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Employee performance management has long been regarded as a key player in the territory of talent development and organizational excellence. However, in our modern world, one characterized by relentless digital transformation, the way we approach employee performance management is undergoing a profound shift. The infusion of technology into this pivotal aspect of human resources has ushered in a new era filled with opportunities and challenges alike. This article aims to examine the future of employee performance management, underscoring the imperative to strike a harmonious balance between technology-driven solutions and a resolute human-centered approach. Over the course of this discussion, we will explore three central themes that encapsulate the evolution of performance management in our digital age.
Technology’s vital role in employee performance management
In the current era defined by digitization, technology is a crucial partner to optimize the performance management processes. It is obvious that the arrival of artificial intelligence (AI) has changed the business environment. AI tools offer immediate performance tracking, data analysis, and the ability to provide real-time insights—which were previously not visible. For example, machine learning (ML) procedures can discover complex trends within employee performance data, which supports management to take proactive actions that are designed to improve productivity and enhance job satisfaction. Moreover, cloud-based platforms have made performance evaluations more accessible, facilitating the maintenance of consistent and efficient performance management practices, particularly for geographically spread teams and organizations.
Technology’s role in performance management extends beyond the scope of data sifting. It also encompasses the streamlining of administrative tasks, which fosters transparent communication channels, and the accessibility of performance data. Ultimately, this results in a shift towards more agile and approachable performance management processes. Keeping in mind that technology assists in automating routine tasks, HR professionals will be able to allocate more time and resources towards the all-important human elements of performance management, such as coaching and mentorship. In essence, technology is the engine that drives employee performance management into the digital age, allowing organizations to harness the full spectrum of new opportunities that come with it.
Maintaining a human-centered approach
While technology assumes a pivotal role, it is paramount to recognize that it should serve as an enabler and not a replacement of the human element in employee performance management. Employee engagement and motivation remain deeply rooted in personal interactions and the provision of constructive feedback. HR professionals must thus prioritize these core aspects, leveraging technology to facilitate, rather than displace, these crucial facets of the employee performance management process.
In a world increasingly characterized by virtual communication and remote work, the importance of face-to-face interactions cannot be overstated. Employees derive immense value from the opportunity to engage with their managers and colleagues in real-time. Constructive feedback, delivered through personalized conversations, holds the potential to drive substantial performance improvements. A technological revolution should not signify the obsolescence of these personal connections but should instead facilitate their continuation in unique ways.
Mentorship and coaching, too, remain essentially human activities. While AI can provide valuable insights, there is no substitute for the guidance and wisdom that experienced professionals can convey to their peers. Employee performance management should encompass these essential human elements, leveraging technology to create an environment where mentorship and coaching thrive alongside data-driven insights.
Transparency and fairness through data
When leveraging technology, organizations can establish objective performance benchmarks and metrics that reduce the influence of biases in evaluations. These data-driven insights serve as a foundation upon which fair and consistent decisions can be made regarding promotions, compensation, and developmental opportunities.
Moreover, the utilization of technology allows organizations to share performance data with employees, which fosters a culture of transparency, accountability, and self-improvement. Once employees understand the criteria by which they are evaluated and witness the fairness with which these evaluations are conducted, it creates a more productive workplace.
However, organizations should exercise caution when using data, especially where ethical considerations are involved, such as protecting employee privacy and ensuring the responsible handling of sensitive data. Moreover, they must also avoid the pitfalls of algorithmic bias, making it a priority to continue assessing and fine tuning their algorithms to mitigate unfairness.
The right equilibrium
The synergy between technology and human expertise will not only drive individual and organizational performance, but also ensure fairness, transparency, and employee satisfaction. By navigating this growing model, organizations that strike the right equilibrium between technology and humanity will not just adapt but thrive in the digital age. The future of employee performance management should be an appropriate balance of technology and humanity—a path that leads to greater prosperity and progress for individuals and organizations alike.
This article is written by Chadia Abou Ghazale, a seasoned banking professional with 24 years of experience and who excels in budgeting, sales performance management, data analysis, and resource planning. Beyond banking, she is a dedicated reader of self-development topics and passionate networker. Chadia believes that life’s purpose is the pursuit of knowledge. Her extensive expertise and unwavering enthusiasm are a dynamic combination, driving success in her career and enriching her life’s adventurous journey.
When used effectively, data can bring valuable improvements in all areas, including Human Resources (HR). Hugely relevant data is to be found in the area of human capital and is usually collected and managed by the HR department in your company. In essence, all organizations seek to keep top performers while reducing the number of low performers as much as possible. The first thing that comes to mind when discussing measurement in the HR area is the Turnover Rate.
Turnover Rate is a common organizational measurement that tracks the loss of talent in the workforce over time, and it may also be used to gauge an organization’s culture. Employee turnover encompasses resignations, layoffs, terminations, retirements, relocation transfers, and even deaths. Businesses frequently measure their employee turnover rate to estimate its impact on production, customer service, and even morale. Turnover is frequently referenced negatively, owing to its high expense of replacing personnel; however, it is a natural part of the employee life cycle and organizational renewal.
Now, how can data be used for maximum insight from employee turnover?
- Gather internal HR data.
Preparing the data is always the first step. If your organization has an HR Information System (HRIS), you should be able to simply get the data and elicit the desired reports from combining different available metrics. However, if your organization does not have an HRIS, the HR department should be able to provide relevant data that can be analyzed.
The turnover data you require is the headcount of the organization, as well as the record of persons who have departed the organization: employee name, date of departure, and position should all be included in the record. If you can gather supplementary information, such as the reason for leaving, the direct manager, and so on, it will help to improve the depth of analysis.
- Document and organize the data properly.
After obtaining the turnover data, it is advised that you set up a separate storage folder for this data. It should be well-documented, including periodic details (e.g. for the year 2021). With a well-structured document system, you will be able to access it and even repeat the procedure for the next period.
- Run the analysis of data at various levels of granularity.
This stage is dependent on the data you have available as well as your objective. The number of separations and headcount are the most vital components in calculating the Turnover Rate. The number of departures divided by the average employee headcount is a typical formula for calculating the turnover rate.
If your data is much more detailed, you can perform a more granular analysis, such as turnover by month and structure. This allows you to gain more specific insight rather than an overall view of the organization. Another example of granular analysis is examining the number of separations and visualizing it by using Structure. The graph will tell you whether there is a certain Structure that needs extra attention; you can also try by Manager, by age, and so on.
This is only a rough idea of how you might use your own internal data to enhance your organization’s retention and engagement. The possibilities for expanding the turnover analysis are limitless. A genuinely effective, high-value data initiative, on the other hand, requires a comprehension of data dynamics as well as how to apply today’s best practices to carefully utilize and assess data.
The last decade has brought a lot of changes to what is expected from the Human Resources function and an accelerated evolution to what is called the “new generation” HR. Few companies today remain unaware that HR can no longer exist as a support function and even the much-cited “earning a seat at the (executive) table” is getting history, as it becomes clearer every day that excellent HR is more about “owning” that table.
Both HR professionals and business leaders need to understand that HR is about a set of results, not about HR. What the business requires from HR is to build a set of integrated solutions, move away from the traditional role of executing HR processes, and use these processes and solutions to accelerate business and create a competitive advantage.
To achieve this shift from activities to business-relevant outcomes and create a more agile organization in the process, the HR organization needs to:
Getting data-driven starts with getting data ready. With an enlarged focus on driving higher productivity, as well as engagement, the HR new function must look beyond basic employee metrics to harness nuanced insights on individual working preferences, career goals, and turnover risk. With latent talent shortages and highly dynamic markets, the HR organization must also focus on continuous reconfiguration to stay current with the marketplace.
In the HR professional’s new role, business literacy and quantitative acumen will become even more important. They will need to collaborate closer and more frequently with Operations and Finance peers, interpret the HR data analytics side-by-side with data from these groups, and contribute with data-driven insights. A data-driven HR function that can make fact-based decisions, predict workforce trends, and flag areas of concern is critical to creating a people-first organization that aligns with employee needs. Thus become not only another stakeholder at “the table”, but provide leaders that are key strategists and decision-makers in a world of work that truly demands their knowledge and insights.
- encourage new ways of working,
- learn to collaborate cross-functionally and respond faster to changing business priorities,
- tap the potential of new technologies and
- leverage advanced data analytics to give relevant insight and inform business decisions.
What is the problem then?
The people analytics revolution has been discussed for a decade now, expecting it to bring us in a new era for HR. But so far, the revolution is for an elite few, not for the masses. Too many companies say they still need help with putting basic people analytics into practice while too many HR departments are still stuck struggling with the basics.
The most cited reasons for this situation include:
Hopefully, this is about to change as 73% of companies declare that improving people analytics will be a major priority for the next five years. Some changes are already in sight, including:
- HR has more data than ever before but lacks knowledge on what to measure or what to do with the data
- Poor data governance entails dealing with excessive, unintegrated, unreliable data
- Analytic capability to turn data into insight is insufficiently developed within the HR teams
- Cloud solutions and cutting-edge technology to enable streamlined and automated HR processes are expensive
Fulfilling the promise of the Data Driven HR is not easy and the challenges are real. Embrace it as being the unavoidable future and accept that more often than not the biggest obstacles are not of a technical nature, but cultural. And the main one is the way HR still regards itself as being a non-business function, while all success stories prove that HR excellence starts and ends with a deep understanding of business.
- A new profile of the HR professional is emerging and a brand new set of competencies are required, as shown by research led by LinkedIn that indicates a significant increase in HR professionals with data analysis competencies.
- Over the last five years, the research showed a 242% increase in HR professionals with data analysis skills.
- Companies have realized that starting small is ok. Value is added right away by combining reliable data with metrics that matter, while also preparing HR for advanced analytics in the future. The experience of these companies give us some insight on where to start:
- address first the issues of data governance, analytic capabilities, and building a data adoption culture. With the implementation of limited, but targeted data governance mechanisms, many companies have managed to ensure the right data is being collected at the right level of accuracy.
- a data plan should start with identifying metrics that matter to produce a report or dashboard that actually fits the intended purpose of tracking progress toward an objective, a critical workforce trend, or to inform a specific workforce decision.
- reports and dashboards should be less ambitious and more focused on the most important talent issues, so the number of metrics should be limited to 20 wherever possible. Small, easy to understand dashboards that drive action can produce a big impact.
The Great Depression of 1929-39, the OPEC oil price shock in 1973, the Asian credit crisis in 1997, and the Great Recession of 2007-08 — these are just some of the most distressing downturns in economic history, and the current pandemic is adding to this list. Apart from these crises, businesses — however small or big — are continuously struggling with the ever-evolving technology. Companies need to deal with disruptive innovations, dynamic consumer likings, pricing, quality, and a high degree of satisfaction in user experience. Such risks arising out of unpredicted conditions coupled with traditional trade risks put a business on tenterhooks with the obvious threat of going into oblivion and give them no choice but to strive for excellence and agility to survive.
The dictionary meaning of agility is quickness, dexterity, alertness, swiftness, responsiveness. While there isn’t a single comprehensive definition vetted by everyone, some authors defined agility as one of the key organizational characteristics that need to be mastered to stay adaptive and competitive in turbulent markets. In the context of the current pandemic and the uncertainty it brings, it calls for an organizational response to the unproductive environment and the ability to convert threats into opportunities. However, the concept of agility was mainly associated with manufacturing industries that too around managing demand-supply variation.
To cope up with a turbulent environment, organizations should have the ability to anticipate the direction and degree of change in a proactive manner. As such, organizational structures should be designed so that they permit greater agility, through flexible response. Enablers like leadership, strategy, people, and business processes play an important role in developing organizational agility. These enablers need to work in cohesion to enhance the agile components of the organization.
The prevailing VUCA (volatility, uncertainty, complexity, and ambiguity) conditions trigger dynamic and continuously changing environments, impacting the organizations. As a response, organizations need to develop the ability to innovate and acquire new knowledge so as to achieve agility for survival. The strategy around flexible HRM empowers organizations or firms to respond to external customers, competitive positions, technology selection and dissemination, creativity, and cycle time reduction. The focus in this paper is on the intangible resource (i.e. human resource) and the important flexibility dimensions of human resource management (HRM).
HRM strategy on agility
The HRM strategy should support reactive agility (organization’s responsiveness), proactive agility (organization’s effectiveness), and innovative agility (organization’s resourcefulness). HRM strategy is required to support the ever-dynamic market so that organizations can respond and achieve decent performance. Organizations paying attention to the HR strategy have been proved more profitable than others.
The key attributes of agility in an organization that HRM should try to focus on and promote in the organization through key leaders are tabulated below. This is not a comprehensive list but can be developed depending upon the organization. As a next step, one should have measures in place around these attributes so that agility can be assessed if not measured. All key frameworks like BEM/EFQM, CMMI, or BSC aim at providing resilience to organizations; therefore, while developing any such framework these attributes can be guiding points.
Image source: The KPI Institute
The challenge to organizations today is how to imbibe and implement agility drivers and later how to judge the organization’s agility. One possible approach is to develop an agility maturity model in line with a capability maturity model in template form. The template itself needs to be dynamic and able to change with environmental factors. The table above is just guidance to look around such agility drivers so that it can be helpful in developing the template.
Strategic HR plays an important part to ensure that the people in the organization understand and support such agility adoption. In fact, the versatility and the adaptive skills of a person are assessed even as early as the talent acquisition stage as this is an important dimension when recruiting an individual into the organization. The employees’ performance management system (PMS) developed by HR should pay greater attention to agility factors in a person rather than just task accomplishment levels. To conclude, understanding and navigating the complex eco-system in which organizations operate is crucial; at the same time, HR should play a bigger role in developing an agile workforce that can’t be just left to line functions.