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Data-Driven Thinking for Continuous Improvement

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Organizations need an objective way to measure performance and tie actions back to business outcomes to improve continuously. Avvo uses a data-driven decision framework with an autonomous team model and a practice of retrospectives to help people make better decisions and proposals for continuous improvement.

Kevin Goldsmith, Chief Technology Officer at Avvo, spoke about building a culture of continuous improvement at QCon London 2018. InfoQ is covering this conference with Q&As, presentations, summaries, and articles.

InfoQ interviewed Goldsmith about what a culture of continuous improvement looks like, what he did to build a foundation for continuous improvement and how agile retrospectives and data-driven thinking fit in, and how autonomous teams and accountability go together.

InfoQ: What made you decide to start working on the culture; what triggered it?

Kevin Goldsmith: My experiences at Spotify taught me the value of building an engineering culture deliberately. When I came to Avvo, the engineering culture had evolved organically. It had some valuable elements, but also some weaknesses. There was a lack of focus on delivery and poor personal interaction models. To improve the delivery and morale of the organization, it was clear to me that we needed to invest in creating a better culture.

InfoQ: What does a culture of continuous improvement look like?

Goldsmith: It’s a culture where there is no "status quo" or "because that is how we do things here." People are encouraged to find better ways of doing their jobs. We allow trials of new approaches. If they work well, we adopt them. We not only give people ownership over their work but also over the organization and its processes. One example of this is our Journey Team structure. We knew that our existing team model wasn’t working well for the individuals on the teams, but they never got "permission" to fix it. After moving towards our new culture, an ad-hoc group of product and engineering team members came together to design a new team structure. Journey Teams are now our organizational model.

InfoQ: What did you do to build a foundation for continuous improvement?

Goldsmith: It was an extended effort that involved creating a solid foundation of multiple elements. First, we created a framework to bring clarity to the company strategy and priorities. For people to make good suggestions, they need to understand the company’s business context. We then created a data-driven decision framework to help people make better decisions and proposals. We devised an autonomous team model, which allowed (among other things) a narrower scope for experimentation. Finally, we built a practice of retrospectives, beyond the normal agile team practices, encouraging and demonstrating how to examine the results of experiments in a non-judgmental way. The retrospectives help us learn from our failures and successes.

InfoQ: How do agile retrospectives fit in?

Goldsmith: Retrospectives are critical in a culture of continuous improvement. They collect the lessons from any change. Without a blameless evaluation and an understanding of the results of an experiment, you are bound to repeat your failures and will be unable to recreate your successes.

InfoQ: How did you apply data-driven thinking for improvement?

Goldsmith: In a creative environment, ideas flow like water in a mighty river. With many choices, how can you determine the best course of action? If you only have opinions to base decisions on, the loudest (or most highly paid) person chooses. Data democratizes the decision-making; it clarifies the options and potential outcomes. We created our own data-driven decision-making worksheet influenced by the Toyota A3 form and Spotify’s DIBBs.

Recently, I was talking to Avvo’s chief product officer about a change I wanted to make to our Data Infrastructure, that would require some effort from our data engineers and would take them away from supporting the product team. He asked me where the decision worksheet was. I hadn’t made one yet. In the course of filling out that worksheet, I found data that made me realize the change I wanted to make wasn’t going to give the company a good ROI. I recognized that it was a bad idea.

The concept of DIBBs, Data Insights Beliefs, Bets, and how Spotify uses them for continuous improvement, is described in the article Spotify want to be good at failing.

InfoQ: How do autonomous teams and accountability go together?

Goldsmith: Autonomous teams and accountability don’t go together automatically. You need to build a structure so that teams feel responsible for their outcomes. Organizations need an objective way of measuring their performance and tying their actions back to business outcomes. Without this objective measure, an autonomous team can lose their sense of accountability. The team doesn’t understand the value of their work for the business. An objective measure, agreed upon with the larger organization, also gives the company leadership visibility into the value that the team is producing, without having to disrupt their work.

Additional information on Goldsmith's talk, "Building a Culture of Continuous Improvement", can be found on the QCon London conference website.

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