Workforce Analytics is a Business Management Software used in the Human Resources & Payroll departments in a business organization. It helps to track and monitor employee attendance, workload, payroll, absence and other HR metrics.. This software is Simple-to-Use, Fast Resourceful and very cost efficient.
Achieve the best total workforce picture in real time. It’s easy to see who’s here, who’s not, and why. Workforce Analytics assists decision-makers in managing absenteeism and turn-over, improving compliance with benefit programs and state mandates, and streamlining HR transactions. We help you make better business decisions and save time and money. Workforce Analytics is regularly updated with the newest software releases, security patches and certifications.
R
R is the most used HR analytics tool. R is great for statistical analysis and visualization and is well-suited to explore massive data sets. It enables you to analyze and clean data sets with millions of rows of data. It also lets you visualize your data and analysis.
The most often used Integrated Development Environment, or IDE, for R is RStudio. An IDE is software that provides additional facilities for software development and data analysis. This makes the software more userfriendly.
Simply put, RStudio does everything that R does but more and better. The RStudio interface contains a code editor, the R console, an easily accessible workspace, a history log, and room for plots and files. The picture below shows all these elements.
RStudio
As previously stated, R is useful because it enables you to work with much larger datasets compared to, for example, Excel. Furthermore, R has a very extensive library with R packages.
These packages are easy to install and allow you to run virtually all statistical analyses and create beautiful visualizations. Take, for example, the caret package. This package enables you to split data into training and testing sets to train algorithms using cross-validation.
Another example of an R package is ggplot, which helps you to visualize graphs. In a previous article on R Churn analytics, Lyndon showed the distribution of employee turnover for a large Canadian company as seen in the following chart using ggplot.
All in all, R is an excellent tool for analyzing and visualizing vast amounts of data.
Python
Python is another programming language and can be used interchangeably with R. In the data science community, there’s quite some buzz about which of the two will become the data scientist’s tool of choice.
R is better at doing statistical analyses, has a more active community when it comes to statistics, and is better suited for visualizations. Python, however, offers only slightly less functionalities but is easier to learn.
Often used IDEs are PyCharm and Spyder. These tools are to Python what RStudio is to R. Both are open-source IDEs that provide data scientists all the tools they need to use Python. Spyder, short for Scientific Python Development Editor, is specifically made for data science. It includes an advanced editor, an interactive console, documentation viewer, and a whole suite of development tools that also include visualization options.
Spyder, a data science IDE for Python
In short: if you already have experience in Python, or want to get started quickly, use Python. If doing statistical analyses will be your job for the next five years, use R.
Excel
When we talk about HR analytics tools, we shouldn’t forget the basics.
Excel is where most of us started. Whenever you manually extract data from any of your HR systems, it most likely comes out in the form of a comma-separated value (CSV) file. These files can easily be opened and edited using Excel.
The good thing about Excel is that it’s very intuitive to most of us HR data geeks and therefore easy to use.
For example, if you wanted to check how clean your data is, you can quickly transform a dataset into a table and check each column’s data range for outliers.
This way, if you select the age column, you can quickly check the minimum and maximum ages. You wouldn’t expect anyone below 16 to work at your company, nor would you expect anyone over the age of 80 to work for you. You can find these outliers in a single click.
Some quick tips on how to use Excel for HR analytics purposes:
- If you want to run advanced analyses, load the Analysis ToolPak in Excel. This package enables you to do advanced analytics, including correlation and linear regression.
- When you work with large files, transform them into Tables. Excel can work much more efficiently when data is structured in a table.
- Don’t use Excel formulas in large data sets. When you calculate a column using an Excel formula, transform the outcome to a numeric value. Formulas recalculate every time you make a change in the data set. This places a significant and unnecessary burden on your computer’s memory and processing speed – and bogs down Excel.
- Categorical variables (Gender: Male, Female) are easy to check in a table. Select the table column and check for errors or inconsistencies. Can you spot the discrepancies in columns in this picture?
- If you want to merge to data sets, the ‘VLOOKUP’ function is your best friend. It makes connecting two separate data sets very easy.
- Pivot tables do a great job in summarizing large quantities of data. Pivot tables and the VLOOKUP function practically enable you to do HR analytics in Excel.
If you want to learn more about how to use Excel to analyze HR data, check the HR analyst course from the AIHR Academy. That course will teach you the basics of HR data analytics in Excel.
Tableau
Tableau is an integrated business intelligence (BI) and analytics solution that helps to analyze key business data and generate meaningful insights. The solution helps businesses to collect data from multiple source points such as SQL databases, spreadsheets, cloud apps like Google Analytics and Salesforce to create a collective dataset. Tableau’s live visual analytics and interactive dashboard allow slicing & dicing datasets for generating relevant insights and exploring new opportunities. Users can create interactive maps and analyze data across regions, territories, demographics and more. Tableau helps to create a narrative story of the data analysis with interactive visualizations that can be shared with their audience.
Why we love it
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Consider ChartHop your single source of employee data for making better decisions. With ChartHop, you can visualize your company data on many parameters such as department, gender, time zone. And the best thing is that it can be fully integrated with your HRIS.
ChartHop
Review
Although ChartHop started out as an org chart software vendor, they see their offering as a new category called organizational management. It is for that reason that they’ve added people analytics and people planning tools to their platform. You can use this tool to understand the state of diversity hiring, for example, or how your organization has changed over time, as well as compensation across the org, etc.
One of the best parts is the ability to forecast headcount, and specifically to do this under various scenarios (if we raise another round, if we built an enterprise business, etc).
ChartHop
Customers
Some ‘hoppy’ customers include better.com, Postman, InVision, OpenAI, BetterCloud, and Rémy Cointreau.
ChartHop
Stats
- They raised $14M in their Series A funding round
- They claim to have saved customers a total of $2.5M in productivity.
ChartHop
Pricing:
ChartHop is priced at a per user per month fee. Their most basic plan is called ChartHop Build and starts at $3.50 user/month. After that there are two plans with disclosed pricing, Grow and Scale. These are $7 and $10 user/month respectively. For enterprises, they offer custom pricing.
Conclusion
Helps you better understand your workforce by turning data into actionable insights, providing decision makers with critical information that leads to higher productivity and improved performance. Furthermore, the analytics platform provides the business intelligence across all of your workforce management initiatives, whether they are based on timecards or mobile check-ins. It leverages the data you have about your workforce for accurate, meaningful workforce productivity insights.