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Featured
5 min read
Chelsea Schott
It’s no secret that taking time off from work is vital for your employees’ well-being. Time away allows people to unplug, recharge, and return to work more productive. But how can you ensure that your employees not only take the vacation time they’re entitled to but also that your organization manages time off in a way that ensures adequate staffing and resource availability? With One Model, you can easily track and manage employee time off, making it one of the best PTO tracking software options available. Leaders can import time-off data to gain a clear view of who has taken time off and who has approved or pending leave. You can filter the data by Division or Supervisory Organization and categorize the different types of leave—whether it’s vacation, sick days, volunteer time, or other types of paid time off accrual. This breakdown ensures you have a comprehensive understanding of how time off is distributed across your organization. Understanding Time-Off Trends Knowing when employees tend to take time off is just as important as knowing how much time they’re taking. According to a study by CalendarLabs, December is the most popular month for vacation in the U.S. and Canada, while July is preferred in the U.K., and April in Australia. One Model enables you to create custom queries for employee vacation trends analysis within your organization. For example, you can build a report to show the most common vacation months, even breaking it down by day, to better understand when certain teams or departments are likely to be short-staffed. Managing Accrued Leave to Minimize Risk Unmanaged paid time off accrual can present risks beyond just operational gaps. If employees decide to take their accrued leave all at once, it can cause significant workflow disruptions. Additionally, accumulated leave poses a financial liability for the company, especially when employees leave and need to be compensated for unused time off. By keeping an eye on accrued leave through One Model, you can identify potential risk areas within your organization and take proactive measures to mitigate them. How One AI Can Help Strengthen Predictions of Future Behavior Use the One AI table insights feature to identify unusual leave patterns. For example, table insights can highlight employees with excessive accrued leave who may need encouragement to take time off, or detect negative leave patterns (where employees take more leave than available). Analyzing these patterns enables leaders to address staffing challenges and support employee needs more effectively. Predictive variables such as employee demographics, performance metrics, engagement scores, and manager or team dynamics, can be incorporated into a regression model using One AI to help predict how many time off days different groups of employees are likely to take each year. More importantly, it would identify the key factors influencing whether employees take more or fewer days. Understanding these drivers can help organizations implement strategies that encourage employees to use their vacation time effectively. Benefits of Using One Model for Time Off Tracking Up-to-date Insights: Track approved, pending, and taken leave in real time. Comprehensive Breakdown: View time off data by division, department, or leave type. Custom Reporting: Build detailed list reports for compliance purposes or to conduct an in-depth analysis of employee vacation trends and staffing coverage. Proactive Risk Management: Identify and manage excess paid time off accruals to reduce financial and operational risks. Predict Future Behavior: Understand factors driving time off behaviors and better forecast future usage. With One Model, you can ensure that vacation time is both well-monitored and well-managed, helping to create a balanced, productive workplace while safeguarding your organization from potential risks associated with time-off accumulation. Ready to learn how One Model can streamline all your HR tracking?
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Featured
6 min read
Christine Virjee
Charts play a crucial role in conveying insights, which is why elements like chart legends are essential tools for interpreting colour variations and understanding complex data sets. Let’s dive into the nuances of chart legends with five tips designed to make your charts more impactful and easier to understand. What are chart legends? Chart legends label and help explain colour variations in your charts. When used effectively, they improve readability and prevent misunderstanding. Chart legends work best when there is more than one metric or dimension, and where colour variations need an explanation in a chart. Let’s work through a few real-world examples and tips to see how chart legends can enhance or detract from a data visualisation. Tips and real-world examples Tip #1: Use legends to explain colour variations In this first example, variation occurs when there is more than one metric and the chart legend explains their meaning. In the chart below, dark blue indicates Start of Period (SOP) Headcount, while light blue represents End of Period (EOP) Headcount. It is easy to see at a glance which number and bar corresponds to each metric. In another example, variation can be depicted when there are one or more Dimensions with more than one group selected. As shown below, the colour variation indicates Male and Female Gender – dark blue for Male and light blue for Female. Again, meaning is quickly and easily discerned with the chart legend. Tip #2: Set legend position to None to hide legend in single-colour charts What happens to chart legends when there is no colour variation? Single-colour charts such as the example below with a single metric like (EOP) Headcount over time don’t usually need a chart legend because all of the bars will be the same colour. In these situations, a chart legend is unnecessary as it only serves to repeat information. Tip #3: Hide metric names when only a single metric is included For cases where only a single metric is included, we recommend the Option to Hide Metric name as this information will likely be already mentioned elsewhere, likely in the chart title or the Storyboard page. In Tile Settings, slide the toggle for Hide Metric Name to On. For pie charts, the Hide Metric option will apply when Legend is set to None and Series named selected as Data Label. Tip #4: Choose a filter to limit chart clutter Chart legends also include the selections for the Dimensions. A selection controls what is visible on the chart, whereas a filter controls what the dataset includes. When only a single selection is made, they work similarly. However, selections show in the chart legend, while filters display on top of the chart and can be hidden if desired. Therefore, it’s best practice to choose a filter to limit chart clutter in cases where selection is used to select a single point of the data. Tip #5: Use Group legends for multiple metrics In the case that multiple metrics are included on a chart or the metric name is not mentioned anywhere else, Group legends should be turned on to avoid any ambiguity. Make your charts legendary Mastering the use of chart legends is essential for creating clear and effective data visualizations. By following these tips, you can ensure your charts are not only visually appealing but also easy to understand. Whether you're dealing with multiple metrics, color variations, or trying to minimize clutter, thoughtful use of chart legends can significantly enhance the impact of your data. Visit One Model's Help Center to learn more about custom chart legends.
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Featured
3 min read
Pria Shah
Struggling to find the truly important information in large tables of data? Say hello to One AI Table Insights – where you can turn your data chaos into clear insights! What Is Table Insights? Leveraging descriptive statistics, Table Insights automatically identifies potential, noteworthy, or unusual patterns within your company's HR data. It analyzes your data, offering the clarity required for decision-making. Discover answers to key questions like: Is there high employee turnover in a specific area of my organization? Are some teams promoting fewer employees? Is there a gender imbalance in any departments? Whether you're tracking employee performance, monitoring engagement levels, or evaluating recruitment and retention trends, Table Insights is your go-to solution. If it can be measured as a rate, Table Insights can P-valuate. Measuring Your Data’s P-Value One AI’s Table Insights measures the p-value of your data. But what exactly is a p-value, and why is it important? Think of the p-value as a spotlight that highlights which results are noteworthy and which ones might just be random noise. In statistical terms, a p-value measures the probability that the observed results happened by chance. A low p-value (typically less than 0.05) indicates that there’s compelling evidence that your results are unusual. This is a strong indicator that the patterns you’re seeing are real and worth paying attention to. One AI’s Table Insights simplifies data analysis and provides you with clear, actionable insights grounded in statistics. With recommendations based on low p-values, you have an additional tool to inform decisions to drive your business forward. How Does One AI Table Insights Enhance Your Workflow? Instant Insights: Forget manual analysis. Table Insights delivers instant observations, pulling out the most important data points with ease. Productivity Boost: Free yourself from tedious data crunching and focus on making strategic decisions that drive success. Tailored Interactions: Customize outputs based on your specific needs. This includes filtering data, focusing on particular metrics, and adjusting visual representations to best fit your requirements. See it in Action Check out our video tutorial and see Table Insights in action.
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