This report is based on time-tracking data from DLabs’ Toggl, from 06.15 to 05.19 (4 years). It encompasses work records of all employees working at our IT data oriented company – python developers, product owners, project managers, front-end developers, machine learning engineers, data scientists, etc. At DLabs, our solutions are known for increasing revenue, optimizing processes, and saving your company resources in the long run. We employ data science and machine learning to build smart solutions that have consistently maximized workflows and redesigned business models for efficiency and growth.
The analysis is made of two parts:
- The first part consisting of analysis of task descriptions. Based on their contents, we try to group them into several types, eg: we classify the task described as ‘model hyperparameters optimization’ into ‘data science’ category.
- The second part focuses on task times, ie. differences in work patterns every day of the week or months of the year – for example, ‘which day of the week do we finish work the earliest?’
There were several a things we wanted to explore and confirm:
- Will the company’s shift from development towards data science be visible?
- Do the projects require more developers than data scientists early on, then switch as the project progresses?
- Are the overall proportions of development/management stable?
- What are the typical working hours?
- What is the most usual time for a lunch break?
- Do we finish working earlier on Fridays?
- Which month of the year do we work the most?
- How has the total amount of work done increased with the company growth?
- What are the most popular dates for vacation?
The report is based on data exported from the time-tracking system used by DLabs and covers the period from June 2015 to May 2019 – full four years. There were approximately 65.000 records describing specific tasks to be done.
