Healthcare data shown on clipboard
Case Study

Technology company discovers actionable insights and trends with SaaS Intelligence

Baker Tilly Digital helps Quest Analytics communicate key metrics with SaaS Intelligence.
Healthcare data shown on clipboard
Case Study

Technology company discovers actionable insights and trends with SaaS Intelligence

Baker Tilly Digital helps Quest Analytics communicate key metrics with SaaS Intelligence.

Client background

Quest Analytics is a technology company dedicated to improving healthcare provider network management and in turn, helping people across America receive the information and care they deserve. Their Provider Network Management platform brings trust, transparency and confidence in the process of measuring, managing and monitoring provider networks. Quest Analytics partners with both providers and healthcare organizations to address two significant issues facing the healthcare industry today: accessible networks and accurate provider directories.

When you keep everything in Excel and split your data by year, it can make trailing twelve-month analysis difficult and it’s less likely that you’ll discover actionable insights and trends. With Baker Tilly’s SaaS Intelligence, we can do that kind of analysis easily.
Sam Robertson, Corporate Controller, Quest Analytics

The business challenge

As the company moved more of its products and services to the cloud, it became clear that Quest Analytics should be measuring itself against and evaluating its business as a Software-as-a-Service company. Upgrading their financials from QuickBooks and spreadsheets was a major step in that direction and the company chose Sage Intacct over NetSuite. Sage Intacct’s subscription billing and contract management capabilities and its native integration with Salesforce made it the best solution for the organization.

Quest Analytics originally looked at Sage Intacct’s Digital Board Book application as a SaaS and subscription metrics tracking solution but ultimately selected SaaS Intelligence to provide those KPIs. Baker Tilly Digital's SaaS Intelligence is built on the Sage Intacct development platform, so it sits natively inside Sage Intacct, and it automatically categorizes transactions in real-time using a sophisticated intelligence engine, providing metrics that are automatic, reliable and insightful.

We spoke with Sam Robertson, corporate controller at Quest Analytics, about the shift the company has made recently and how Baker Tilly Digital has been able to play a part in that transformation.

“The company has been in business since 2003 and had historically been a desktop software provider,” says Robertson. “As we moved more of our solutions to the cloud, we knew we needed to think in terms of more complex multiyear, multi-element contracts, and that managing those contracts with QuickBooks and spreadsheets wasn’t going to work long term.” Robertson knew they needed an ERP system, Sage Intacct, that could manage their increasingly complex billing and revenue recognition requirements, while also automating the tracking of crucial SaaS KPIs for the organization – for this, he turned to SaaS Intelligence.

According to Robertson, the implementation of SaaS Intelligence was straightforward. The product team, led by Baker Tilly' Digital's head of SaaS Vertical, Chris Price, helped Robertson understand exactly how the metrics were being calculated. “The Baker Tilly Digital team was super responsive and always provided me with a lot of detail whenever I had questions,” says Robertson. “The product works exactly as it was sold to us.”

Going in front of the Executive Team to present these metrics is spurring conversations about where to focus our efforts. Having these insights that are actionable and strategic come out of the finance department is really cool.
Sam Robertson, Corporate Controller, Quest Analytics

Strategy and solution

“Spreadsheets aren’t systems,” he says, explaining that it’s too easy to make manual interventions, judgment calls, and even mistakes when you’re using spreadsheets, making it difficult to trust the data and even more difficult to surface insights about the business.

“When you keep everything in Excel and split your data by year, it can make trailing twelve-month analysis difficult and it’s less likely that you’ll discover actionable insights and trends,” says Robertson. “With Baker Tilly Digital’s SaaS Intelligence, we can do that kind of analysis easily.”

Baker Tilly Digital’s SaaS Intelligence automatically identifies different SaaS metrics scenarios to provide an accurate representation of client subscription activity and the impact on ARR or CMRR. The application’s intelligent engine can distinguish between different factors driving changes in CMRR, removing the need for manual intervention or additional analysis of transactions, giving finance teams a single source of the truth.

Surfacing both insights and process and data gaps

According to Robertson, SaaS Intelligence has become a check on previous policies to make sure that KPIs are being calculated properly. “We found ourselves often saying ‘What does the spreadsheet say?’ and then ‘But what does SaaS Intelligence say?’ and that process has taught us a lot about our assumptions and our policies around SaaS metrics,” says Robertson. “It gives you the flexibility to look at things differently, to challenge your assumptions and to look at true KPIs. It spurs conversations we didn’t use to have around things like Customer Acquisition Cost (CAC) and Customer Lifetime Value (CLTV).”

Transforming finance and accounting into a strategic asset

Robertson is having these conversations at the executive team level and SaaS Intelligence is helping him communicate these key metrics.

“Going in front of the Executive Team to present these metrics is spurring conversations about where to focus our efforts,” says Robertson. “Having these insights that are actionable and strategic come out of the finance department is really cool,” he adds.

Person paying for a purchase with credit card
Next up

Retail manufacturer establishes data governance approach