Realizing the True
ROI of Analytics & BI

the True ROI
of Analytics & BI

How to Identify Untapped Opportunities and Drive Business Outcomes with Sigma

Understanding the return on investment (ROI) of a new software tool is critical to making an educated purchase decision. While many companies measure returns by calculating cost, time, and resource savings compared to alternatives, certain tools also drive value by addressing specific challenges or opportunities.

Traditional ROI Formula


  1. Payload Unlocks a New Revenue Stream in Record Time
  2. Migo Achieves Transformational Customer Retention and Recovery
  3. What Could You Accomplish with the Right A&BI Solution?

For example, customer service software is built to help companies better manage support tickets. By delivering faster time to issue resolution, these tools function to improve customer satisfaction and reduce churn, which have clear and positive impacts on ROI.

However, measuring ROI for data analytics and business intelligence (ABI) software is far more complicated. These solutions can certainly save data and BI teams time and resources spent on reporting, as well as empower business leaders to make better decisions faster — line items that deserve to be factored into any ROI analysis.

But the true value of the data insights ABI tools generate can’t be measured based on a finite series of applications. The possibilities are endless, and it’s the unique or unknown opportunities these solutions can uncover and make possible — and the business outcomes they generate — that function as true measures of ROI.

Put another way, when considering the ROI of ABI tools, companies must factor in the cost of not being data-driven and leaving these crucial insights and business opportunities on the table.

Evaluating ABI tools through this lens behoves BI and data leaders. The ability to transform data into a company-wide asset that drives business outcomes is the key to becoming a true organizational leader and securing a seat at the table.

To help data decision makers more effectively evaluate and determine the true ROI of ABI solutions, this guide examines two real-life use cases of companies that were able to tap into new opportunities that generated a variety of business outcomes using Sigma. We will also provide relevant analyses around traditional cost, time, and resource savings metrics along the way.

Payload Unlocks a New Revenue Stream in Record Time


Payload is an easy-to-use cloud application for logistics and supply chain management, delivering simple, accountable logistics tracking and reporting. Companies turn to Payload when seeking to digitally manage field tickets, drive operational efficiencies, and manage compliance requirements.

Chris Lambert


Iain Letourneau

BI Lead & DevOps Analyst

ROI Highlights


cost savings per report


faster report delivery times


BI resource savings

Increased customer retention and new business opportunities

Creation of a new revenue channel

Lower Snowflake compute costs

The Opportunity

After spending years focused on perfecting application functionality, Payload realized it needed to change its strategy to truly differentiate itself from the competition. “To improve retention, generate new business, and ultimately enable customers to get the full value of our application, we needed to build analytics solutions into our product,” recalls Chris Lambert, CTO at Payload.

This shift also presented Payload with the opportunity to monetize the vast amounts of data it collects through its application. This includes real-time coordinate capture, field ticket data for pickup and delivery, events that occur along a route, and much more.

The ability to quickly analyze this data in real-time would provide Payload customers with the insights needed to streamline operational efficiencies and create competitive advantage. It would also position Payload as a truly differentiated industry leader.

“This was a major opportunity for us to jump leaps and bounds ahead of the competition,” says Chris. “The cost of not doing this was incredibly high — we had to make it happen. No one else in the industry was providing this type of insight to customers. And it didn’t take us long to figure out why!”

The Challenge

It soon became apparent to the team at Payload that they would not be able to fully realize this opportunity and achieve their goal with their current BI tool. “We used Fivetran to ingest data across sources and pull it into Snowflake, which was working great. But then we were using Looker to analyze and visualize the data, and CSV exports to share reports with customers,” remembers Iain Letourneau, Payload’s BI Lead.

Reports had to be created ad hoc and required significant development effort to build, deploy, and release. “You have to know Looker’s proprietary coding language, LookML, to use the tool,” says Iain. “This really limited the number of people who could generate and manage these reports without exporting them. Not to mention, one small schema change in our cloud data warehouse meant hours of manual updates in Looker.”

Report lead times reached an average of 4-6 days as request queues grew, rendering the data stale and insights outdated by the time they reached customers. Building an analytics solution into the Payload application was projected to take 2 full-time employees 6 months with Looker.

“People won’t pay for week-old insights — and they shouldn’t,” says Chris. “Hiring the number of BI experts needed to build an analytics solution using Looker in a relatively timely fashion and then maintain it over time simply was not a cost-effective option. It simply wasn’t scalable, and the ROI just wasn’t there.”

The Sigma Solution

Payload began the search for a new ABI solution that didn’t require teams to learn a proprietary coding language or export data to spreadsheets. After a series of trials, the team chose Sigma for four key reasons:

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