Enriching Artificial Intelligence with External Data for Commercial Real Estate
In business, there are always going to be circumstances outside of your control. Minimizing these, or improving your ability to react in real-time is what separates successful property managers from those that flounder.
The advances in Big Data and Artificial Intelligence are a great example of the way businesses are attempting to gain more insight and control. By using existing datasets, companies can benefit from trained models that alert your staff to anomalies in real-time, uncover the root cause of business challenges, and even predict future events such as tenant retention or maintenance needs.
What if you could take this further, and harness the power of the data outside of your company walls? At Okapi, this step has been on our roadmap for a while, and we’re excited to announce the first of our integrations with external datasets – our weather API. Weather is a perfect example of a parameter which historically has felt out of a property owner’s control. For the first time, Okapi can now enrich a business’s AI notifications with weather-driven insights that support you in managing risk and enhancing your day to day operations. These could cover a wide range of metrics, from temperature and humidity, to wind chill or direction, snowfall, rainfall, and sea-level.
Preparing for the Storm
Some of the benefits are immediately obvious, especially when it comes to maintenance costs and resource management. Knowing in advance that you’re due to have a heavy snowfall allows you to hire the right equipment and contractors ahead of time. Being aware of sub-zero temperatures can pre-empt the organization of plumbing support to deal with frozen pipes. Air conditioning units can be serviced in the lead up to a heatwave. This doesn’t only optimize your own operations, it also has a direct impact on tenant satisfaction.
Let’s take this further, though. By enriching a company’s existing data with weather parameters, we can uncover previously hidden factors in achieving everyday business goals. By giving the model new data, we are enriching its ability to make predictions, to find root-cause, or to highlight anomalies.
One good example is a ticket queue. An overarching business goal could be to cut down on abnormal wait queues of more than 10 tickets for their tenants. By enriching the ticket data with weather information, the company could uncover that a large percentage of these abnormal queues happen on a day with extreme temperatures. By separating out this data, the company can create a new normal for exceptional weather, optimizing their policy to handle fluctuations, and gaining a better insight into what seemed like anomalies at first.
Clear Skies Ahead
This is just the beginning. External datasets provide a new layer for your business’s operational insights, deepening your ability to optimize performance and get more out of your existing information. At Okapi, our weather API is a powerful start.
Want to find out more about how weather analytics could boost your performance? Get in touch to schedule a demo.
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Interested in seeing how it works in practice? Get in touch to schedule a call.