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Online Tool to Analyze your data in HR

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As an HR, have you ever wanted to use analytics and gain insights into your data?

There are many times when we want to gain insights into why a particular thing is happening in our organization and how it can impact future operations. But that actually requires knowing how to use analytical tools like RStudio, Python, Power BI, and Tableau, etc.

Several other software also can be used, some of which are free and others might be paid.

But most of the time, the learning curve of those tools is really on the steep side, and as a professional, you don't have much time to learn all the software and then implement the same in your company.

To understand which software can make our work easy, we will have to work on some questions;

Q. Why is analytics difficult?
I want to assure you, analytics is something that you are using on a day to day life and you don't even know that.

And when you say it is difficult, remember one thing, even a child that is just born, uses machine learning algorithms to learn about its environment and other things.

So, how can one be bad in something that he/she uses in everyday life starting from birth!

The answer is, we all are analytical organisms, hence we can analyze speech, text, and other things without even putting effort. It is natural to us all. It's just like we have to pay more attention when we are bringing something from the subconscious mind to conscious thinking.

Whenever you are thinking to take a person onboard in your team or you think of implementing a new leave policy, you are using analytical thinking to decide if all the factors that are contributing to decide that you are going to take are data-backed and accurate or not.

Analytics becomes difficult when we have to use the same analytical methods on a huge dataset. For Example, when you are working on a data set of 10,000 employees in your company and data is regarding the Performance Review Feedback.

There is going to be 50 columns with feedbacks of employees with different response in an excel sheet, hence it becomes difficult for your mind to digest the data, and hence you think analytics is difficult.

If the same data was from 2 people in your organization, you would not even use an excel sheet to give your insight, but to digest and gain some insight from huge sets of data, we require tools that can crunch data sets for you.

Therefore, if you know how to use those tools, crunching data and giving your insights becomes easier for you to do, and analytics never feels like a difficult subject altogether.

Q. What kind of software can we use to analyze HR Data?
In HR, where we have more often qualitative data, it is advisable to use tools like RStudio, Python, or Power BI.

There are several factors that we should take into consideration before choosing a type of tool to analyze data. 

During my college days, when we started learning about analytics in HR, we were introduced to pie charts, and how one can use them to show parts of a data set. In no time we used pie charts to define everything that can be possibly shown. 

This is not the right way to use these tools. You should understand, what a particular tool is used for before using it on a data set.

Therefore, if you want to analyze financial data, like HR budget or attrition rate, use tools that are easier to work with financial data.

Most of the work can be done in excel as well. So no need to include heavy machinery in your ammo, when you don't have data that requires that kind of insight.

But if you are thinking of handling textual data and you want to gain insights about sentiments of an organization or how a particular policy change is affecting the behavior or culture of your organization, then you can go for tools that can give you the capability to analyze that kind of data. 

For Example, you might require tools like R or Python to do sentiment analysis or classification, etc.

Q. What is Monkey Learn?


Monkey Learn is a website, with ready-made algorithms, that you can use to analyze several data sets.

There are also features, which can help you using Monkey Learn with an API, in RStudio or Python. With integrations like these, it becomes easier for people to analyze more qualitative in nature.

Some examples for the same are;

  1. Software Feedback Classifier
  2. Sentiment Analysis
  3. Urgency Detection
  4. Keyword Extractor
  5. Profanity & Abuse Detector
  6. Language Classifier
  7. Role Seniority Classifier
  8. News Classifier

and many more ...

You can use these models or can also create new models to use. You can even train the models as per your requirement.

For Example, if you want to check the feedback of 10,000 employees, you can actually use Abuse Detector to check who all have been abusing the organization or you can also use Urgency Detector to check which are the most important tasks to accomplish as per the feedback so that we retain more employees.

There are several models categorized under the below subheadings, which makes it easier for people to use them;

  1. Classification
  2. Extraction
  3. Sentiment
  4. Topic
  5. Social Media
  6. Content Moderation
  7. Business Intelligence
  8. Productivity
  9. Services
  10. Customer Support
  11. Marketing & Sales
  12. E-Commerce

So, you all can use this website to understand your data and make more data-driven decisions, without any knowledge of coding.

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