Hello to Canada’s SaaS Community,
Measurement doesn’t need to be complicated. Unfortunately, though, brainstorming a million complex metrics is easier than doing the simple-yet-difficult work of identifying the *right* metrics to track. Speaking with SAAS NORTH, serial entrepreneur Joseph Fung shared his framework for identifying the right metrics to track in your startup.
- Metrics are about tracking progress toward an outcome, rather than being an outcome by themselves.
- Finding the right metrics for your organization means answering the question, “How do we know we’re heading in the right direction?”
- Check metrics weekly and leave room for iteration—even if you got it right the first time, things change over time.
Co-Founder/Producer, SAAS NORTH Conference Editor, SAAS NORTH NOW
The ocean of data available to startups is bigger than ever. But the real challenge is identifying which metrics you need to track.
Joseph Fung knows this well, having built and scaled TribeHR through data-driven decision-making before exiting to Netsuite. He went on to found sales enablement platform Kiite and has recently raised over $14 million for his current startup, career success platform Uvaro.
Speaking with SAAS NORTH, Joseph shared the question he asks to help teams identify the right productivity metrics to track.
The first step toward measuring the right inputs is knowing what outcomes you need to achieve. This starts with the big vision (the “rallying cry”) and distills down to the departmental and eventually individual level.
Unfortunately, said Joseph, this is often where startups can get stuck. What often ends up happening is that outcomes seem relatively easy to identify–for instance, the Product team needing to release a certain feature this quarter–but tracking progress falls by the wayside.
“Everyone agrees that data is good and very few people agree on how to leverage it day to day,” said Joseph.
In an effort to track something, leaders might choose an obvious metric like lines of code written for that feature.
But is this the right metric?
Does it actually tell you whether the feature is any closer to being completed? In a way, yes, since code is the foundation of the feature. In a more real way, though, it doesn’t, since more lines of code do not necessarily correlate to a high-quality feature shipped on time.
This is where Joseph said companies go wrong.
“A lot of companies make the mistake of saying ‘How do we measure our activity?’” said Joseph. “Your activity could be spinning your wheels and staying in place. And you can have a beautiful number, but it doesn’t tell you where you’re going.”
A simple question to find productivity metrics
What companies need, said Joseph, is two parts in a single system: the first part is a way to collect data effectively and the second part is collecting data that tells you when something is going wrong so you can act on it.
To find the productivity metrics that work for your organization, Joseph said you need to ask one question and answer it deeply: How do we know we’re heading in the right direction?
In the feature release example, lines of code don’t really tell you if you’re heading in the right direction. However, another metric, like the percentage of developer time spent on that feature compared to other work, might do the trick.
“If you start from that question–how do we know we’re heading in the right direction–that’ll elucidate a much better set of KPIs,” said Joseph.
Once you have a few metrics to track, you need a process behind them so those metrics can drive action.
1. Identifying on-target versus problems
In the percentage of time spent example, this might mean balancing developer priorities against other work and figuring out what amount of time makes sense for the new feature. It could also come from a work-back of estimated hours to complete a feature versus developer capacity.
2. Reviewing weekly
Each week, review the KPIs to see what’s green (on-target) versus red (needing attention). Weekly check-ins are crucial, said Joseph, because it helps avoid problems.
“If you’re not doing it weekly… you’re just not pivoting fast enough,” said Joseph. “Every change ends up being a massive one instead of a very small course correction.”
One note Joseph added is that metrics may need to change, particularly if they don’t align with reality.
“If they’re all looking green and your high-level metric is off track, that means your understanding of the business is inadequate,” said Joseph. “You picked the wrong KPIs. And so you need to double-check on your understanding and add the right KPIs to your scorecard.”
3. Follow a rigorous meeting agenda
Review meetings are not just to talk about existing metrics; they are also to create space for iteration.
To make sure this happens, Joseph recommends following a strict meeting agenda:
- Review existing metrics with a discussion about how to fix any “red” numbers.
- Opportunity for team members to bring up additional metrics they feel should be tracked.
- Opportunity to debate and/or remove existing metrics if you find they don’t actually help you identify if you’re heading in the right direction.
Leadership meetings would follow the same agenda with a different first step and last step: the first step becomes addressing multi-team metrics (e.g. whole go-to-market metrics rather than just sales lead gen metrics). An additional final step is to give leaders space to bring up any lower-level “red” metrics they feel merit additional discussion.
“The consequences of not doing that is red matrix problem areas go unspoken,” said Joseph. “They end up hiding in teams and departments and you need to have a clearing house where people can elevate them into higher-level meanings.”
The real problem plaguing startup teams
A concern CEOs might have when building dashboards and selecting KPIs is that employees will go into an obsessive metrics-tracking mode, focusing more on that than their actual work.
While this is a fair concern, Joseph said it almost never happens in reality.
“If you’ve got a scorecard with 20 metrics and they’re not, they’re always green and nothing’s moving, your team is going to hate talking about them,” said Joseph.
Instead of thinking about productivity theatre, Joseph said the real issue CEOs should worry about is data literacy. This doesn’t mean training everyone to do SQL pulls, though; it means ensuring people actually know how to read data when it’s put in front of them.
“What you really need across the board is data literacy,” said Joseph. “That means really understanding how ratios are calculated and how to read your financial statements; how to actually consume the data as a reader. And that’s an important skill to have across all of your management layers.”