8:00 AM – Start of the Day
Sarah, a Senior People Analyst at a large, multinational corporation, begins her day by checking emails and messages. She looks for any urgent requests from HR business partners or leadership teams that might require immediate attention. Today, there’s an email from the Head of Talent Acquisition urgently requesting an analysis of recent hiring trends by end of day. Sarah knows this request will be a challenge given her current workload and that some things will need to be reprioritized.
8:30 AM – Daily Stand-Up Meeting
She joins a virtual stand-up meeting with her teammates to discuss ongoing projects. Each team member shares updates on their tasks, challenges faced, and any support they might need. Sarah mentions that she’s finalizing a report on employee turnover rates segmented by department and tenure.
9:00 AM – Data Extraction and Cleaning
Sarah accesses the company’s Human Resource Information System (HRIS) to extract raw employee data needed for the hiring trends analysis. She then also needs to access the company’s Applicant Tracking System (ATS) to extract relevant talent acquisition data. After these time-consuming, manual pulls, she realizes that one critical field required for the hiring trends analysis isn’t available in the standard system reports. While waiting for the HR tech team to create a custom report, Sarah tries to organize the data she already has, but the delays are frustrating and eat into her morning.
10:30 AM – Data Extraction and Cleaning (continued)
Once she receives the datasets, Sarah imports the raw data into Python. She spends hours cleaning it—handling missing values, correcting inconsistencies, and verifying data integrity.
12:00 PM – Collaboration with HR Partners
She meets with the Talent Acquisition team to understand the context behind the data she has been analyzing. They discuss factors that might influence hiring trends, such as recent recruitment campaigns or changes in the job market. This qualitative input is crucial for her analysis, which will inevitably be limited because she’s spent so much time just preparing the data. Because of the challenges gathering the necessary data and time constraints, Sarah had to let her cross-functional partners know that many of their additional asks were out of scope, leaving them disappointed and Sarah feeling a bit dejected.
1:00 PM – Lunch Break
Sarah takes a quick break, reading an industry article on people analytics while eating a sandwich at her desk. She wishes she had more time to decompress and focus on professional development during lunch, but the day’s demands leave little room.
1:30 PM – Workforce Planning Meeting
After lunch, Sarah attends a large meeting about an upcoming project focused on workforce planning. While she’s eager to contribute, her mind is preoccupied with the hiring trends report and the unfinished analysis. She knows she’ll have to prioritize the urgent request at the expense of this strategic initiative.
3:00 PM – Data Analysis and Report Preparation
Finally able to begin analyzing the data, Sarah has limited time to work. She focuses on basic cross-tabulations and simple bar charts to meet the minimum requirements of the request. There’s no time for deeper analysis or advanced visuals, leaving her dissatisfied with the quality of insights she can provide. Sarah quickly compiles her findings into a report. The executive summary is straightforward but lacks the nuance Sarah would typically include.
4:30 PM – Meeting on Employee Engagement Survey
She attends a meeting with cross-functional teams to discuss the upcoming employee engagement survey. They talk about survey questions, distribution methods, and how to maximize participation rates. Although Sarah is eager to provide analytical support for the survey, she can’t commit to much given her current workload.
5:00 PM – End of the Day
In a rush and feeling stressed, Sarah sends the hiring trends report to the Head of Talent Acquisition. She hopes the data joins were done correctly and that the visualizations meet expectations. Her day ends in exhaustion, knowing she had to postpone other projects she was excited about, like the workforce planning initiative, due to this urgent ask.
5:30 PM – Professional Development
Despite her fatigue, Sarah spends some time on an online course about predictive analytics. She knows that acquiring new skills is essential for her career growth, even though her current workload rarely allows her to apply them effectively.
Summary
A day in the life of a people analytics professional like Sarah is dynamic and multifaceted but can often be overwhelming due to workflow inefficiencies. Her role is pivotal in transforming raw data into strategic insights, but with the bulk of her time spent on manual, time-consuming tasks like data extraction and cleaning, she does not get to impact organizational decisions related to talent acquisition, employee retention, and overall workforce optimization to the full extent possible.
Here’s a breakdown of how Sarah spent her day:
- Data Extraction and Cleaning (50%): This grunt work consumes half of Sarah’s day, leaving little time for high-value tasks.
- Collaboration (20%): Despite its importance, collaboration time is limited due to inefficient processes.
- Data Analysis (10%): Sarah’s actual analysis is rushed, reducing the depth of insights.
- Reporting (15%): Most reports are basic, focusing on quick turnarounds rather than strategic value.
- Continuous Learning (5%): Occurs outside regular work hours, adding to Sarah’s stress.
Why It Matters
Sarah’s experience highlights the challenges that many people analytics professionals face in their day-to-day due to inefficient workflows and limited tools. AI-driven people analytics solutions, like Included, could dramatically reduce the time spent on data preparation, allowing analysts to focus on more advanced analysis, as well as strategic consulting and collaboration with stakeholders. By eliminating manual tasks and one-off data requests, Sarah could get valuable time back to serve as a strategic advisor, driving greater value for her organization and unlocking the true potential of people analytics.
