In our recent webinar, Scott Friesen, SVP of Analytics & Data Science at Echo, sat down with Gabriela Mauch, Chief Customer Officer at ActivTrak, to discuss how workforce analytics helped Echo optimize costs while driving workforce productivity. These are some key highlights from their conversation.
Inside Echo: Business Drivers Behind Workforce Analytics
Gabriela: Scott, can you start by sharing a bit about Echo and what led you to explore workforce analytics?
Scott: Absolutely. Echo is a 3PL (third-party logistics) provider, meaning we move freight but don’t own trucks — we connect shippers and carriers. With $4–4.5B in revenue and 3,000 employees across a dozen or so locations, we operate in a highly cyclical industry where workforce demand fluctuates.
When we first reached out to ActivTrak, we were trying to solve two major challenges:
- Measuring the impact of technology investments on productivity. We build a lot of our own technology but measuring whether new tools actually improved productivity and efficiency was difficult
- Aligning headcount with actual work needs. Finance and operations often debated whether we had too many or too few employees but we lacked clear data to make informed decisions
Essentially, we needed visibility into how employees spend their time — what tasks were taking the most effort, where inefficiencies existed and how workload fluctuated based on market conditions.
From Guesswork to Data-Driven Decision-Making
Gabriela: You mentioned headcount discussions between finance and operations. How has ActivTrak changed those conversations?
Scott: Before ActivTrak, headcount decisions relied on proxy metrics like loads handled or tasks completed — measures that overlooked task complexity and workload variability. Finance and operations often approached staffing from different angles, making alignment more difficult. Now, both teams can look at the same reports and work off the same playbooks — eliminating guesswork and enabling data-driven decisions.
Instead of debating staffing needs leaders can see actual productive hours by person, team or business unit — leading to smarter workforce allocation.
Smarter Staffing Decisions, Real ROI
Gabriela: Can you give us an example of how this data has improved workforce decisions?
Scott: We had a high-performing sales rep who had grown her business very successfully but was completely drowning in work and needed more operations support. It had gotten to the point where she was going to pass some of her accounts to other reps if she couldn’t get more help.
Rather than escalate the request to finance or make assumptions about adding headcount, her SVP used ActivTrak data to identify underutilized people on his team and reallocate headcount to provide support where it was needed most.
We’ve realized over $600,000 in labor savings so far due to better workforce allocation — and that number is just going to continue to grow.
Culture, Clarity and Earning Trust
Gabriela: I’ve really admired how you’ve prioritized outcomes while maintaining deep respect for your workforce. How have you intentionally integrated culture into the way you’ve implemented and used ActivTrak?
Scott: One of our core values at Echo is “Carry the Load Together.” We have a deep respect for our frontline employees — they’re the ones generating revenue — and as leaders, our job is to ensure they have the right support.
One of the biggest misconceptions about productivity tracking is that it’s a tool for micromanagement. That’s not how we use it. Our approach has been 100% transparent — employees know what data is collected and how it’s used.
We’ve also been really explicit that when numbers look unexpectedly low, the first response should be to seek to understand — not to assume poor performance.
This connects directly to our culture. When some employees carry a full workload and others in the same role with the same compensation are underutilized, it creates imbalance. Seeing that in the ActivTrak data helps us spot it early and address it quickly and fairly.
Beyond Time: Aligning Effort with Impact
Gabriela: You’ve moved beyond tracking productive hours to understanding if teams are focused on the right work — what we call activity alignment. How do you use ActivTrak to assess that alignment and drive better results?
Scott: One way we’ve started to explore this is by looking at how time and task data come together to tell a more complete story.
In one case, we had an employee working fewer hours but completing just as many tasks as their peers — in about two-thirds of the time. With ActivTrak, we can combine time and task data to see not just how time is spent, but how effective that time is. That’s opened the door to new conversations about efficiency — and how we recognize performance.
We’ve also started to evaluate client time demands. ActivTrak helps us see which accounts require significantly more effort than others, which is informing how we think about pricing — factoring in the actual workload required to support different customers.
How Value Scales Across Teams
Gabriela: You’ve shared some great use cases in finance and sales. Are there other teams or leaders at Echo who are seeing value from ActivTrak?
Scott: We started with a pilot of just 75 people in operations and ran that for a while to get basic insights. Once we saw what was possible, we expanded to about 150 and then eventually scaled to 2,000 licenses across sales and operations.
What’s interesting is some teams that weren’t part of the initial rollout started raising their hands after seeing the insights other groups were getting.
For example, our Mexico operations team is its own unit, and their president came to us and asked to get his team on the platform because he saw the kind of value it was providing other parts of the business.
Getting Started — Even Without a Data Team
Gabriela: Not every organization has someone in a dedicated data and analytics role. For teams with limited time or resources, where do you recommend they start?
Scott: We’ve done some more advanced things like integrating ActivTrak data into our own environment through the API, but even without that, you can get a lot of value right out of the box.
Just from our initial 75-person pilot, we uncovered something really surprising — employees were spending 43% of their day in email. That was double what I expected.
That insight kicked off conversations about email efficiency and how tools like AI could help reduce that load.
None of that required deep technical work — it just came from starting small and looking at the dashboards. Some of these things really jump off the page.
Benchmarking has also been extremely valuable. Every industry has its own culture and work rhythms, so being able to compare against relevant peers — without exposing any company-specific data — made the insights far more actionable. It helped us frame where we’re doing well and where there’s room to improve.
Final Thoughts: Lead with Transparency, Align with Purpose
Gabriela: Amazing Scott, thank you. To close us out, any final words of wisdom for those tuning in?
Scott: I’d say the key is going into this with the right mindset — one grounded in transparency, fairness and openness. Workforce analytics isn’t about control — it’s about aligning the needs of the business with the needs of your employees.
When expectations are clear and met on both sides, you end up with a stronger culture, a more productive team and ultimately a high-performing company. At Echo, that mindset has made all the difference.
