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For those without the technical know-how, software development — which more often than not involves a tangled web of commits, reviews, bug testing, and validation — isn’t exactly easy to keep an eye on. Emails and pivot tables help to a degree, but when it comes to deciphering the meandering app design process, the C-suite often finds itself at the mercy of dev team leaders.

Appcelerator veterans Jeff Haynie and Nolan Wright hope to change that. They’re the cofounders of Pinpoint, a nearly three-year-old Austin, Texas-based company developing a data analytics platform for software engineering. Through the use of instrumentation that plays nicely with systems of record like Jira, GitHub, GitLab, Bitbucket, and SonarQube, it’s able to translate activity and contributions into actionable, natural language insights that don’t require a computer science degree to understand.

Pinpoint — which formally launched its platform today — announced that it has raised $13.5 million in series A financing led by Bessemer Venture Partners, along with existing seed investors Storm Ventures, Boldstart Ventures, Bloomberg Beta, Slack’s eponymous Slack Fund, Social Capital, and Cherubic Ventures. This brings the company’s total capital raised to $16.5 million.

“It’s been years since things like marketing automation and CRM transformed how go-to-marketing teams track, measure, and improve departmental operations,” said Haynie, who serves as CEO. “But for most engineering organizations, that’s still really hard. With Pinpoint, we’ve created a way to instrument the systems where the actual work is occurring, and then use data science to interpret current organizational performance, highlight improvement opportunities, and predict outcomes.”

Pinpoint’s software-as-a-service offering automatically generates visualizations for things like cycle time, throughput, workload balance, defect rate, backlog change, and quality, without the need for any sort of manual data entry. Dev teams are scored and percentile-ranked across signals (and optionally geographies) and graphed on a cost-to-performance diagram, while employees are ranked individually both by performance and salary range.

This level of transparency, Haynie says, affords CTOs and managers the data they need to asses how teams — and engineers within those teams — are delivering against objectives over time. It might sound a little insidious, but he stresses that the goal isn’t to target underperformers unduly — rather, it’s to suss out roadblocks to productivity and determine ways people and teams can build products more efficiently.

“Software engineering is home to some of the most creative and technically astute minds in any company, but we’re behind in one really important way: namely, being able to show our contribution to the business,” he added. “With Pinpoint, we said: ‘What if we instrumented the activity in software source systems like Jira and GitHub and combined that activity with data science to understand how people, teams, and work are actually progressing?’ You get a true, data-driven view of engineering performance.”


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