Analytics for Optimizing HR Investment Strategy

Published by MBA Skool Team, Published on May 21, 2015

Many recent studies argue that HR needs to become a strategic partner. Latest research, however, advocates that HR is not making much headway towards becoming a strategic partner in spite of the belief by HR professionals that it should.

Owing to the growing significance of human capital in driving organizational effectiveness, the potential exists for HR to play a pivotal role in developing and implementing corporate strategy and becoming a high value added part of organizations. If the HR function can make a strong case for being a vital part of strategy development and implementation because of the status of human capital, why does HR repeatedly fail to be a strategic partner? At least one probability is because HR lacks the type of analytic and data based decision-making capability that is needed to impact organisational strategy. One of the explanations for this may well be because it lacks the right metrics and analytic models. In comparison to finance and marketing, HR often falls short of the mark when it comes to providing metrics that assess HR processes and practices from a strategic perspective and analytic models that show the relationship between HR practices and the effectiveness of the organization.

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"Many companies favour job candidates with stellar academic records from prestigious schools—but AT&T and Google have established through quantitative analysis that a demonstrated ability to take initiative is a far better predictor of high performance on the job."

In their quest to build high performance cultures; leading companies are increasingly adopting practices of analysing employee data, and applying sophisticated data warehousing, data mining and business analytics techniques to such data. The practice allows for getting the most from their talent and providing insights for effectively managing employees so that business goals can be reached quickly and efficiently. Although most organizations have enough data to make analytics valuable, it is often generated and stored in multiple places in multiple formats. The goal of HR Analytics is to use high quality data, and build high-performance business processes to leverage the human capital in the organisation. The use of analytics so as to appreciate how HR practices and policies translate into organizational performance is a powerful tool for HR functions to add value to their organization. Statistical techniques and investigational methods can be used to test out the causal relationship between specific HR practices and such performance outcomes as customer satisfaction, sales per employee and the profitability of particular business activities. In many respects the ultimate test for HR functions is the ability to show the bottom line effect of its activities. This is an impactful way to increase its buy-in on company business decisions and future business strategies.

Optimization Techniques for HR initiatives

As HR we often fail to pin point how exactly our initiatives are impacting the business outcomes. For example we might be measuring a lot through metrics developed for capturing multiple aspects of human resources. They might be as simple as the turnover rate, the direct costs incurred to complex ones like engagement scores, ROI, etc. But where we fail generally is that all these are taken as working in silos and thus the initiatives are such designed that they cater to each individually. But often than not these might give us greater impact than the combined impact of the two individual initiatives due to powerful synergies that are formed or sometimes they might work against each other and form a deadly combination. Optimization techniques here help in isolating the impact of various investments and give us better understanding on where they are working and which areas they are failing to get the desired result. It can highlight the areas where we need to give extra attention and design more suitable initiatives. So lets us now see how this idea of optimization can be implemented.

“Analysis of data using ‘regression analyses’ helps to determine the number of days/hours spent by employees on a task and repetitiveness of a job. Career aspirations of employees are factored in to arrive at an ABC risk model for high performers (high, medium, and low category risk). The HR team then uses these insights to create the right engagement and management strategy for the different risk categories,” states Ravi Shankar, EVP & Chief People Officer, MindTree.

From the Strategic Human Resource Management perspective, HR initiatives need to be appropriate, integrated and strategy consistent to garner the best impact of the investments that we make for desired results. So how can we make these initiatives appropriate? The key here is that we need to look beyond ‘one size fits all’ kind of an outlook. Initiatives need to be segment specific. Each employee segments have different needs and different contributions to make, so we cannot use same program for all. For example training requirements for R&D team will not be same for that of the Production team or the incentive structure for Sales team will not be same for the Finance Team. Not only this segmentation can be in terms of managerial and non-managerial levels, new hires and old timers and so many other ways. So ideally even before we start with designing a HR initiative, we first need to segment employees and then decide which plan fits whom and implement accordingly. Not only this, before designing an initiative we need to remember what is the bigger picture in our mind, what exactly are we trying to do and why? This should be based on the business strategy and how in alignment with that strategy the various human resource talent segments will have changed criticality in terms of strategic value or uniqueness of the available resources. Thus all our initiatives need to be strategy consistent. Lastly now that we have identified the vision and mission and objectives of our initiatives and the employee segments for which we are customizing them, we need to look into various HR sub-functions like training, performance management, compensation, staffing, recruitment etc. and then redesign HR practices and programs accordingly and design initiatives for each of the supporting areas. Thus we can integrate them into synergistic combinations that can give us greater impact than their arithmetic summation.

Using Analytics as an Optimizing Tool for the HR Investment Strategy

The work of HR professional does not end by just designing and implementing the various HR initiatives. He also has to keep a track about the impact that it is actually creating, where returns are positive and where it is going wrong. But here comes the problem as HR managers need a mechanism to know what are the optimum investment levels, so that neither it lacks the required time and effort required for the initiative to start giving results after crossing the threshold investments nor does it overdo things and cross-over the boundaries of maximum effectiveness and move towards declining impact. Organizations have multiple linear metrics measuring multiple aspects of HR investments and concepts like ROI, turnover, engagement etc. but they do not know how to combine them together to create a self-evolving predictive model that can tell them precisely what they are doing correct and what they are doing wrong. Here we can take a simple example to understand how the model works.

Let us take a situation where the HR department wants to identify what HR policies, programs and initiatives positively impact employee engagement in their organization. This can then help them to decide what kind of HR initiatives can bridge the gaps that are adversely affecting the engagement levels of employees currently.

Almost every company says it values employee engagement, but some including Starbucks, Limited Brands, and Best Buy—can precisely identify the value of a 0.1% increase in engagement among employees at a particular store. At Best Buy, for example, that value is more than $100,000 in the store’s annual operating income.

What we propose is to first decide what metrics are relevant in capturing the indicators that influence engagement levels of the different employee segments. We dig deep into each of the HR sub-functions and try to understand what kind of information can give insights for this kind of analysis. For example, we can take metrics which capture employee satisfaction (this in turn captures aspects like growth opportunities, training and development options, compensation and benefits etc.), employee commitment towards co-workers and supervisor, employee autonomy and empowerment levels and many others across multiple sub-functions of HR. Now the million dollar question is that from all these metrics which in some way or other impact the Overall Engagement Index of the various employee segments, which all should be taken for the formulation of the final Index Metrics and what will be the relative weightages for the sub-metrics that will constitute it.

Application of statistical tools and methods can be a way to decide the weightages. If we have data relevant to all these metrics for last 5 years or more, we can use it to perform a regression analysis. Based on the coefficients of the regression equation, we can decide the weightages of the constituent metrics. The major draw of using such a technique is that the regression analysis is based on the historical data of the firm and thus proprietary to the organization implementing it. Not only this, we can directly infer which are the metrics which have the highest impact on the Index Metrics and which areas of HR are they related to. Now if the regression analysis is executed at regular intervals with the updated data, it can become a dynamic self-evolving and self-learning metric where the weightages will directly vary based on the raw data thus capturing real time picture of the various initiatives and their impact for various employee segments. For example, in case of managerial levels we might realize that satisfaction related to growth and autonomy are more critical for engagement; whereas for sales team, the compensation and benefits aspects might be more impactful.

Professional sports teams, with their outsize expenditures on talent, have been leading users of analytics. To protect its investments, the soccer team AC Milan created its own biomedical research unit. Drawing on some 60,000 data points for each player, the unit helps the team gauge players’ health and fitness and make contract decisions.

In case we find that over time a critical metric is losing its relative impact based on the regression analysis, we can relook at the related initiative and decide further improvements in the area. Discriminant analysis can be used to compare initiatives which are most impacting and differentiating between the two employee segments in the comparative study. For example, if we implement a new initiative for all employees in our organization, discriminant analysis can help provide how differently the initiative is impacting the two groups (the adopters and the non-adapters) and what steps can be taken to bridge the gaps and offer a similar organisation culture to all.

Future Scope

This model can be further improved by applying predictive modelling technique to it where the final model can compare the coefficients across time and predict based on the modelling technique how effective an initiative will be. It would help us decide correctly where we should invest and how much we should invest, more accurately. However this is an area which needs to be explored further to help enable HR strategize its investment moves and predict its impact even before asking the top management to commit to its proposal for new investments.

The KPMG in India’s HR Analytics solution helps clients generate meaningful and actionable insights across five key talent areas, the 5Cs: cost, capacity, capability, connectivity and compliance.


Although ROI provides a valuable measure of impact, as a true Strategic Partner to the business, the HR function needs to go forward another step. The next hurdle for the HR team is optimization, a forward looking prescriptive analysis technique which identifies investment areas for Human Capital improvement, which can provide for a maximum increase in effectiveness, efficiency and impact to the organisation. The objective is to use targeted adjustments in investment strategies using models that are able to learn from historical trends. Optimization, here, is able to estimate how to take steps to predictively improve future outcomes, which is done by leveraging the magnanimous amounts of employee data. To make the most of such data, the HR function has to embrace Technology and move hand in hand with it to create a high performance culture.

This article has been authored by Arpit Jain and Anirban Ghosh from XLRI,Jamshedpur

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