Embracing Analytics - The Tech Boom In CRE

[Posted On: 26-09-2019]

Decision-making process is one of the most important activities for a business. This responsibility lies on the shoulders of the leadership in any organization. They need to decide from an array of choices for solving various problems. The decisions that are implicit and intuitive rather than explicit and logical create an illusion that “all rests with the leaders”. The drawback to this approach is that people lose trust and commitment to such decisions. A good decision, however is based on analytical insights derived from data.

Types of Analytics 

The first step in analytics is to collect robust, comprehensive data throughout the various stages of a business. The data collected is both structured as well as unstructured. It includes not only numbers but also images, videos, e-mails, transactional data, content from social media and a lot of other non-numerical information. There are four types of analytics that can be applied to the obtained data – Descriptive, Diagnostic, Predictive and Prescriptive.


3 benefits of using analytics in business


Application of Analytics in the realm of RealEstate

Descriptive Analytics – What is happening?

It is probably the most commonly used analytics. It provides information about past events, occurrences or historical records. Organizations need such information to understand how a particular product, service or an asset has performed in the past. Debt Service Coverage Ratio (DSCR or DCR), Loan toValue (LTV) and Return on Investment (ROI) are few examples of descriptive analytics.

Diagnostic Analytics- Why is it happening?

It lays foundation for both Predictive and Prescriptive Analytics. It answers why a particular pattern or event occurred. For example, you may find that there are a quite a few lease deeds pending for closure in the months of March to May. This pattern suggests that the months of March to May lie around the closing of the financial year. Now this is an important piece of information and hence as an organization, you may want to take appropriate actions to expedite the process so that there is a reduction in pending leases.

Predictive analytics – What is likely to happen in future?

It helps in risk analysis and better planning for future. For instance, you can predict purchase pattern for a new product based on past buying behavior of the consumers. Sentiment analysis is another example of Predictive Analytics. It uses content from social media to generate a sentiment score that determines the consumer sentiment for a particular business, product or service.

Prescriptive analytics- What do I need to do?

This is an action oriented phase where you can recommend strategies and actions basis your predictions. It is the course of action that you apply to achieve certain goals in future. Prescriptive analytics involves use of advanced analytics techniques, simulations and artificial intelligence.

In a number of organizations, the application of data-driven analytics is still confined to driving operational efficiencies and workforce productivity based on quantitative insights. It was not too long back that real-estate leaders mostly followed reactive decision-making practices. This was mainly due to limited data accessibility and availability. But, today, with the emergence of big data, companies have the tools to be proactive and come up with solutions that operate in complete unison with the business goals.

Commercial Real Estate is rapidly pacing up to become a more data-driven industry than ever. The process of leasing, maintaining, renewing or exiting properties involves numbers that depict investment vis-à-vis overall profitability from a property. Analyzing data produces meaningful insights not decisions. It enables insights based robust decision making that lies with the leadership. Such decisions provide businesses a competitive advantage.

Here are 4 simple ways in which analytics can be used to strengthen the Corporate Real Estate framework within an organization.

Location Analytics  – With the help of an analytics based integrated portal, Real Estate leaders can study the demographics, shopping zones, brands present etc. for a particular suggested commercial property. It empowers the leadership with more sophisticated site selections and can be combined with the company’s growth goals in order to develop a model that would guarantee the success of various location choices.  It covers aspects like:

  • Customer and Competitor Analysis
  • Helps in deciding the format of the store
  • Forecasting sales

Retail Analytics – A retail company needs to plan the design of the outlet and plan the layout of the inventory. Analytics can not only help in understanding the buying trends of the consumer but also can suggest the most visited sections of the outlet and the best place to display a product to the target consumers. 

Portfolio Analytics – A well designed analytical dashboard can highlight the existing, pending, up for renewal and expiring leases across regions. The report can be well summarized on a monthly, quarterly or yearly basis. It can be used to study the renting trends. Analytics can automate the process of tracking and handling portfolios.

Pricing Analytics – Businesses always need to study the target segment and price the product or service such that it is attractive enough to catch the consumers’ attention. Analytics can help in defining the latent constructs that influence the purchase patterns of consumers. The pricing algorithms are an important tool that suggest a price or price range for the goods and also indicate factors to consider while making changes in the product, promotions or actual pricing in future.

To summarize, analytics tools and techniques must play a lead for the future-looking organizations. However, the real opportunity to exploit the potential of analytics lies with the people and processes in the organization more than the technology. There are tremendous opportunities and a huge scope for transforming the teams in order to become more data-centric. There is a need to transition from data-supported enterprises to data-centric businesses. In order to achieve the business outcomes that are in-tandem with corporate strategy, the corporate real estate leadership must shift gears, move from a tactical approach and focus on strategic opportunities using the power of analytics. This would not only benefit the bottom line of the company, but also enable commercial real estate investments to have a competitive edge over others in the industry.