How to include data in your answers to behavioral interview questions
It’s important to include data in your answers to behavioral questions. Companies are looking for data-driven candidates.
By data I mean specific, quantifiable, granular information, like amount of money, number of hours, number of gigabytes, etc.
Your answers should have a balance of enough data but not too much. Use enough to show that you clearly know details but not so much the answer becomes hard to follow or boring to listen to. If your answer is longer than 4 minutes you’re probably including too much detail/data.
Data is often the difference between a mediocre answer and an excellent answer.
Why is adding data to your answers important?
Hiring managers value critical thinking and analytical reasoning.
Data-driven people go beyond their instincts to observing data, understanding it, and proactively using it to make informed decisions and recommendations.
What interview questions assess your data skills?
Here are a few questions that are asking you to talk about using data:
How did data help guide certain decisions you made in your previous role?
When did you use data to form a strategy?
When did you have to dig down a few layers of a problem to solve it?
How do you navigate decision making in the absence of quantitative data?
Tell me about a time you had a measurable impact on a project.
What should you show in your answer?
Collecting information, interpreting the evidence, and taking the appropriate action
The judgment to know important decisions don’t happen without first seeking and assessing relevant information
Ability to gather data and extract what’s necessary to back up or refute an option
Ability to identify and analyze quantitative and qualitative data to make balanced decisions
Knowing how to use alternative forms of data – like focus groups, one-on-one interviews, existing records, and observation – in the absence of hard numbers
Detailed actions, citation of specific stats, qualitative results, or anecdotal feedback
Examples of how to add data at the sentence level
Whenever you can, replace adjectives or vague/general information with data.
Here are some examples of how to do this:
Without data: We made the performance much faster
With data: We reduced server side tp90 latency from 10 ms to 1 ms
The phrase “much faster” is so vague - What was the speed in the beginning? What was it in the end? What type of performance were you measuring? And who is “we” - I assume you already explained this earlier in the story.
Without data: Nearly all customers
With data: 92% of Bonus-club members
“Nearly all” and “customers” are both vague terms. Give the number of customers and also specify the type, unless you are talking about the total number of customers. But even then, you should say that.
Without data: Significantly better
With data: Up 34 bonus points
“Significantly better” is too vague.
Example of how to add data to an entire answer
In the following scenario the candidate is the CEO of a mid-sized landscaping company. You may not be able to relate to this business, and in fact I don’t think I’ve ever had a client in landscaping, but it’s a simple answer that will show you the right way to use data.
Question: You mentioned you didn’t make revenue in 2020. Can you walk me through why?
Poor answer:
In 2020 there wasn’t as much rainfall as there had been in previous years so it led to a lot of our customers’ grass yellowing and subsequently not being cared for by our team. This ultimately hurt revenues.
Better answer:
In the area of Texas around metropolitan Houston, where my company Johnson Landscaping does 65% of our business, the average rainfall in the summer is 6 inches. In 2020 the rainfall total was down to 2 inches.
The grass that is most common in that area of Texas is St. Augustine, which requires at least 4 inches of rain to sustain a natural growth pattern. When the grass grows naturally, we are able to remain on a typical cadence of lawn service for our customers, which is bi-weekly. When the grass doesn’t grow enough (like when it doesn’t rain as much), customers generally cancel some of their work with us because the grass simply doesn’t need to be cut. This is what happened in 2020 after the rainfall shortage. We lost 25% of our revenue, and most of that was because of the rainfall affecting grass growth.
In order to prevent the same loss of revenue in 2021 and subsequent years that we had in 2020, we knew we needed to do as much as we could to prevent the same thing from happening again. We can’t control the weather, but we hired a weather analytics firm to give us estimates of rainfall 60 days prior to summer. We also began to develop other ideas for low-rainfall year gardening, such as educating our clients about xeri-scaping (low-water requirement landscaping) and varieties of grass that require less water. Educating clients needs to be done in advance; it isn’t a last minute fix. So we began this plan quickly before we had the weather reports for the next year.
When our weather firm let us know that there might again be less rain in 2021, we had already begun educating our clients about their options. Some of them did wish to take precautions and changed the plants in their yards in advance, including grass. There was 3 inches of rain in 2021, but we only lost 20% of our mowing business because some of our clients now had low-water requirement grass.
Analysis of the answer
The “Poor Interview answer” above is an example of a very surface level response and does not go into enough detail for what interviewers are looking for.
In the “Better answer” the candidate used data to work though the scenario. There are a lot of facts and numbers in the answer.
The “Better answer” still doesn’t have enough data.
Even though there are facts and numbers, I doubt the interviewer would accept this as enough info.
They would ask:
“Why is this what you chose to do?”
“Did you think about X, Y, or Z?”
“What happened in 2022?”
In your answer you should give these details about what you did to prevent the problem from happening again and what the results were.
Read this article next for a checklist of types of data you can include in your answer, particularly in your Results section.
Related topics:
The STAR Method for answering behavioral questions
How to answer behavioral questions in your Amazon job interview
