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Data Gathering: Why Automation Improves Accuracy

It’s 2004, you put down your Blackberry and get back to balancing your chicken-scratched checkbook by sifting through faded receipts and bank statements. Fast forward 15 years: it’s 2019 and you’re dialed into a conference call on your smartphone while simultaneously reconciling your budget on Mint.

The difference is clear – we live in an age of automation where every transaction made is tracked and fed back to a database in milliseconds. This instantaneous feedback loop has allowed many to keep a close eye on metrics that matter. In the age of ESG awareness, utility data should and must be treated with the same consideration as financial data.

 

Why Automate Data Collection

First and foremost, automating utility data simply saves time. The checkbook example? Not so farfetched in the world of utility data collection. In fact, most of the companies that adopt Measurabl move away from manual data collection that looks fairly similar to our 2004 processes of aggregating information by hand.

However, the number of man-hours required to sort through paper bills and key manual data can be reduced significantly by making a computer do the work. Not only does automation complete the job faster; these processes do it more accurately. You can remove fat-finger mistakes – accidents from manual data entry – by using technology to collect the data accurately. Plus, machine learning algorithms can systematically identify anomalies in datasets and correct them. Data quality is more and more important, and your program deserves that level of quality.

Some people have fat fingers, but inflating ESG Data doesn’t make anyone richer.

 

Outcomes of Automating Data Collection

The value of automation is clear:

  1. Timely utility data.
    In the era of quick decision-making, waiting 3 months for last quarter’s utility data isn’t conducive to stakeholder timelines. Implementation of efficiency projects, disclosing sustainability data, and other data-dependent exercises get delayed, or decisions are made with incomplete information. With data automatically delivered to your team, you can make smart decisions when you need the information – no more waiting for your utility bill to arrive in the mail.
  2. Utility data lineage.
    Manual data collection doesn’t track data from source to screen. Data automation allows anyone to view the original bill that was digitized by a specific script creating the numbers that appear on the screen – like farm-to-table, but for data. Gone are the days when tracking down humans and papers was the only way to trace a number to its origin.
  3. More time spent on value-add efforts.
    Less time spent typing manual data, more time focusing on value-add efforts. A computer can collect data easily, but humans are needed to provide the context around the information. With these insights, you can create data-driven change to make measurable improvements.
  4. More accurate data allows for more accurate initiatives.
    Initiatives are pursued when data reveal inefficiencies; if the data is inaccurate, then the initiatives won’t drive meaningful change. Accurate data supports better, smarter decision-making. And that affects your bottom line more than ever.

As the demand for data quality and integrity within the CRE space grows ever important, data automation will no longer be innovative. It will simply be the status quo.

We’re beyond the world of you manually balancing your checkbook by hand, people. Shouldn’t your utility data be the same way?

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