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
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.
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BI Lead & DevOps Analyst
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
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!”
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:
Sigma’s spreadsheet-like user interface gives everyone the power of SQL without having to manually write any code. “Business people who had never seen Sigma before were able to jump right in and start creating reports, whereby with Looker I had to train them for weeks just to be able to do basic edits to LookML, ” says Iain.
“Business people who had never seen Sigma before were able to jump right in and start creating reports.”
BI Lead & DevOps Analyst
Sigma empowers business teams to visually analyze data by taking the familiar Excel-like functions they know and love to the next level. “Now anyone on the team can spin up a customer dashboard or dig into an existing one to do further analysis, ” Chris shares.
Iain continues, “Business teams being able to explore data independently with Sigma is extremely valuable. As those closest to the customer, they’re able to surface highly relevant and impactful insights that the BI team simply doesn’t have the domain expertise to tease out without a ton of back and forth.”
Purpose-built for the Cloud Data Warehouse
Empowering business teams to independently explore and analyze data with direct, real-time, governed access to the cloud data warehouse drastically reduces time to insight. Eliminating reporting request queues and time-consuming back and forth also frees data and BI teams to focus on more strategic and innovative projects.
“With Sigma, our workflow is very fast and fluid, ” says Iain. “Everyone on the BI team felt like a weight was lifted off their shoulders when we moved off of Looker. It was such a roadblock that the BI team had to get involved and update the layer between Snowflake and our Looker reports everytime a new question or schema change arose.”
In contrast, Sigma doesn’t require any updates to the central data model to access or analyze data. It sits directly on top of the cloud data warehouse, so any changes in the warehouse are immediately reflected across reports. “Not only does your data stay safe inside the warehouse with Sigma, but you also get a complete log of every query your team runs, ” Chris says. “So it’s really easy to see who did what and even roll data back to a specific point in time.”
Sigma never moves, stores, copies, or caches company data. This significantly minimizes the need for risky CSV extracts, which are quickly outdated and can easily fall into the wrong hands. Leaving the limitations of CSV extracts behind has also made it possible for Payload to easily query the large volume and variety of data captured by its application.
“With Sigma, you can analyze data at the lowest level of detail and literally query billions of data rows at once and not run into any scale issues.”
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“We work with a ton of data, so we needed a tool that wouldn’t choke on us or force us to do reduced data extracts, ” says Chris. “With Sigma, you can analyze data at the lowest level of detail and literally query billions of data rows at once and not run into any scale issues.”
Analytics in Action
Confidence in the security and scale of Sigma’s tool made it possible to share data externally with customers using Sigma’s Embedded Analytics functionality. “We embed Sigma dashboards into Payload and authenticate our customers through our own application, ” continues Iain. “Sigma’s modern approach to data governance keeps our data safe and secure, but does it in a way that enables data access, visibility, and insight, rather than forcing our team to act as gatekeepers.”
What’s more, BI and business teams can work together in Sigma to build contextual, reusable datasets and conduct complex analyses at scale. “You can still write SQL in Sigma, ” tells Chris. “I like that there’s one tool where business and data experts can each harness their expertise, collaborate with one another, and work the way they want.”
Using Sigma’s Embedded Analytics functionality, Payload has launched two new data products for its customers: Service Vendor and Oil & Gas Client Data Analytics Packages. These packages provide clients with actionable insight into load utilization, field ticket visualization of events, vehicle speeds and safety, carbon footprint, and more.
“We built these data products plus more than 30 other standard reports in just a couple months without having to add any additional headcount, ” recalls Iain. “Harnessing this untapped market opportunity and achieving our goal of building an analytics solution into our product was a huge win for Payload and our customers, and would not have been possible without Sigma.”
Payload provides all customers with a standard set of Sigma dashboards, significantly up-leveling the value of its application. They have packaged the more advanced analytics as an additional feature that must be purchased separately, effectively monetizing their data and generating a new revenue stream.
“Adding Sigma dashboards and insights to the Payload application has had a huge impact on the perceived value of our product, ” says Chris. “It’s not only helping us retain current customers, it’s enabling us to expand these accounts as well.”
“Sigma’s ABI solution allowed us to create an entirely new revenue stream and now plays a key role in generating and closing new business.”
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Payload has already identified additional business opportunities using Sigma, and plans to roll out a prescriptive analytics solution over the coming weeks. “By using Sigma to quickly and effectively analyze the dense volumes of data we collect with our application, we’ll be able to help our customers determine what receiver stations on which days of the week yield the best cost savings, which routes are safest and result in the least fuel consumption, and so much more, ” shares Chris.
Payload has been able to achieve their goals and drive these business outcomes quickly and cost-effectively with Sigma, providing additional proof that their ABI investment is generating significant returns.
“We were up and running reports in Sigma on day one because it was so easy, ” says Chris, “while we had to wait a week before we could even get set up — let alone run reports — with the other ABI tools we tried.”
Organization-wide access to real-time data inside Snowflake and Sigma’s spreadsheet-like UI have enabled anyone at Payload to quickly create up-to-the-minute reports, visualizations, and dashboards that meet customers’ needs. Not only did this cut the dedicated BI manpower Payload needed to provide customers with an analytics solution by 50%, but it also reduced report delivery times from 4-6 days to 4-6 hours.
“If you add up the time and the manpower we needed to generate standardized customer reports in Looker, each report came out to about $9,500 to build, test, and deploy, ” calculates Chris. “Sigma has brought that number down to $1,400 per report. That’s over 600% cost savings due to the fact that anyone on the team can go into Sigma and generate an analysis in seconds.”
Snowflake compute costs have also decreased with Sigma compared to Looker — even though the team is running more queries than ever before. “Sigma allows us to write better queries and pull only the data necessary, ” says Iaian. “The SQL created by Looker includes many unnecessary steps like inline transformations and casting of the data, so it slows things down and drives up compute costs.”
“Peace of mind is worth a lot, ” says Iain. “Sigma’s support team is second to none. They respond to questions extremely quickly and always go above and beyond to make sure we have what we need. You just don’t see that with many companies.”
“Sigma’s support and product teams have far exceeded my expectations, ” agrees Chris. “We’ve sent a number of feature suggestions and requests over time, and they always find a way to roll them out within a few weeks. It makes you feel like you really have a stake in the product and a voice in the company.”
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