Creating a Data-Driven Culture: Getting Everyone to Move the Same Direction

If you’re in the Seattle area, I will be giving a short presentation on data-driven culture tonight at Web Analytics Wednesday. Join us!

Changing company culture is about as simple as getting my recently acquired backyard chickens back into their coop. It seems straightforward – why wouldn’t people want solid data? Yet, somehow a broken report, cross-domain problem or communication gap will easily unravel any progress you feel you are making.

At our most recent BEST Practices conference in San Francisco I hosted a table to discuss this topic. The industries and job descriptions around the table were all different, but the problem was the same. Getting everyone in the organization to value, use and trust data is incredibly challenging.


What Exactly Is A Data-Driven Culture?

To make sure we are all on the same page, here are a few of the specific characteristics that define a data-driven organizational culture.

  1. An investment has been made in acquiring, storing and analyzing data.
  2. There is a general hunger for good data and an appreciation for the effect it can have.
  3. Data is used to inform and guide important decisions.
  4. Access to the data is not limited to top-level management.

Organizational value can be determined by what is getting attention. If analytics is simply a side project within your regular job, you will have an uphill battle and it is even more important that you set reasonable goals.


What Often Gets In The Way?

We often see a combination of factors getting in the way of a solid data culture.

  1. Disinterest: At the end of the day, people just aren’t interested in seeing data. If there isn’t curiosity or perceived value, it is really hard to get time, budget and support.
  2. Distrust: Unfortunately, bad data is all around us. You might be working with a team that has been burned by data that led them astray or made them look foolish in an important meeting.
  3. Disconnection: If the metrics provided have nothing to do with actual business goals or pressures, there will be a disconnect for members of your team, executives, and other stakeholders. This also happens when the overall vision for digital analytics is unclear or when the actual data received is confusing.
  4. Discord: It’s hard to believe, but not every team is working in perfect harmony. When teams are divided by competing priorities or personalities, it is hard to get momentum around shared metrics.

None of the items above – individually – are difficult to fix. In combination, however, you might feel caught in a vicious cycle of dealing with one problem after another.


So How Do I Fix It?

If you feel like I just described your world, I’m very sorry. It can feel incredibly daunting to change a culture that is plagued by any of the problems listed above. But it’s not hopeless. Small, deliberate steps made with much persistence will make amazing progress.

The steps below may seem obvious but often get skipped because of their misleading simplicity. They must be followed in order. Skipping straight to data and action is often what created the distrust in the first place.

  1. Plan: Sit down and decide what piece of data will be attainable, interesting and actionable. Make a plan for collecting and communicating that data. Be reasonable and focused. You can’t change everything at once, so choose something simple and be persistent in maintaining that simplicity.
  2. People: If you are drowning and need help, make sure you take time to think about the skillset that will be most helpful. I’ve talked to quite a few people that just want more analysis firepower – but at the end of the day, they need someone who is a solid networker, communicator and encourager to actually disseminate the data throughout the organization. Don’t underestimate the power of someone who is good at small talk.Also, think about what team or coworker you will provide data to first. If the VP of Something is demanding data but wants unreasonable metrics, you might get much further by finding a less powerful, but more reasonable, team member to serve first. Remember that you are looking for small wins.
  3. Data: Please, if you do one thing for me, double-check your numbers. No matter how interesting the data, if it is inaccurate you will have to work twice as hard to gain that ground back.

    Practice restraint. In the process of researching Interesting Insight A, many people also happen upon Interesting Insight B. Be very careful about throwing extra information into a report, even if it is interesting. You want a clear goal, clear expectations and clear metrics. Don’t muddy that water until you get some momentum.

  4. Action: Once you have your insights, use them. Talk about what you found and what changes that helped you make. Take the time to write up case studies and make a little noise. Then treat yourself to a frosty beverage – you’ve earned it.

Overall, the process isn’t easy, but it is not impossible. You just need a plan, some tenacity and an occasional sympathetic ear. If you are in the Seattle area, join us tonight (June 25th) for Web Analytics Wednesday – I will be giving a short presentation on this content and would love to chat more. Or, join us for one of our upcoming BEST Practices conferences to find a whole room full of people working through the same challenges.

Happy analyzing!

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