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Cleaning Up User-Submitted Data

by | Maintaining BI

Ad Hoc Endowment Reporting

Today’s guest poster is Amber Bigler Newman, VP Marketing at Exago client company AMTdirect, producers of lease administration and accounting software that helps companies prepare for new accounting mandates like FASB 842 and IASB 16. This helpful tutorial on improving data hygiene originally appeared on their company blog.

Computer processes generate some of our transactional data, but in many industries—and certainly in the real estate industry—a great deal of it comes from user-submitted forms. In the case of our users those forms contain information about locations and equipment. In your case they may contain information about clients, inventory, invoices, or a host of other critical business data. Inconsistencies in how users record values can result in poor data hygiene, but there are lots of ways for administrators to maintain data quality despite these issues.

What’s The Big Deal?

Benjamin Franklin once said, “For every minute spent in organizing, an hour is earned.” Smart guy, and he’d never seen a real estate asset management database. Every software vendor will talk about the importance of good data hygiene, “Garbage in, garbage out,” we like to say, but we don’t always do a good job explaining why it is important and what you can do about it. To clarify, let’s start with a few examples of problems that we see all the time.

Inconsistency in Numbering

In this example, the same unit was entered into the system with 5 different names. Setting a procedure around how to create the number would keep the entries uniform, prevent duplicate entry and ensure accurate reporting.

Sloppy Text Entry Fields

In this example, the same property name was entered with several different naming structures. Keeping the entry uniform allows for easier-to-read reporting and faster searching.

Duplicate Contact Records

In this example, the same contact was set up three times. Once for his address, a second time for his email address, and a third time with an abbreviated name.

It’s easy to see why these practices could make things a mess. How do you prevent it or fix it if you already have the problem?

Ways to Ensure Clean Data

Develop Naming Conventions: Having structure around your data, like suite or store numbers, location names, vendor codes, and more, keeps a standard that everyone can follow.

Create a Validation Process: A simple search before entering data can help identify if it already exists, instead of creating a new entry that may cause issues in the future.

Document Your Data Policies: Whether it is a quick reference guide or a full-blown User Manual, create a policy or procedure and distribute it to the people entering your data.

Eliminate Redundant Fields: Do you have several fields that are meant to deliver the same information? Think about consolidating those fields to eliminate the potential for errors.

Audit: Set routine times for data clean-up. Removing or updating data that is no longer valid will increase your ability to make reliable business decisions.

Why Do I Care if My Data Isn’t Clean?

Your data is often used by multiple departments and managers to make important business decisions. Confusing or inconsistent data can incite clerical errors that snowball into much larger problems that then cost considerable time and money to correct.

Here’s how good data practices help everyone.

Administration: Having rules that are easy to follow allows for increased productivity, allowing time for other tasks.

Responsiveness: With a confidence in the data, you can respond quickly to requests for information from other departments or teams.

Due Diligence: Timely, accurate data leads to improved decision making across the board.  Your data can save or cost you money.

Legal: There are important legal reasons why the data should be not only accurate, but also easily searchable. Data consistency is the key to effective searching.

Executive Management: With every department optimized, your business will run more smoothly and you will have access to your metrics at a moment’s notice.

Keeping the data clean is the responsibility of everyone who touches it. Make sure to set the rules, communicate them, and validate that they are being kept. Because as Jim Rohn said, “Success is nothing more than a few simple disciplines, practiced every day.”

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