How to develop technical empathy — and why it’s worth your time
By: Alexandra Khoo
Tags: Data Literacy, Data Science, Teamwork, Communication Skills

Tech teams can work better together with other teams

If only it was as easy as A,B,C..

Imagine this. You have a queue of important tasks to tackle when someone approaches you with yet one more issue they just discovered and doesn’t understand why it can’t get tackled instantly. After all, it “just” involves changing one thing. It’s a “small ask”. The same person has more to say, but all you hear are a string of marketing buzzwords.

How it can feel like when you’re not speaking the same language

The solution isn’t to scream into the wall. Instead, ask: is there something we can do to overcome this disconnect between tech teams and the rest of the company? The answer is yes, and it begins with us.

We need technical empathy: an understanding of where people are in terms of their technical knowledge and the ability to see through their eyes. For those whose interaction with tech or data is mainly as end-users, they see the solutions but not the challenges that tech teams face.

Empathy is a trainable skill, and you get more mileage when practising it instead of expecting others to do it. Here are some actionable steps to develop technical empathy.

Think Beyond Your Role

The best way to help yourself is to stop waiting for others to relate to you. Instead, meet your colleagues and other internal stakeholders where they are. It’s helpful to ask probing questions, especially if the requests are vaguely-worded.

To identify the broader objective: “Is the aim to prompt further discussions, persuade them to seize an opportunity, or something else all together?” To find out the scale of effort required: “Are we looking at using a simple heuristic to arrive at this metric?” To gauge the task’s importance: “Is this an immediate priority or more of a nice-to-have?”

Understanding the context or priorities that are driving their requests can make the difference between time well-spent and toiling over tasks in vain. It’ll help you better appreciate how your contribution fits into the bigger picture and hone your strategic thinking skills.

The bottom line is to avoid letting your official job title dictate what you can offer to the team. At Synthesis, we are a melting pot of brand strategists, data scientists, designers, and developers. While we have our own areas of expertise, I love that our open culture makes it possible to explore cross-domain ideas in team discussions without the risk of a turf war. For instance, a data scientist can recommend layering the market insights in a certain way for better storytelling. Likewise, a brand strategist can suggest new data features that would be useful for analysis.

Note: This is not the same as telling others how to do their job, which is as counterproductive as it is annoying. Instead, it’s about adopting a collaborative approach on how we can deliver better as a team.

Find a Bridging Language

Think back to some of your earliest technical ‘aha’ moments. Perhaps it’s something as fundamental as grasping the difference between print and return statements when coding. Or when you understood what the Document Object Model had to do with the webpage. You’re a different person from who you were prior to those moments.

In some ways, talking to colleagues outside the tech team about what you’re working on is like empathising with your past self. Take reference from something they are familiar with. Our product team frequently uses food analogies during a tech demo to make it easier and more appealing for everyone to follow the discussion. Think using smoothie-making to explain how a hash function works: it’s fairly easy to blend fruits (input values) into a smoothie (values returned by the function) but it’s difficult to reverse-engineer

Smoothie: A delicious analogy to make hash functions more relatable (Photo by Joanna Kosinska on Unsplash)

The same principle applies when you’re trying to raise concerns from your end. Ideally, because you have thought beyond your role, you’re aware of the business team’s priority and you can use that as an anchor to explain. If they have a “small ask” or a “quick one”, and you know it would be anything but that, help them understand in terms of how much time that leaves for the other important things.

So what you might think is a “small ask” to update may involve 15 people, 125 hours and five different development tools. — Thomas Griffin, OptinMonster

Encourage everyone to be tech-curious 🎉

Communication is a two-way street. This doesn’t mean that everyone needs to be a coder, but it’ll go a long way if they appreciate the fundamentals. In other words, if data science is not seen as “magic” but the application of science. It helps if there’s a general understanding that machines are not going to read inputs the way humans do.

Every discussion with the business team or company-wide showcase is an opportunity to spark some curiosity about what’s “under the hood”. At our weekly Synthesis showcase meeting, we highlight the work that we are doing and it’s where we share some cool tech inroads too.

Feel free to think outside formal office settings. If you feel passionate about tech or data, and you wish to share that joy, consider organising casual fun events like brown bag lunches to explore and exchange ideas. There are plenty of resources out there to support you: The Data Literacy Project, The Data Culture Project, and a Data Literacy video series by Arizona State University are just a few examples.

ASU’s Data Literacy series provides a crash course for anyone anyone interested in learning how to understand and interpret data

What else can be done?

If you’re also a leader, co-founder, or someone with the influence to effect change across the company, there are a few other steps you can consider:

Begin with the onboarding of new staff : We have a standard Synthesis onboarding timetable that covers all aspects of the business and data science work (at a high level), regardless of how technical one’s role is. It’s a great way to bring new starters up to a common baseline on the technical work that goes into our consultancy and product.

: We have a standard Synthesis onboarding timetable that covers all aspects of the business and data science work (at a high level), regardless of how technical one’s role is. It’s a great way to bring new starters up to a common baseline on the technical work that goes into our consultancy and product. Be intentional about creating an inclusive culture: Strip sentences of jargon, including business jargon, as it puts up barriers. There’s a lot you can do here. Remember, the higher up you are in your organisation, the more likely your suggestions are going to be perceived as orders and your actions as a behavioural norm.

Strip sentences of jargon, including business jargon, as it puts up barriers. There’s a lot you can do here. Remember, the higher up you are in your organisation, the more likely your suggestions are going to be perceived as orders and your actions as a behavioural norm. Find your bridge-builders and empower them: Recognise and encourage those who take the effort to foster better understanding between tech and business teams. There might even be scope to introduce hybrid job roles. We’re exploring the data scientist-strategist skills as a continuum in our training plans, and with that, the new roles of Data Science Strategists.

It’s time to rethink our role as tech professionals. The 1930s American humorist Will Rogers summed it up best: “Everybody’s ignorant — just on different subjects.”