Evolving Work with Connected Worker Analytics

Contributed by: Brent Kedzierski

Integrating transformative technologies with human-centric strategies is crucial to the rapidly evolving landscape of businesses and industries. One such pioneering approach is Connected Worker Analytics, which seamlessly integrates operational data (O-data), experience data (X-data), and human resource data (H-data) to revolutionize decision-making and enhance the overall human experience within an organization through a data-driven approach.

Understanding X, O, and H Data: The Triad of Connected Worker Insights

The power of Connected Worker Analytics is in its capacity to seamlessly integrate three distinct data streams—X, O, and H—into a cohesive narrative.

While O-data and HR data provide factual insights into workforce and operational aspects, X-data unravels the subjective layer, revealing motivations and attitudes that drive behaviors. Leveraging these three data categories opens a plethora of possibilities to combine X, O, and HR data in ways that unveil correlations and causal relationships between operational processes, employee experiences, and business outcomes. For example, understanding how employee engagement (X data) correlates with productivity metrics (O data) can inform targeted HR interventions. Another combination can shed light on how workforce demographics (HR data) influence production levels (O data), offering valuable insights for workforce planning and resource allocation. Let's delve into each category for a shared understanding and explore the creation of analytics within these evolving dimensions.[1]

X-Data (Experience Data)

Within Connected Worker Analytics, X-Data emerges as a transformative force, delving into the intricacies of the Human Experience Cycle (HxC)[2] within connected worker ecosystems. Unlike traditional organizational data, X-Data introduces subjectivity and contextual richness, shedding light on the 'why' behind employee actions and perceptions, profoundly shaping the landscape of connected worker insights. This dimension involves a continuous process of gathering feedback to understand the Human Experience Cycle.

Within connected worker environments, employees contribute feedback (X-data) through diverse data collection channels, including employee engagement surveys, exit interviews, or specialized platforms. This feedback offers valuable insights into technological usability, collaboration effectiveness, integration of digital tools, work-life balance facilitated by connectivity, and employee perspectives on integrating innovative technologies into their work processes.

In essence, X-data are fundamental for informing and influencing HxC. By harnessing X-data related to experiences, expectations, perceptions, attitudes, and behaviors, organizations can strategically enhance and optimize the narrative of human performance experience at every stage of the work cycle.

REGISTER: Elevating Industry 4.0: Unleashing Human-Centered Connected Ecosystems

O-Data (Operational Data)

O-Data has long stood as the bedrock of business insights within industrial domains, notably manufacturing. It encompasses factual and quantitative information, offering a precise portrayal of day-to-day operations through a diverse array of crucial metrics.

O-Data sheds light on the 'what' in business scenarios, offering insights into actions and outcomes with precision. However, it often falls short in revealing the 'why' behind events or predicting future occurrences. This is where X-Data steps in, capturing how individuals, particularly connected workers, perceive and engage within the work environment.

Integrating O-Data with X and H-Data brings about a comprehensive 360-degree view of the human aspect within an operational context. This integration enriches the understanding of employee behavior within operational settings by offering insights into how operational activities align with employee characteristics and requirements.

HR-Data (Employee Data)

In the dynamic landscape of connected worker analytics, HR Data emerges as the keystone, offering critical insights into the dynamics of the workforce. It encapsulates fundamental elements of an employee's journey, encompassing crucial facets such as employee identification, employment and performance history, compensation structures, training records, demographics, recruitment details, education qualifications, and more.

When seamlessly integrated with operational metrics like production, maintenance, and safety (O-Data), HR Data unveils discernible patterns. These patterns establish vital links between employee attributes and experiences to productivity and safety, revealing valuable opportunities such as the need for upskilling or reskilling. This agile alignment of skills with evolving operational demands ultimately translates into heightened performance and efficiency.

Furthermore, when woven together with operational data (O-Data) and experiential insights (X-Data), HR Data enriches the analysis of employee behaviors and performance. This fusion provides a comprehensive view of employee engagement and contributions within their respective work environments, empowering organizations to make informed decisions that optimize productivity and foster a thriving work culture.

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Sample Structures for Connected Worker Analytics

The world of Connected Worker Analytics is emerging and teeming with possibilities, offering a triage of data combinations that unveil profound insights. These insights transcend mere data; they serve as invaluable tools for optimizing the work environment, productivity, and overall worker satisfaction. Now imagine the transformative potential of integrating these fundamental insight capabilities into an organizational portfolio. Connected Worker analytics, fueled by the fusion of O-Data, X-Data, and H-Data, holds the potential to redefine operational strategies and profoundly enhance "the human experience" within the connected worker ecosystem.

Table 1.0 offers a glimpse into the dynamic potential of connected worker analytics, presenting a rich array of insights ready for exploration. This curated collection of data combinations represents a triage that holds the key to unlocking strategic insights for an organization's knowledge portfolio. The possibilities within the realm of connected worker analytics are vast and transformative, paving the way for a future where empowered decisions drive progress and elevate operational excellence.

^{Table 1.0: Unveiling the Dynamic Potential of Connected Worker Analytics}

Foundation of Connected Worker Analytics Architecture

In today’s data-driven landscape, Connected Worker Analytics stands at the forefront, aiming to unlock insights across four fundamental levels: Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics. For each level, a good analytic will include a consistent structure, incorporating key elements like title, data sources, calculation methodologies, and consequential business insights. This comprehensive breakdown serves as a definitive blueprint for organizations, guiding them on how to leverage the immense potential of Connected Worker Analytics effectively. See basic examples below:

1. Descriptive Analytics: Enhancing Productivity through Employee Engagement Insights

- H Data Source: Employee engagement survey data
- X Data Source: Employee feedback and sentiment analysis
- O Data Source: Call center logs and interaction patterns
- Analytic Calculation: Correlating X, O and HR data to identify engagement levels affecting productivity
- Business Insight: Descriptive analytics can reveal that higher employee engagement, indicated by positive X-data and increased nudge learning, directly correlates with higher productivity

2. Diagnostic Analytics: Optimizing Operational Efficiency through Performance Analysis

- H Data Source: Employee performance records and incident reports
- X Data Source: Employee feedback on work environment and operational processes
- O Data Source: Time and incident logs, maintenance reports
- Analytic Calculation: Analyzing past performance data and correlating X and O data to identify factors influencing efficiency
- Business Insight: Diagnostic analytics might uncover that a more flexible and employee-friendly work environment, highlighted by positive X-data, correlates with fewer operational incidents and higher efficiency. Organizations can then focus on tailoring work environments to suit employee needs, thus reducing incidents and boosting efficiency

3. Predictive Analytics: Proactively Enhancing Safety Measures Through Data Forecasting

- HR Data Source: Employee training records and incident reports
- X Data Source: Employee safety feedback and incident narratives
- O Data Source: Maintenance schedules and safety logs
- Analytic Calculation: Applying machine learning to predict future safety risks based on historical data
- Business Insight: Predictive analytics can forecast potential safety risks, enabling the proactive identification of areas for targeted safety enhancements. For instance, foreseeing potential risks related to a particular machine can prompt enhanced safety training and precautionary measures for employees operating that machine

4. Prescriptive Analytics: Ensuring Reliability through Maintenance Optimization

- HR Data Source: Employee skills and training records
- X Data Source: Employee feedback on equipment performance and maintenance processes
- O Data Source: Equipment logs and maintenance history
- Analytic Calculation: Identifying patterns in equipment maintenance and recommending tailored maintenance schedules
- Business Insight: Prescriptive analytics can recommend specific maintenance schedules for critical equipment, optimizing reliability and minimizing downtime. For instance, recommending a predictive maintenance schedule for a crucial machine based on both historical performance data and employee feedback can ensure maximum uptime and efficient operations

Connected Worker Analytics seamlessly integrates across these four analytical levels, amalgamating insights from X, O, and HR data. This integration empowers workplaces to achieve elevated levels of operational efficiency, safety, maintenance, and reliability. As this synergistic approach propels organizations to the cutting edge of efficiency and excellence, leveraging these insights becomes a critical strategic advantage. It enables organizations to tailor their strategies, refine work processes, and optimize human performance support structures, ultimately fostering a work environment that not only boosts productivity and efficiency but also prioritizes the safety, well-being, and overall satisfaction of connected workers.

READ: Implementing Connected Worker at Duravant

Conclusion

In the midst of the big data and advancing AI era, the intrinsic value isn't merely housed within the data itself, but rather in the astute action’s organizations take guided by the insights it unveils. Insight, growing in significance, becomes a strategic imperative as work dynamics and employee expectations continuously shape-shift and evolve.

Connected Worker Analytics definitively lays the cornerstone of a data-centric workplace that necessitates being not just connected, but also dynamic, agile, and remarkably responsive. The triad of the X-O-H data dimensional architecture constructs an all-encompassing view of the workforce, empowering data-driven decisions that ignite more probative actions. These actions endeavor to fundamentally evolve how organizations operate and deeply engage with their employees, ultimately enabling better worker/workforce Experience Management (XM).

Thriving in the high-concept, high-touch experience economy unequivocally calls for the embracement of a new data synergy that transcends the 'what' and 'why' of data. It requires delving into more profound levels of strategic inquiry that propel progress and enablement beyond conventional boundaries.

And in this transformative landscape, #XOH Analytics emerges as the gateway, where data transcends its traditional form and evolves into the linchpin for elevated levels of analysis, discernment, and innovation. It heralds a new era of strategic questioning and more probative decision-making enabled by deeper analysis and assessment of connected data.

Interested in learning more?

Brent Kedzierki will be leading our upcoming webinar: Elevating Industry 4.0: Unleashing Human-Centered Connected Ecosystems. Join us on November 2, 2023 at 10am EST for a comprehensive exploration of connected worker ecosystems and their transformative impact on the industrial landscape in the era of Industry 4.0. Don't miss this opportunity to gain actionable knowledge and strategies for elevating your manufacturing operations. Register for free here!

^{[1] Dimensions of Connected Analytics: Equipment Maintenance Analytics, Safety and Compliance Analytics, Quality Control Analytics, Workforce Planning Analytics, Talent Management Analytics, Process Optimization Analytics, Employee Engagement and Productivity, Energy Efficiency Analytics, Supply Chain Analytics, Cost Management Analytics, Reliability and Downtime Analytics}

^{[2] The Human Experience Cycle (HxC) provides a structured model to comprehend how individuals navigate and perceive their experiences, whether as customers, employees, patients, or in any other role. This model comprises five key elements: Experiences, Expectations, Perceptions, Attitudes, and Behaviors. Understanding each element in the context of experience data (X data) allows for a comprehensive grasp of the human performance experience narrative.}