Q&A: How clean is your real estate data?

Unless you’re a data analyst, likely, you’ve not paid much attention to this kind of question before. But clean and structured real estate data is vital if you want to gain worthwhile and actionable insights from it.

Any good analyst would quickly pick up most mistakes, like – if the passing rent is too high or incorrect unit sizes pop up. But would you notice if there were different date formats used across the same dataset?

To understand why clean data is essential, we have to look at what exactly clean data is.

What is clean data?

Clean data is free of incorrect information, corruption, formatting errors, duplication, or missing fields. Technically, it adheres to the properties defined by the field. In reality, it helps you to prove or disprove a working theory.

Some errors or inconsistencies may not be noticeable to the human eye, such as – “N/A” and “Not Applicable” being used in the same category or text in a currency formatted field on just one record. Still, simple issues such as typos, incorrect capitalisations or inconsistent naming conventions can throw up huge problems later down the line.

Unless you remember to apply all variances when running a search of your data, you will only see a handful of the results you intended.

Trusting that data

When using data to support critical business decisions, you need to know with absolute certainty that you can trust the insights you’re getting from it.

Many real estate companies opt to outsource aspects of their data management, sometimes to various suppliers. For example, an asset manager might have tenancy schedules held on multiple property management systems.

By combining these data sources, there is more risk of the data becoming corrupt with mislabelled fields, spelling mistakes, or date discrepancies. With an inherent culture for periodic reporting in the commercial real estate industry, inaccuracies like this can often go undetected for months and sometimes even years.

During a client meeting, the last thing you need is the embarrassment of realising your assumptions have been entirely incorrect.

Quality over quantity

It’s no secret that many real estate professionals are sitting on an abundance of underused data.

Not many investment managers would have logged the details from every marketing brochure they’ve ever received, but the power held in that kind of data is unfathomable. Making it work for you isn’t as simple as you might think, though.

Whether using Excel or specialist commercial real estate software such as Coyote, if the data referenced is incorrect, has inconsistencies or missing fields, it will be reflected in the analysis. Ultimately, you get out what you put in.

Do you have irrelevant information in your dataset? Have you logged the same asset twice or accidentally input the wrong postcode somewhere?

These are all factors that can make analysis less efficient and distract from achieving your business goals. With the right tools, clean data can help you and your team initiate smarter and more accurate decision-making quicker than your competitors.

Maximising efficiency

Auditing is not about looking for mistakes but getting to the root of the cause quicker to ensure optimisation.

Take Coyote Software, for example – data feeds into Coyote directly from property management systems, via bulk uploads, and of course, from manual entries. Our advice remains the same on all counts – it’s always worth spending some time auditing your data and ensuring it’s clean before you begin to draw any conclusions from it. The extra time invested at the start will pay dividends in the long run.

Our data analysts have extensive experience in all the leading property management systems – Yardi, Tramps, Qube and MRI, and understand commercial real estate data’s nuances. The collective experience of our Professional Services team is a valuable resource to the majority of new clients – many of whom have never had reason to question the quality of their data before and are often surprised at the difference in conclusions once our team have removed inconsistencies.

Whilst the initial task of data cleansing is no mean feat, it will create a culture for quality and data-driven decision making within your organisation.

In summary

Using Coyote Software, you can encourage quality data within your business. By consolidating your data sources, you create your own live and accurate picture of both your Assets Under Management and the wider market. Combine this with ongoing professional support, and you’ll find that you can pinpoint issues in minutes that would otherwise take days to resolve.

Complete transparency on a centralised platform gives you and your team complete confidence that your real estate data is accurate at all times.

Your single source of truth.

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