People Analytics Enabling HR Strategic Partnership: A Review

HR Strategic Partnership: What Does It Mean for the HRM Function to Be a Strategic Partner?

For decades now, academicians have been conceptualising and empirically establishing the role of HRM as a strategic partner. In a comprehensive meta-analytical work by Lengnick-Hall et al. (2009), some pertinent research themes which emerged from the reviewed literature on HR strategic partnership are internal alignment and integration of HR systems and subsystems, popularly known as contingency perspective; research relating to shifting of HR focus from managing people to strategic contribution; research seeking to expand the scope of strategy and HRM; research about achieving the execution of strategic HRM; research measuring and relating outcomes of strategic human resource to organisational performance; and finally research on evaluation of methodological issues about strategic HRM research. The latter is beyond the scope of this article; the remaining themes are briefly discussed below to arrive at an understanding of HR strategic partnership.

The contingency approach extends the idea that HRM practices need to fit with the organisation’s desired strategic outcomes and interests. In other words, this approach proposes that an effective HRM approach is contingent on the desired strategic outcomes of the organisation. Over the years, the concept of contingency in the domain of strategic HRM has seen an expansion. It started with a focus on alignment to the firm strategy (Baird & Meshoulam, 1988; Lengnick-Hall & Lengnick-Hall, 1988; Miles & Snow, 1984; Schuler & Jackson, 1987), and then emerged the idea of fit not just with the strategy but also with the external environment at large (Jackson & Schuler, 1995; Milliman et al., 1991). Latter entails legal, social and political environment, labour market conditions, industry features and national culture.

As the contingency perspective evolved, there was a growing realisation that this ‘fit’ between the strategy and HRM could render the system inflexible (Lengnick-Hall & Lengnick-Hall, 1988). Therefore, a more reciprocal relationship involving the role of human resources in both strategy formulation and implementation was emphasised. The proponents of this perspective view ‘fit’ as dynamic, as the organisation’s context and strategic priorities are constantly changing. Further, HRM is envisaged to actively influence strategy formulations, making the relationship bidirectional.

The second theme which emerged from the literature indicated a complete overhaul of expectations from the organisation’s HR function. If earlier it entailed maintenance and administration, today it involved accountability of human capital contribution, delivery of strategic capabilities and causal connection to the organisation’s competitive performance. Thus, a strategic partnership involves changing focus from mere people management to contributing towards strategic ends.

The third strategic partnership implies an expanded scope of the HR function which extends beyond the organisational boundaries (Boxall & Purcell, 2008; Colakoglu et al., 2006). This is reflected in Tsui’s (1987) ‘multiple constituency approach’, Gardner’s (2005) concept of ‘HR alliance’ and Lengnick-Hall and Lengnick-Hall’s (1999) inclusion of the customer in the domain of HRM.

Another critical theme in the literature on strategic HRM has been establishing causal links between HRM and the organisation’s strategic ends. This theme is evident in the ‘employee–customer profit chain’ (Rucci et al., 1998) or in the notion of ‘line of sight’ (Boswell, 2006). The line of sight entails making the connections between the function and corporate ends visible and comprehensible.

Measuring the impact of HRM has been a crucial theme in the HR strategic partnership realm. Becker et al. (2001) employed Kaplan and Norton’s (1996) balanced scorecard approach to HRM to link people, strategy and performance. Lawler et al. (2004) proposed that for human resources to play a role of strategic significance in the organisation, it would have to demonstrate how HR decisions affect business and vice versa. Lawler and Boudreau (2009) emphasised that information concerning the following three aspects needs to be furnished for the aforementioned reason: HR efficiency, HR effectiveness and impact of HR. In line with this research, considerable literature on HRM emphasises the need for scientific rigour in the field. Measurement embedded in robust frameworks gives the field credibility and foundation for effective strategic contributions through informational inputs and guideposts for strategy formulation and execution.

To summarise the research reviewed above, the following facets of strategic partnership have been discussed: the alignment and integration of human resources with its internal and external context and stakeholders; shift in focus towards meeting strategic ends from mere people management; scope of human resources widened to extend beyond organisational boundaries; demonstration of a causal link between human resources and organisational or strategic outcomes; and HR measurement as means to establish human resources’ credibility as a science. Lawler and Mohrman (2003) propose that human resources can have three kinds of roles as strategic partners. The three kinds include

That of strategy implementation, where the strategy has been formulated, HR aligns its practices to the same; Input and implementation role where HR plays an indirect role in strategy development by providing information or competitive intelligence on labor markets and helps in strategy implementation; and full partnership role which entails participating as the member of the strategic team that formulates policies. (Lawler & Mohrman, 2003)

Another analytical perspective to understand strategic partnership has been offered by Florkowski and Olivas-Luján (2016). The authors propose that being involved and possessing informational (through technology and data) and expert (knowledge and expertise on the part of HR professionals) power would ensure human resources’ influence on strategic decision-making.

Thus, research in the area points towards multiple yet interrelated facets of HR strategic partnership. The subsequent section briefly discusses the gaps in the field and how these make it fall short of its true potential as a strategic partner.

A Review of the Gap Between the Human Resources’ Grasp and Its Reach

A significant amount of research in the field has raised concern about how human resources as a function is falling short of realising its potential as a strategic partner. Human resources needs to align the services it offers inside the organisation with the expectations outside the organisation. From this perspective, every practice needs to be assessed based on the extent to which it creates value for various stakeholders. The multiple stakeholders include customers, employees—current and potential, investors, community, government and line managers. Ulrich and Dulebohn (2015) emphasise that the value that human resources creates needs to be aligned to the stakeholders’ expectations beyond the organisational boundaries.

Boudreau (2014) attributes human resources’ inability to realise its true potential to ‘stubborn traditionalism’, where stubborn traditionalism is this preoccupation with the administrative role and lack of flexibility in breaking this tradition to assume a more strategic role. Human resources’ inability to leverage its information power to advise and inform the decision-making of strategic significance is proving detrimental.

Boudreau further discusses that another major challenge faced by human resources as a profession is the lack of integration within the HR function. There has been a focus on new trends and practices such as employer branding, technology in human resources, use of big data in human resources and employing social media for talent acquisition, but these remain very much stand-alone initiatives. When it comes to an integrated response to broader issues such as globalisation, increasing uncertainty in the organisational environment, need for greater flexibility and leadership, human resources is rendered inadequate. The author expresses concern that this ‘contentment’ at the local level is the biggest threat to the profession.

Ascertaining and communicating causal links between human resources and strategic priorities and outcomes is another area where human resources is wanting (Boudreau, 2014). Lawler et al. (2004) suggested that measuring human resources’ impact on business would be necessary for human resources to become a strategic partner.

Cohen (2015) discusses the chasm between academic research and practice in the field of HRM. A more succinct explanation of theory and practice guiding each other is that ‘theory can inform practice; and practice needs to get better at laying out where they need stronger scientific underpinnings for designing HR practices’ (Vosburgh, 2017). For the field to achieve a status worthy of being a science and a credible practice, there has to be rigour, relevance and cumulative progress (Dipboye, 2007). Furthermore, the Society for Human Resource Management (2014) prescribes critical evaluation competencies coupled with business acumen as essential to the advancement of human resources as a field.

Based on the literature reviewed above, specific themes have been distilled. These indicate critical shortfalls in the field which demand address. Table 1 summarises the field’s challenges as it takes on a more vital and central role in business.

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Table 1.

Challenges Faced by Human Resources as It Emerges as a Strategic Partner

S. No.	Challenge	Explanation
1	Need for a more aligned human resources both vertically and horizontally; a refurbished outlook, from the inside/outside approach to the outside/inside approach.	An internally streamlined and integrated human resources is supporting the organisation’s strategy. Importantly, human resources creates value by ensuring that the ‘value that it creates inside the company aligns with expectations outside the company’ (Ulrich & Dulebohn, 2015).
2	Need for better integration with strategic planning.	Need for human resources to become integral to strategic planning in the organisation where human resources is involved in the planning and influences strategic decision-making.
3	Demonstration of a causal link between human resources and business performance.	This enables human resources to prioritise, ascertain and communicate its impact. More importantly, this enables human resources to furnish critical inputs for strategy formulation and implementation.
4	Human resources as a science.	The field is characterised by rigour, relevance and cumulative progress (Dipboye, 2007). Also, this theory and practice gap needs to be optimal so that both the aspects of the field benefit from each other. Theory ‘can inform practice; and practice needs to get better at laying out where they need stronger scientific underpinnings for the design of HR practices’ (Vosburgh, 2017, Deadrick & Gibson, 2007).

Source: The authors.

People Analytics: Advent and Promise

Like most HR concepts, multiple terms are used to connote what we term ‘people analytics’. Keywords used interchangeably for people analytics include HR analytics, human resource analytics, talent analytics, workforce analytics, human capital analytics and employee analytics (Tursunbayeva et al., 2018).

People analytics in its limited avatar, as the measurement of human resources/HRM, can be traced back to the early twentieth century (Marler & Boudreau, 2017). More recently, Jac Fitz-enz has been considered a forerunner in the domain of HRM measurement. His book entitled How to Measure Human Resources Management was published in 1984. His later work provides a comprehensive understanding of people analytics. In his article entitled ‘Predicting People: From Metrics to Analytics’, he described human capital analytics (HCA) as a ‘method of logical analysis that uses objective data as a basis for reasoning, discussion, or calculation’ (Jac Fitz-enz, 2009). Simple metrics, such as quantity, quality and timeliness, were seen as the starting point of HCA. The next level entailed the analysis of data to predict, steer and drive business outcomes.

The term ‘analytics’ began to be associated with HRM in the early twenty-first century. The term was first introduced in an article titled ‘HR Metrics and Analytics: Use and Impact’ by Lawler et al. in the year 2004 (Marler & Boudreau, 2017).

Lawler et al. (2004) demarked people analytics from HR metrics by emphasising that people analytics is essentially a decision-making process or an analysis process which could deploy HR metrics for requisite ends of people and organisation performance. Boudreau and Ramstad (2004) defined people analytics as not just the use of statistics and research design but also identification and articulation of meaningful questions, gathering and using appropriate data from within and outside the HR function, setting the appropriate standards for rigour and relevance, and enhancing the analytical competencies of human resources throughout the organisation.

Levenson (2005) suggested that although research and statistical tools have been used earlier, the essence lies in when and how to apply these tools. He also provided an evolutionary framework of people analytics to include frameworks focused on description (typical data-based activities, scorecards, dashboards and so on); predictive or behavioural modelling—available data is searched for patterns and causal links, which is then used for predicting future outcomes; and, finally, impact analysis which deals with assessing the impact of human resources on crucial organisational outcomes.

Davenport and Harris (2007) described talent analytics as the use of big data in the workplace so that the talent decisions are based on statistical data rather than instinct. Talent analytics entails the application of statistical techniques to improve the precision of talent management decisions. Davenport et al. (2010) noted that the range of talent analytics applications constitutes ‘from simplest Human Capital facts to the most sophisticated statistical applications that optimize Talent Supply Chain’.

Bassi al. (2011) emphasised that ‘People Analytics is about taking an evidence-based approach to making decisions on the people side of the business. It consists of an array of tools and techniques ranging from simple reporting of HR Metrics to predictive modeling.’ More comprehensively, the author views people analytics as a means to improve the quality of people-related decisions by employing integrated processes and logical frameworks. This is done to improve individual and organisational performance.

Burdon and Harpur (2014) discuss the evolution of people analytics. They define Analytics 1.0 as the 1950s analytics dealing with the use of information systems to facilitate the understanding of company processes and actions. Analytics 2.0 company analyses the data beyond internal company operations. Analytics 3.0 company records, collects and analyses everything about itself and its industrial environment. The latter also employs prescriptive analytics, which deploys models to prescribe the right behaviours after factoring in the numerous contingencies and multiple variables.

Another comprehensive definition of people analytics has been compiled by Marler and Boudreau (2017). They conceptualise people analytics as ‘an HR practice enabled by information technology that uses descriptive, visual and statistical analysis of data related to HR processes, human capital, organizational performance, and external economic benchmarks to establish business impact and enable data-driven decision making’ (Marler & Boudreau, 2017).

Gill (2018) underscores the need for evidence-based management in the HR domain. The author defines evidence-based Human Resource Management as the use of those HR practices that have demonstrated links to organizational performance. formal practices to manage human resources that evidence demonstrates are linked to organisational performance. Her key argument is that if the practice is rooted in evidence/research, the impact would be more effective.

To summarise the research on the conceptualisation of people analytics, first, people analytics encapsulates a systematic and logical approach to carry out the function of HRM as against a largely intuitive approach; second, people analytics starts with raising relevant questions/defining decision opportunities and framing problems, followed by the use of research design, metrics and statistical tools in the service of these decisions and problems; third, people analytics relies on data—integral to the people analytics approach is the use of data, both qualitative and quantitative; fourth, an evolved people analytics ensures alignment and integration within human resources, of human resources with the organisation and consequently of human resources with the environment, which is achieved by gathering data from functions beyond human resources from the organisation’s larger context; and fifth, people analytics aims to equip human resources with effective HR decisions translating into robust HR performance, eventually leading to organisational performance.

The next section sheds light on the objective of this study and the research question that this study seeks to address.

People Analytics Enables HR Strategic Partnership by Aligning the HRM Function

HRM attains the status of a strategic partner only if its own house is in order. Alignment within the function, commonly known as horizontal alignment, entails all the HR sub-functions streamlined in a manner where they do not act on cross purposes and cater to the same goal (Baird & Meshoulam, 1988). Alignment for any system starts with its subsystems, which together need to be in line with the strategic inclinations and interests of the organisation. Latter is termed ‘vertical alignment’ (Schuler & Jackson, 1987). As discussed in the section above, human resources needs to be responsive to the context beyond the organisational boundaries (Lawler & Boudreau, 2009; Lawler & Mohrman, 2003; Ulrich & Dulebohn, 2015). The following statement illustrates the aforementioned: ‘We want to be the employer of choice to the employees our customers will choose’ (Ulrich & Dulebohn, 2015). The application of analytics to people management facilitates greater alignment of the HR function horizontally and vertically.

HR analytics has helped in streamlining the HR function. Harris et al. (2011) have documented the role people analytics has played in streamlining the recruitment function at Google. Google leveraged the tremendous amount of data available regarding employee attitude, behaviour, personality, biographical information, job performance and so on. The same data was collected from the job applicants. Algorithms based on the best predictors of job success in a role were then used to assess the new candidates. A score indicating their likelihood of success on the job/in the role was calculated. This score then became the basis for the hiring decision. Analytics has enabled the organisation to invest its time and energy in candidates who demonstrate high potential for the role, based on the predictors of success derived from the data specific to the organisation. More importantly, this efficient algorithm-based approach aligns the talent processes to the organisation’s growth needs by saving time and ensuring that the right talent does not slip through the cracks in the system. Ghosh and Basu (2020) discuss that a misaligned talent acquisition process in a highly competitive industry such as IT has severe implications in terms of quality of deliverables, high recruitment expenses and loss of revenue for the organisation. Authors employ a data-centric and analytics-based approach to examine the critical determinant of a streamlined talent acquisition process. The study was carried out in the Indian IT context. The following parameters emerged as the critical basis for assessing talent strategies—expected cost to the company, candidate sourcing channels and optimal joining period. Aral et al. (2012) found that companies which deployed people analytics in conjunction with performance-based compensation and software-enabled human capital management were more productive because these technologies enabled managers to streamline incentives and encourage desirable employee behaviour. McAbee et al. (2017) have discussed how predictive analytics and data mining techniques could be employed to explore the relative importance of the individual (knowledge, skills, abilities and other attributes), contextual (environmental conditions, workforce trends and so on) and organisational (goals, values and so on) factors to predict the need and success of the developmental initiatives.

People analytics has helped the HR function to align with the organisation’s strategic ends. An illustration by Harris et al. (2011) demonstrates better vertical alignment through people analytics. Convergys, an organisation which manages billing, payroll, pension and benefits of organisations across 40 countries, leveraged people analytics to align its human resources to changing business needs. Subsequent to the firm’s initial public offering in 1999, the need for a trained workforce went drastically up amid a very high turnover. The organisation employed predictive analytics to identify a mix of benefits which would help retain employees. As a result, they came out with customised benefits for the segments of employees situated in different locations. Interestingly, giving a partial salary increase bi-annually as against a complete salary hike annually positively impacted retention. According to a report published by the IBM Institute of Business Value (Fern et al., 2014), people analytics enables the HR function to serve an organisation’s strategic ends by aligning it in multiple ways. This study sampled employees with workforce analytics responsibility in around 41 firms across Europe, North America and the Asia-Pacific. These firms were from across industries. It was found that people analytics aligned the HR function to a myriad of business issues, including increasing sales, cost optimisation, encouraging innovation, transformation of the business model and enriching customer experience. People analytics helped achieve these ends by providing greater access to data and information, assisting them to achieve more transparency and more significant insights, and facilitating judicious resource utilisation. Escolar-Jimenez et al. (2019) highlight the role played by artificial intelligence in aligning talent decisions to organisational performance. They have proposed a compensation algorithm which helps in aligning the firm’s compensation and performance systems with the organisational objectives. This algorithm factors organisational policies and philosophies and ensures minimal scope for biases and irregularities. Cotes and Ugarte (2021) demonstrate and propose a framework which employs people analytics to align the training need analysis process and machinery in an international bank to its strategic goals.

Van der Togt and Rasmussen (2017) demonstrate how effective implementation of people analytics results in effective utilisation of human resources, which has significant implications for not-for-profit set-ups with minimal resources at their disposal. A similar prescription is made by Sharma and Bhatnagar (2017). They propose that talent analytics leads to strategic talent management outcomes such as consistent talent supply, talent engagement and talent retention. This further leads to business performance. Giermindl et al. (2021) emphasise that greater digitisation and people analytics optimise HR practices. However, they do express concern regarding the application of efficiency-driven logic to human beings. They find this approach precarious with the peril increasing with the analytical power of people analytics. Srivastava and Eachempati (2021) find deep neural networks to be robust predictors of churn in the organisation. McIver et al. (2018) demonstrate through a case study on Foot Locker retail organisation that how the application of people analytics translates into better hiring, reduced turnover, more employee selling time, double-digit increase in productivity, increased customer satisfaction and a significant increase in in-store sales. Sivathanu and Pillai (2020) employed a grounded theory approach to ascertain the role of people analytics in aligning HR systems. This study based in India sampled both national and international organisations and concluded that people analytics helped create high-performance work systems. These systems were further found to impact organisational performance positively. Vargas et al. (2018) found a prevalence of people analytics among high-performance work systems.

Ellmer and Riechel (2021) demonstrates how people analytics helps in more significant linkages and better alignment with the external environment. The author identified boundary spanning, customised dashboards and speaking a language of data and numbers as helping human resources align with the decision-maker’s perception of the business realities. Boundary spanning refers to linking internal knowledge on an issue with sources of information external to the organisation. For example, big data generated about customers, employees and competitors (sourced from social media) could be a rich source of external information. Customised dashboards refer to dashboards being flexible enough to accommodate customisation of analytical output to the decision needs of the Board. Speaking a language of numbers helps human resources correspond with the surrounding data-driven culture. Incorporating financial information into the analytics outcomes could help human resources get the attention of the Board.

In conclusion, the research reviewed above sheds light on the literature emphasising the role of people analytics in aligning human resources as a function. As discussed, this alignment entails streamlining HR sub-functions, aligning HR function/sub-functions with the strategic interests of the organisation and with the expectations beyond the organisational boundaries (Aral et al., 2012; Harris et al., 2011; Levenson, 2018; McAbee et al., 2017; McIver et al., 2018). Further, people analytics permits optimisation of the function (Fern et al., 2014; Giermindl et al., 2021; Ghosh & Basu, 2020; Van der Togt & Rasmussen, 2017) and aids human resources in aligning with the decision-makers’ perception of the business realities (Ellmer & Reichel, 2021; Fern et al., 2014). Levenson’s (2018) idea of diagnostic analytics is a great mechanism to achieve the alignment discussed above. He proposed that traditional workforce analytics be preceded by two diagnostic analytics: competitive advantage analytics and enterprise-related analytics. The former ensures that any group or individual-level analytics aligns with the specific business challenges. It also ensures that the business challenges are prioritised based on their relative value assessment. The enterprise-level analytics ensure that the organisation is viewed as a system focusing on its components in their entirety. Levenson (2018) cites the case of the merger between TD Bank and Canada Trust in 2001 to illustrate the significance of what he calls diagnostic analytics. Given the regulatory and competitive landscape, the competitive advantage analytics revealed that customer retention was imperative for the merger to succeed. Customer retention was explicated as more customers joining than leaving at any given period. Enterprise-level analytics revealed that to cater to customer retention, the culture of the acquired entity, Canada Trust, had to be retained. These inputs from the diagnostic analytics further channelised workforce analytics towards identifying the leadership competencies for the desired culture facilitating customer retention. The outcome of these analytics incarnated in the decision to have leaders from the acquired entity at some key leadership positions of the merged entity. The case demonstrated how the analytics at multiple levels could be leveraged to ensure vertical alignment of the HR function.

Thus, in the light of the reviewed literature, the following propositions have been presented for further empirical enquiry.

Proposition 1: People analytics enables HR strategic partnership through greater alignment of the HRM function.

People Analytics Enables HR Strategic Partnership by Integrating HRM with Strategic Planning

An aligned HR function is a necessary condition for HR strategic partnership. However, it is insufficient to ensure that human resources gets a seat ‘at the table’. Levenson (2011) has expressed concern that though there is no shortage of talent analytics applications, analytics finds lesser application to decisions which are likely to impact the most.

People Analytics Enables HR Strategic Partnership Through Demonstration of Causal Links Between HRM and Business Performance

The twenty-first century has underscored a need for a shift from practices and programmes towards supporting strategic talent decisions. Any human capital measurement system is envisioned to enhance decisions by explaining the logical relations between talent and desired organisational ends. Boudreau and Ramstad (2006) suggest that this focus on measurement is necessary for developing HRM as a decision science. However, these measurements need to be embedded in logical frameworks which spell out the linkages between talent decisions and an organisation’s strategic success to be of any value to the organisation. DiBernardino (2011) expressed a need for human resources to move beyond efficiency measures to effectiveness measures. Measuring critical strategic outcomes and providing a clear line of sight between human capital performance and business performance will bring human resources on the same page with the finance and strategy teams, speaking the same language and collaborating as true strategic partners. Lawler and Boudreau (2015), in an empirical study involving 416 HR leaders, concluded that the use and effectiveness of talent measures were significantly related to a stronger strategic role.

Coco et al. (2011) documented a case study illustrating the application of people analytics to demonstrate a causal connection between HR initiatives and business outcomes. They discussed how a home improvement retail chain, Lowe’s, used people analytics to establish a link between HR processes, employee engagement and store performance. As a result, people analytics helped demonstrate that highly engaged employees achieved higher average customer ticket sales per store.

Harris et al. (2011) discuss a case study of Sysco Corporation. The organisation deals with the marketing and delivery of food services to myriad institutions. Three metrics were devised and monitored across the Board: organisation climate and employee satisfaction, productivity, and retention. These metrics were monitored for years, and then causal links were demonstrated between effective talent management practices and business outcomes. The analysis revealed that organisations with satisfied employees have higher revenues, lower costs, higher customer loyalty and better retention. This causal link enabled the organisation to prioritise and manage employee satisfaction and thereby impact strategically critical outcomes.

Hamilton and Sodeman (2020) emphasise that the advent of big data has been transformative for many domains. Similar applications should be exercised for HRM as well. As per the authors, human resources should use big data to capture the strategic linkage between the human capital that the organisation possesses and its profitability. They recommend people analytics to be applied to assess human resources’ contribution to the skill and knowledge of the employees and relate the same to some measure of overall firm performance resulting from competitive advantage driven by enhanced employee knowledge and skill.

Larsson and Edwards (2021) assert that human resources still has a very long way to go when it comes to establishing a causal link between HR investment and organisational performance. According to the authors, people analytics could be helpful in this strategic endeavour. They recommend a combination of the business impact perspective of people analytics with insider econometrics (an approach that provides empirical estimates of the value of HR practices and is used in personnel economics) to aid the research exploring the link between HR investment and organisational performance.

Although these causal chains and linking models are very informative and compelling, these do run a risk of oversimplifying rather complex relationships and value chains. Nonetheless, based on the research reviewed on the strategic role of HRM, one cannot overemphasise the significance of the demonstration of causal links between HRM and business outcomes. Demonstration of these links does not only help in proving, ascertaining and justifying HR existence or contributions, but as discussed in the sections above, these also enable evidence-based practice and aid strategy formulation and implementation. People analytics is believed to go a long way in establishing and demonstrating these causal links with critical organisational outcomes (Cheng, 2017; Saraswathy et al., 2017). Thus, it would be meaningful to examine this claim’s efficacy empirically.

Proposition 3: People analytics enables HR strategic partnership by demonstrating a causal link between HRM and business outcomes.

People Analytics Enables HR Strategic Partnership Through Increased HRM Credibility

Boudreau and Ramstad (2003) emphasised that to be competitive, organisations compete in three markets: capital market, product market and HR /talent market. Except for the talent or HR market, the other markets have well-developed decision science. The future of HRM as a field will require a decision science that is ‘logical, reliable, consistent’ yet affords flexible frameworks, enhancing decisions about a critical resource; in this case, the resource is talent. As per the authors, people issues have been ‘at the table’ in the knowledge economy. However, being ‘at the table’ entails answering challenging questions from shareholders, investment analysts, communities, and present and prospective employees. Lawler et al. (2004) emphasised that applying analytics to ascertain the impact of HR practices and policies on critical organisational outcomes is a powerful way for the HR function to add value to the organisation. Mondore et al. (2011) endorse that impact quantification on the bottom line and top line is made possible through people analytics. Shrivastava et al. (2018) have used a case study to discuss the role of people analytics in quantifying HR activities and bringing transparency to HR processes.

Ulrich and Dulebohn (2015) propose that people analytics enables rigorous HR investments and outcomes tracking, thus enabling human resources to prioritise, justify and improve. Therefore, analytics holds the potential to enhance the credibility of human resources as a function. Metrics improve professional respectability and render rigour to the decision-making process. People analytics can be leveraged to measure HR activities such as communication, people, work and performance; intermediate outcomes such as individual competencies, organisational capability and leadership quality; and ultimate business outcomes such as financial earnings and shareholder values, customer commitment and so on. Patre (2016) notes that human resources has struggled to establish its credibility and value in the eyes of key stakeholders, be it the top management or the line managers. The author attributes this deficiency to the inability of human resources to present data-driven and business-oriented proposals. The author uses the six thinking hats approach to illustrate the relevance of people analytics.

As per Snell (2011), facts and figures are the language permissible in the boardroom. Without a data-backed causal linkage between effective people strategies and business performance, human resources is always at the risk of being underappreciated. Uen et al. (2012) revealed that rigorous and consistent HR services increased the prospect of strategic participation for human resources. Amalou-Döpke and Süß (2014) have proposed a striking framework to convey the instrumental role HR measurement plays in power dynamics in organisations. The management of any organisation enjoys formal legitimate power given its position, and therefore it has a great deal of control over critical entrepreneurial resources and decision-making. The other player in this power equation—the HR department—enjoys power based on the information and expertise on the critical organisational resource called human capital. This relationship is highly impacted by the HR department’s skill at measurement. Without robust scientific measurement, human resources will not be able to provide information to the management in a form understandable and actionable for decision-making purposes. Thus, measurement contributes to the professionalisation of the field and increases the perceived legitimacy in the organisation. King (2017) has illustrated how quantification and quantitative tools positively influence management.

Lawler et al. (2011) demonstrated that HR leaders who emphasised numbers experienced more significant gains in power and effectiveness of their HR function. Suryanarayana (2015) emphasises that lately, there has been increasing pressure on managers to justify their investments and defend their plans in measurable terms. The author proposes this using data, facts, analytics, scientific rigour and critical evaluation to support HRM proposals, decisions, practices and conclusions. A case is made for the need for evidence-based decision-making in human resources.

Barends et al. (2014) define evidence-based practice as ‘making decisions through the conscientious, explicit and judicious use of the best available evidence and multiple sources by asking, acquiring, appraising, aggregating, applying, and assessing to increase the likelihood of a favorable outcome’. A survey carried out by the authors which sampled 950 American practitioners showed significant discrepancies between what practitioners thought was effective and what scientific research ascertained as effective. Similar results were found in the studies conducted in other national contexts. Vosburgh (2017) indicated that people analytics could go a long way in bridging this gap between the practitioner and academician. The use of analytics aids in making practice robust and rigorous, and it makes academics much more receptive to practice.

Boudreau (2014) has presented a very interesting prescription. This overarching recommendation proposes that human resources develops mental models and cognitive frameworks which shape how people approach and solve business problems. These should then become the basis for all standardised measures. These should inform the leadership across the organisation concerning any human capital and strategy-related decisions. Measures without appropriate mental models would at best be ineffective and at worst be disastrous. Suitable mental models and standardised measures will bring more consistency and, therefore, greater credibility to the field. The beauty of these frameworks would be enabling human resources to have a shared language to transact across silos.

The application of people analytics has a long way to go, even though it renders credibility to the field. Wawer and Muryjas (2017), in a study based in Poland, conclude that although 50% of mid-high-level managers do not use people analytics, the ability to assess and measure business processes and people activities is key to determining organisational performance. Van der Laken et al. (2017) provided an extensive toolbox for HRM to increase the scope of HR research as it calls for more multi-level and longitudinal complexities. General linear models for measuring the impact of HR decisions might not be adequate or justified. Minbaeva (2018) shed light on human resources’ inability to move from operational reporting to HCA. The author attributes this inability to the lack of capability on the part of human resources to establish a credible HCA machinery within the organisation. It is recommended that human resources work at three levels—individual, process and structure—along the three dimensions of data quality, analytics capability and strategic ability to act.

Thus, a well-established people analytics machinery bequeaths human resources with credibility and confidence to take on the role of a strategic partner.

Proposition 4: People analytics enables HR strategic partnership by enhancing the credibility of the HRM function.

Table 2 summarises the research on why and how people analytics enables HR strategic partnership. Based on the review of the identified literature, the following themes have emerged that shed light on people analytics’ role in facilitating this partnership. First, the information generated through people analytics ensures horizontal, vertical and contextual alignment of the HR function. Second, the application of people analytics helps integrate HRM with the organisation’s strategic planning process by furnishing insight and foresight which is integral to the strategic planning process. It also aids in the identification and development of strategic talent pools. People analytics exhibits considerable promise in helping organisations accomplish their strategic goals of an inclusive workforce and a robust employer brand. Third, people analytics makes it possible to demonstrate causal links between HRM and critical organisational outcomes. This validates and reinforces management commitment to the function. Fourth, people analytics provides the field with scientific rigour and consistency, leading to enhanced credibility of the function. Table 3 summarises the outcome variables which have been either studied empirically or theorised in the literature with respect to people analytics.

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Table 2.

Summary of Reviewed Research on People Analytics and Its Role in HR Strategic Partnership.

S. No.	Challenge	Role of People Analytics	Key Reviewed Research	Propositions for Empirical Enquiry
1	Need for a more aligned human resources both vertically and horizontally; a refurbished outlook, from inside/outside approach to outside/inside approach.	People analytics aligns HR sub-functions, human resources with the organisation’s strategic interests and expectations beyond the organisational boundaries; people analytics permits optimisation of the function and aids human resources to align with the decision-makers perception of the business realities.	Harris et al. (2011) Aral et al. (2012) Fern et al. (2014) Van der Togt and Rasmussen (2017) Sharma and Bhatnagar (2017) McAbee et al. (2017) McIver et al. (2018) Levenson (2018) Escolar-Jimenez et al. (2019) Ghosh and Basu (2020) Sivathanu and Pillai (2020) Ellmer and Reichel (2021) Cotes and Ugarte (2021) Giermindl et al. (2021)	Proposition 1: People analytics enables HR strategic partnership through greater alignment of the HRM function. Proposition 1a: People analytics enables HR strategic partnership through greater vertical alignment.Proposition 1b: People analytics enables HR strategic partnership through greater horizontal alignment.Proposition 1c. People analytics enables HR strategic partnership through greater alignment with external stakeholder expectations.
2	Need for better integration with strategic planning.	People analytics integrates talent decisions with business strategy; holds potential for business opportunity identification; enables organisations to achieve strategic goals such as workforce inclusivity or diversity management; and makes it possible for the organisation to identify and capitalise on strategic talent.	Harris et al. (2011) Aral et al. (2012) Fern et al. (2014) Van der Togt and Rasmussen (2017) Sharma and Bhatnagar (2017) McAbee et al. (2017) McIver et al. (2018) Levenson (2018) Escolar-Jimenez et al. (2019) Ghosh and Basu (2020) Sivathanu and Pillai (2020) Ellmer and Reichel (2021) Cotes and Ugarte (2021) Giermindl et al. (2021) Levenson (2011) Boudreau and Ramstad (2004) Cappelli (2011) Harris et al. (2011) Mondore et al. (2011) Dulebohn and Johnson (2013) Varshney et al. (2014) Schiemann et al. (2017) Stoian and Tohanean (2020) Mitchell et al. (2021) Bhatnagar (2007) Al-Ayed (2019) Liu et al. (2020) Minbaeva (2021) Boudreau and Ramstad (2004) Wang and Cotton (2018) Hamilton and Sodeman (2020) Wassell and Bouchard (2020) Boudreau (2014) Buttner and Tullar (2018) Kashive et al. (2020)	Proposition 2: People analytics enables HR strategic partnership through better HR integration with strategic planning.
3	Demonstration of a causal link between human resources and business performance.	People analytics helps reveal cause–effect relations to determine HR efficiency, effectiveness and impact on ultimate business results (financial, customer and other stakeholders).	Boudreau and Ramstad (2004) DiBernardino (2011) Coco et al. (2011) Harris et al. (2011) Lawler and Boudreau (2015) Hamilton and Sodeman (2020) Larsson and Edwards (2021) Cheng et al. (2017) Saraswathy et al. (2017)	Proposition 3: People analytics enables HR strategic partnership by demonstrating the link between HRM and business performance/outcomes.
4	Human resources as a science.	HRM, where decisions are based on insights drawn from data analysis using scientific techniques, becomes credible in the scientific sense of the term. ‘People Analytics includes statistics and research design, but it goes beyond them to include identifying and articulating meaningful questions, gathering and using appropriate data from within and outside the HR function, setting the appropriate standards for rigor and relevance, and enhancing the analytical competencies of HR throughout the organization’ (Levenson, 2005).	Boudreau and Ramstad (2003) Lawler et al. (2004) Snell (2011) Barends et al. (2014) Amalou-Döpke and Süß (2014) Lawler et al. (2011) Boudreau (2014) Ulrich and Dulebohn (2015) Suryanarayana (2015) Patre (2016) Wawer and Muryjas (2017) Van der Laken et al. (2017) Minbaeva (2018) Shrivastava et al. (2018)	Proposition 4: People analytics enables HR strategic partnership by enhancing the credibility of the HRM function.

Source: The authors.

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Table 3.

Summary of the Outcome Variables Studied in Relation to People Analytics

S. No.	Variable	Author
1	Job–person fit	Harris et al. (2011)
2	Process efficiency/optimisation/efficient talent acquisition process and strategies	Giermindl et al. (2021), Ghosh and Basu (2020), Cappelli (2011), Harris et al. (2011), Van der Togt and Rasmussen (2017), Levenson (2018)
3	Optimised work units	Schiemann et al. (2017)
4	Employee/talent retention	Ghosh and Basu (2020), Sharma and Bhatnagar (2017)
5	Employee productivity	Aral et al. (2012), McIver et al. (2018)
6	Employee engagement and satisfaction	Harris et al. (2011)
7	Increased sales	McIver et al. (2018), Fern et al. (2014)
8	Enhanced customer experience	McIver et al. (2018), Levenson (2018)
9	Encouraging innovation/business model transformation	Stoian and Tohanean (2020), Fern et al. (2014)
10	Talent engagement	Sharma and Bhatnagar (2017)
11	Talent supply chain	Harris et al. (2011), Sharma and Bhatnagar (2017)
12	Identification of developmental needs	Cotes and Ugarte (2021), McAbee et al. (2017)
13	Assessment of developmental initiative	McAbee et al. (2017)
14	High-performance work systems	Sivathanu and Pillai (2020), Vargas et al. (2018)
15	Boundary spanning and knowledge beyond boundaries	Ellmer and Reichel (2021)
16	Systematising complex decisions through algorithms	Escolar-Jimenez et al. (2019), Varshney et al. (2014), Aral et al. (2012)
17	Inputs for strategic decision-making	Dulebohn and Johnson (2013), Minbaeva (2021)
18	Competitively differentiating organisational capabilities	Stoian and Tohanean (2020)
19	Organisational learning	Bhatnagar (2007)
20	Organisational resilience	Al-Ayed (2019)
21	Managerial decision-making	Liu et al. (2020)
22	Team performance	Wang and Cotton (2018)
23	Competitive advantage emanating from strategic HR practices/strategic talent identification and development	Hamilton and Sodeman (2020), Wassell and Bouchard (2020)
24	Creation of inclusive workforce	Buttner and Tullar (2018)
25	Informational power to HR function	Patre (2016), Amalou-Döpke and Süß (2014), Varshney et al. (2014)
26	Employee value proposition	Kashive et al. (2020)
27	Agile development	McIver et al. (2018)

Source: The authors.