Trust as the Foundation for Analytics Success

Trust as the Foundation for Analytics Success

Building a successful analytics team starts with trust. Without it, even the most skilled team will have their work questioned or overlooked. I learned this firsthand when I joined Twitch nearly nine years ago, where trust became the foundation of everything I set out to accomplish.

Like many people starting a new job, I felt both excited and anxious. Twitch, at the time, was a 400-person newly-acquired startup, and I was a 40-something mom with a daughter in kindergarten. I knew I wouldn’t easily fit in there. Thinking back on it now, onboarding at Twitch was one of the most challenging periods of my professional life.

While I was confident in my qualifications, I recognized that earning mutual respect in this new environment would require extra effort. I did a few things to prepare. First, every data person should understand their company’s domain, so I began to learn about gaming culture. For a confidence boost, I updated my work wardrobe. And, to structure my entry, I reread the classic business book, The First 90 Days. These actions were all aimed at making a good first impression and starting off on the right foot.

Not long after I joined, I conducted a “listening tour,” inspired by The First 90 Days. In nearly 30 one-on-one conversations, I asked my colleagues and stakeholders a consistent set of questions. I listened carefully and synthesized their responses. The core theme was clear: people wanted more trust - both in the data itself and in the data team’s work.

Several common issues surfaced during my conversations. There was confusion around which dashboards were reliable and trustworthy - a problem many companies face, where dashboard sprawl creates uncertainty. There were also challenges with self-service analytics. While people were expected to get and use data independently, many lacked confidence in their ability to find the right data. Finally, though not always stated directly, there were underlying questions about the data team’s priorities. People weren’t sure whether we were truly focused on the most important things.

After reflecting on this feedback, I made trust the cornerstone of my work. Building trust wasn’t just a slogan on a cheesy motivational poster. I was genuinely focused on fostering trust in the data team and its outputs. It became the foundation of everything I did.

During my nearly four years at Twitch, I built the core analytics and BI functions as the company grew. I introduced a data quality management practice, established foundational datasets, implemented self-service platforms for data exploration, and launched weekly business reporting for the executive team. These experiences have shaped all the work I’ve done since. As I’ve shared my thoughts as a writer over the past few months, I’ll leave you with some articles that explore different aspects of trust-building.

Reliability?

Credibility

Partnering with the Business

Alban Gér?me

Founder, SaaS Pimp and Automation Expert, Intercontinental Speaker. Not a Data Analyst, not a Web Analyst, not a Web Developer, not a Front-end Developer, not a Back-end Developer.

5 个月

You should have given me a trigger warning before mentioning "self-service analytics". Whenever I hear that I get the hives! https://www.dhirubhai.net/posts/alban-g%C3%A9r%C3%B4me_measurecamp-digitalanalytics-data-activity-7109411417237135360-BTZQ?utm_source=share&utm_medium=member_android

Krissy Tripp

Senior Director, Decision Science

5 个月

I think you bring up an interesting juxtaposition about the analyst role. In order to have trustworthy and reliable data at scale, sometimes analysts need to focus on the tedious details that give the impression they're not focused on the big picture. There are a lot of trade-offs to make between the hyper-fixation of getting everything exactly right and getting to a business answer that will satisfy decision-support needs.

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