Erin Marshall is the data and information manager for Azavar Government Solutions. She has been with company since 2014 and is responsible for acquiring the necessary documents and data for the analysts to use in their audits.
In this interview, we learn what types of data are necessary for a municipal audit and the challenges that come with acquiring that data. We also learn how Erin uses the latest technology to automate data cleansing and improve data quality, helping to produce faster, more efficient audits.
Question: You’re typically the first person who starts the ball rolling for an audit. What are the first steps you take to begin the process of working with a municipality?
Answer: Once I receive the approved contract, I immediately contact the client and set up what we call the “kickoff meeting” where we discuss our next steps, what we expect, what they will need from us. This would also include what we need from them and a game plan of the specifics on how the process works.
At the end of the kickoff call, we will set up an intake. Since we do all the work for the municipality, it’s important to have everything in place.
For the next step, I visit the community and they will direct me to where the necessary information is located. This process includes identifying the relevant files, scanning the information and immediately replacing those files back to their original location.
Once all the information has been collected, I will let the analysts know that the audit is ready to begin.
Question: What types of documents and data do you typically collect?
Answer: I look for remittances, invoices and any lists they may have. Our goal is to create a full picture of the community by collecting lists like their water billing and their GIS list.
We also collect all their tax remittances and their invoices to help identify how much they’re paying for a service like telecom, so we can hopefully find ways to reduce their costs. We’ll also look at revenue streams such as food and beverage and hotel/motel to make sure they’re all being remitted properly.
Question: Are there any consistent challenges you face in process of acquiring and processing the data for each municipality?
Answer: It’s actually not consistent, because a lot varies from community to community. Sometimes the challenge is just the sheer volume in large communities.
Other times the biggest challenge is bringing a digital mindset to municipalities that may be less progressive in terms of technology. In those situations, I try to be mindful of the needs of that community while also working to help them take full advantage of the technology that we provide.
Question: Is establishing a level of trust with the municipality a priority with each project?
Answer: I think it’s a natural human thing to be a little nervous about allowing an outside resource to come in and work with your sensitive information. That’s why I think it’s important to communicate consistently with them about what we’re doing and that we won’t cause them any additional work or disrupt their existing processes.
Question: After you collect all this data, do you use specific tools to clean and prep the data leading in to the audit?
Answer: We have a couple tools that we use. We use a case management system and another tool to scrape data into the database.
Question: Once the data is being analyzed, are you still involved in the audit?
Answer: I will be called in if we have to do some catch-up with documents. I’m always looking for new ways to analyze and speed up the process to assist the analysts so they can produce the best results for the client as efficiently as possible.
Question: What do you think are your key strengths that help you achieve success in your role?
Answer: I have a lot of client contact, so good communication is key. I try to always be cognizant of the needs of the client and their culture, while also working to identify and collect the highest quality data possible so our analysts can produce the best results.
Another important strength for me is my master’s degree in Library Science. I’m kind of unusual in this environment and my focus is on metadata and cataloging, which means I’m always trying to make things easier to find.
I have a strong background in identifying the data that we’re looking for, how we process information and how we access information. I’m always trying to make that entire process easier while looking for more ways to improve efficiency.
Question: How much has technology changed during your time with Azavar Government Solutions?
Answer: I actually brought in a couple tools to help increase our ability to access and process information quickly. With these tools, rather them combing through a list of invoices, the invoice information is all put into a spreadsheet that is easily accessible.
Technology has definitely helped improve our processes for cost audits, where we can grab the relevant data and all the analyst has to determine is yes or no. If yes, they have a bit of work to do. If no, I’ve created an automated process that takes care of the entire follow-up process.
Question: Have there been anything consistent lessons or takeaways from either data collection or cleaning the data or working with a client?
Answer: One consistent lesson that I’ve learned is it never hurts to over-communicate. I tend to be completely transparent and open, just to be certain and make sure that everyone is on the same page.
Another important takeaway in my role is to always be aware of how I’m managing my time and resources. I’ll ask myself questions like, is it going to take me three hours to program an automation? Am I saving time by automating a process or is the automation necessary? Finding the correct answer to those questions only comes through experience.
Question: What do you think the future is going to look like for the work that you do in the next few years and how will that affect audits in the future?
Answer: I am really looking into working with big data and finding ways to see patterns. We’re at an early stage in the process, but there are publicly available sources of data that we can be utilizing for comparison to find patterns in our data. An easy example would be finding communities of a similar size that should roughly be getting the same amount of remittance. And then if they’re not, why aren’t they?
We have a lot of data and we have a lot of tools to look at that data. Eventually we’ll be able to quickly identify broader patterns while looking for more ways to maximize those findings.