Anna Ready, founder of bookkeeping firm Accrew, knows a thing or two about what makes data valuable. Her firm serves several non-profits, which means that data entry is often done by multiple people with varying degrees of data management skills. Anna and her team are in the business of ensuring that their clients get the most out of their data, even if there’s a lack of data management experience on their clients’ teams. Anna’s seen firsthand how bad data can slow processes. But she’s also seen how solving issues with bad data can mean better business, which means happier clients.

Anna’s approach to engaging her clients with their data is a holistic one. “When working with non-profit clients, we like to talk about how it’s our role to be good stewards of the funds entrusted to us to do good in the world,” Anna says. Data isn’t just about the numbers, it’s about making a meaningful impact in the community.

Anna also says: “Non-profits have strict budgets, so data conversations revolve around systems to ensure that every deposit and expense are tagged to the right budget line item. Then, we figure out the best ways to get buy-in (on the part of the client) for the collaboration tools we implement to make it all possible.”

 

What do you see as the main barrier to creating or working with clean data, consistently?

The main barrier to clean data is people. Whether it’s adding the data in, or waiting on answers to questions, the biggest challenge to consistently and accurately getting clean data is the human element. We also see that as the biggest opportunity because people are what’s most affected by having accurate and timely data to base strategic decisions on. When we can get clients engaged in the process, that’s where we see the best results.

 

When it comes to managing data, where do you usually look for discrepancies or inaccuracies?

Dirty data can hide in many places, but we typically see it on the balance sheet, a.k.a. where they bury the bodies. Many of the non-profit clients we work with engage staff or volunteers who have varying degrees of accounting training to help get data into their accounting records, so the balance sheet is the first place we go digging. Then, we look for anything in “uncategorized/ask my accountant” type accounts, which is another typical dumping ground for transactions they aren’t sure how to code.

 

Dirty data is the catalyst to create a data organization that incorporates processes to ensure data integrity. How do you use dirty data to start a conversation about business best practices that lead to success and growth?

Dirty data is a great conversation starter. No one wants to hire a housecleaner if their house is already clean. When we pinpoint areas that need improvement, it starts the conversation about what else could be done to ensure data is being well maintained on an ongoing basis, so that we can get the most out of the data we have.

 

Do you feel like your cloud accounting software helps or hinders your exploration of data? If it helps you identify dirty data?

Cloud accounting software absolutely helps with using data. Connecting bank feeds and other apps to automatically get data in means we have more time to validate it. It also allows us to speed up the process of turning that data into useful metrics that are relevant to our clients.

 

How does having clean data help you help your clients?

Clean data leads to more productive conversations. When we can trust that the data is valid, then we can do something with it––track trends, look for anomalies, and project and forecast. When we aren’t sure whether the data is valid, we end up spending the time we could be using to have high-value conversations on low-value tasks like asking questions about transactions and recoding previous entries.

 

How do you typically search for and find dirty data? How do you perform regular “data checkups” or “data hygiene”?

We take a tiered approach to our monthly workflows to keep data consistent. Each client has an account manager doing the day-to-day data inputs and reconciliations, but we add another layer of review by our accounting manager to check for data or accounting errors. We’ve found that putting a fresh set of eyes in front of the data ––someone who hasn’t been in the weeds all month––helps to catch outliers and keep things clean.

In an ideal world, we would work with our clients to distinguish between the kinds of transactions that are the same every time, and things we might need more clarity or insight on before it’s locked in. Then we would leverage apps so every person with financial responsibility can easily communicate how their data should be classified at the time the transaction takes place.

 

This Q&A is part of our clean data blog series. Next up, Sherri-Lee Mathers shares how she handles data from her hospitality clients, so they can make great decisions that please patrons and boost their bottom line. In part three, Erich Ly shares how he helps his small business clients take advantage of their data to spend more time working on their business instead of in their business.