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May 16, 2019

How Data Storytelling Changes Our Engineers’ Approach to Performance

At Narrative Science, we recently implemented our newest product Lexio across the entire company. Lexio turns business data into plain-English stories. The entire company regularly uses our Lexio Sales Application, which writes stories from our internal Salesforce data. It has been amazing to be able to read about how our sales team was doing at all times.

At Narrative Science, we are extremely passionate about data storytelling and use it in many aspects of our business. Because Lexio isn’t just built for sales data, it can take in almost any type of business data and write interactive stories from it.

As an Engineering Delivery Manager at Narrative Science I’m responsible for our adoption of agile methodologies with a large focus on helping teams deliver value more quickly. To help that end, the Scrum Masters and I are always looking at data with our teams.

I work closely with our Cloud Operations Engineering team, for which we have not yet prioritized building a metric dashboard. Last week, I uploaded some Jira data into Lexio for them and I was instantly able to read stories about the team’s cycle time (avg time an item takes from start to finish) and throughput (how many items/points completed in a given time period) metrics.

How Data Storytelling Fosters Greater Engagement

Usually reviewing metrics with the engineering teams is not very engaging. It’s mostly blank stares and a lot of explanation. When I pulled up the Lexio stories for the Cloud Ops team, it was a completely different reaction. The entire team was engaged and asking questions – a rarity in my experience

When viewing throughput, the team couldn’t believe that 51 points were closed a few weeks ago, so I went into Jira and ran a query to pull up the stories to prove it. After that they wanted to see how many points they closed in the current month and quarter and how those related to last month/quarter. Both showed we’re on pace to get more done, which helped them all feel that their recent efforts are paying off.

We then flipped to a story about our team cycle time and viewed various timeframes. The team was surprised to learn how consistent they have been over the past few months.  They routinely average about 3.5 days for an item from start to finish! This was an insight the team never had before and was not expected. Lastly, I pulled up which stories took the longest over the past quarter and year. This turned out to be a mini trip down memory lane for the team… “I remember that story, it took so long too…”.

As someone that’s tried compiling and viewing a lot of different metrics and tools, it was very exciting to see how quickly I could have metrics that engaged the team and allowed the flexibility to quickly answer the teams questions.

We’ve used Lexio the past few weeks and it’s been great at quickly giving us high level insights into what capacity of work is reasonable for us to plan for each week and what type of items usually take us the longest (and are therefore areas we can focus on improving).

The experience with Cloud Ops lead us to create Lexio stories for all of our product development teams, and to use them in all of our iteration planning meetings.

As Lexio evolves and grows, I’m confident it will provide even greater insights. If you’d like to try out Lexio for yourself, sign up below.

 

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