Workplace

Performance reviews suck. These tech companies are trying to make them better.

Slack integrations and keywords and AI, oh my!

An illustration of a performance review on a clipboard.

Time will tell how smart HR technology has the potential to be, or how smart users want it to be.

Image: Christopher T. Fong/Protocol

Arguably nothing elicits more of a collective groan at work than performance review season. Managers hate giving them. Employees theoretically want them, but dread receiving them. It's as clear how much time and effort they take as it is unclear how useful formal performance reviews actually are in measuring and evaluating performance.

It's an arena ripe for disruption.

A flurry of startups are attempting just that and raising a lot of money in the process.

Global year-to-date VC investment into HR tech is approaching $12 billion, according to an August report from WorkTech. One leading HR software company, Lattice, just announced its expansion to Europe and an investment of $110 million in the UK. Other more nascent startups like ChartHop and OnLoop are attracting millions from top-tier investors.

So what's wrong with performance reviews?

Performance reviews are performed by people, and "people are biased," said Dr. Evelyn Carter, a managing director at Paradigm, a San-Francisco-based strategy firm that works with tech companies on their DEI goals.

One example is what Dr. Carter refers to as the "prove it again" trap: Research shows that marginalized groups like women and people of color tend to be evaluated on the results they deliver — can they "prove it again?" — while dominant groups are evaluated based on pure potential.

So how are these new HR tools attempting to make performance reviews suck less, and how can managers circumvent their own biases?

Establish a consistent set of metrics by which to evaluate people.

And make sure they're tailored to the job and level. You don't necessarily want to judge an engineer by the same standards as an operations person, said Carter.

Having clear metrics for evaluating success also helps people see what they need to do to get promoted, according to Lattice CEO and Co-Founder Jack Altman. Lattice, for example, has a section called "Competencies," which allows companies to articulate the expectations of each role, as well as the skills required for promotion. Those competencies are then pulled into the performance review form, and managers can rate how well the employee has fulfilled each one.

Up the cadence of reviews. Take notes all the time.

The biggest problem with traditional performance reviews is how infrequently they happen, which can introduce recency bias, according to Ian White, founder and CEO/CTO of ChartHop, an org chart startup that has a performance review component.

Most HR experts today recommend shifting from the annual review cycle to at least twice a year, or even quarterly. And they suggest supplementing those reviews with weekly one-on-one meetings to go over goals and feedback. That way, managers can keep regular tabs on how their reports are doing, rather than relying on memory to write a review once a year.

Taking the stress out of writing performance reviews is a major premise of OnLoop, a new mobile-first performance review app that aims to make the "data collection process more bite-sized and approachable," according to CEO and Co-Founder Projjal Ghatak.

OnLoop users are encouraged to evaluate team members once a week using "captures" in three potential categories: "celebrate," "improve" or "goal." One of the biggest issues with giving feedback, said Ghatak, is finding the language to describe a person or encounter, which OnLoop bypasses by prompting users to select relevant "tags" to input in each capture, like "growth mindset," "authentic self" or "subject matter expertise."

Collect feedback and data points from all directions, and automate it.

Remember the pain of writing extemporaneously about someone once a year with no other context? Another way to counter that, according to Altman, is through clever Slack integrations. Lattice can take compliments from a company's existing #praise channel, for example, and automatically feed them to its platform, adding another point of reference for managers while they're writing their reviews.

Lattice isn't the only company dabbling in off-platform integrations to streamline performance reviews. Betterworks, a performance-management system focused on OKRs and goals, has an even more literal feature that integrates project-management tools like Asana or Jira into an employee's "performance snapshot."

For example, a marketing manager might have an objective of revamping a website, which might be measured in a series of assigned Asana tickets or tasks. When that employee completes one ticket out of 10, that objective would display a 10% completion on Betterworks, explained Dennis Villahermosa, the company's senior director of product marketing.

Consider performance ratings. Or don't. They're controversial.

Having objective criteria by which to evaluate people as well as a rubric for what success looks like in each role is important from a company inclusion perspective, according to most DEI experts.

Having that numeric score also allows companies to compare performance ratings across the board and analyze them for potential areas of bias. For example, if more female employees received lower ratings across a department than male employees, perhaps there's an issue there, explained White.

Some companies, like Zenefits, are moving away from issuing ratings. "Where ratings get tricky is they end up being opinionated and subjective even in all of that effort to try to avoid being subjective," said Zenefits' VP of People Operations Danny Speros.

Most agree that the worst thing to do is to give stack rankings, pitting employees against each other as Microsoft notoriously used to do.

Actually use performance reviews to help make promotion and raise decisions fair.

Doing that is easier said than done, especially when your performance review platform isn't integrated into the rest of your HR management systems. Integrating these systems is ChartHop's whole selling point.

The platform allows executives to "slice and dice" their employee data and compare performance ratings against compensation and promotion data, which allows for more agility and continuous planning, according to White. If a person has three outstanding performance ratings in a row but hasn't received a raise in that same period, maybe they deserve a bigger equity refresh, he explained.

Do you want AI to get involved? Maybe.

At the end of the day, managers are still responsible for writing summaries of how their direct reports are doing and aligning with their goals. Or are they? OnLoop's loftiest goal is trying to simplify that process by integrating all the captures — the kudos, the constructive feedback, the self-reflections — into an AI-generated natural language summary that managers can then use to write their employee reviews.

They're not alone. Part of Betterworks' future plan also includes developing "intelligence engines" that would make suggestions to managers informed by performance data, said Villahermosa.

Time will tell how smart HR technology has the potential to be, or how smart users want it to be. What's clear is that, as with all AI systems, if the humans that create the tool are biased, the tool may very well end up biased too.

In other words: Managers, it's still on you.

Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

Keep Reading Show less
Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

Keep Reading Show less
FTA
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.
Enterprise

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

Keep Reading Show less
Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

Keep Reading Show less
Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Enterprise

Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

Keep Reading Show less
Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

Latest Stories
Bulletins