I have been in data, in some form or another, for over 20 years and have come a long way in both my technical and soft skills during that time. There are plenty of roles for data professionals that do not require soft skills, and if that’s what you are into, more power to you. However, I have found that these types of roles are usually at a lower level with lower pay or are highly niche skillsets that take years to learn. If you want to expand your career beyond a low- to mid-level individual contributor role, you need to also upskill your soft skills. Soft skills are necessary for interacting with others in your company, interacting with stakeholders and clients, and managing or mentoring others. But what soft skills should you focus on and where can you get training and practical experience to learn them?
There are two common concerns I hear from leadership about highly technical teams:
- A customer will ask for ABC_DATA, which they think will answer QUESTION_XYZ, but what they really need is XYZ_DATA. The technical team will deliver ABC_DATA, but it doesn’t answer the original business question. The data team is frustrated because they successfully delivered what they were asked for, but the customer doesn’t want it. The customer is frustrated because they can’t answer their original business question, and they’ve waited weeks or months for the data they thought they needed. Everyone has wasted a lot of time and money on the project.
- A customer will ask for ABC_DATA, which they think will answer QUESTION_ABCD. They are close to asking for the correct data, but they are missing a few essential elements, or there is something about the data that isn’t exactly what they need to answer the question. The technical team will deliver ABC_DATA, but then the customer realizes that they need additional data to fully answer their questions. The data team is frustrated because it would have been much easier to pull in ABCD_DATA together than to go back and add data now. The customer is again frustrated because they can’t answer their original business question and after waiting weeks or months, they’re going to have to wait longer. While time and money aren’t completely wasted here, things will end up taking longer and costing more than they had to.
So, how can we avoid these situations? Hire a business analyst for every project? Yes, that would work, but only if your business analysts were technical enough to understand the nuance of data complexities. What we can do is upskill the soft skills of data professionals to prevent these types of things from happening. There are probably thousands of lists of different soft skills that you can find on the internet. I have tried to distill those down into what I think are the most valuable and most lacking in data-centered environments. (I also want to note that there are plenty of soft skills that data professionals are great at like reliability, analytical reasoning, analysis, creativity, etc.).
- Communication – Both written and verbal communication are essential for customer-facing projects to be successful. The tricky thing for many highly technical professionals is that they can forget that they are talking to someone who is not necessarily as technical or as knowledgeable about the data as they are. In these situations, it is important to explain everything in a way that someone with a high school education could understand, so consider explaining things to a parent or grandparent who is possibly not as familiar with technology in general. How can you clearly articulate back to someone what they have asked for, what questions that data can answer, and most importantly, what you understand as the core reason for the data request (more on this with empathetic listening)? Many times, there is a disconnect between what a customer will ask for and what they really need to answer the business question, if you upskill your communication skills, you should be able to determine the actual business question and suggest what data should be used based on your technical understanding of the data (regardless of what the customer thinks they need).
- Empathetic Listening – Listening is essential for understanding what a customer needs, again regardless of what they think they need. Empathetic listening is an active listening technique where one listens without passing judgement and then works to find a common ground to work on. In technical environments, this basically means that you would listen to what a customer tells you is their problem, what questions they want to answer, what data they think they need, and anything else they feel is important and then work with them to define what the project needs to focus on. As I mentioned above, it is possible that someone will ask for something that does not align with what they need; by using active and empathetic listening skills, you can work with them to guide them to realize what data is actually needed to effectively answer their questions.
- Critical Thinking and Problem-Solving – Maybe you have gotten to this point in the article, and you are thinking, I have never seen this issue in my company. It’s possible that your customers are just really well versed in the data and understand data engineering, analytics, data science, and visualization concepts well enough that they fully understand and can identify what data they need to answer every question… or it could be that you are focusing on doing your work without thinking about the implications of the data that is being delivered or how it can and will be used. If this is the case, firstly, you aren’t doing anything wrong, you are doing your job. Secondly, if you want to upskill into a new or different position, you could focus on critical thinking and problem-solving. Try to step back from your day-to-day work and see the bigger picture. How does data connect to other data? What questions can the data answer and what methods would you use to answer those questions? What are the company’s overarching goals, and how do the data and the questions the data can answer relate to those overarching goals?
Now that we have identified what skills are needed and why, how and where exactly can you learn them? There are plenty of free resources out there to learn and practice each of these skills alone and with others. I would recommend:
- Communication
- Wharton’s “Improving Communication Skills” course for general tips and tricks on communicating effectively.
- Toastmaster’s local and national groups for presenting or speaking in public or group settings (there is a small fee here, but sometimes you can try the local groups out for free).
- “The Charisma Myth” by Olivia Fox Cabane is available in free formats online.
- Empathetic Listening
- Consider a course on improving your listening skills.
- Coursera has a class on active listening.
- I also suggest practicing these skills at local networking events where you can interact with and listen to people with different interests and skills than you. Most areas have a local Rotary group, or events can be found on Meetup or Eventbrite.
- Critical Thinking and Problem-Solving
- Critical thinking and problem-solving are very hard to teach. Some suggest reading philosophy or watching videos about philosophy on YouTube, but honestly, if you start working on empathetic listening, then some of the critical thinking should come with it. Other than that, working with a mentor or coach on this might be your best bet. There are several free mentorship programs available online, but you might have better luck searching locally and finding someone you can talk to in person.
Learning soft skills can be a lengthy and difficult process for data professionals, many of us are not used to using or needing them to do our day-to-day work and therefore have not practiced them. Set small goals, work on one thing at a time, and be patient if things don’t come naturally. It can also be helpful to invite others into your learning journey, so you can work together to learn these skills. With time and effort and one small goal at a time, you will improve your soft skills and your potential to expand your career into different areas.
