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Employee Tracker

The large Retail company was facing a significant challenge in managing and tracking our employees' working hours and needed a solution that would automate the process and ensure accuracy. We developed a system for counting employees' working hours. Employees simply approach the device upon arrival and the system automatically identifies them and records their check-in time.

Data Science

Business process automation

Web applications

Retail

Data Science

Business process automation

Web applications

Retail

100h+

manual work reduced

13%

work experience boost

About the client

Large corporate company with over 4k employees working part-time in 10 different time zones. Due to the constantly changing daily shifts of employees, the company needs additional departments with more than 100 employees who fill out the time sheets of all employees of the company.

Tech stack

Python

Pandas

Pyspark

SciPy

TensorFlow

Hadoop

Challenges & solutions

Challenge

Main task is to track and generate time lists for more than 4k company employees for subsequent control of the worked hours number, optimize/reduce costs spent on control of the employees work hours number, as well as improve the accuracy of filling in time lists, thus avoiding the factor of human error.

Solution

Developed a solution for counting employees' working hours. After arrival, employees approach the device (tablet/computer), stand in front of the camera and the system automatically determines who that person is and notes check-in time. When an employee's shift ends and he leaves, the device notes check-out times in the same way.

The system operates in two modes: manual or fully automatic. The system automatically switches to manual mode and the operator on duty initiates the employee identity manually if any problems occur.

The system works in a centralized form - each department can work autonomously without having to communicate with the head office.

DATAFOREST has an excellent workflow and provide constant and close communication. The team brings in a range of technical talent to address issues as they arise.

Bernd Herzmann

CTO Retail company

The way we deal with your task and help achieve results

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.

In Data Science, there are numerous models and approaches, so at this stage we perform a set of interviews in order to define project objectives. We elaborate and discuss a set of hypotheses and assumptions. We create solution architecture, a project plan, and a list of insights or features that we have to achieve.

Step 3 of 5

Solution development

The work starts with data gathering, data cleaning and analysis. Feature engineering helps to determine your target variable and build several models for the initial review. Further modeling requires validating results and selecting models for the further development. Ultimately, we interpret the results. Nevertheless, data modeling is about a process that requires lots of back and forth iterations. We are result focused, as it’s one of our core values as well.

Step 4 of 5

Solution delivery

Data Science solutions can be a list of insights or a variety of different models that consume data and return results. Though we have over 15 years of expertise in data engineering, we expect client’s participation in the project. While modeling, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.

Step 5 of 5

Support and continuous improvement

We understand how crucial the solutions that we code for our clients are! Our goal is to build long-term relations, so we provide guarantees and support agreements. What is more, we are always happy to assist with further developments and statistics show that for us, 97% of our clients return to us with new projects.

Success stories

Check out a few case studies that show why DATAFOREST will meet your business needs.

All Success Stories

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Data Science

Data parsing

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pages processed daily

43 sec

updates checking

Sebastian Torrealba

CEO, Co-Founder DeepIA, Software for the Digital Transformation

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These guys are fully dedicated to their client's success and go the extra mile to ensure things are done right.

Data-driven marketing

We created a solution that helped optimize the customer base to get the most out of the customer data. This solution notifies the client about the services/goods, which they would likely buy, according to the gathered information.

20%

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200%

traffic boost

Jeremy Groves

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They developed solutions that brought value to our business.

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100k+

hourly users

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Shopify stores

Josef G.

CEO, Founder Software Development Agency

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If we experience any problems, they come back to us with good recommendations on how the project can be improved.

DevOps Experience

The ML startup faced high costs during its growth for a data-driven platform infrastructure that processes around 30 TB per month and stores raw data for 12 months on AWS. We reduced the monthly cost from $75,000 to $22,000 and achieved 30% performance over SLA.

2k+

QPS performance

70%

cost reduction