Driving data adoption [Win swag!]

Developing an amazing Looker instance and taking the time to build a model is just the first step in empowering your company to make better use of data. Through this new community category, Data Adoption, we want to encourage the sharing of best practices for building a data-driven company culture.

To kick off the discussion, we want to hear from you what steps you’ve taken to drive data usage at your company. Anything goes, from how you train business users to what your documentation system is, and beyond. The top five answers will be rewarded with some cool Looker swag!

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@cassidy.kjeldsen - great initiative!

I am happy to kick-off and share two ways in which I raise Looker awareness and adoption within the company:

  1. Relay system usage data back to users in Explore models - I do this via ingesting daily Looker usage data into our BigQuery warehouse via Looker schedules and Google Cloud Platform tools. Internals such as team managers can then assess their team’s data queries by volume, frequency, content, etc., and beyond 90 days prior.

  2. Biweekly Q&A on Slack - people throw Looker questions at me in a #Looker channel and I answer back, often with additional tips and tricks with direct links to Look reports.

I am looking forward to reading more fab ideas and experiences in raising a better company data culture!

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@Lewis_Osborne Thanks for jumping in and starting off the conversation!

I can sure speak to this one!

We’ve been working on our Looker install for about a year, and I’d say the biggest thing for us has been actively holding Looker Tours, which last for about an hour, and are roughly half front-end showing-off along with a sort of internal sales pitch: I liken Looker to having a superpower, where anyone is able to explore our internal data as though they know the sum total of everything each developer knows (which is a lot!) - and then half back-end, here’s how the sausage is made type of thing.

These are live, via Zoom, probably 80% screenshare. I try to be as approachable and conversational as I can be, and welcome any and all questions: I’ve done enough at this point to appreciate the way that a group of marketers will think/approach it differently than a group of developers, but it’s great fun for everyone. We also record many of these and keep them in a shared Google Drive, where folks who are in tough time zones or don’t prefer a live conversation can still benefit.

Our team that focuses on Looker has also started to shift our ongoing Data Request process into Looker: where once we’d run ad-hoc queries and share .csv files, now we model data and produce and share quick Dashboards: the first time someone expects a .csv and gets a full color interactive dashboard with drill fields has been a huge source of a-ha moments for our organization, and almost always leads to later joining a Tour and then becoming an active consumer of Looker reporting.

We also work pretty hard to be super approachable, to answer questions, and to really advocate for the platform: having everyone on-board and also friendly and positive can make a huge difference.

Excited to see what other folks are doing here!

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To me, I like to think it’s about authenticity, purpose, and assuring that those who are using the dashboards receive value from them.

Why do we show service plan attachment rates? So that we can show the commissions salespeople can earn if they bump their sales by 5-10%.
Why do we use an item affinity model? So that we can be guided to create item kits that offer greater value to our clients.
Why build customer models? So that we can be an awesome company that shows its care for our clients by reaching out regularly, while making it easier to stay current for our teams.

If we can design authentically with the purpose of making improvements for the users we serve, and meet them not far away from where they’re already working, then we’re doing our part.

Useful Products + Usable Products = Used Products!

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I use Looker extensively as part of my work at Moderna, Inc. My team has been using it for one and half years now. It has become indispensable in providing us what we need and more.

Nearly all our applications have dedicated Looker dashboards. These give so much insights and specially the Visualization blocks built by us can be replicated by other teams with little or no modifications.

I have also experimented with LookMl models in order to provide navigation from Looker dashboards to our in-house web applications. And I think I will be using it more going forward as it is very easy to implement and very intuitive too. Our research associates and scientists love these Looker dashboards as they can keep track of all the metrics they need and their data is more organized now. My presentations are also more informative thanks to Looker.

Personally I can say that my switch from Tableau to Looker has been worth it.

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I have done two major efforts to drive adoption of Looker. The first is when we first rolled out Looker (and I have done this at two different companies) is to have a dashboard contest for all the users. Criteria was based on usability and value to the company. There was an impartial panel of judges and prizes for 1st, 2nd and 3rd places, along with, of course massive bragging rights. This served two purposes, first, obviously it got many to jump in and learn Looker and the second was to seed it with some really valuable dashboards. Second are roadshows, which was really just going to different groups in the company, doing a demo and then do a hands-on workshop where they could build looks and dashboards with out help.

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We have started to heavily focus on our looker instance’s usability and how we can improve it to drive data adoption. Our team performs regular UX research and testing with our analysts to understand how they use our instance.

We also do regular show and tells based on our user submitted business questions they want to use looker to understand. We take an ongoing rolling list of these, and will put on brownbags walking through and explaining how to interesting questions into actionable reports and data. We find this inspires our users to try more.

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Operating in 12 different countries with even more offices, our key to user and data adoption have been having a local Looker expert user in each country. A local Looker expert is a business user that have an extensive knowledge about all our data that you can find in Looker. If the expert get a question that is above his knowledge then the data team is always ready to step in.
New employees gets an intro session from the local data expert, tailored to the need of his or her work. In our experience having a local person makes it a lot easier for our colleagues to ask their data questions, which helps creating a lot of confidence in our data.
On top of that the data team creates complex analysis which is presented to each country, the dataset behind each analysis is added as an explore in Looker, so everyone have the option to dig deeper into the data.

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For context, I’m a data team of one supporting about 30 users. Roughly 25 of those users are active at least on a weekly basis. We’ve been using Looker for almost 1 year. YMMV for some of these suggestions depending on the scale of your team and company.

Thorough training
We’re a small company, so I can actually afford to train every new Looker user in group sessions. I hold beginner (monthly) and advanced training sessions (less frequently) to make sure each person with a license really knows how to use the tool, including Browse and Explore. I believe it’s really important that you teach people to use Looker within their first week or so at the company so they will incorporate it into their habitual workflows from day one.

Focus on Explores
We are an Explore-first company, and we encourage our users to self-serve their own requests. My goal is that 80% of all data or analytics requests can be self-serviced by each user in Looker. This helps with adoption because people become active users of Looker, not passive users, and spend a LOT more time in Looker when they feel empowered to answer their own questions.

Update emails and Slack
I add each new user to a contacts group that I frequently email with release notes: new explores, dashboards/looks, examples of cool things other Looker users are doing, etc. I probably send these emails monthly. These are all updates I should document anyway, so why not email them out as an extra touch point for people who have forgotten about or lost interest in Looker? Maybe the new explore I rolled out suddenly makes Looker relevant to one of my colleague’s jobs, when previously it was not.

Weekly KPI report
Our weekly KPI report goes out to most people in the corporate office every Monday. This helps reinforce Looker as the source of truth for performance metrics and is a natural point for people to do their own analyses in Looker when they have questions about the weekly report.

Automated feedback collection
I wrote about an Airflow job I set up that uses i__looker and the Looker API to email inactive and active users different email templates asking for feedback on their experience. This is a good opportunity to catch “sticking points” or frustrations that otherwise would cause a user to become inactive.

Weekly data exploration sessions
I make sure I spend some time in Looker browsing Explores and answering my own questions. Sometimes, this helps me find bugs before my users do! Other times, I find interesting insights that I can pass on to my stakeholders on various teams. These are insights they a) may not have known how to pull or b) may not have thought to investigate.

Looker "ambassadors"
Each team has 1-2 people who have organically developed into Looker power users. These people are becoming ambassadors for Looker across the company and the word-of-mouth credibility they provide is powerful. I make sure to support these people really well, meeting with them quarterly to gather feature requests.

With any product, you want to:

  • Remind people it exists and actively demonstrate to them how it makes their lives easier
  • Understand frustrations of active and inactive users and fix them
  • Create a community of users who can help and support each other

I believe the same goes for driving adoption of Looker at your company. A little empathy goes a long way!

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