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If you care about remote employees, start tracking their performance

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Alex Circei

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Alex Circei is the CEO and co-founder of Waydev, a development analytics tool that measures engineering teams’ performance.

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Remote work has been thrust upon us, but are business leaders ready for it?

More than half of U.S. companies now plan on making working from home a permanent option. However, most of us still don’t know what an optimal business machine with remote operations looks like simply because reaching that point requires years of trying, testing and adapting.

One major thing we haven’t all realized yet is that, without the visibility of face-to-face contact, data is essential in tracking employee progress and well-being, as well as the company’s overall health.

And not just any data — granular (ideally automatic) data is needed to give us accurate insights and stop us from making burdensome mistakes, especially in tech companies where even more of the work effort is purely digital. Take productivity. If we were to focus on people’s work hours alone, we’d likely get the wrong picture. Half of software developers have been working more during quarantine. But what does this tell us about the toll this workload is taking on their mental health? Or the quality of their work, and how much extra time is going toward bringing their tasks up to scratch? Nothing at all.

Putting data at the core of project management is not about Big Brother; far from it. Data isn’t inherently good or bad; it just gives you the tools to implement intelligent strategies and reduce errors. If anything, it will minimize the number of times you have to interfere with employees to ask for updates and micromanage.

Embracing data to create your new remote-ready project management strategy will enhance you and your team’s work lives in the following ways.

Reduce wrong decisions

Managers don’t have accurate visibility into remote employees’ productivity. Radio “silence” from team members can be misinterpreted to mean they’re not working enough, especially independent workers like software engineers. You might think you wouldn’t notice if they spent half their work hours on a coffee break, and your mind can run away with you. (The opposite — for those who talk too much — is also true).

However, a digital lifestyle produces digital indicators. Data-driven project management tools such as Wrike can tell you about employee output, but also about iterations and quality indicators on the same task. Such as how many times a pull request went back to a developer, why (due to error or for minor improvements?), or how many other employees stepped in to help before the final product was achieved.

Of course, correctly interpreting the data needs some qualitative input too; many tech workers’ reviews and resubmissions are an expected part of the task. But with the information in front of you, you can inquire in a quick and hypertargeted way to determine whether there is an issue.

The data also tells you how people’s work behavior compares to pre-COVID, so you can step in if you detect a worrying change.

Reports that don’t use data are inherently inaccurate. They’re primarily qualitative assessments, based around targets that can jump around month to month, and progress reports scattered across different documents, so you’ll likely lose track of how each individual is doing. Data is not a generic measurement stick to apply across employees. Still, it is a consistent measuring system that will show you how every individual is doing because you’re analyzing the same data.

Once you know what’s happening, it’s up to you to decide whether you prioritize quality over quantity or the number of deliverables over hours spent at work. But only having one part of the picture is bound to lead to misunderstandings of your employees’ actual efficiency.

Furthermore, having objective evidence when making high-level decisions is more critical than ever. A quarter of U.S. companies still expect layoffs in the future — measures that need to be justified indisputably.

A red flag for employees’ well-being

Data is visual. When an employee’s data is off somehow, you’ll be able to tell pretty fast.

If your tech team has employees that are not dealing well with the pandemic and remote work (which is very likely), it may be almost impossible to see this when you’re talking to them, even if you have several video calls a week.

Data can help you understand this. A plummet in productivity coinciding with the lockdown is a clear red flag, but there are other insights too. Has someone’s productivity stayed steady, but they’re missing one-on-one meetings? Have they gone from early bird to night owl, or do they appear to be always online, unable to switch off?

When you see something out of the ordinary in the data, you can ask the right questions and drill down on whether there’s a problem. The night owl may just be settling into their natural preferences now that they don’t have to appear in the office; or, they may be spending their day as a caregiver and are exhausted by the time they log in to work.

When approaching employees about these red flags, make sure you don’t give them the impression that they’re being pressured to work harder, just that you have genuine concerns. If you want to be more hands-off, liaise with HR for this.

Identifying individual employees’ preferences is crucial now that everyone has been forced to tackle the crisis in their way. You can’t force all employees into the same mold, and that means gathering data not across teams, but on every staff member.

Identify wider problem areas created by remote shift

In tech teams, it often happens that progress on a specific action has been blocked for several days because everybody is waiting on a task to be completed from another department or level of the company. But no one is communicating effectively, and as, say, vice president of engineering, you haven’t been aware of the problem. It’s hard for people to always be transparent and open with management about such issues, especially if they’re not sharing an office and establishing more informal relationships.

With data, it will be obvious to see this blocker visually — you’ll be able to pinpoint the source of the problem and attack it right away. You may well identify patterns regarding the source of the blockers or notice bottlenecks in related areas of your company. As everything is happening remotely, it is likely that other managers will also be experiencing visibility issues if, for example, senior engineers on another team are not reviewing code thoroughly enough (which can increase the risk of putting bugs into production). In uncovering business-wide issues that you can take to other executives in the company, you’ll contribute to maintaining the business’ overall health.

Productivity will increase for everybody.

Consider this — according to Stripe, companies lose around $3 billion per year due to engineering inefficiencies. The best way to manage a tech team is to set targets, track progress automatically and be aware of how everyone is advancing. If this kind of data is being continuously generated, managers can focus efforts on continually refining the specific areas that need improvement, optimizing code collaboration and overall team performance.

As a manager, you will be able to intervene only when necessary. The rest of the time, employees’ work will flow uninterrupted (which is when engineers are the most productive, alongside code review from senior developers). Setting clear targets helps your team concentrate on the task at hand while giving them the freedom to complete the task independently.

And you will be wasting less time compiling manual (and subjective) assessments judging team members’ progress. How do you record progress if you don’t have the data to start? Do you use report cards, Word documents? This is just not feasible if you’re managing several software developers at a time.

The next step: Automatically-generated reports

That said, not all kinds of data make the job easier on your team. Burdening teams with data that needs manual input and activity logging increases stress in an already pressurized environment.

Managers should prioritize automatic data collection tools that work alongside or integrate into work platforms. These also overcome possible developers’ feelings of being Big Brothered.

Programs like Trello and Asana are at their core task/list-making tools. Still, they’re compatible with a host of excellent plug-ins that automatically generate and visualize data such as burnups, burndowns and bug counts. ClickUp also offers comprehensive reporting on employee deliverables and work quality.

Keep in mind that concrete metrics are weak compared to highly detailed and multilayered data tools such as Jira software. A metric can be skin-deep if, for example, it only tells you whether a sprint is “Done” or “In progress.” Visualizing that sprint using a more detailed burndown chart — which tracks progress a lot more closely using metrics like story points and hours spent — immediately shows you when something’s wrong. That could be staggered progress rather than a smooth line, which suggests work was not distributed evenly (and may be causing unnecessary stress among developers). Or, if teams are always finishing their sprints early, they may not be setting good targets.

The downside is that Jira, like many other tools, is based on manual input. Among products that prioritize automation for tech teams are Pivotal Tracker, which has automatic planning features and a GitHub integration that automatically inserts data such as pull requests and commits to the project management platform.

Operating at optimal levels during the pandemic means being as informed as you would be when the regular workday involves checking in on the developers next door, impromptu updates with senior team members and friendly chats at water coolers. With this no longer being realistic, managers must start integrating intelligent data as permanent fixtures to their strategy.

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