ML to gain insights and improve efficiency.
How Analytics helps shape Business Strategies
Data analytics can provide the necessary business intelligence at a faster pace to the management of the company for enabling timely delivery of projects coupled with cost savings. Through analytics, large datasets from multiple sources can be analyzed to gain useful insights. From design to procurement to execution, at every step, data analytics can provide a competitive advantage to a real estate company over its competitors.
Let’s discuss some details. A project is divided into overlapping phases of design, procurement, and execution with different timelines for completion. These tasks are executed by different teams with their respective members. Most of these tasks are interconnected, and a delay in one has a potential impact on a future milestone and derail the timelines. In our experience, project delays happen due to the domino effect of such misalignments between various functions. Even today, with available technology, project managers typically work with silos of information that makes the understanding of this interconnection and future impact difficult to unearth easily. Having an integrated project controls solution that intuitively and natively allows for this data to be connected is the first step to gaining insights into future delays. As of today, the technology solutions depend on an experienced planner to make the inter-connections. The application of AI and ML can make this process easier. Over time, the systems can infer the inter-links tailored to a sector or company. If the power of these technologies can be combined with the experience of planners and project managers, decision makers can get forward looking insights into project delays and its cost implications.
As a second step, data analytics can now provide required decision support for course correction and mitigate the delays. Data analytics engines can draw comparison with past performance of similar activities, enabling project managers to reduce duration of activities and hence potential delays and gain insights into how to achieve the same.
With a prudent combination of these technologies, today project managers can truly have a decision support system to mitigate project delays and get projects done on time and within budgets. Applied judiciously, these technologies can also be further used to align material inventory purchase and management to be in sync with project execution. Collectively, this will be free a lot of working capital for the company, adding to its liquidity. Safety and quality are other areas where visual data analytics combined with AI and ML can (are) being used to predict and avoid safety and quality violations. These are additional areas of productivity improvement, reduction of delays and bleeding of cash.
The adoption of technology in real estate today, truly has the potential to improve the return on investment on a project. But decision makers have to have a strategic roadmap to realizing the potential. On the foundation of an integrated project controls system and in built alert management system for decision support, they should add analytics and insights in an ongoing manner to gain insights. Over time and with better insights, projects can be delivered within budget and within time. To be a winner in this competitive realty market, it is crucial to look at technology and take support of AI, ML, and analytics to gain insights into project planning and delivery.