One Foot Out the Door: Identifying the Tenants Who are Ready to Leave
Commercial Real Estate has been described as being ‘fashionably late’ to the Big Data party. We believe it’s been worth the wait, as the benefits of AI and Machine Learning for CRE surpass anything that has been achieved in the past with manual analytics.
Using AI can identify and answer the industry’s most valuable questions for the first time, giving you a competitive advantage that is a game-changer for CRE.
The Difference Between Data Analysis and Machine Learning
The opportunities that AI has unlocked go far beyond what many people are aware of. Let’s look at a question that many CRE stakeholders would want the answer to. Do I lose more tenants on average compared to my competition? It’s a good question, and as a business you can delve into your data and look at how your business measures up according to the market at large. But why stop there? Using Machine Learning, we can use the data you already have to predict in advance which tenants are going to renew their lease, and which are at risk of leaving.
Using our predictive model, we identify the variables which are important, and are likely to lead to a tenant opting out of renewing their lease. These vary from property to property, and could include factors like location, SQF, the classification of the building, or the amenities on offer. We enrich this further with external information from the IoT, connected services, unstructured data from places such as Social Media, and more.
Once the data is analysed, in real-time, you can identify the tenants considered ‘at risk’. If the predictive engine identifies a parameter within your control, such as price point, you can decide to act on this. In other cases, the knowledge ahead of time can help you prepare and strategize in the best interests of your business. If your company has 1,000 leases up for renewal, identifying a percentage that are ‘safe’ and being able to home in on the tenants that need your focus is invaluable.
Understanding the Reach of a Well-Taught Algorithm
While leases are a topic we get asked about a lot, the same benefits can be seen in other areas of your business. Let’s take maintenance for example. Data analysis can tell you which machines have broken down the most in the previous year, and root cause analysis could tell you why. These are certainly powerful metrics to have to hand. However, our Machine Learning takes it further, allowing you to answer the question “Which assets will break down next, and when?” Real-time alerts can show you which maintenance needs should be top of your to-do list, before the calls start coming in from your tenants.
This kind of predictive analysis is a real game-changer. Not only does help you achieve 5* tenant satisfaction, but it also saves you time and money, and prevents you from fixing problems in crisis mode, after the fact.
Using Insights to Ensure You’re Asking the Right Questions
In some cases, you may identify what we call a ‘break-point’ or a pattern that can help you make smart business decisions. These trends can be seen in various areas. For example, above a certain price point, my tenants opt out of renewing their leases, or under a certain SQF, I have more maintenance costs.
These kinds of actionable insights can help you align your goals correctly. For example, a client might come to us wanting to know whether they can raise their lease prices without losing tenants. We look to uncover the outcome they are looking for underneath the knee-jerk objective. In this case, they are searching for ways to increase profitability and have decided on this course of action. In reality, our algorithms might suggest that they can simply and easily reduce on unnecessary maintenance costs or change their business model in another way, resulting in the same boost to their bottom line.
It Takes Less Data than you Think
One of the largest myths around Machine Learning is that you need thousands of records or data points in order to get accurate predictions for your business. We see companies with as little as a few hundred datasets gleaning actionable analytics from their data and benefiting from predictive and root cause analysis.
Gone are the days where you can put three engineers in a room for two months and expect them to be able to rival the latest technological advances. Not when smart AI and Machine Learning technology can do the hard work for you, and with better results, giving you continuous insights that would be impossible to manage or uncover by hand.
Is Your Business at Risk of Falling Behind?
According to the Deloitte 2019 CRE Industry Outlook report, more than 80% of stakeholders believe that predictive analytics and business intelligence should be a priority for CRE. In fact, “over the next 18 months, nearly two-fifths [of companies] plan to increase the use of these two technologies in their business decisions.”
Understanding what AI can do for your company means recognizing the power of the data that’s already in your hands, and leveraging predictive analytics to get ahead of the competition.