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Data in a Downturn: Protect your data career with these 3 tips

Nicole Mitich is the content marketing manager @ Census. She's carried a love for reading and writing since childhood, but her particular focus is on streamlining technical communication through writing. She loves seeing (and helping) technical folks share their wisdom.

Nicole Mitich is the content marketing manager @ Census. She's carried a love for reading and writing since childhood, but her particular focus is on streamlining technical communication through writing. She loves seeing (and helping) technical folks share their wisdom.

Data in a Downturn: Protect your data career with these 3 tips

After the Great Depression, we decided that calling economic downturns "depressions" is just a little too scary. 

But let’s face it: Tweaking the name doesn’t really make a downturn any less daunting. No matter what we call it, recessions are scary. 😱

Any time the economy takes a turn for the worst, businesses – regardless of their size – face declines in sales and profits. And as individuals, the most spine-tingling creature of all looms just inside your career closet: Potential job losses. 👹

In 2022 alone, over 150,000 tech folks lost their jobs – and the losses haven’t leveled off yet. But if you're prepared for a recession, there are ways to survive and even thrive in a downturn. 

So, to put things in perspective, we talked to Mark Menatti, director of data science at Agency Real Estate. Mark has survived previous downturns in the data sector and had some words of wisdom about when to worry (or not) and how to proactively protect your data career in an economic downturn.

Pandemic hiring sent the pendulum into motion

In 2020, the pandemic-fueled surge in online activity sent tech companies on a hiring spree. And for a few good years, talented data folks could just about have their pick of positions. We all knew it was too good to last, but most of us weren’t prepared for how fast the pendulum would swing the other way. ◀️ 

Now, we’re on the other side of things. The industry made an abrupt about-face, leaving a lot of folks reeling and worried about their jobs.

Mark started by addressing this concern, warning that there’s really no way to predict when layoffs are coming. 🔮 He’s been laid off twice and was blindsided both times.

“It’s easy to look at KPIs and see business trends going in the wrong direction … but when and the severity of it I couldn’t predict,” he said. “It’s like driving in the forest and seeing those Smokey the Bear signs: ‘Fire danger is high/low today.’ It doesn’t mean there is or isn’t going to be a fire; it’s just a question of whether you should be surprised and how severe it’s going to be.” 🔥

What data jobs are safest in an economic downturn?

Major tech companies like Twitter and Alphabet have posted some scary high layoff numbers, but it’s important to realize many of those layoffs were nontechnical roles. 365Data Science did a mini study on layoffs at half a dozen tech companies and found the largest group affected was HR and recruiting, which isn’t surprising considering that hiring has slowed.

“If you’re a good engineer, someone will want to hire you,” Mark said. “I hesitate to throw that out there because I still say in the long term, what’s best is to do what moves you, what you’re passionate about. That will be what you’re best at. But in the short term, in a recession, high-level engineers are in short supply.”

How to protect your data career in a shaky economy

Layoffs might be unpredictable, but that doesn’t mean we have to sit back and wait for them to happen. There are a few things you can do to help you protect your job or bounce back more quickly if you do get laid off. 👇

✅ Tip 1: Upskill

A blessing and a curse of the data industry is that we can never stop learning. Technology moves fast, and some of the skills you use today won’t be relevant in five years. So in any economy, you should always be upskilling. 📖

When we asked Mark what he thinks are the most important skills to master, Python and SQL topped the list. He emphasized the importance of understanding not just the tools but understanding when and why to use them.

“The ‘why’ behind the modeling is super important, and that’s also in short supply,” he said. “The person who brings that to the table connects a lot of dots for the company. A lot of people think our job is to predict stuff, which is a little bit true, but I think what’s more true is that we tell people where there’s uncertainty and the costs of that uncertainty. Being able to make those connections is super useful.”

✅ Tip 2: Learn to sell your value

The decision-makers at the top of most companies come from a sales background. While that’s logical from a business standpoint, it means they don’t necessarily understand the importance of the work data teams do.

Teams directly supporting revenue operations with projects like supply chain optimization or fraud models have an easier time backing up their work with actual dollar signs. Teams focused on strategy and analytics, while no less important, have to work a little harder to demonstrate their value in an economic downturn. 🫰

One way to do that is to speak the language of sales. Mark recommends talking to people leading different parts of the company – especially those driving revenue – and finding out what they think is happening in the business.

“I want to understand who the customer is, what facilitates a sale and what doesn’t,” Mark said. “Companies don’t usually have that background from a data standpoint, but it’s a story that resonates with people. If your CEO is a salesperson, and you can demonstrate why a sale did or didn’t occur, then take a step further and recommend things you can do to facilitate more sales, that tends to be pretty compelling.”

Business users find a lot of our critical behind-the-scenes activities – like architecture and governance – super boring. They don’t understand it, don’t care about it, and don’t see its value. That means you can’t wait until everything is in place before you start delivering insights. To position yourself as a valuable partner to revenue-driving operations, you have to demonstrate the usefulness of what you’re doing from the start.

“Data needs to be delivered as a story because that’s what most people understand,” Mark explained. “It’s got to be a steady drip. If it comes time to choose between limited resources and you haven’t done the groundwork and demonstrated value you’re going to lose.”

✅ Tip 3: Make connections

A lot of factors go into layoff decisions, and sometimes there’s just no way to protect your job. 🤷 If you do find yourself on the receiving end of a layoff, it helps to have a network of people ready to help you find your next role.

In 2008, when the Great Recession hit, Mark was working remotely for a London-based company. Everyone he knew in his field was an ocean away, so when he was laid off, he found himself without a local community to fall back on.

“I didn’t have people I knew that trusted me, and that matters a whole hell of a lot,” he said. “Every application was a cold application, and those are really hit and miss, even if you have a great background.”

Build a strong network of people outside your company, both in your field and in related fields. Connect with recruiters so you can tap into their networks when you need a job.

The Operational Analytics Club is a great place to start networking with other people in the data community. You’ll immediately benefit from some great relationships and the ability to learn from really smart, innovative folks. And if you should ever find yourself looking for a job, you’ll have people in your corner who know you, trust you, and can recommend you to their networks.

Don’t lose sight of the big picture 📷

Getting laid off stinks. There’s no way around it. But it’s important to remember it’s not the end of the world – or even of your data career. 🌎

“It’s frustrating. It’s demoralizing. It’s also short-term,” Mark said. “But it’s hard to see that in the moment.”

The reverberations from an economic downturn can be felt for years as companies slowly rebuild and recalibrate. You might find yourself taking a job for less pay or outside your preferred field just to pay the bills. You can either be mad about that, or you can take the opportunity to reflect on what you really want and realign your journey.

In the years after the Great Recession, Mark took a job he wasn’t really interested in. It ended up being the job that taught him SQL, and he came out of it with a new skill he hadn’t expected to learn.

“People look for opportunities more aligned to what they were doing before, but watch out for new opportunities that spring up out of nowhere,” Mark said.

Want to hear more from Mark? Check out the full webinar here 👇

🛡️ If you’re worried about protecting your job, or you’re struggling to find one, it helps to get some support. Join the Operational Analytics Club today to find a community of like-minded data folks who can help you keep your perspective and get through the scary times.

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