HR ANALYTICS-DATA WILL TALK TO YOU IF YOU ARE WILLING TO LISTEN

Do you think that you could ever find a job that was customized for you, for your needs, skills, and personality? Do you think the companies which we work in can ever get to know us the way we want them to know? The answer to this we can get by understanding HR Analytics in its true sense. Human Resource Analytics or HR Analytics as we know is the process through which we apply analytics to the Human Resource Department of an organization in the hope of improving its employee’s performance. Try Affiliate Marketing in Amazon for a better earning from home. So, HR Analytics does not just deal with gathering data on employee efficiency instead it aims to provide insights into each process by gathering data and then using it to make some relevant decisions regarding how to improve these processes. What HR analytics basically does is to correlate the business data and people data. The key aspect is to provide data on the impact the HR department has on the organization as a whole. So, this is what HR Analytics is all about.

So, what can you do in this kind of field? It turns out that you can do a lot of interesting things. For example, if you have 300 different things you might know about somebody that like we call the predictor variable like where you went to school or maybe where you worked but also how frequently you changed jobs. What things you were into as a kid, what hobbies do you have, how many of these things will actually predict performance once you actually get there? So performance variables like your first performance score on the job or even altruistic behaviors how much you help other people at work so when you throw all these things into interesting analyses then you find out that most of them actually aren’t that predictive but you do find some gems in there. For example, as I'm able to find things like the age at which you got into computers compared to your peers was a really good predictor of whether you are a good software engineer later on in life and also found things like people who are highly neurotic make better product managers.

Let's take up another example. Let's say Bob has been working for Company X for the past 3 years but now he is getting bored because he is a millennial and he wants to make a change but he doesn’t have such a good relationship with his boss so he doesn’t feel like talking about it and honestly he doesn’t see a lot of opportunities within the company. So, what now? Bob feels trapped and he starts to change, his response time is faster and shorter, he changes his LinkedIn profile, starts connecting with recruiters, starts to actively look for job applications, he’s just different. When he finally decides to walk away, he just tells his boss who panics and runs to HR and notifies about the urgent vacancy. HR starts to look for a replacement after Bob’s gone. It takes them about 4-6 months to find a new one, another 2 months to train the new guy. In the meantime, Bob’s team is asked to take more responsibilities and workload. So, they get pissed off and they also get disengaged but once again no one notices and this continues. Now HR Analytics would be able to identify the change in Bob’s behavior and it would send a notification to his boss suggesting how to proceed based on who Bob is and what he wants.

Scary or brilliant that you can decide but through this using an algorithm in HR-related processes could allow the possibility of creating predictive tile and pipelines since now companies would be able to tell when someone’s ready to leave before they do it. Yeah, the system could potentially inform the recruitment team about skills they need to start hiring for and even suggest a list of global candidates analyzed based on success, job factors rather than traditional Job Descriptions and Static Resumes.

If you ask people are you considering leaving people are not actually good at telling you that even a year from now. So, you can do all these cool things, you can get all this cool data and you want to have all these happy employees. The issue is you have the boss in the middle the decision-maker the executive and some of the fidelity and the power of that analysis gets degraded as you go through the entire process of executing it and you end up being the messy sometimes well-meaning sometimes slightly clueless person in the middle. So why is that the case? I have found that there are a couple of reasons for which this happens. The first is that your intuition you feel like its way more important than the data you are shown so if you ask somebody, I want to interview you but I'm going to give you a bunch of questions and you have to stay to this structured script and answer then everyone is like no don’t do that give me 5 minutes with this person I will tell you if you need to hire them and it’s a little bit like being told that’s great you signed for match.com you don’t have to go meet the person at a bar just go to the chapel the algorithm is so good it will tell you to show up there this is the person you need to marry. People don’t like that; they want their intuition in there and speaking of intuition it's one of these examples of all these biases and heuristics that we all have that we bring to the table that is really hard to ignore. The third is we want an easy answer we want a top free list right. We are like just give it to me. The issue is that the robots are still coming, AI is still here, machine learning is still here so we need to find a way to prepare for this. So, what I think we need to do is as HR professionals we need to act as the Rosetta Stone. We need to have the data that’s here, we need to have people that can interpret it and make it sing for our executives because they are busy and they are mostly well-meaning and they just have 5000 other things to do and you need to help draw that out for them.

How we can blend all this together. How can we be an AI (Artificial Intelligence), a data-driven AI-enabled HR function, and what this could look like for the end-user? You trade emails back and forth and at the end of this, you have a conversation with a virtual human that asks you basic questions about yourself. How much are you looking, what are your salary expectations, what you want to do when you grow up and it can record all this stuff and score this, and if you score high enough it alerts the human recruiter who gets in touch with you and you eventually fly out? You get the job, you start in the job but it turns out your manager’s not so good and you go talk to your human HR person and say I am not liking my manager that much, that human has a nice conversation with you, codes that into a database which identifies a trend with this particular manager that they are not nice to multiple people that person can then get sent a nudge email for training that’s been given by real humans so this is the kind of world I am thinking I am moving towards where it’s a combination of real-life humans, big data and AI working together to enhance the experience so I will end with a quote of Frederick Taylor who kind of started this who said in the past man has been the most important, in the future the system must be the most important. Now, the answer to the question that I had first asked you do you think you could ever find a job that was customized for you turns out to be yes.