How Leaders Can Motivate Teams to Analyze Data
Making data easy to access is not enough to avoid the “analytics-free” environment.
Leaders need to provide the proper motivation.
A broad definition of motivation includes compelling teams to change their behaviors, holding them accountable, avoiding demotivation and praising teams who are early adopters of consistent data analysis.
Asking "Why" a team is working on something gives them the chance to think more deeply about how their work connects to the company's goals and solves a customer problem.
Only discussing "What" teams are working on persists the "analytics-free" environment.
[ This is Part 4 of the Analytics Transformation series ]
Concrete steps to motivate teams to analyze data:
Change the conversation
Start team meetings with metrics so they don’t get left out
Require one team to present data analysis every week to the whole group
Devote at least 25% of 1:1 sessions with PMs to discuss metrics
Ask teams whether analytics tagging has been done. Follow up.
Set and use metric goals
Use metrics in design reviews (“How will this design help you achieve your key result?”)
Use numeric outcomes instead of deadlines when discussing if a feature is “complete”
Set a product team success metric and link to a company goal through intermediary metrics in a connected chain
Have teams add success metrics to their engineering tasks
Encourage curiosity
In the early days of a data analysis transformation, set internal metrics for the frequency and usage of analytics tools by team members to get them comfortable using analytics tools
Leaders also need to beware of their own behavior.
They need to avoid these demotivators:
Only focusing on deadlines
Dictating features
Not using data themselves
You can read more about motivators (promoting pressures) and demotivators (inhibiting pressures) in the behavioral science book Start at the End by Matt Wallaert.
Successful leaders get good at creating a better working environment and changing behaviors.
When teams have easy access to data and are motivated to analyze data, they become self-learning engines of innovation.
Reach out to me if you’re interested in accelerating your team’s adoption of metrics in Product Management.
Jim coaches Product Management organizations in startups, scale ups and Fortune 100s.
He's a Silicon Valley entrepreneur with over two decades of experience including an IPO ($450 million) and a buyout ($168 million). These days, he coaches Product leaders and teams to find product-market fit and accelerate growth across a variety of industries and business models.
Jim graduated from Stanford University with a BS in Computer Science and currently lectures at UC Berkeley in Product Management.
