Connected Worker Analytics: Shaping the Future of Work
Welcome to the third installment of the Hexagon Blog Series, "Building Industrial Competence." In our opening article, we introduced the concept of Whole Person Competence Development (WPCD) and its significance in a world increasingly reliant on cognitive, creative, and collaborative skills. In the preceding article, we advocated the incorporation of human-performance engineering models in designing connected worker ecosystems.
In this article, we delve into the critical significance of Connected Worker Analytics1, a transformative discipline poised to revolutionize human centeredness, operational intelligence, and the human performance experience in our rapidly evolving business landscape.
Part 1: Harmonizing Industry 4.0: Fostering a Symbiotic Tech-Human Ecosystem
Industry 4.0 signifies an era of unparalleled technological advancement, promising immense potential for heightened efficiency, productivity and safety to meet the evolving industrial demands influenced by sweeping mega-trends. At its core, Industry 4.0 envisions a seamless integration of smart factories and interconnected workforces2, fueling innovation through cutting-edge technology and data-driven insights.
However, beyond its technological advancements, lies a deeper narrative: the imperative to cultivate a symbiotic relationship, where the rapid advancement of technology, the holistic well-being and progression of humanity, and the imperative of environmental sustainability synergize and elevate each other in harmony.
The Elephant on the Table: Balancing Technological Triumphs with Human Well-being
Regrettably, Industry 4.0's journey has revealed a poignant challenge: how to harmonize technical innovation with humanity. The growth of connected-worker ecosystems presents ongoing hurdles due to a lack of human-centered design, inadequate needs assessments, suboptimal engagement, resistance to change and unrealistic expectations. The unmistakable elephant in the room of digital transformation remains the need to prioritize the human element.
Sadly, achieving this equilibrium is proving elusive and worrisome. As a well-known fact, technology's rate of advancement accelerates with time, attributed to its ability to self-enhance, setting off a cascade of faster and more profound innovations. Each stride in innovation builds on the previous, propelling the pace of change in the technological landscape into an exponential sprint3. This acceleration is disconcerting, given the widely acknowledged gap between the rapid progress of technology and the comparatively slower rate at which societal and organizational structures, as well as human skills and behaviors, adapt to fully utilize and keep in step with these advancements4.
Is Perception Reality: CEOs and the Value of the Human Workforce
Recent research highlights a concerning trend: CEOs and business leaders undervalue their human workforce. A significant 2016 global study by Korn Ferry,5 encompassing insights from 800 business leaders representing multi-million and multi-billion-dollar organizations, revealed a startling perspective. Two-thirds of these leaders viewed technology as the primary creator of future value, overshadowing the importance of their employees.
This trend is especially disconcerting given the continuous surge in investments in connected-worker ecosystems, with the connected-worker solution market projected to surpass $4 billion by 20266 continues to be human-centric design and management. Unfortunately, studies such as the Korn Ferry investigation provide evidence supporting the perception held by workers that companies marginalize the human element, resulting in employee disengagement.
Part 2: Introducing Connected Worker Analytics as the Next Frontier
In Part 1, we delved into critical challenges, driving the need for innovative solutions. In Part 2 we introduce the concept of Connected Worker Analytics as an innovative solution to ensure human-centeredness within connected worker ecosystems and the human performance environment.
Evolution of Human Resources (HR) Reporting: Tracking People Related Data
The journey of HR reporting began with centralizing people-related data within a single Human Resource Information System (HRIS). This consolidation enabled data presentation, often in a spreadsheet format, focusing on administrative tasks, compliance and fundamental workforce management. Core reporting elements encompassed head count, employee demographics, compensation, time and attendance, compliance training and turnover.
Evolution to People Analytics: Integrating People Data for Insight
The introduction of Human Capital Management Systems (HCM) triggered a significant shift in HR reporting, seamlessly integrating HR data from various HR applications. This integration unlocked new insights into talent management, workforce planning and HR processes, ushering in the era of Business Intelligence, data visualization and data-driven decision-making for HR professionals.
A notable trend shaping the HR landscape is the advent of People Analytics, driven by AI to transcend traditional descriptive and diagnostic insights. HR is now striving to provide business leaders with predictions and prescriptions, enriching decision-making. While traditional HR focuses on a broad spectrum encompassing employee engagement, experience and satisfaction, Connected Worker Analytics explores the employee's actual daily performance environment.
In today's era of convergence between work, technology and humanity, embracing Connected Worker Analytics is not merely a preference; it’s a strategic imperative to close a growing gap. This approach offers a practical, data-driven solution that overcomes the constraints of conventional People Analytics by intricately capturing the integration of people, processes and technology in our interconnected operational environments.
However, HR departments currently face challenges in fully understanding how individuals interact within their digitally connected work environments or in establishing connected analytics. They will lack requisite capacity for some time, highlighting the need for new and specialized roles like Chief Connectivity Officer or Connected Worker Analytics Officer. These roles will collaborate with, within, or alongside HR, emphasizing the necessity of a unified and insightful approach to navigating the evolving workplace.
Connected Worker Analytics: Individual and Organizational Performance Dynamics7
In this digital age, the unparalleled ability to comprehend the depth and breadth of human performance offered by Connected Worker Analytics cannot be overemphasized. These analytics provide a more practical, operational and data-driven approach that transcends the limitations of conventional People Analytics. Imagine being able to seamlessly merge HR data with a full spectrum of connected data sources, presenting a panoramic view of the workforce and its impact on business outcomes. Picture how the expanding usage of artificial intelligence and machine learning will help to understand how an employee's actions and performance experience resonate across the entire organizational performance environment and impact broader business outcomes. For instance, analyzing downtime or safety data in relation to workforce schedules to prescribe how to optimize maintenance planning, ensuring minimal disruptions to production cycles.
However, the significance of Connected Worker Analytics extends beyond data integration. It is a crucial tool for ensuring human centeredness in work design and technology deployment. Consider the example of combining quality and employee performance data to understand how workforce actions affect product quality. This insight can drive targeted training and process improvements, ultimately enhancing product standards.
This emerging discipline acts as a conduit for advanced integration with technology, people, and the broader work environment, establishing a bridge that harmonizes human potential and technological innovation with the performance environment. In doing so, it positions the essence of humanity at the core of our swiftly evolving workplace. Imagine using energy consumption data to optimize resource usage during different shifts, fostering sustainability while enhancing productivity.
The time to champion the widespread adoption of Connected Worker Analytics is now; it embodies a pressing need that encapsulates the very essence of human-centered progress, ensuring a brighter, more productive and symbiotic future of work. These examples show the tangible benefits that arise from the integration of HR data with various process and system data, underlining the transformative power of Connected Worker Analytics in driving a human-centric approach to workplace design and performance optimization.
The Four Levels of Analytics
In the realm of Connected Worker Analytics, four distinct and progressive levels provide deeper insights into connected worker strategies.
- Descriptive Analytics: This foundational level leverages historical data to unearth valuable insights into past events, trends, patterns and outcomes, shedding light on the impact of worker performance on safety incidents, and productivity over time. For example, analyzing historical data can reveal patterns of peak productivity times for workers or identify common behavioral factors leading to safety incidents.
- Diagnostic Analytics: Moving beyond descriptions, this level explores the underlying causes of specific outcomes by scrutinizing trends and correlations and identifying root causes of issues based on human or environmental factors. An example could be analyzing data to identify the correlation between certain maintenance activities and subsequent increases or decreases in worker productivity.
- Predictive Analytics: Positioned on the forward-looking horizon, predictive analytics empower organizations to anticipate future outcomes and plans based on historical patterns, forecasting worker performance and maintenance needs. For instance, analyzing historical data might predict when a certain piece of equipment is likely to fail, prompting field staff to perform proactive maintenance actions.
- Prescriptive Analytics: At the highest level, prescriptive analytics not only forecasts outcomes but also prescribes precise actions to maximize efficiency, elevate outcomes, and enrich experiences. This suggests interventions to improve worker performance and safety based on prescriptive insights. An example could be recommending specific refresher training based on the analysis of worker performance data to enhance productivity and reduce errors.
See Table 1.0 Connected Worker Analytics for the Human Performance Model presents sample analytics for the three environmental and three Individual factors driving human performance.
Table 1.0 Connected Worker Analytics for the Human Performance Model8
Connected Worker Analytics brings into focus the transformative potential of a novel data analytics approach, effectively aligning technology and work processes with human performance, experience, and overall well-being.
Understanding the profound impact of measurement on outcomes, these analytics emerge as catalysts for substantial advancements within the human performance ecosystem across industry. Their significance goes beyond mere analytics; they possess the power to reignite engagement levels and steer industries toward a future of work that is symbiotic, sustainable and notably more productive.
What's Next in Our Series?
Having emphasized the importance of people, the systems in which they work, and the role of Connected Worker Analytics in management and improvement, our next article will delve deeper into aligning these models with prioritized vulnerabilities within an organization's current performance environment. We will explore how to engineer Connected Worker Analytics that continually scan for opportunities as well address vulnerabilities across the human performance ecosystem. Stay tuned for actionable strategies to strengthen your organizational performance ecosystem.
- Can also be referred to as Connected People Analytics
- A connected worker is an employee who is integrated into their environment by connective technologies
- Kurzweil's Law of Accelerating Returns
- Avoiding the Technology Trap in the Future of Work, Forbes Magazine August 5, 2019
- Korn Ferry Global Study: Majority of CEOs See More Value in Technology Than Their Workforce
- Market Size And Forecast: Connected Worker Solutions 2020-2026 (Global) (verdantix.com)
- In the context of connected ecosystems, "performance dynamics" refers to the fluid and interactive patterns, behaviors and changes in performance that occur within an interconnected network of people, processes, and technology. It involves the study and analysis of how various elements in the ecosystem, such as individuals, teams, technologies and processes, interact and influence each other to impact overall performance and productivity.
- Note: Table 1.0 illustrates the positioning of the Connected Worker within the Human Performance Model. In addition to this contextual framework, the author has curated a comprehensive catalogue of Connected Worker Analytics, refining the profiles to align with specific intents and Performance Domains. Notable examples encompass Biometric Worker Analytics in the Biomechanical Performance Domain, Healthy Worker Analytics in the Health and Well-being Performance Domain, Virtual Worker Analytics in the Virtual Performance Domain, Augmented Worker Analytics in the Augmented Reality Performance Domain, Cognitive Worker Analytics in the Cognitive Performance Domain, Creative Worker Analytics in the Innovation and Creativity Performance Domain, Collaborative Worker Analytics in the Collaborative Performance Domain, and AI-Powered Learner Analytics in the AI-Driven Learning Performance Domain. These analytics types comprehensively encompass diverse dimensions of worker performance, embodying the outcome of extensive research, dedicated development and expertise within the realm of Human Performance in Connected Ecosystems.