With this question, the interviewer is looking at your thought process and your level of logic. Begin by discussing the problem you were trying to solve. Next, discuss the data set you used to analyze the problem. Lastly, talk about the recommendation you gave, and the positive outcome from your recommendation.
"Using my previously discussed blog, bounce rates were at 65%, meaning visitors would visit the blog, but 65% of them would only stay on the page they landed on. I had to analyze their behavior. I found that 80% of visitors never scrolled down to view the rest of the content on the home page. By analyzing that data, I knew a problem existed at the top of the page. I made a recommendation to the web design team to remove 50% of the graphics and text. This enticed our visitors to scroll down to view the rest of the content. By removing the clutter, our bounce rate dropped by 15 percent."
"I recently wrapped up an organizational effectiveness survey with our team. I analyzed the results by leader, location, and department, then came up with recommendations of how the company can improve trouble areas."
"Once it appeared that productivity was slowing down, so I was asked to look into it. I pulled data from a variety of sources and poured through it, from order types, changeovers, employee turnover, absenteeism, etc. I identified all of the changes from the previous quarter to the current and made several recommendations."
Sales answer example
"After bringing on a new customer, the account is handed over to the customer success team and assigned an account manager. However, after a few weeks, my client was emailing and calling me expressing his frustration. I had to hear him out, look into the account on our backend, talk to the account manager, and shadow a call in order to really assess the situation to see what the problem was and avoid him deactivating his account. I suggested a new account manager and that I would help with the new transition. By doing so, we were able to avoid any cancellation issues and left with a happy customer."
Retail answer example
"I was tasked with staffing our department adequately for the seasonal holiday rush. This boiled down to assessing if we should be hiring seasonal help, and if so, how much. I looked back at the past three years' data and focused on the amount spent on overtime. On the surface, it looked as though it would be most effective to hire a number of seasonal employees to avoid this overtime expenditure.
However, what isn't considered in these reports is the amount of time, cost, and training poured into seasonal hires who don't stick around. Not only opportunity cost, but true dollars. That said, I determined that it would be most effective to spend a bit extra on overtime and bring on one part-time employee who would stay beyond the holiday season, thereby avoiding all seasonal hires."
Teacher answer example
"I feel perhaps the best example of assessing and recommending comes when addressing the IEPs of my students, and what modifications I believe would best suit them in order to fully participate in the mainstream classroom. For years, students with IEPs or special needs were not included in Spanish since the district thought the time could be better used for other services, and that it was too hard of a subject for students with IEPs or learning disabilities. It's not a fair generalization, so I like to make recommendaitons for those students I believe could benefit from Spanish inclusion. I feel it's very important to get to know the student as an individual and not base anything off of his or her diagnosis and instead figure out a way to make him or her successful in my class."