HUMAN IN THE RESOURCE AND TECHNOLOGY

The first 10 results for job search with keyword “Project Manager” on a popular professional social networking website

Analytics In Human Resources: The first 10 results for job search with keyword “Project Manager” on a popular professional social networking website showed 200+ applicants for each of the 10 postings. There were some neat graphics on the apply page. The graphics summarised insights regarding applicants. The same graphic will be received differently by different users. The point in case is: analytics helps. Put yourself in shoes of the hiring manager collating responses. If there are 200 applicants for a single position and a hiring manager is handling 5 such positions, it adds to a talent pool of approx. 1000 applicants. Stronger brands, multiple recruiting sources will add significantly to the talent pool created by a single job posting. What you have is Big Data without making a conscious effort to make one.

Analytics In Human Resources: Human is the dominant theme when you hear of Human Resources (HR). How do you do justice to a talent pool that runs into thousands! The answer intuitively lies in relying on machines and their ability to analyse.

Human Resource Management Systems (HRMS), comprehensive recruitment software, talent management systems, Applicant Tracking Systems (ATS) among others are collectively expressed as HR Technologies. Such tools have opened up new possibilities. The gamut of HR technologies is as wide as the human imagination. The more commonly exploited avenues are:

ANALYTICS IN HUMAN RESOURCES

Analytics In Human Resources:

Analytics In Human Resources:

Challenges that embody HR analytics are similar to all projects that attempt to overlay Data Science over legacy systems.

There is the case where data is non-existent. Traditional HR systems have extensively relied upon the HR manager, their ability and more importantly intent to store information being generated at their desks. The human resource function is essentially a function to analyse the subjective and intangible. For long, the set legacy is that subjective aspects are only deciphered by humans. Lack of guidelines on what to store, where to store and how to store has resulted in a ‘no store of data’ or data not recorded at all.

Early adoption of technology in the field of Human Resources can be seen in the areas of employee record keeping and performance evaluation. Systems were often adopted on ‘as and when needed’ basis. The result of that today is inconsistent data format and multiple sources for possibly similar information. Every tool will create its own data repository. A major challenge today is to integrate systems and data bases that exist in the organisation, but in isolated silos.

HR, as a function, has for long been a champion of the human learning curve. It has been a witness to resistance to change. There is a hesitation to learn a new skill especially when it is a technically advanced subject. This experience applies to human resource managers as much as they apply to anyone else.

Privacy and security is the newest challenge. Storing sensitive information about individuals is a position of responsibility. A responsibility, which is now shared by machines and storing devices, exposing new vulnerabilities. Virus attacks, hacks, worms and swarms are real. The ability to simply copy data by unauthorised personnel is an equally real concern.

Analytics In Human Resources:

The Human Resource function for long has relied upon the human skill. Efficacy of the skill is well established. A dynamic environment demands that the human skill be augmented.

HR Analytics carries the capability to substitute repetitive tasks. Automated tools offer the possibility to have reports in real time and/or with no human intervention. It would free up man hours for other critical tasks. HR technologies reduce errors and improve user experience.

The human effort is prone to biases, cultural and social influences and latent factors that find mention mostly in conversations at the cafeteria and after work, when colleagues catch up! Technology and analytics can be tools that mitigate human bias. It is a powerful tool to introduce objectivity and fact based decision making.

Analytics In Human Resources: Why-HR-Analytics-indiqa-analytics

HR ANALYTICS: USE CASE

Capability: Building specialist groups that cover primary areas of data management, analysis and interpretation drive the impact on the overall business. Hunting through the repository of existing information, matching these with business plans aided by an automated process can prove to be a powerful and efficient tool to generate core competencies that a business needs to seek.

Competency acquisition: The digital age has undoubtedly formatted how a talent pool is generated, accessed and managed. It offers a bird eye and possibly real time information of success in acquiring desired competencies.

Capacity: HR Analytics carries the capability to substitute repetitive tasks. Improved operational efficiency has a direct impact on human resource service delivery. It reflects on how employees perceive organisations. A survey on time management concluded that employees spent a sizeable amount of time in meetings and up to 4 hours a day preparing for them. Appropriately captured data and access when needed would present the relevant information on tap to all stakeholders.

Recruitment channel analytics: Ease of access has encouraged volumes both for job postings and applications to the posting. Larger volumes of job applications pose set of challenges and opportunities alike. Analytics helps refine the recruiting effort by generating empirical and unbiased facts about which recruiting sources are yielding desired results.

Employee performance: There is a steady and constant shift towards ensuring that what employees are paid is closely tied to their contribution to the organization. Alignment of pay for performance is the number one shared agenda among HR and CEO.

Employee churn and attrition

A decision tree based model that can predict attrition. Prediction and modelling possible outcome is an effective way to hedge against traditionally unpredictable human behaviour. Another example; if the cost of voluntary turnover has been established at approximately 1.5 times annual base pay and you prevent two high value employees, with salaries of Rs. 50,000, from leaving the organization, you have saved approximately Rs. 150,000.

Corporate culture analytics

Employee-churn-and-attrition

The human behaviour though fraught with subjective definitions can nevertheless be classified into words and adjectives such as self-motivated, polite, candid, accessible as a manager etc. Values that an organization wishes to stand for. These can then be given scale based quantification. Analytics can offer valuable inputs on what has traditionally been subjective and excessively latent.

IN CONCLUSION:

Human resource decisions have a real cost attached to it. There is a cost associated to the recruiting and inducting process; incorrect choices can have larger and longer negative impact on the business. Long term business planning is based on ability of the human resource to deliver. It is thus imperative that the human resource function uses HR technologies to predict. Deep drilled analysis, modelling and predictions can offer information that is critical to success of business plans.

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