Data Quality Issues List – No more messy, inaccurate data! 

Written by Ray Sabharwal

According to a study conducted by MIT Sloan, staff members have been found to waste up to 50% of their time dealing with avoidable data quality issues. It also found that organizations easily throw away 15 to 25% of their revenue dealing with data quality issues. Eliminating data quality issues is one of the easier ways to reduce costs, make smarter decisions, and enhance the client experience.

So what exactly is data quality (DQ) and how can it help you? 

 The National Institute of Statistical Sciences in the U.S. states that data quality is the capability of data to be used effectively, economically and rapidly to inform and evaluate decisions. Poor DQ can create several economic inefficiencies, and that’s why, in a world where technology and massive datasets are used everyday, it’s important to ensure minimal gaps and errors in your data. Examples of the economic damage that data quality issues are known to cause include increased unnecessary costs when files are sent to the wrong client addresses, lost sales opportunities because of erroneous or incomplete customer records, and fines for improper financial or regulatory compliance reporting (

 Enter Penelope’s latest module, the DQIL

 You already have enough on your plate. So to help ease this additional burden, we’ve created the Data Quality Issues List (DQIL), a simple way to address common data entry errors at any organization.

The DQIL appears as a tab on the collaboration suite in Penelope, giving each user one-click access to any data entry errors that need to be addressed. Checking the DQIL tab can become part of each user’s daily routine, and supervisors can easily track the progress of data cleanup.

Examples of scenarios in which you would likely use DQIL include:

  1. Individual with default date of birth

In Penelope, System Administrators can set a default date of birth for individuals added to the system (e.g. January 1st, 1900). This allows users to complete an intake for an individual where the date of birth may not yet have been provided. Forgetting to go back and update the field once the date of birth is known, however, can negatively affect demographics reporting.

With the DQIL, keeping track of which individuals still have a default date of birth is now a simple process that allows users one-click access from the DQIL tab to correct the information once the actual date of birth has been provided.

  1. Service File Close reason not selected

When closing a client out of a Service File, it’s important to indicate the closure reason for organizational tracking purposes. Penelope has a field for this where organizations can create a drop-down list of common closure reasons that provides insight into why clients are being closed out of service.

The DQIL will ensure that this key step is no longer missed by showing the users responsible which clients are missing a Service File Closure reason. From there, it’s a simple click to correct the information and keep the organization’s data up to date.

  1. Individual policy not in billing sequence

Many of our customers have clients who receive services that are partially or fully covered by an insurance policy. In Penelope, users create a policy for each covered individual, indicating which services will be paid for, along with the rates, date limits, etc.

One crucial element to this process in Penelope is making sure that the client’s policy is added to the ‘billing sequence’ in the system. If this step is missed, it will appear that the client is responsible for paying for a given service that’s been provided. This can lead to confusion and extra work to go back and fix, not to mention a potentially poor experience for the client.

The good news is that the DQIL will now catch instances where a policy has not been added to the billing sequence, meaning this situation can be avoided by addressing the error proactively.

There are many other common situations that can be addressed via the DQIL, including:

·      Past event attendance has not been taken (important for reporting and to ensure that billable services can be invoiced)

·      No collateral contacts have been added for a client

·      Main contact method has not been entered for a client

For Australian agencies who report to DSS, there are also a number of specific options that will appear on the DQIL, including:

·      A client is part of a DSS Service File but no DSS information has been filled out on their Individual Profile

·      DSS Member Information has not been filled out on the DSS tab of a Service File or Group

·      DSS Session Details have not been filled out for a Service or Group Event marked as Show

The options described above can be activated or deactivated during implementation according to an organization’s needs. Also, if an organization requires additional rules to be added to the DQIL, Athena Software’s Tailored Services team are happy to provide a quote on customization.  

Ensuring your data is clean and error-free doesn’t have to be difficult. Together, we can save you valuable time and lessen the stress caused by avoidable issues.

Alternatively, you can contact us directly or fill out a consultation request form to speak with one of our Penelope experts.

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