How to Use the Right Metrics to Motivate Employees & Improve Startup Success
Metrics matter. But if you track the wrong ones, everything goes to shit. (#4)
One of the toughest things for employees is not understanding how the work they’re doing really contributes to the overall progress of the company. There's often such a huge disconnect between what someone is working on (i.e. building a new feature, fixing something, etc.) and the core focus of the business. Unfortunately, I see this challenge quite a bit. People are busy--always busy--but somehow not making real progress. Things are happening, people are crossing tasks off their to-do lists, and yet the top-line metrics that tell you if the business is heading in the right direction aren’t really shifting.
In Lean Analytics, Alistair Croll and I suggested that companies have a single metric to track everything: the One Metric That Matters.
Our intent wasn’t to say, “scrap all that data you’re collecting, and only track one single number.” But the easier it gets to track more data, the harder it is to figure out which numbers actually matter. Suddenly, there’s so much data, the dashboards are overflowing with information, and no one can make an actual decision. So the principle of the One Metric That Matters is to simplify--focus on what actually matters, and empower yourself and your team to make better decisions.
In the diagram below, what you see is the One Metric That Matters at multiple levels within an organization (be it a startup or big company.)
At the project level, we’re focused on small initiatives such as adding a new feature, initiating a new marketing campaign, or improving our customer success systems. Each of those initiatives has a One Metric That Matters, which tells us if the project was successful. For example, our new feature was meant to increase engagement, because we need customers using our software platform more frequently. We’ll track actual usage of the feature as a proxy of value creation; i.e. if they use the feature we expect they’re getting value from it.
That project level OMTM bubbles up to our department level OMTM. In this example, the “department” is the Product team, which is running a few sprints on engagement and trying to increase MAU (Monthly Active Users.) The hypothesis is that more use of this new feature increases MAU, which is considered a good thing, because the more that people use the product, the more likely they are to renew (and not churn.)
Finally, the department level OMTM bubbles up to the single One Metric That Matters for the business, which I would describe as the “Business Health Indicator.” This is a high-level metric, not necessarily as actionable as others, but indicative of how things are going.
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Case Study: MOZ cuts down on metrics to track
In 2011-2012 when writing Lean Analytics, we connected with Joanna Lord, who was VP of Growth Marketing at Moz, and wrote a case study for the book. I’m sharing the case study below because it does a great job of illustrating the importance of simplifying metrics:
Moz is a successful Software as a Service (SaaS) vendor that helps companies monitor and improve their websites’ search engine rankings. In May 2012, the company raised $18 million. Its CEO, Rand Fishkin, published a detailed post about the company’s progress up to that point. Rand’s update did include a number of vanity metrics—when you have roughly 15 million visitors on your site each year, you have the right to a bit of vanity—but he also shared some very specific and interesting numbers related to conversions from free trials to paid subscriptions and churn.
We spoke with Joanna Lord, Vice President of Growth Marketing at Moz, to learn more about how the company handles metrics. “We are very metrics-driven,” she says. “Every team reports to the entire company weekly on KPIs, movement, and summaries. We also have a huge screen up in the office pumping out customer counts and free trial counts. We believe that having company-wide transparency into the metrics keeps us all informed, and is a great reminder of the progress (as well as the challenges) we are seeing as a company.”
For a company that’s found product/market fit and is now focused on scaling, it becomes more challenging to focus on a single metric. This isn’t surprising; there are multiple departments all growing quickly, and the business can tackle several different things simultaneously. But even with all these concurrent efforts, Joanna says that one metric stands above the rest: Net Adds. This metric is the total of new paid subscribers (either conversions from free trials or direct paid signups) minus the total who cancelled.
“Net Adds helps us quickly see high cancel days (and troubleshoot them) and helps us get a sense of how our free trial conversion rate is doing,” Joanna says.
Moz tracks other related metrics including Total Paying, New Free Trials Yesterday, and 7-Day Net Add Average. All of these really bubble up into Net Adds per day.
Interestingly, when Moz raised its last round of financing, one of its lead investors, the Foundry Group’s Brad Feld, suggested that it track fewer KPIs. “The main reason for this is that as a company, you can’t simultaneously affect dozens of KPIs,” Joanna says. “Brad reminded us that ‘too much data’ can be counterproductive. You can get lost in strange trends on numbers that aren’t as big-picture as others. You can also lose a lot of time reporting and communicating about numbers that might not lead to action. By stripping our daily KPI reporting down to just a few metrics, it’s clear what we’re focused on as a company and how we’re doing.”
In the context of levelling up metrics from a project to a department to the entire business, Net Adds is an interesting “business health indicator” because it can quickly help you ask better questions and dig into good or bad things that may be going on. Below is a screenshot of a slide I often share when doing presentations on Lean Analytics and product management.
The talk track for this slide is basically as follows:
By using one metric (Net Adds) to measure the overall health of the business, on a daily basis, you can move quickly to figure out if things are going well or not.
If Net Adds go up, celebrate! 🥳️ Then quickly figure out why Net Adds are going up because you want to “do more of that.”
If Net Adds are flat, take a deep breath, but dig in a bit more. 🤨 You can’t afford to have Net Adds staying flat for too long, because you’re not growing.
If Net Adds are going down…ya, panic. 😰 OK, don’t panic, but raise the alarm and move fast.
In each scenario, you can go to each department or team (i.e. Product, Marketing, Sales, Customer Support, etc.) and ask good questions. Ultimately that’s what analytics is all about; providing you with the necessary information to ask more informed questions (of the data, the people, etc.)
Diagnosing real problems may never be this easy, but at the same time things get a lot simpler when you know what One Metric That Matters is critical to assessing the overall health of the business, because you can align the entire company and dig into what’s going on. Every employee knows that the work they’re doing should be geared towards improving Net Adds. Easier said than done, but directionally simpler for people to understand and get motivated around.
A couple key points to make:
The project and department level OMTMs will change quite frequently. The highest level business health indicator may change less frequently, but it still changes based on the stage of the company.
You’ll rarely get a perfectly straight line from lower level to higher level metrics. In our example, we may see good usage of a new feature, but it may not have a meaningful or direct impact on MAU. That’s why the lines are drawn as squiggles; we’re making best efforts to directly link all the work people are doing to higher-order value creation, but it’s not a perfect science.
This framework is relevant for startups and corporate innovators. In my work with corporate partners I often get asked, “How can we better connect the growth innovation we’re doing with our corporate goals or mandate?” This is incredibly tough to do. There are some organizational challenges that you’ll face, and also plenty of questions on impact. Thinking about relatively simple metrics that you believe matter at each “level” of the process may help.
And I always go back to the employees and the people working every day to create value. In the end, without people committed to doing the right work, there’s no startup or corporate innovation mandate that will be successful. A framework such as the One Metric That Matters can provide a way of asking the important question, “Does this work really matter? Do we genuinely believe this will move the right needle?” If you can’t figure this out, your startup, corporate growth innovation project or anything else is in real trouble.