Abstract
Historically, the human resources (HR) function and functionaries have struggled to establish their credibility and value in the eyes of key stakeholders, including the top management and line managers. Arguably, one of the reasons for this struggle for acceptance is their inability to present data-driven, business-oriented proposals, requiring urgent attention to elevate the analytical capability of the HR function. This paper focuses on the role and significance of HR analytics to organizations through a Six Thinking Hats approach. It presents a holistic understanding of HR analytics encompassing the concept, benefits, limitations, and likely solutions.
Introduction
“In God we trust. All others bring data.”
The highly competitive, uncertain and often paradoxical business environment today poses complex problems forcing organizations to make critical decisions on how best to capitalize their precious resources and maximize productivity. Accordingly, most of the functions are tied to a standard set of performance metrics that allow them to design, implement, monitor and improve their business performance across varying business cycles. The human resources (HR) departments crave to gain a seat at the senior leadership table. But the root cause of the problem is that HR today is mostly doing descriptive analysis by presenting transactional measurements of HR functional tasks which lacks analytical insight. This calls for urgent attention to elevate the analytical capability of the HR function.
HR professionals have readily available, rich data of their workforce and also the required tools and techniques to take on predictive and further prescriptive analysis. Using the immense power and potential of HR analytics, they can provide predictive and prescriptive insights by using its knowledge and experience of the workforce demographics, skill, competency and performance profiles. It not only helps the hiring managers to source the right talent but also identify employees who are at risk of leaving, especially the key performers.
According to Deloitte’s Global Human Capital Trends 2016, 77 per cent of executives researched rate HR analytics as a key priority, and 6 out of 10 organizations are planning to implement HR analytics in next 5 years. Forty-four per cent of companies are using workforce data to predict performance today as against 29% in 2015. As a result, 51 per cent companies are now correlating business impact with HR progress as against 38 per cent in 2015 (Deloitte, 2016). This shows how more and more companies are now connecting their HR data to business outcomes.
This article aims to examine the critical role of HR analytics in organizations through the Six Thinking Hats method (De Bono, 1985). It is a powerful and proven technique emphasizing parallel or lateral thinking instead of adversarial thinking such that when practising six hats thinking, everyone is using the same tool at the same time on the same challenge and thus many brains think together creatively and collaboratively. Thus, this method promises to be one of the most effective techniques to provide a holistic understanding HR analytics as it promotes supportive and collaborative thinking from six different perspectives.
What is Six Thinking Hat?
Six Thinking Hats® is a practical and effective management tool developed by Edward De Bono (1985), one of the pioneers of brain training. For over 50 years, he has presented new and interesting ideas through his books, courses, games and speaking engagements. Dr De Bono invented the L Game (1968), coined and introduced the concept of Creativity Step by Step (1970), Lateral Thinking for Management (1971), Po: A Device for Successful Thinking (1972), Textbook of Wisdom (1996), Simplicity (1999), New Thinking for the New Millennium (1999), How to Have A Beautiful Mind (2004), Six Value Medals (2005), and H+ (Plus): A New Religion (2006), among others. Of these, Six Thinking Hats is considered to be one of his greatest literary works.
Six Thinking Hats is a simple and effective “parallel thinking” process that helps people to walk outside the limits of small-mindedness, unidirectional thinking and fixed positions (De Bono, 1985). It is a practical and systematic process for individual and team thinking, predominantly helpful in problem-solving, decision making, generating innovative solutions. The traditional method of thinking, also known as adversarial thinking, results in too many, too stretched, non-productive meetings which are dominated by ego and promote more status quo than bringing any change or innovation. On the other hand, the Six Thinking Hats method includes the fundamental elements of efficient thinking focusing on a specific virtual colour “hat,” thinking in one particular direction at a time instead of switching from one idea or thought to another. These thinking elements include the following:
Blue hat thinking: The Planner—managing and controlling thinking
White hat thinking: The Prober—focusing on the facts
Red hat thinking: The Partner—using intuition and feelings
Yellow hat thinking: The Provider—generating positive ideas
Black hat thinking: The Preventer—evaluating the risks and potential problems and
Green hat thinking: The Proposer—searching for solutions to overcome barriers
As a result, each person contributes his/her unique thinking on a particular challenge, resulting in a much better and impactful solution. When teams engage in Six Hats Thinking, they practise “parallel thinking,” thus speeding up the discussion, reducing meeting time by up to 50 per cent and increasing their productivity manifolds. This has been proven over the years by many top-ranked organizations operating in different sectors and located in different countries across the globe. A few to mention are as follows: IBM, Prudential, GM, BT (UK), NTT (Japan), Nokia (Finland), Mondadori (Italy), Total (France), Siemens (Germany), Bosch (Germany) and Ericsson (Sweden).
HR Analytics and Six Thinking Hats
Being a relatively new concept, HR analytics is more often poorly understood by organizations including its benefits and impact on business results. A Six Thinking Hats approach may enable HR professionals understand this better. Since this technique encourages the most pessimistic people to think of positive outcomes of a given situation, resulting in those who have not yet started with analytics to give a start and those who have started but are stuck midway because of lack of clarity, to get a boost to move ahead.
In order to have a Six Thinking Hat discussion with clarity, let us consider a hypothetical situation where the top management is quite disappointed with the business value of HR deliverables. After having a microscopic view of the situation, the head HR realizes that they are just doing descriptive analysis by presenting transactional measurements of HR functional tasks which lack analytical insight. For a collaborative discussion on the matter, he/she decides to experiment with the Six Thinking Hats approach on the role and relevance of HR analytics to the organization’s business value and the readiness of the organization for its implementation. So, let us put on different hats to examine if and how HR analytics is the solution.
Blue Hat Thinking: The Planner
Wearing a blue hat, the head of the HR team who acts as a facilitator opens the discussion, explaining the agenda. He/she expresses the desire to make a clear and convincing business case for the value that the HR function can deliver to achieve strategic objectives. Hence, he/she proposes implementing predictive analytics in HR and asks everyone to wear different hats and express their views.
The HR head decides the sequence of hats to be worn. Putting on the blue hat he/she opens the discussion with white (to present background information on HR analytics), followed by red (to gauge the feelings of the participants), yellow (to capture positive aspects of HR analytics), black (to study barriers and limitations of applying analytics), green (to develop new alternatives to overcome barriers), once again red (to assess the final views of participants) and finally, concluding the discussion with blue hat thinking. Accordingly, the different thinking approaches are mentioned below.
White Hat Thinking: The Prober
It attempts to answer few questions on the basis of facts and available information:
What is HR analytics and its role?
What are the required HR analytical capabilities in the organization?
What is the future of HR analytics or predictions of HR analytics?
HR analytics can be defined as
a methodology for understanding and evaluating the causal relationship between HR practices and organizational performance outcomes (such as customer satisfaction, sales or profit), and for providing legitimate and reliable foundations for human capital decisions for the purpose of influencing the business strategy and performance, by applying statistical techniques and experimental approaches based on metrics of efficiency, effectiveness and impact. (Boudreau & Ramstad, 2006; Lawler, Levenson, & Boudreau, 2004)
Seven types of collected data are used for carrying out HR analytics,
Workforce statistics, financial ratios relating to people and productivity, measures of people’s values; measures of people’s engagement, measures of efficiency of the HR function, measures of effectiveness of people processes and measures of investment in one-off initiatives and programs. (Mayo, 2006)
The success of any business depends on the level of expertise and skill of the workforce. Coolen and IJselstein (2015) introduced the HR analytics capability wheel and argued that “only those organizations that manage to create and maintain a balanced blend of different relevant capabilities will be successful in HR analytics.” These “relevant capabilities” were described as perspectives and include the business perspective (e.g., proper understanding of business challenges and strategy), the HR perspective (e.g., knowing about HR processes, available HR data and ethics of analyzing employee data), the consultant perspective (e.g., “selling HR analytics to business” and presenting results in a convincing manner), the data scientist perspective (e.g., conducting statistical analyses and also being able to work with more cutting edge development, such as machine learning algorithms), the IT architect perspective (e.g., understanding of the HR IT landscape and data warehousing) and the software perspective (e.g., in-depth knowledge of working with analytical software, depending on whether outsourced or conducted in-house). Organizations equipped with analytical capabilities have a great potential to generate better quality decisions by using advanced analytics.
In terms of the future potential and trends in HR analytics, it is predicted that
Companies will seriously focus more on data quality and its validity rather than data quantity.
Leaders at all levels will have HR data at their fingertips, to view, analyze and make decisions instantly.
Instead of individual analysts, analytics teams will take over the task to mine data, unearth patterns and provide high quality recommendations.
Thus, HR analytics will have a major influence on decision making in organizations and on the composition and role of HRM as a function. It can help to ensure lean and agile organizational structures that are based on an optimal combination of people characteristics and skills on the one hand and strategic business targets on the other hand. Thus, HR analytics may have the potential to transform organizational models.
Red Hat Thinking: The Partner
The red hat on HR analytics focuses on the emotions and feelings towards the HR analytics implementation of all those involved in the discussion.
The typical positive emotions associated with it are as follows:
People analytics sounds great.
Other companies are successfully using it, so it’s possible for us to do the same.
It has become very common; hence, getting proper guidance won’t be a problem.
It will supplement human efforts and not replace them.
HR decisions and also the judgments, are based on both proven metrics and intuition, hence a sense of elation.
The negative emotions might include the following:
A fear of the unknown.
HR analytics will take away jobs.
Implementing HR analytical model brings with it a big change making people feel insecure, anxious and nervous.
To meet new expectations of the analytics driven jobs, training will be required and hence demand more efforts by employees which may not be forthcoming.
Applying data in the right context is tricky and challenging.
Right way of looking at data requires lot of trial and errors and lot of patience to get the outcome.
HR analytics in business can be risky and dangerous if the models designed fall in wrong hands posing a security threat.
Implementing HR analytics will require a change in the business model and requires support from top management which may be quite difficult to secure, resulting in discouragement, demotivation and disappointment.
Yellow Hat: The Provider
The yellow hat thinking focuses on benefits of implementing HR analytics in an organization. The most alluring feature of data-driven decision making is the ability to predict trends and likely threats and opportunities. Trends and data will provide managers with the opportunity to make more informed and accurate decisions about what is likely to happen in the future. It will help them
Determine if existing approaches are working: Metrics allow HR executives to see if their existing programmes and tools are working. Analytics can also be used to assess the effectiveness of new talent programmes by having a microscopic view on the issues that may arise in future.
Identify hidden causes of problems: It’s difficult to improve weak-performing programmes without knowing the critical success factors that make them effective. By using forward-looking data analysis, HR can discover the latent root causes of HR problems.
Continuous improvement: The unearthing of suboptimal performance data can motivate leaders to realize that there is a scope for improvement, although on the surface, everything may appear to be running fine. Since data highlight process errors, proper use of data reports can notably reduce the number of major errors and weak decisions within the HR function.
Speed up talent decisions: By gathering and reporting data on best practices, companies may see more consistent and accurate workforce management decision making across the organization.
Opportunity to be strategic: By implementing analytics, HR can contribute to a large extent to the corporate business plan by forecasting, assessing risk and preparing for the future.
Justifying investments in human capital: Employee-focused investments will result in tangible outcomes which will benefit shareholders, customers and employees themselves and can also be quantified. Few specific areas where analytics can be applied are employee retention, employee engagement, talent acquisition and performance management.
Black Hat: The Preventer
Organizations are most likely to face tough challenges and barriers in the course of implementation of HR analytics programmes which may include
Lack of infrastructure: Poor infrastructure is a serious hindrance for scale and speed.
Insufficient and inappropriate data governance: Proper data governance ensures that people are using analytics as it is intended. The absence of this can result in chaos.
Lack of analytic capability: Scarcity of talent with analytical capability is a major barrier to success.
Cultural readiness: Knowledge for the sake of knowledge is meaningless unless it is put into action, resulting in a creative solution or output. The key here is to integrate analytics to decision making. This calls for organizations to have analytics-driven culture to leverage its power.
Fear of failure: If we overcome the fear of using analytics, HR analytics can truly be leveraged to deliver enhanced results contributing value to business performance.
Lack of skills: HR analytics demands certain specific skills in the employees such as domain knowledge, communication, presentation, inquisitiveness, problem solving, business analysis and pattern recognition. These skills are in short supply.
Security, privacy and confidentiality of data: HR analytics poses a serious risk of information being used in a destructive and damaging way.
Complexity: Various sources of truth (validity) of data, dirty data and poor legacy human resources information system in the organizations create complexity in implementing HR analytics.
Green Hat: The Proposer
Some of the solutions to address the barriers to implementing HR analytics are as follows:
Increase visibility of HR data: Creating a common view of all relevant workforce data to various internal stakeholders is the key to correctly aligning talent with the fluctuating needs of the business.
Improving analytical skills of HR function: Data literacy training can be incorporated in employee development programmes. A better strategy may be to hire people with analytical backgrounds in HR, rotating employees from line functions such as finance and marketing into HR, analytics to be part of every job descriptions and encouraging employees to apply analytics in their work by boldly experimenting with new ideas without fear of punitive actions resulting from failures.
Data security: HR professionals need to be trained regularly in data security, privacy and identity protection to ensure the maintenance of data privacy.
Frame the right questions: It is very important to frame proper business-centric questions.
Selecting the right tools for analytics: Look at the technology market for investing in self-service, customized data analytics tools.
Robust analytics infrastructure: The analytics infrastructure should be broad and deep enough to accommodate every important aspect of HR that impacts business outcomes, including absence rates, fraud, theft and customer satisfaction.
Social analytics: This can make the leaders aware and alert them in advance by providing warnings on the employees’ social activities which may be professionally objectionable. By monitoring blogposts of employees about company, we may gauge the trends from the social media and hence anticipate employee engagement scores and labour unrests and accordingly respond in time.
Understanding legal and ethical complexities of employee monitoring: HR analytics can offer critical insights to organizations to understand and predict ethics and compliance problems by developing a tool which can accurately forecast which employees are most at risk of committing ethical transgressions.
Conclusion
If used strategically, HR analytics is a powerful tool for organizations in optimizing their workforce decisions for best business results. Hence, HR and other departments need to have an understanding of the purpose and execution of workforce analytics. It is not only about using advanced techniques but also about reducing human bias and creating new insights. HR can successfully contribute as a strategic function by implementing analytics aptly. While this article explored the concept and contribution of HR analytics from the perspective of the Six Thinking Hats technique, future studies may examine how HR analytics can predict the economic value of human capital investments to demonstrate the impact of people on performance.