Illustration by Matt Peet

Plenty of modern software leaders are scooping up mountains of data to better understand their users and their needs. But how many are collecting data from within their organization to drive more strategic decisions. Whether you’re the VP of engineering or the director of HR, understanding what’s happening within your organization and teams is just as critical as collecting app usage data. 

From homegrown data management and paying for platform solutions, to no internal data collection, many organizations suffer gaps in the data that would support their strategic decision-making. Without synthesized data to help drive decision-making in an objective way, leaders are only partially informed on everything from development cycles to hiring processes.

Brenda Jin, founder and CEO of Guanyin Labs explains the need for sound data has become critical for any tech leader. 

Jin taught herself to code in 2013, and quickly went on to create mobile web experiences for Macy’s and led several initiatives at Slack, including Slack’s developer platform, enterprise and shared channels beta. After her time at Slack, Jin set out to start her own company that puts the focus on data-driven decision making, specifically around how organizations hire and manage their teams. 

“The more data leaders have, the more benefit they stand to gain from really aggregating their data because the benefits really scale with the volume. And so does the impact of the decisions that they make.”

Jin believes that data has to be more strategic and nuanced than just compiling the metrics you’ve been tracking for years. It’s about knowing what information your organization needs to be successful, and using the data to drive better outcomes.

“A lot of companies don’t have the infrastructure to get started,” Jin says. “They're not able to connect the dots between long-term impact and changes they’ve made to their workforce.”

“There is a wealth of under-leveraged data in a number of different sources,” she says. “Organizations are getting more sophisticated and strategic about aligning people operations metrics to their key business initiatives and objectives.”

We chatted with Jin on how leaders can and should be thinking about their data, and she offered up insights from her perspective as a developer and a founder.

Successful engineering leaders have many qualities that keep their customers happy and their teams behind them through smooth or choppy waters. Things like honesty and transparency are surely part of the recipe, but Jin also argues that leadership is about hitting goals and objectives regularly.

“That’s the difference between luck and leadership—consistency,” she opined on Medium. “What matters is not that you can do one thing well, one time. What matters is that you can do it again, and again, and again.”

Consistency is more than showing up every day with a can-do attitude. It’s about setting realistic expectations so everyone on your team knows what the goals are, and measuring the incremental progress toward those targets. As Jin puts it, “In order to be excellent at work, you’ll need to understand your team, and ultimately, your company.” 

In times when team performance is lagging, and data is not helping make sense of why, you are forced to glean information from the past, which may be missing critical metrics. In this case, your retrospectives become similar to a backwards dot-to-dot puzzle with only half of the dots available. Jin backs the notion that the metrics any leader monitors should be continuously revisited.

“What many of us do today is look at employees at a snapshot in time and try to work backwards to figure out exactly what happened.” Jin says. “Leaders often rely on the metrics that are already available. But nowadays, there are opportunities to enhance or aggregate data in new ways to gain insights that can really isolate the key factors that support strategic decision-making. With better data, we can proactively identify which initiatives or leadership behaviors are highly correlated with success.”

With the inherent business need for data in setting and measuring progress toward goals, it’s just as important to make data as consumable as possible. Your metrics have a story to tell. But humans, unlike computers, are visual learners. Recalling her time at Slack, Jin highlights how her team used visual dashboards to deliver key information in a timely manner. 

“When we changed rate limits to API tokens, one of the first things we did was set up a dashboard so that our business partners across partnerships, product and customer experience could have real-time visibility into which developers and teams were affected by the new rate limits,” she says. “Because we had this visibility, we were able to stay in sync as we deployed the changes while minimizing negative end user impact. It would have been much harder to do if any of the business stakeholders had to pull ad hoc reports.” 

Developing a strategy behind the metrics your organization is tracking toward and making it readily available offers tech leaders the ability to make informed decisions that can be implemented quickly. According to Jin, the right data allows leaders to see the issues at hand and act much faster. “Data can help you discover the number one thing that we can influence and change today,” Jin says. “Companies can course correct much faster if they can isolate issues at that level.”

Prioritization is key to leading a high performing team. Finding and fine-tuning the high impact points of your business delivers clarity on what’s worthy of your time, and what needs to be dropped. with the insights that we're able to do with computing, like we can just zoom in on exactly what matters. 

“This question of prioritization has been really front-and-center in my mind because the priority of strategic decisions that leaders have to make can be at such a large scale,” Jin explains. “With the insights that we're able to do with computing, we can just zoom in on exactly what matters.” 

But how do you decide where to put the time and resources of your team? Strong data can help you understand how your efforts are working toward company goals, and can make quick work of the daily divvy of workload and resource allocation. 

“Most decisions must be weighed on multiple axes. Do you tackle the tech debt today or lay the foundation for tomorrow? Is it better to squash bugs, build tools or ship features?” Jin asks. “There is a limited total amount of time and energy you can devote at work. Being able to align your efforts with the company will ensure that your contributions have maximum impact.”

Currently undergoing the first wave of hiring software engineers at Guanyin Labs, Jin is using learnings from her work with customers as she prioritizes. She has seen just how time-intensive the hiring process will be, and how much she has to prioritize her time around that effort.

“Eventually the priority of my strategic decisions will scale out to everyone on the team,” Jin says. “That’s highlighted the importance of figuring out what the top priority for my team is, making sure it’s actually the priority, then clearing the way for execution.”

Data is powerful. It can help organizations make more informed decisions. And the more data available to you, as a leader, the more insights you can extract from it. But for leaders who want to find their weak points, data can spot-check their instincts and open investigations into deeper issues—if they are truly willing.

“Data is only as good as our own biases,” Jin reminds us. “In order to truly find gaps and blindspots, leaders need to be as open to seeing those in the data as they are about finding them in their organizations.”

To get the most out of your data, it’s more than just gathering it. It’s about mapping your efforts to the organization’s goals and objectives, then creating metrics to seek out understanding regarding your progress.

“It’s not just about using the data that you have, it’s about aligning the data you collect to your strategy as a business,” Jin says. “For example, you could just look at lines of code committed or number of pull requests per engineer, but that doesn’t speak to the quality of an engineer’s output, or the strategic initiatives they’ve contributed to. That’s why companies really need to think about their data strategy and the infrastructure they’re going to need to support the data insights that they want. It’s often not straightforward to get the metrics that are actually correlated with impact and success.”

Your data has a story to tell, and by understanding it, you can make strides in delivering consistently. You’ll have new-found abilities to prioritize what matters and continuously increase your team’s results. The learnings can spur drastic changes and improvements across any organization. But capturing and deploying that data requires honest commitment to the cause.

• Drive consistency with data. Successful teams are consistent. Performing consistently requires sound benchmarking and progress tracking.
  
• Visualize your metrics. Create ways to make your data consumable. Deploying visual dashboards allow real-time understanding of your data.
• Deploy data-driven priorities. By identifying the high-impact points in an organization’s success, leaders can add the time and resources necessary to increase results.
• Data is what you make of it. For any data to be useful, leaders must be willing to use it to identify their own blind spots, rather than simply confirming their current (and often unsupported) understandings.