When we talk about being “data-driven” what we usually focus on is the “data” part. The focus is on ensuring data drives our decisions. By doing so we are missing the whole point which is the “driving” part of being data-driven.
What DRIVES us?
In his book Drive Daniel Pink discusses what truly drives people in our age:
- Autonomy — the desire to direct our own lives
- Mastery — the urge to get better and better at something that matters
- Purpose — the yearning to do what we do in the service of something larger than ourselves
Out of the three I find that creating a culture that truly embraces autonomy is the hardest challenge for most leaders who were “imprinted” in command and control hierarchal organizations.
Data can play an important “bridge of trust” in unlocking autonomy if we start looking at it as an aligning and driving tool instead of merely a decision-making tool.
Step 1: Stop digesting and isolating data on the decision-maker level
When we focus “data-driven” efforts on decision making what happens often is that the data is kept isolated in the decision making level of the organization.
The rest of the team “experiences” the data on the goal or KPI level. “This quarter we’re gonna improve retention by 50%”.
But what does this “retention” number mean to the team if they weren’t part of the discussion making process?
Most of them never saw a funnel or analyzed a cohort. This means they don’t understand the mechanics of “their” goal (retention) and as a result, they aren’t positioned to impact the goal.
What are the chances we will be DRIVEN by and stay engaged with a goal you can’t impact?
By isolating our teams from the “data-driven” decision-making process we are taking really smart people and focusing them on execution.
We are taking the “driven” out of data-driven.
Step 2: Expanding the data-driven decision making circle.
Autonomy, as defined by Daniel Pink = The desire to direct our own lives.
If we accept this then creating autonomous driven teams means asking the team to use the available data to direct their efforts. To own their direction and be accountable for the result.
But this is really hard for leaders to do. It requires a huge leap of faith as opposed to the roadmap/planning format where people commit to projects and deadlines instead of outcome and impact.
Step 3: Building a data-driven trust bridge
Let’s take our goal of “increase retention by 50%” as an example.
If you’re a leader then setting that goal and leaning back is really stressful. How do I know as a leader that we are progressing? How can I know we’re on track?
This is where having data-driven teams becomes really handy. If your team is part of the decision making, and truly understands the data and mechanics of the goals they are taking on, then they would be able to breakdown the large goal into much smaller outcomes and signals of progress.
For example:
- The data shows that users who are engaged more than 5 times in the first 48 hours are retained x2 longer than average.
- The team also identified that 90% of the engaged users used our killer feature
- But they also identified that only 10% of the users actually discovered the killer feature.
Armed with the data, the team can now create a data-driven plan that has shorter-term, measurable goals with clear signals of progress.
Our focus for Q3 is increasing retention by 50%
Our #1 priority in increasing % of people who discover our killer feature to 80%
The signal we are looking at to see if we’re prgressing is % of people who are engaging more than 5 times a week
Notice that nowhere above did the team commit to features or delivery. They have identified and committed and own a direction. They are fully committed to the business goal, and they have provided management with a progress signal everyone can follow.
Step 4: Create data-driven habits
Setting goals, even data-driven goals and KPIs isn’t enough. To really drive the team data has to be integrated into our company workflow and “habits”. for example…
Commit to impact vs delivery
When committing to or holding others accountable, try to avoid questions like “What are we committing to DELIVER this quarter?”
Instead, ask questions like “How will you measure success this quarter?” or “What would be different this quarter for our users or our business? How will we measure that?”
Done isn’t done
When we start to tie the success of projects to their impact instead of their delivery then our teams start to be driven by the data and impact instead of the “progress”.
They become literally data-driven
Step 5: Measure how many people start their day by opening their dashboard
There is a simple, yet extremely difficult success metric, that indicates the level of “data-driveness” of your team. Simply put in place tracking and measure: How many people in our team start their days with a quick view of the dashboard?
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What is the data that drives you? How has it impacted your action in the past year?
