How to use data analysis to see if your team is using your systems effectively
In this blog, I emphasize the importance of actively monitoring software usage within a team to ensure effectiveness, advocating for a data-driven approach rather than relying on assumptions. I outline key metrics to track and suggest methods for accessing this data. Then I detail how to establish benchmarks for "good" usage and interpret usage trends to identify areas for improvement. Ultimately, I advocate for using data analysis to gain an objective understanding of system adoption and effectiveness.
SYSTEMS AND SOFTWARE3PL


How to use data analysis to see if your team is using your systems effectively
It's crucial that your service delivery system or internal operations software is not only useful (See my post on this.), but also actively used by your team. How do you actually ensure that?
How do know if the tool is being used? I’ve got a way. We use data analysis. We don’t rely on what we think is happening, but listen to the story data gives us. We do this internally and for our clients.
Every software is different, but what should you be looking at? It often comes down to tracking these kinds of key metrics:
How often are core actions being processed? Eg how often are new transactions created, tasks marked as completed or tickets updated? This looks at the timing and frequency of real work getting done in the system, not just logins.
How many transactions are being processed? Eg, number of invoices created, PO’s cleared or tickets escalated per week or month. This shows you the volume and helps figure out if your team is using it to its full potential or just moving things around.
Are users using the advanced or specific features they should be? Are they going into the Automation module and creating/updating automations? Are they building their own reports? This is especially important if you want to capitalize those features for efficiencies.
How does individual activity look? Is it just one or two power users doing everything or is the whole team involved like they should be? Are certain people lagging behind?
When did users last perform key actions? Has anyone not touched the important stuff recently? This helps you spot if someone's checking out.
Where do you find this info? I would start by checking for built-in admin dashboards or reports in the software. Sometimes you might need to export system/audit logs, or even query the database directly if you have that access and capability.
Now, in order to be able to compare the data, you need to establish what 'good' usage actually looks like? You could figure this out by running through the key tasks yourself, or by looking at how a really effective team member uses the system.
The idea is to track these numbers over time, maybe weekly or monthly. Are things getting better, worse, or just staying the same? Compare current use to how things were before, or even against your original goals for the system.
What could the data actually be telling you?
Low overall usage might point to training gaps, the system being clumsy to use, or the team just not seeing the point.
Uneven usage can show you who needs extra help or maybe who your internal champions are that others can learn from.
Underutilized features often mean users don't know about them, or don't get how they help with their actual tasks.
Declining trends could signal problems with your process, people finding clunky workarounds (a bad sign!), or just growing frustration.
Based on the insights, you might need to:
Run specific training sessions on the tricky bits or underused features.
Actually talk to the team – find out the 'why' behind the numbers.
Tweak system settings to make things easier, or push the vendor for improvements.
Rethink your team's workflow and how the system fits into it.
Be clear about expectations – make sure everyone knows why using the system properly matters.
By digging into the data like this, you can stop guessing. You’ll get a clear, objective picture of what's really happening.