Time & Attendance
Keep track of employee work hours and attendance with precision and ease.Explore
Ease the burden by automatically allocating work to the appropriate projects. Let your workers dedicate more time to completing projects and less time worrying about timesheets.
Monitor the time allocated to each project stage at any given moment and make precise forecasts regarding the resources required for your upcoming tasks.
Get more accurate statistics and precise billable hours tracking for each project. Your employees are relieved from the hassle of manually mapping time entries.
Track time, prioritize tasks, and provide clients with clear insights into project progress for improved productivity and client satisfaction.
Identify the most time-consuming tasks to empower teams to prioritize work effectively and allocate resources accordingly.
Enables transparent reporting to clients by displaying the time invested in their projects and ensuring a clear understanding of the work done.
By automatically recording breaks and idle time, the app ensures no gaps in time data, offering a comprehensive view of each employee’s workday.
Integrate Workstatus with various project management apps like Zoho Projects, Trello, etc., for smoother workflows and data synchronization.
Customize the app to your unique needs and access real-time task management on the go. Optimize your workflow like never before.
Users can tailor the Workstatus app to suit their different work scenarios for a more streamlined workflow.
Streamline and simplify your task management to make tracking time, prioritizing activities, and boosting productivity easier than ever.
The app categorizes time data based on different tasks, offering a clear breakdown of how employees spend their time on various activities.
Detect when employees switch between different tasks by automatically recording the start and end times for accurate time tracking.
Track task hierarchies to have a hierarchical view of project progress and help teams stay organized.
Say goodbye to tedious reporting processes and embrace Workstatus to simplify reporting, freeing you to focus on what truly matters - your business's success.
Clients can view the time spent on their projects to facilitate transparent billing and build client confidence.
View detailed reports on work hours and activity levels, providing valuable insights into their productivity.
Easily track and manage attendance records for a smoother payroll process by removing manual errors from the system.
The all-in-one solution that empowers companies to track time, monitor activity, and optimize workforce performance for maximum efficiency and success.
Calculate productive and unproductive time to gain insights into employees’ most valuable contributions and identify areas for improvement.
Track teams’ website and app usage, ensuring optimal resource allocation and controlling distractions.
Visualize team productivity trends over time with interactive graphs to help you understand performance patterns.
Managers can review and approve timesheets of employees. Better team management leads to better outputs.
Just click and start the tracker to start monitoring your employees. Start your day and leave rest to our fully automated screen monitoring app, which silently monitors time, tasks, and activities for you.
Set automated reminders to ensure you track time throughout the day, including breaks and idle time.
Workstatus automatically tracks employees’ idle time on the machine and sends them a personal reminder to keep it off or add an idle time entry with a note.
Employees can request time off, leave, or plan a vacation. Managers can view, accept, or reject requests.
Transforming Workforce Productivity and Project Excellence
Login as an employee or manager and exercise control as per your role & requirements. As a manager, you can allow or deny access to screenshots and reports to your employees.
Get access to APIs and integrate Workstatus data with any other tool/software your team uses for a single user interface.
Use raw data to generate custom reports on the minutest details based on second-by-second tracking of your team’s time.
With Workstatus, you are always informed on which projects need your attention. You can schedule your team, prioritise tasks, allocate time on projects accordingly and ensure timely completion of your projects. Switching tasks and schedules is easy, allowing you to manage multiple projects efficiently, everytime.
Yes, you can increase profitability in more than a few ways. You not only track employees’ time to manage their productive hours better but also to track the billable hours, along with proof of work. Bill for your every employee hour spent while also boosting your teams’ productivity. When your employees manage their time to be more productive, ROI automatically boosts up.
Enjoy a self-driven team in a positive work culture and keep your clients satisfied with accurate time estimates, timely progress reports and on-time delivery, and real time statuses without any active interference in day to day activities of team members. Generate invoices and present proof of work, for transparent project management.
Automatic Time Mapping is a sophisticated data processing technique associating timestamps or temporal information with data points, events, or sequences within a dataset.
In essence, it helps establish the chronological order of events or observations, thereby enabling a deeper understanding and analysis of temporal data.
By automatically mapping time to data, this process allows for more effective visualization, querying, and modeling of time-dependent patterns, trends, and relationships.
It is precious in datasets where time is critical, such as time series data or event logs.
Automatic time mapping significantly reduces the manual effort of timestamping data, making it efficient and scalable for large datasets.
The significance of automatic time mapping lies in its broad applications across various domains and industries.
Some key areas where it plays a crucial role include:
Time Series Analysis: Automatic time mapping is fundamental in time series analysis, which involves studying data collected at regular intervals over time. It facilitates accurate forecasting, identifying patterns, and understanding the underlying dynamics in time series data. Industries like finance, climate science, and sales forecasting heavily rely on time series analysis.
Event Recognition and Anomaly Detection: In domains like cybersecurity and network monitoring, automatic time mapping helps recognize unusual events and detect anomalies in real time. By associating timestamps with events, it becomes easier to pinpoint irregular behavior and potential security breaches.
Time-based Pattern Recognition: Understanding temporal relationships is crucial in natural language processing and speech recognition. Automatic time mapping aids in recognizing temporal patterns, enabling more precise language processing and contextual understanding.
Decision-making and Trend Analysis: Automatic time mapping assists businesses and organizations in making data-driven decisions based on historical trends and time-dependent patterns. It empowers stakeholders to identify growth opportunities, assess performance metrics, and plan strategies based on temporal insights.
Automatic time mapping utilizes various techniques and algorithms to establish temporal associations within the data. The choice of method often depends on the nature of the dataset and the complexity of the temporal relationships:
1. Rule-based Time Mapping Approaches: Rule-based methods rely on predefined patterns or rules to map data points to specific timestamps. For example, if the dataset contains a regular interval between data points, simple rules like uniform spacing can be applied to assign timestamps.
2. Machine Learning-based Time Mapping Methods: Machine learning algorithms can learn and predict temporal relationships based on labeled or unlabeled data. Regression models may be employed to predict timestamps based on features, and classification models can classify data points into specific time intervals.
3. Deep Learning for Automatic Time Mapping: Deep learning techniques like recurrent neural networks (RNNs) or transformer models excel at capturing complex temporal dependencies. RNNs, with their ability to retain sequential information, are particularly useful for time series data, while transformers can handle long-term dependencies and parallel processing.
Regardless of the chosen approach, the success of automatic time mapping hinges on the availability of quality temporal data, the suitability of the selected algorithm, and thorough model evaluation.
Here are some major challenges with Automatic Time Mapping:
Accuracy Concerns: Automatic time mapping relies on algorithms and data inputs, which may not accurately reflect actual work hours and activities. Technical glitches or proper tracking methods could lead to accuracy in time mapping.
Integration Complexity: Implementing automatic time mapping systems may require integrating with existing project management tools and workflows. Ensuring seamless integration and compatibility with various software platforms can be challenging.
Tracking Remote and Mobile Workforce: Managing time mapping for remote or mobile employees can be complex due to varying locations and network connectivity issues, potentially impacting data accuracy.
Privacy and Data Security: Automatic time mapping involves collecting and analyzing employee data, which may raise privacy and data security concerns. Employees may feel uncomfortable with continuous monitoring of their work activities, leading to potential ethical and legal issues.
Addressing these challenges involves striking a balance between data-driven insights, respecting employee privacy, ensuring proper implementation, and educating employees about the benefits of automatic time mapping.
Temporal data encompasses information that evolves over time. Time series, a common temporal data type, involves observations recorded at successive time points. For example, daily stock prices, hourly temperature readings, or monthly website traffic data are all examples of time series data.
Common Challenges in Handling Temporal Data:
Managing temporal data comes with unique challenges.
Missing data points, irregular time intervals, and temporal outliers can significantly impact analysis and predictions.
Seasonality and trends must also be considered while processing and interpreting time series data.
Preprocessing and Cleaning Temporal Data:
Preprocessing and cleaning are vital steps to ensure data quality and meaningful results.
Techniques like imputation of missing values, handling outliers, and normalization play a crucial role in preparing temporal data for time mapping and analysis.
Here are some future trends of Automatic Time Mapping:
Advancements in Time Mapping Research: Researchers continuously explore new algorithms, architectures, and techniques to improve the accuracy and efficiency of time mapping methods.
Potential Applications in Various Industries: As automatic time mapping technology matures, its potential applications will expand across diverse industries, including healthcare, manufacturing, transportation, and more.
Ethical Considerations and Responsible Use of Time Mapping: With the growing impact of AI and time mapping on decision-making, it is essential to address ethical concerns, ensure data privacy, and promote responsible use of these technologies.
“ Workstatus employee time tracking tool tells us the moments our people are being
productive and uses that data to help us create productive schedules, deadlines, and tasks. With a simple to use tool, we are able to make our employees more
productive while saving time we used to spend earlier. ”
“ We have further noticed that as a by product, our employees are also motivated to work harder and smarter by taking control of their time by having this app on their devices. ”
“ Glad that we moved to Workstatus and cut down on wasted time. We are now clutter- free, more managed and relaxed. Our people have reported a better work-life balance since we made the move. ”
“ I was exhausted after working full days. I used to spend my entire day running around like crazy trying to finish everything. But things have changed since I made a shift to Workstatus time tracker. Coming home after work with time to spend with family is great. And picture not dreading the next day at work because I am less stressed and don’t feel like there’s too much on my plate. ”