As organisations are undergoing vast amount of change in terms of leveraging the technology to make valuable business impacts, HR function of the organisations’ are brought to the fore, harnessing this change. Data, digitalisation and analytics are becoming crucial in HR and to decode the future capabilities of this function from adaptation to transformation using analytics, the thought leaders Raju Macharla, Country Head, Bravura Solutions, and Rajeev Naithani, EVP, Chief People Officer, Infogain took questions from Rajesh Padmanabhan, Chairman, HONO. The questions moved between the topics ‘Analytics Advantage in Human Resources’, ‘HR Dashboards of the future’ and ‘How managers can drive engagement & productivity’.
This conversation was a part of the NASSCOM Round Table Conference held on 18th October, 2022.
Rajesh – I am passionate about HR Analytics. I will start with these little bit of context. Yes, first is, I think ideally we need to figure out what analytics could be in terms of an ideal dashboard. All we are talking about is – the first point I want to say is – HR from a lifecycle management gone into a complete state of business cycle integration. We are going to talk about it. With business cycle integration, what I really mean is, it’s not just managing hire to retire, or recruit to retain and stuff like that. It’ already been done and many of its parts have been dealt with by the machines now. You hardly get involved these days. I say that the 4 P’s have been substituted with the 4 C’S. What typically used to be Policy, People, Processes and Practices have got converted to culture, capabilities, contribution and credibility.
There is a notion of change. So it’s not lifecycle, it’s lifestyle now. And all of us are dealing with this change, grappling with this change. I don’t mean to say that any of us can say with conviction that we are all dealing with it. Some of us have been successful partly; some of us are learning to cope with this; there are some people, who’ve post this metamorphosis of change, have fallen out. Some of them have tried to survive; some of them tried to level and come back where they were. Some of them are really excelling in the situation. So it clearly tells us there are a lot of opportunities. So from a business cycle integration, HR has really got to figure out into the futuristic world, be amongst something that is contributing to business value, decision making of tomorrow, futuristic, enabling the entire enterprise evaluation, etc. If you’re not part of that, if you don’t see the journey, might as well jump into it; and that’s where the HR analytics part come into being.
Number two – the shift from the qualitative to a quantitative HR, I define it as hashtag QuantHR, and you will find me blogging quite a bit about it – What I mean is – HR has always been a soft function; it always dealt with people, with emotion, dealt with something that got to dealt on human to human basis & we’ve kept the science part of it, out. But I think there is a lot of stuff glaring at us to say why not get a few things into it because at the end of the day, an enterprise is bound by the top-line, bottom-line and cash. Yes, there are social contributions that are got to be done but at the end of it, this is where the demand comes down to. And with a lot of compression happening across a lifecycle, there are a lot of challenges w.r.t that. Can we see it today? So, the shift from qualitative to the quantitative part of it.
The third one is insights to foresights. A lot of us do the analysis. Right? I mean, whether it is the attrition part of it; whether it is hiring rates; or whether it is w.r.t the overall performances. The entire stuff has got to be converted to foresights. What does it mean to be doing show rates for example? If you are to look at every single dimension of the lifecycle – let’s start with recruitment for example – It’s important to figure out what’s the quality of the hire; it’s important to figure out what’s going to be the show rates; how many people are going to show up at the end of the day. It’s important to figure out what the stickiness is, that’s going to be there. Etc. Now these are all complex stuff. There are not very simple stuff. But, can it be codified, can an algorithm be written, can something be done with reasonable amount of conviction and probability. The answer is – Yes. Today, we have the opportunities. And I take pride to say, in HONO, we do a lot of stuff around it. I am not saying we are successful in every single stuff but we do a lot of it and we make an attempt to build around it.
Similarly let me a take a big one – five decades, we’ve all been measuring performance, right? God knows – right from the day management was discovered. But is it performance that is going to be measured? It is the contribution that really is making an impact. Performance is a measure of effort. Contribution is a measure of outcome. That’s where analytics come in. Just to give you a case in point.
That’s where I said earlier – The 4 P’s to 4 C’s – The third C that I said was the contribution. If you don’t know what your contribution is going to be – and that brings me to the point of talent to value. At the end of the day, an enterprise is compiled of talent. Now, how do you really define value to that talent is what analytics could do.
There are the four points I wanted to set the context with and dwell deep into the analytics space. So every single area that you di in terms of managing; try and see – how could you take it to the next level of predictive. It could be predictive capability, it could be predictive performance, it could be predictive attrition, it could be flight-risk prediction, it could be show rates. Every single aspect actually makes life bring to a decision making level where you bring the line and people function together. At the end of the day, that is what matters.
Yes, HR is no more a function, in my view, I call it a functional conglomerate because you suddenly are expected to do so many things; but that’s where the opportunity is.
So let me start this conversation with a debate. I think I spoke about was little bit of heavy stuff. Is all this is true? May be true, may not be true but at least, it’s staring at all of us.
So let me turn to my left and ask Raju. He is a business guy at the end of the day. And I am going to start with a provocation to say – Are we expecting too much of science? Are we building too much of stuff? Is this a false world? Do you think there is merit in whatever we were discussing or push back if you think that this is not what it is? It got to focus on best employees, do engagement service, concentrate on swings, figure out what your health is, do some exit interviews and life is good. So, I am starting with a provocation Raju.
Raju – Thank you Rajesh. Having come from an engineering background for 30+ years, what I’ll say is that I can’t measure, I can’t improve. So, it’s very important for us to add some metrics into everything we are doing. HR function I know is an EQ function. It is not an IQ function. However, I see everyday conflicts in various functions of HR managers. You all will know these functions. If you take a couple of examples like recruiting. It is a big tassel between the hiring managers and the recruiters. Hiring managers say that you are not giving me quality candidates and the entire funnel from the top to bottom – when a person comes on board – it is almost like one is to thirty. If I get 30 resumes then I get finally one candidate. And, then when I see from the business angle, oh my goodness! This guy is interviewing 30 people to get one person on board – this guy has 10 positions open, then 300 interviews is what the team has to do, and then I will multiply the number of hours team is going to spend.
From the HR side, you won’t see – “okay, I am able to hire these many people.” You are going to report to the management. But the thing is – I see – how many hours are being spent by the lead engineers to hire the people. And, then I will ask the question – is it going in the right direction? How can you improve on it? Then of course, other parameters I just don’t want to repeat on talent acquisition alone. But, there is a lot of metrics and analytics of course. Many of you might be already doing or mentally doing it but that data has to be presented to the management and people so that right decisions can be made using that data. And of course, Rajesh talking about predict tools. That is really next step – if I think about it.
If I can measure it, then improve it, the next level of prediction – If I can do the prediction, that’s even better for next quarter – next half a year – That predictive analysis is going to be much more useful so that we can get some business directions out there. And so, especially when are resolving the issue between the hiring managers and this one, the data is going to help a lot.
And other part of it is learning and development. We have so much of it available in the market for people to learn and develop their knowledge, right. And leaders, somewhat at middle level, top levels, we think that okay, so much is there – thirty years back I started my career with fortran programming. Probably, you guys don’t know even the translation of those names. Right? That was the kind where we started. Point is that, the difference is much now, you can take your phone – these days I speak to my phone - I press the mic button and say whatever I want, and it answers back. That’s the advancement. Then I think, how much is available, why would I need to spend learning and development. But how our mind set hasn’t changed. Engineers do complain when it comes to reviews or the surveys we conduct, that’s where they say there is no learning and development in this company and then that came as a surprise to me. And, I am sure, this is done by HR functioning in my office and it came as a surprise. Then we thought, what are we doing and we started improving on that and we started publishing the data. And career development – that is another thing in HR function but actually but all the things we are talking about is everybody’s function. Manager, every individual in the company has to be responsible for all these functions. Then only as a company it will be successful.
I would say put everybody together and bring in the data to show that this is what is available. We publish in-house. It is a smaller company. There are 1400 employees in the company and close to 550 employees in India. This is a service organisation, right. So a lot of people ask when I am going on-site; same thing happen in product-based company. So what we did, we published that data also. Every month we publish the data. At least nobody complains you are not sending anybody, at least if I can’t see it, it doesn’t exist, right! That’s why we are making that data available. And next type is predictive, we haven’t gotten there yet.
Rajesh – Thank you and you made a life little easy. You said it’s not too much of science but common sense side like glaring at the business, try and resolve it and be there and bring some science to it but don’t make it completely science. This is what you said, so thank you. I am turning on to you Rajeev, and the next question to you is, has the HR function been agile and in adoption of particularly the technology stack– I think w.r.t. when you look at the social part of it, mobility, and the cloud part of it is reasonable done but how much of penetration so you to speak on behalf of the fraternity but not for you because I know you are fairly agile and how much of an opportunity is there for the HR function. How much of absorption being done, how much of evolution is happening and what’s the gap that needs to be done going forward just bringing what I said and Raju added. Just stich that together and then we will move onto stage 2.
Rajeev – The people organisation has become much more agile, in last few years at least, to say. But coming to the question you asked Rajesh, let me put it in the context of HR function that you take maturity as one, organisational maturity as two and then the journey which we are getting into at and I will give some experiential perspective to that.
So there are certain HR organizations that aren’t much mature in terms of even going beyond the basics. They are struggling to deliver the basic experience to the people. Expecting them to be agile to be adopting to analytics or technology oriented solution would be a big expectation. I think they need to do much more than enhancing their capabilities from a function perspective.
Now the second important thing is the organisation commitment. Now there are HR organisation that are competitive and they do understand the important of analytics; they have gone beyond the basic dashboards and they have dedicated people working on bringing the insights from the data providing some kind of predictability to some extent but then they need help. They need help in terms of acceleration, they need help in terms of sustainability, they need help in terms of predictability and for that the investment has to come from technology solutions perspective. And that technology solution has to be different from automation. Automation can help you bring the efficiency and scale. It can replicate your manual excel base processes into the workflow and that can help in efficiency and scale as I talked about. But it may not necessarily give you insights. It may not necessarily give you predictability and that’s what is the most important aspect from the decision making stand point. Now that’s where organisational commitment is very essential. As an organisation, are we committing to make investment in that space. Because you need help. Whether you go outside or you put team together to build those capabilities in-house, if you are a technology organisation.
Now if I give you some experiential perspective from my own journey so we have all three aspects of maturity. There are certain things where we are just managing at dashboard level. For example, predictability, performance, reviews, managing people, career – that’s all basic information level that we retrieve from system, we maintain some dashboard as and when it is needed and that is done. Then there are some insight based which is all about – attrition for example. Entire storyline about what is my resignation of today – there is a dashboard which is available. Every day I can see how many people have resigned, what is the status from the extent point and at the same if we would like to see what our risk probability of the organisation is; the monthly views are available. So, those insights are available; now predictability is a stage where we want to be almost in every aspects but from an organisation perspective I would like to give realistic example – One is recruitment where we actually have been able to gain a lot of predictability. So we will know today basis the data insights which we have been putting together; which kind of people will likely join us, which kind of recruiter will give us better yield, which kind of skill hiring will have specific impact from overall on-boarding perspective, which kind of companies will struggle still even if we give offer to those candidates in terms of bringing them on-board, so that kind of insights and predictability, beforehand is available. We also know which sourcing channel today helps us the most. Within what notice period a person is going to be joining us. Those predictability has been brought in. So can we say that this predictability is going to be100 percent accurate all the time? The answer is no. The reason is very simple. Because we deal with the human psychology and behaviour and this is very unique. God has been very kind enough to make us very unique and our preferences, values, behaviour while we may bucket them under psychometric tools and say okay, I am part of this – but the reality is there are so many other variables which influence and enable my journey as an individual which could be very unpredictable. So even if you bring in human intervention coupling that with the technology, you wouldn’t be able to make 100 percent predictions correct. Even with the managers, for example, you would see, when we talk about early morning systems, you will have managers feeling to make the right prediction and they may say that, “oh, I had a great relationship with that person and I am surprised that he resigned or she resigned,” that is the complexity of the human behaviour and that’s why we don’t call it applied science. We call it human science or behaviour science because you can’t replicate the same formula and say that the outcome will be similar. And remember every company is different, every culture is different, and every context is different. Now that’s where the predictability won’t help you but at least it will have some hour value which will enable you to make some predictability and have some mitigation around that.
The second space where we have been able to bring a lot of predictability is our equity and compensation process. We are actually able to do it in a very methodological and scientific way. We have designed framework because that is one area where you can still drive a lot of predictability. Because you know that there will be only one specific behaviour which will be driven by that. And the third area where we are working very extensively and we are leveraging one of our practise organisation which is into AI/ML – we are trying to work with them to create predictability on employee risk. There are various variables and it so complex, it is too difficult to put all the variables together and say that if every things remain the same, the outcome would be this. It is not going to be happening. But still we are trying, it is a trial and test phase in which we figure out some possibility for us and in future the more we get into that space of predictability, it will benefit us as an organisation and that’s where as HR people and HR fraternity we need to move towards, because it will help us bring in much more credibility in the organisation standpoint. So there are some of my perspectives.
Rajesh – Awesome. Few good takeaways - Point number one is – you don’t need to be 100 percent perfect. I think wherever you have questions, make an attempt and get there. It is big takeaway. I think, it gives away a lot of questions. In terms of hiring to contributions to attrition to stickiness to the entire other value chains as well. Point number two – you don’t need to pick solutions by yourself. It depends upon expertise which is available. Don’t worry about solving it yourself. There are enough experts in the market. That’s where we make our living. But importantly, the behavioural part of it, I think, is a very complex stuff. So the macro is, human behaviour is a function of ability and motivation; ability is a sub-function culture, education, experience and expectation. And motivation is further sub-function of personality and environment. It is a very complex value chain in terms of how people behave. You know the macro but to define all of that and then to convert it to value and then empirical value is very difficult. But nevertheless, I think, we’ve at least gotten there. Today, we are able to define this, to understand. Who knows, may be few years down the line, if we move into this particular direction, we’ll be able to do. Always keep giving a simple example of IPL. At the end of the day what do you do in an IPL – you bet on a few players and at the end of the day they deliver performance. So it’s all about betting on people. So if we’re betting on people – are we betting on the right people? Can there be some value that can be brought in? That’s where analytics come in. So whether it is hiring, whether it is performance, whether it is retention, whether it is capability building, there can be values.
So, let me take this discussion one level deeper – Now, one example – Raju and Rajeev – one concrete example where you did something – whether it was a success or failure – doesn’t matter. Where an attempt was made to convert this into a business value creation. One HR process or a practise or a transaction where you applied a little bit of analytics view, tried to do something and derive some business value of it. And if you derived, share that example. I think it will be some insights in terms of how analytics can be taken.
Raju – I am going to take that talent and team’s example where we had issues with a lot of complaints at the mangers level saying that we are unable to hire. We are failing to execute our projects. And all of you would have experience in the last two and half years – the great resignation – we all as leaders and HR team are on the hot seat. That time, we started working and putting together a hiring funnel. Within that funnel, we interpret various steps – from JD creation and what is exactly people are looking at. All I am saying is a basic stuff. We did that because we were doing a kind of ad hoc. We needed a JD creation properly. We don’t want people that are walking on the water. We needed skills particularly for that job – that is filtering of that part. Next part is – giving some basic questions from the hiring manager to the recruiters and creating a one-on-one relationship between them. So that also helped in improving the process – reducing some of the escalations. For all these people who have to take the online test, we tied up with a company would conduct the online test and some people are like – “Why will I write a test?” But we do want to hire such people, so that’s okay. They have a different interview process. That data also we started publishing.
Then, we found out that the inconsistency in the interview panel members – so we wanted to build some kind of consistency in the way they interview and accept or reject the candidate. So we kind of adjusted that part of it. And finally offers – HR team thinks that for this much role and experience, we want to offer this much package. However, in large companies, there will be flexibility. May be there, may not be there. In smaller companies, we do have the flexibility – for one lac, two lac difference – the HR team will come to me and discuss with me – because I know the business angle compared to the HR side. So I would think about it and see how important that person is to come on board quickly compared to delaying it for any other candidate. So that also helped in reducing some kind of attrition and improving our ability to hire. And like Koffee with Karan, hiring manager will call the candidate to have a coffee with him. And recently what we started with is – that joining kit – which we give to candidate when they join – we decided to give that anyway – we want to gain that emotional loyalty. We also do is we create a collage of office pics and send to the employee as a soft copy – if that person is not coming to the office, we will send that one. These are small things – it’s not analytics I am talking about – things which worked for me and are working; and we are learning. I tell my people that I am happy to be a part of my developing nation than developed nation – developing means I am continuously developing and learning. Developed means I am already done.
Rajesh – Thank you Raju. I think it is good to have a business guy in the discussion. They speak so simple and we complicate many a times. The way you expressed was so simple – I think that conversion between the business and talent example that he gave – has been narrowed down. He just put it in simple terms. I will turn to Rajeev and let him share an example. And after that, I also have some example to share. So talking about something specifically in the area of analytics. May be just one example which really strikes a chord with the audience. Which gives you a business value.
Rajeev - I will give the complex response you got the sample response from the business line. Complex response because the sample response from the business side when we talk about business value creation it's very contraction to the organisation again at the end everything really goes to the top and bottom and contacts and the associated enterprise value around that but if I give you more relevant examples from my journey perspective at Infogain which is a private equity-backed organisation. In a private equity space it's always the enterprise value which is the real business value creation but that's what investors would be looking for from any portfolio organisation. Now there are so many examples and I am finding it very difficult in my head how to actually reach to one, but let me set the broader context in terms of what are the three key priorities which are going to be helping as one of the pillars or three independent pillars to achieve what we want to deliver to our shareholders or the investors. And there are 6 pillars which CEO is driving. Out of six, there are three which are people driven. The number one is the employer brand promise, which we did we need to deliver to our employees it's like we say, our go-to Market Positioning to a customer is x y z, they should be knowing us as Infogain like that. If you are calling ourselves as a human-centred digital platform organisation, that’s how they should relate to us.
It's not us saying this but they experience it while working with us. Similarly, what is the brand promise you are delivering to our employees. And we are actually looking at that from multiple measures perspective. One is we partner with great place to work to diagnose the overall trust index of the company and a we’ve a very great journey when 2018 when we did it first time we came out from being a Legacy founder-driven company to a private equity back door company and that’s when most of us join the organisation. Our trust index was 55 only in 2018, this year it was 80. 55 became 66, 66 became 71, 71 became 80 and India was 82. That’s how journey has happened. Now there is a lot which goes behind this. It is filing the analytics around it. What GPW gave us was the trust index and the data. Now the sustainability around it, the transformation around it, and the commitment from the leadership top-down was all the initiative. And at the end that got measured. As Raju was saying at the beginning that you don't measure basically. He brought in the aspect of measurement to drive the actions and decisions in the organisation context. Now going back, GPW is one element to it; second is when you're telling our people - this is our brand promise - One we want them to feel engaged and that’s where GPW comes to play. Second we want them to learn, that’s where the learning perspective of the organisation will come to play and I'll talk about it as one of the pillars and the third is that they really feel belong with your organisation. They want to refer the people. Now, I say positive about the company and that reflection will come through the social media like Glassdoor and referral as internal. We measure all of that and we have observed that from a sourcing channel perspective, the most successful sourcing channel for us is the referral. The joining ratio is the best in that and that's how you leverage the analytics in terms of linking and then combining all of it together to say that what is the ultimate business value which were driving through that pillar, And the second pillar is all about learning where for us TNI has become obsolete. We don't do TNI thing at all so what we’ve done as we came up with the platform. The entire learning map for everybody basis a role has been deployed in that platform and we have made it more pull based and we are sponsoring a lot of certification as part of the journey as well. What we have seen is the hours investment on learning which we used to drive earlier, we are automatically achieving that. In certain cases, the nomination to learning journey has been higher than that and that's a real value because what is happening is and how did we actually make the entire excellence program as we call it and forget excellence program as we call - Infogain Excellence Program - We have linked it with what we have said to our customers. Now from starting point of the SFDC, we’ve linked everything. Sorry, I am going little longer. We’ve linked it with the SFDC where we're seeing that at a sales funnel level, what are we selling, what capabilities are we offering to our customers and these capabilities have become much more Complex in the last few years particularly with the pandemic because we worked with customers who are fortune 50, fortune 100 companies. They have acceleration from the technology perspective. And we are enabling that for them. In that space, if you are sending very complex which we had not done in the past for example kubernetes skill which we didn’t have in the past - we got deeper into cloud, we got deeper into data insights - AI/ML, the entire full stack perspective, front end technologies, backend technologies, micro services; all that has been evolving in a very different context. It’s a combination of multiple scales which are playing out. Now, do we have those capabilities in-house and at the same time - One is IGP, you can publish that but are you enabling employees to get to it to that learning fact. And that's that we wanted to address.
At the same time, we wanted to address the capability part in the organisations so that what we are selling and what we are building in-houses are aligned well and we are creating that learning culture in the organisational context which will actually help us move in that direction and all of it gets tracked, monitored, measured because it's part of our pillar and third is all about sustainability, social and diversity impact. For us as a traditional organisation, we’re 30 years plus old company. We were founder driven Company until 2015 2016. We were very Indian context oriented. India's the largest delivery centre for us. We are over 5,000 people in India and globally we are 6200. So only thousand plus outside of India that way. Now what we are doing is we are building capabilities from diversity point of view in the organisation context. We opened our office in Latin America - Uruguay. We opened our office two years back in Poland. Our headquarters in USA. Definitely we are a US headquarters organisation. Now, ethnicity is one important denominator for us to measure Diversity. Gender perspective is another aspect for us. The cultural context, the presence of organisation across different continent is another important perspective for us because collectively all these intangibles will also add to the overall business value from which will drive the enterprise value for investor at some stage. Diversity brings a lot of different good perspectives for the organisation. Our ability to sell in the market where we don't have sale engine right now will also go up because of those because we will offer near show location to those customers. Now that is one element - the social element is another perspective. So there are these designated pillars which are driving the actions for us as a priority to impact the business outcomes from investors’ point of view as a business value creation.
And then there are so many other stories which keep happening. There is an OD function which will be running. Change management and analytics has to play an important role in that. There is a CNB function which can't exist without analytics because our analytics in CNB function is the best. We have very robust framework in place and the way we manage our compensation equity program in the organisation - is word class. So I'll leave it here. There are so many things - otherwise I'll keep going. Thank you.
Rajesh - I think the amount of stuff Rajeev spoke just now is worth an applause. He gave numerous examples. He touched and scratched through a few things and got out. One could really get a flavour of right from a go to market customer point to diversity to organisational health index. How do you really link all of this convert into business valuation because the end of the day it’s a story. All of this is real living in real-world.
Let me give two examples. I am not going to blow it up. Those who are interested actually can come to me at a later part.
First one is - I did something 12 years back and this was like I did a predictive attrition code myself if you believe that so I did not know how to write a code but nevertheless I attempted. So what I did was more out of a lot of difficulty when line was going after me for like attrition - attrition - attrition; like you know what is happening and the people were actually getting into the attrition and swings as to what is going wrong instead of that I converted that to predictive attrition so I had a BI team at the backend and I had the benefit of using them and then really wrote a code which I got with the 60% probability of success so I can tell you the full engine in terms of how it works but due to paucity of time I wouldn’t get there. But it's perfectly doable exercise. If I have done that twelve years back maybe in a defined environment, why can't it be done now? It's perfectly doable - number one. In HONO, we’ve done it for a client actually which is predictive absenteeism. Now this is immediately converting to value because we predict the absenteeism an hour before the absenteeism actually happens. And in that also, there is an allocation of resources that happens to the client. Automatically the fulfilment of the resources happen and then this is translating into productivity straight away. This is a tried tested, working one for one of our client. So similarly we can do as you know some of the show rates as he said or it is predictive absenteeism or predictive attrition; linking it to the overall organisational health index - you can keep on doing. The only stuff that is little vague and you can get some fields around it is this learning part of it. Nobody knows what the future capabilities are all about. If you are able to get into a zone where you are able to predict the future capabilities and ready them today I think you're clearly an enterprise of tomorrow. I think those are the apples of tomorrow. So that's a difficult architecture, it's not an easy one but is it doable. It's not impossible; it's doable with reasonable amount of success it may be as low as 40 to 50 % but it's doable. So every single aspect of the human resource functions there can be some blended. and then I want to turn to Raju you know because he eventually said to keep it simple and don't complicated it, Being an engineer and that coming from him and being a business guide, if it comes from him then we got to be real and let's not complicate it but all this stuff is what we need to bring together.
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