Five Ways To Design A Better Job For Yourself In The Age Of Automation

What’s easier for a robot: playing chess or gardening on a windy day? How about playing a video game or balancing on one foot?

Some tasks that are trivial for humans, yet immensely difficult for robots. This is encapsulated by Moravec’s paradox, named after Hans Moravec, a robotics researcher at Carnegie Mellon University. 1 Complex, abstract tasks, such as chess or algebra, are tiring for us yet trivial for robots. Small movements and balancing, on the contrary, are easy for us yet taxingly difficult for artificially intelligent beings. These uniquely human benefits come in handy when thinking of what your post-automation job will look like.

What makes us human

The automation-resistant tasks that remain for us at work after automation further progresses will need our uniquely human abilities. Skills like creativity, empathy, and dexterity are much easier for people to exhibit than computers. 2 After all, we’ve practiced these skills since birth, with many opportunities to learn and adapt. Armed with insights about what tasks you’ll be doing after a wave of automation, you can look to the future and design a more automation-resistant role within your organization.

The process of designing a new role for yourself in your existing job is called job crafting. By crafting your job, you can increase your ability to deal with stress,3 find new motivation at work, and gain career flexibility by giving yourself more opportunities to master new skills.4

Going through this process might sound like overstepping your bounds as an employee, yet senior leadership would likely be quite receptive to the gesture. CEOs and other top-level leaders are worried about low levels of innovation leaving their companies behind. Specifically, 77% of CEOs surveyed were worried that their companies didn’t have the creativity to reinvent their business in a slowdown.5 Now that we’re in the middle of a slowdown, you’d be surprised at how valuable job crafting can be for helping yourself and your company thrive.

Say you want to use job crafting to build a more automation-resistant role in your company. How exactly should you do this?

You’ll want to use the principles of work design below to enrich your job.6 The acronym ‘FIVAS’ covers the five ways you can make your tasks more desirable, less routine, and more valuable, especially in service and knowledge industries.7 FIVAS stands for:

  • Feedback: When you see the results of your work sooner, your job is high in feedback.
  • Identity: When your work is more holistic than piecemeal, you have high task identity.
  • Variety: When you do many different tasks instead of one repetitive function, you have task variety.
  • Autonomy: When you can make independent decisions about your work, you have greater autonomy.
  • Significance: If your work is meaningful to you, it has significance.

These five job design elements can better match your skills to your work. The current skills-job mismatch affects many workers, keeping them underemployed and disengaged because their work isn’t challenging.

If leaders ignore these elements of work design, automation can make skilled jobs more externally controlled, giving workers less autonomy.8 Here’s what a data analyst’s job could look like before and after job crafting:

Job Design Elements Before Job Crafting After Job Crafting
Feedback The data analyst only gets feedback once a year in their annual review. The data analyst gets weekly feedback on smaller tasks and sees their impact after each project is done.
Identity The analyst’s role involves reviewing datasets. The analyst’s role involves data-driven projects from beginning to end.
Variety The data analyst spends all their time cleaning financial data in one computer program. The data analyst prepares, analyzes, and presents data from multiple sources, including financial and marketing information.
Autonomy The employee follows a script to review data quality that specifies every step in the process. The employee explores multiple ways to solve the company’s new challenges using data.
Significance The analyst plays a small role in the reporting function of the company. The analyst owns data-driven projects from start to finish, seeing the impact of their work on its recipients.

The benefits of mindless work

Yet, it is possible to go too far with a job redesign. When crafting your job to be more motivating, you’ll want a balance between challenging, unique tasks and mindless work.

“Why would I want some mindless work?”, you might ask.

Surprisingly, repetitive tasks can inspire creativity by letting your mind wander and make new connections.9 When your job has variety, you’ll be switching tasks more often. This takes a cognitive toll, so you’ll need some low-energy work to recover from all of these demands.

During those recovery periods, you might find yourself dreaming up new solutions to challenges in your role. This will motivate you to do more challenging, unique work. Balancing “brain breaks” and difficult work can create a virtuous cycle of tasks that spark — instead of drain — your energy.

We don’t need to be passive in the face of automation. By bringing our uniquely human skills to newly redesigned jobs, we can craft more motivating and impactful work even as our economy rapidly transforms.

Fitting The Behavioral Science Piece In The Organizational Puzzle

I often joke that if a contest for the most mysterious job title in my company existed, I would be the clear frontrunner. It seems as if every time I’m introduced to someone, I’m asked the same question: “So, exactly what do you do?”

This week marked my two year anniversary of working as a behavioral scientist in a product-driven tech company, and I still don’t have an exact answer to that question. But, having worked my way through the company, I’m now in a comfortable position to think about the question more clearly at least. 

My biggest realization about this role is a double-edged sword: Behavioral science actually overlaps with many roles in product-led tech companies. That’s good because that means behavioral science is becoming increasingly relevant to everyone, irrespective of what role one is in. That’s also bad because the onus of proving the importance of a stand-alone behavioral science role is entirely on us.

Based on my experience, I’ve put together some thoughts on where product organization and behavioral science overlap, and what differentiation a behavioral scientist can bring to an organization as a whole. 

Is behavioral science the same as user research?

In a generic sense, yes. User research is, rather obviously, about understanding users. Behavioral scientists do the same; yet, the nuance is in the process.

User research teams conduct qualitative research through in-depth interviews, discussions, and usability tests. They also conduct quantitative research through surveys. This research is then condensed into a form that product and design teams can consume and use for the product development.

Behavioral science research is more focused on uncovering the reasons behind why people do what they do. While interviews and surveys are useful techniques, it is more important for behavioral scientists to understand the context under which decisions are being made. Doing so helps them use that context to map and diagnose the behavior of the user. In other words, putting into words what the user cannot say. This comes not just from interviews, but from experiments and observations and conducting literature reviews of existing theories.

Can user research benefit from behavioral science?

Absolutely. If you are a user researcher and you have a behavioral scientist in your organization, integrate them into your research to help you uncover biases and blindspots that are not necessarily visible in plain sight.

Is behavioral science the same as design?

As someone who loves all things design, I wish that this answer is a yes. A designer in a product organization focuses on putting the product into a visual form, taking into account the users’ and the business’ needs. This is a highly technical process that involves immense stakeholder management and a deep understanding of how various systems interact in the backend, with the goal of producing a front-end that is simple enough for the user.

Behavioral design is a subset of design that is concerned with using design elements to affect behavior change.1 Borrowing heavily from behavioral science, this stream helps designers design for the real user — the one who is busy, inattentive, biased and not perfect, as opposed to the perfect user (who may or may not exist). 

Can design benefit from behavioral science? 

Absolutely. Behavioral science helps designers understand the actual user, rather than the theoretical user. If you’re a designer and you want to involve a behavioral scientist, reach out to them in the initial phases of design. They can help you understand the ‘why’ behind what people really do. It is immensely beneficial to get a behavioral scientist to audit your design from a behavioral perspective so you can uncover fail points early on in the process.

Is behavioral science the same as data science?

No. Data science is a field that analyses structured and unstructured data using machine learning and algorithms to extract useful insights, as well as predictive models.2 Data Scientists typically use mathematics, statistics, analysis, and machine learning to investigate existing patterns in data. The models that they create feed directly into products, making them smarter. For instance, if you have used Spotify and love the recommendations the app gives you, that’s the output of a data science model at work, which takes into account your music preferences and a bunch of other variables to predict what songs you might like.

Behavioral science, on the other hand, puts the predictions of data science models into the real world and helps drive the ‘last-mile’ behavioral change.3

Can data science benefit from behavioral science? 

If examples are anything to go by, then yes. The 2012 Obama presidential campaign was a groundbreaking experiment that employed data scientists to predict voter behavior, which was then used to optimize marketing resources.3 The distinctive part about the campaign was the complementary use of behavioral nudges along with data science models. The data science models could accurately predict which way a voter was likely to vote. But the campaign’s main objective was to sway voters to vote for Obama, and that’s where behavioral science comes in. The campaign team was able to get more votes in their favour by using nudges in communications towards those who were undecided, or not likely to vote for Obama. In other words, behavioral science provided the “last mile” connect that the data science models needed to reach the voter.

If you are a data scientist and you want to see your models being used to drive real behavioral change, reach out to a behavioral scientist — they might just know exactly what to do.

Is behavioral science the same as product marketing?

Not quite. Product marketing is the connection between business and product, and is a critical part of the product life cycle. Before a product is launched, product marketers create the positioning and the go-to-market strategy based on user research. During the launch, they help business teams understand the product and drive its adoption through campaigns.4

Behavioral science plays a critical role in parts of this process, such as providing a deeper understanding of the consumers’ behavior, conducting a diagnosis of the users’ current behavior to identify biases, and identifying interventions in communications that can nudge the adoption of a product.

Can product marketing benefit from behavioral science? 

I’m sure you’re seeing a pattern now, but the answer is yes.  Product marketing relies heavily on understanding users and creating positioning based on that. However, marketing thrives on insights, and behavioral science can help unravel insights that allow a product to be positioned better.

A simple example of this is the difference between explicit and implicit goals.5 If you are marketing a food delivery app, the explicit goal is to make it easier to order food. This is what you would learn from talking to consumers. But, if you were to dig deeper to understand the implicit goal, you might uncover the goal of “excitement” — that is, when customers order food because they want every meal to be a surprise and different from what they’ve had previously. The product positioning then changes from convenience to a more nuanced “variety with convenience”. So, if you are a product marketing manager, talk to a behavioral scientist to uncover insights that might help position the product better.

Be all, end all?

My advice seems to be that everyone in the organization should talk to behavioral scientists. But, my intent is the opposite of that. I want behavioral scientists to proactively reach out to others in their organizations to offer insights. The simple truth that runs the world is “ask, and you shall get”. A stand-alone behavioral science role comes with the responsibility of proving its value, and this will happen only and only through collaboration. So, if you are a behavioral scientist in a product organization waiting for someone to give you a project, don’t waste your time. Instead, reach out and tell others how you can add value.