A Perfect Match: Data Analysts Pair Technical Skills with Soft Skills
I hope everyone had a good Memorial Day Weekend – the unofficial kickoff to wedding season! In that spirit, I’m going to discuss a very important relationship in every data analyst’s life: the marriage of technical skills to their soft-skill counterparts.
Just like every relationship, this one requires understanding and balancing complementary aspects to be successful. For our model skill-coupling, let’s look at how the skill for knowing how your sphere of influence—i.e. awareness of what you can do yourself, and how you can influence others—works hand-in-hand with your skill for driving data-based decisions.
In data-reliant work, awareness of your sphere of influence and data-driven decision making make for natural career-long skill partnerships. They work better together, and enable you and your team to do the best work.
Here are two ways these skills blend and support each other:
When interpreting the results of an analysis for the purposes of making a data-driven recommendation, it is critical to understand your sphere of influence.
For example, say an analysis is requested because your organization wants to know the best way to increase profits. If hiring decisions are out of your (and your supervisor’s) control, then you shouldn’t suggest adding more staff. Instead, focus on data that supports efficiency and cost-cutting measures within your influence.
Data-driven recommendations are more effective when they consider both the analyst’s and the decision-maker’s sphere of influence, and are centered around practical action steps.
Consideration for sphere of influence must come with a healthy dose of technical analysis. The balancing act of building a practical recommendation based on what you can influence, and following the data’s lead, can be a difficult one to master. If you lean too far towards what you can influence, sometimes the decisions aren’t strongly supported by data.
On the flip side, basing recommendations solely on data, without any organizational context, can lead to impractical decisions that stray from strategy. Striking the right balance allows decisions to be not only actionable and immediately useful, but mindfully and strategically aligned with what the rest of the organization is working toward.
To achieve balance and understanding, try asking yourself three questions whenever your data analysis reaches the point of needing an action or a decision from others:
Why is this decision important and why is it a good move?
What about this issue is in your control, what is not, and who can help?
Does my analysis support our strategy, and is that clear to others?
Technical, hard-analytical skills and soft skills are natural, complementary partners—they make up for what the other lacks, and the two are more powerful together than apart. When united, they can take data analysis, decision making, and people to the next level.
But as common wisdom would have it, relationships take work. Register for our upcoming training opportunities to improve your decision making and evaluating and presenting analysis, and other analytics skill areas, and learn how you can improve your strategic communication and influencing skills.