Dashboards - Under-delivered Over Budget


Last time we talked about blind spots buyers need to be aware of in relation to data visualization software. In this post we will take a deeper dive into data combining challenges.

One of the first frustrations you will run into is when you want to combine data from different systems or even subject areas within the same system. Based on Will Mitchell's article in Propmodo the average company already uses 16 external SaaS systems but even with 5 systems or even 1 large one, this problem will quickly grind your project to a halt.

Imagine you handle your home viewings in a system like Rently, and your properties and leases in Propertyware or Yardi. The Rently data may show you high-level overviews of the number of viewings you have had over time, but your property management system will have data that you may want to slice and dice these viewings by like your portfolio, lender, neighborhood, floor plan, construction status, etc., etc. The next insight you probably want is how did these viewings convert and why; which prospect became renters and what influenced them.

This will require a level of combining of the data that will be very tricky using off-the-shelf systems. Simply matching two addresses from two different systems together is a lot harder than you may think, there are probably 5-10 legitimate ways to write the same address, imagine all the other possibilities that contain misspellings. There are technologies out there that do nothing but try and accurately match addresses, and the off-the-shelf tools won’t offer you any of these.

You will find that your dashboards and reports remain very siloed covering one subject without any relation to other important data elements.

Next time we will talk about why data transformation, cleaning, and organization is crucial to report accuracy and developing the insights you want.

September 3, 2021
by Nikolai Narvestad

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