What if your dashboards could do more than just display metrics? What if they could bridge the gap between strategic goals and daily execution? Sleuth explores how to design dashboards that bring teams together rather than pull them apart: https://lnkd.in/gq7icUKv
关于我们
Sleuth helps Engineering align and execute at an elite level so they can deliver more business value. Sleuth does that by combining all the ingredients for a true data-driven engineering culture: Metrics, Reviews, and Automations. Metrics include quantitative ones such as DORA metrics, as well as qualitative ones such as DevEx score that fit frameworks like SPACE. Reviews are Sleuth's secret sauce for turning metric insights into real outcomes and ultimately business value. Examples of Reviews include: State of Engineering check-ins, resource allocation planning, sprint reviews, ops reviews, sprint reviews, and more. Sleuth provides pre-built, auto-filled, and AI-powered templates to make such Reviews painless and productive. Automations ensures the data for Metrics is clean and accurate, while helping increase both developer happiness and experience. Visit Sleuth.io and request a demo to learn more.
- 网站
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https://www.sleuth.io
Sleuth的外部链接
- 所属行业
- 软件开发
- 规模
- 11-50 人
- 总部
- San Francisco，CA
- 类型
- 私人持股
- 创立
- 2019
地点
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主要
获取路线
US，CA，San Francisco，94114
Sleuth员工
动态
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These are the Top 3 anti-patterns when you use AI for Engineering management purposes: #1 - Replacing team members with AI ?? #2 - Augmenting junior devs with AI ?? #3 - Automating recruitment with AI ?? Read here to learn more ?? https://lnkd.in/gpQZmXpj #EngineeringManagement #AI
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Meetings are Killing Your Gains!! Many teams struggle with endless stand-ups, status updates, and check-ins that disrupt deep work. Great teams run well-structured, data-driven Engineering Reviews instead. Read how ?? https://lnkd.in/gXGhsR_e
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DORA or SPACE? Both of course ??
I think the SPACE framework [1] should be the starting point of any discussion about which metric to use to measure software engineering. I love that it encourages a more balanced view of productivity while leaving it up to the reader to adopt to their situation. It doesn't give you answers but helps you ask better questions. [1] https://lnkd.in/gvF2ns-S
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The good and bad of "DX Core 4" set of metrics ?? (How cool is that to come up with your own metrics framework, every vendor should do it... or not)
I almost didn't include DX Core 4 one as I'm a co-founder of Sleuth, which provides a competing product to the framework's author, DX. We did anyway, because like others in this series, they have some good, some bad, and as we discuss [1], the metric itself doesn't matter as much as how you use it. Fighting about which metric is like fighting about the best camera - just take pictures already! [1] https://lnkd.in/eZr9tqRn
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Cycle time is a more encompassing metric than change lead time. It is a measure of how fast an Engineering team can deliver value. It starts from when a ticket is created as a result of collaboration between Eng and Product to document something of value to the business. As Don said, the first step to tracking cycle time is to start creating tickets for product roadmap items.
I love the idea of cycle time; I just don't think it actually works. If you have a defined point like the moment a product team puts a task on a roadmap, great. But, if you define cycle time starting as the moment of concept, boy, that'd be a pretty impressive process to document at that detail. Even the concept of putting work into tickets/issues is surprisingly not rigidly adopted in many places.
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# of PRs merged can be the perfect software engineering metric? ??
I admit it - I break my own rules and sometimes use number of merged pull requests within my team. When combined with a bunch of other context like their role, recent activity, collaboration rates, etc, looking at how many PRs a dev gets pushed to production can be a good indicator of how well things are going. Often, I already have an idea that things aren't going well, and the data either backs that up or it doesn't. I don't, however, think it is a good idea to put that type of information into a comparison up on even a management dashboard. This is one of those metrics that is useful to have available to dug into a bit, but only rarely.
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Sleuth转发了
DORA [1] metrics are like the British rock band Blur. Both got famous for something that they aren't. Blur's most well-known song, "Song 2", was a joke to the record label, with many seeing it as a parody of vapid pop music. They, along with others like Beastie Boy's "Right to Party", were unironically adopted by mainstream as they things they were parodying. DORA, originally the DevOps Research and Assessment group, sought to understand, with data, what are the best DevOps practices. To do that, they needed a way to measure and came up with "the four keys". To tell the story, they grouped company responses into categories from "Low" to "Elite". Unfortunately, DORA is now synonymous with "DORA metrics", with people often mistakenly thinking that they must be "Elite", thereby missing the whole point of the metrics and research in the first place. Ok, those two things aren't exactly alike, but if squint, they are, and really, do you appreciate how hard it is to bring Beastie Boys up in a conversation about developer productivity metrics? [1] https://dora.dev/
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One year ago we set about building the next generation of Sleuth, code-named Pulse for the heartbeat of the Engineering organization. Fast forward a year, and Sleuth 2.0 is officially here: AI-driven, fully-interactive, engineering metrics intelligence platform designed for engineers, by engineers. Our vision for this product, from day one, was to move away from dashboards towards actionable metrics infused into your teams' rituals and cycles: - Standup reporting with git and Jira data - PR-approval delays and productivity bottlenecks - Epic progress in sprint reviews - Investment streams in monthly CTO discussions - And more! Sleuth Reviews combine PR-style submissions and approvals with templates for every type of activity, like sprint reviews, quarterly reporting, DevEx surveys, and more, enabling Engineering to drive improvement via operationalization of core metrics of quality and flow. Read the full post here ?? https://lnkd.in/g5PBb4GG