Text analytics solutions play an integral role in securing the top jobs in Human Resource. It is a serious field. It will help if you keep in mind that it is necessary to have more robust data ties to make the right business decision. Text analytics contribute to being an indispensable part of the data. Hence, it is a prerequisite to step such skills.
Benefits of Text Analytics
Natural language or Text is considered to be an integral part of life. People are known to communicate the deepest thoughts through natural language. Also, it is possible to translate such thoughts into the right insights for different HR analysts. Text Analytics contribute to being the algorithm applications for the processing of text information. In the past few years, there has been an accumulation of unstructured data, which are inclusive of different things, such as audio, images, Text, video.
You should remember that this data is not similar to the classic data view. Such kind of analysis is vital for Human Resource, as it results in detailed insights. Natural Language Processing or NLP analysis offers information that confers clues to the human disposition and intention. It is recognized to be a blessing for the Human Resource as the attitudes and thoughts of different team members provide a helping hand in improving the overall performance.
Things you should learn from Text Analytics.
Text analytics features three different core applications that are useful to the HR practitioners in transforming the way of operation. These are inclusive of:
Counting of phrase and words frequency
As you count the phrase and word frequency and combine them through statistical analysis, you will be successful in identifying different themes and trends. Such kind of research is useful to the leaders of Human Resource to understand the things the employees want in the organization. It helps boost the productivity of the organization.
Natural Language abilities
With the sophistication of semantic language, you will get the opportunity to analyze the Text in such a way that it will be useful in interpreting the meaning. It is possible to make the proper use of advanced analytics solutionsto identify different complaint patterns in other open-ended questions, like the concerns regarding changes in the policy, the requirement for additional vacation time, to name a few.
Identification of features
Such kinds of analysis make the proper use of a more extensive set of data for finding the prerequisite features. Take, for instance, two different CV batches. One batch includes the resumes hired by the business. The other CV batch is of the individuals, which is rejected by the company. From the part, the analysis will uncover the similarities, which are present in every group for refining the recruiting strategy effectively.
The recruitment team makes the proper use of such applications across different areas such as feedback analysis, survey, and appraisal, to name a few. It will help if you keep in mind that text data is the representation of untapped and enriched opportunities. Natural Language Processing ensures more accuracy and more improvements in text analytics. In addition to this, it is efficient in decreasing human interference in taking those vital decisions.
Challenges in Text Analytics in Recruitment applications
Certain limitations and challenges are present in text analytics. To execute algorithms and automate the tasks, human language is not the best option. It will help if you keep in mind that the algorithm might fail to get the prerequisite tone, primarily when a person is trying to be sarcastic. It is an indication that Natural Language Processing happens to be a beneficial tool. It will not replace the human operator who might break different language complications completely.
Context is highly valuable in text analytics. A machine cannot learn it easily. The fact that business organizations is trying to create a language of its own, can be challenging. There are risks that there will be jargons that might be lost on algorithms.
If the practitioners lack prerequisite skills while adopting text analytics, they might fail to analyze and access the data correctly. The processing and cleaning of data happen to be a challenging task and needs a practiced eye.
Applications of Text Analytics in the Recruitment Sector
HR managers can import different open-ended responses in QDA miner and explore the results through various data analytics solutions. The proximity plot will be recognizing other relations between the primary word and different words present in the document. The tool’s Crosstab feature provides the suitable choice to diagnose the relationship between the numeric valuable and frequently used words.
It is also possible to use text analytics to perform the evaluation. Users are capable of defining codes, following different deductive and inductive approaches. The other text extractionare useful in boosting manual coding techniques. After completing the coding, it is possible for the potential audience to conduct several analyses, like code frequency for the recognition of different topics specified in the evaluation. It is useful in exploring the relationship between various themes with the aid of the text analytics tool’s co-current feature.
QDA Miner is a popular text analytics tool that is useful in codifying various kinds of interviews. It is possible to codify such kind of data carefully and manually. This tool is helpful for the researcher in retrieving all types of text segments, which are related to the specific concept. In addition to this, it is useful in codifying different paragraphs and sentences relevant to the idea.
The recruitment organization or department might come across specific challenges as it tries to opt for text analytics. At times, you might encounter a lack of support and training for the recruitment industry’s analytics function. However, inspite of having many challenges, text analytics is now used on a wide scale rapidly. The recruitment practitioners will now make the proper use of the skills in the specific area. It is essential for the Human Resources Department to brush their skills so that they can overcome the challenges of text analytics in the recruitment industry.
Author: Muthamilselvan is a passionate Content Marketer and SEO Analyst. He has 7 years of hands-on experience in Digital Marketing with IT and Service sectors. Helped increase online visibility and sales/leads over the years consistently with my extensive and updated knowledge of SEO. Have worked on both Service based and product-oriented websites.
Author: Muthamilselvan is a passionate Content Marketer and SEO Analyst. He has 7 years of hands-on experience in Digital Marketing with IT and Service sectors. Helped increase online visibility and sales/leads over the years consistently with my extensive and updated knowledge of SEO. Have worked on both Service based and