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Christopher Rosett
HR Leader, Researcher, Speaker, and Author
Professional Background
Christopher Rosett is a talented HR professional whose extensive experience spans across several critical areas in human resources including analytics, learning design and development, employee engagement, job analysis, and organizational design. With a profound interest in enhancing the workplace experience, Christopher has devoted his career to advancing HR practices through a scientific lens. His work within various functions of talent management—particularly organizational development, learning, talent acquisition, and HR analytics—has positioned him as a trusted authority in the industry.
A current member of the esteemed Amazon team, Christopher works in operations and analytics with a specific focus on driving business impact. His commitment to harnessing data to inform HR strategies sets him apart. Christopher articulates his vision through four primary professional objectives: equipping business professionals with superior HR knowledge and tools, fostering a data-driven decision-making culture in HR, underscoring the strategic significance of HR within organizations, and enhancing organizational structures to provide seamless career experiences for employees.
Education and Achievements
Christopher's academic journey laid a robust foundation for his HR career. He holds a Bachelor of Science in Psychology and Theology from the University of Scranton, which equipped him with a unique blend of expertise in understanding human behavior alongside strong ethical and philosophical considerations. Building upon this education, Christopher pursued a Master’s degree in Industrial-Organizational Psychology at Iona University, further developing his skills in applying psychological principles to workplace settings.
His career achievements are noteworthy, reflecting a trajectory marked by leadership and innovation. Previously, he served as the Director of People Analytics, Technology, and Operations Excellence for North American Operations at Amazon, where he played a crucial role in integrating analytics into HR strategies to drive efficiency and impact.
Before his tenure at Amazon, Christopher held various influential positions at Comcast, including Senior Director of Business Impact and Results, as well as Senior Director of HR Analytics and Reporting. These roles permitted him to pioneer analytics initiatives that fostered a data-informed culture, significantly improving HR practices at the organization.
An advocate for continuous learning and sharing of best practices within the industry, Christopher has presented insights at countless professional conferences and universities across the United States, further solidifying his reputation as a thought leader. His contributions to the field culminated in the recent publication of his first book—"Introducing HR Analytics with Machine Learning"—with Springer Publishing, a testament to his dedication to educating others on the transformative power of analytics in HR.
Achievements
Christopher's professional journey exemplifies a commitment to both personal and professional growth. His roles across major organizations like Amazon and Comcast demonstrate his capability in leading teams toward effective data utilization, operational excellence, and strategic alignment of HR functions with overall business objectives.
His influence extends beyond organizational boundaries, as he actively engages with other professionals to share insights and enhance industry practices. By combining theoretical research with practical applications, Christopher has successfully bridged the gap between academia and industry, providing actionable recommendations for business leaders looking to leverage HR as a vital component of their strategy.
As he continues to push the boundaries of what HR can accomplish, Christopher remains focused on leveraging technology and analytics to shape positive workplace cultures and improve employee experiences. His engaging presentations, along with his published work, serve as guiding resources for HR professionals looking to adapt in an ever-evolving work environment.
Highlights
Model of the Month: The Ink to Insights Ratio
“Data looks better naked” is one of my favorite quotes from an article I read on #datavisualization by Darkhorse Analytics many years ago.
Every pixel you add (or don’t remove) sends a message. How you use the quantity, color, white space, contrast, size, and direction of ink makes it easier (or harder) to understand your message. This isn’t artistic opinion, it’s based on the science of salience, attention, and cognitive load.
The Ink to Insights Ratio is a model I use to coach people toward better visualizations via one question: how much ink are you spending to get your point across? In grad school we are taught specific visualization “rules”: label your axes, use gridlines, sequentially number your figures… and while important for standardization across academia, applied settings have different freedoms and constraints.
The freedoms and constraints vary (and tend to be scenario specific), but consider the major goals of any informational graphic: (1) guide the viewers’ eyeballs where you want them to start, advance, and finish, and (2) clearly articulate what you are expecting them to attend to and/or learn.
You know more about the data than your viewer (i.e., you know where to look and you know what the message is). This means it’s much easier for you to “ignore” useless ink, but your viewer has to figure it out for themselves. Said differently, that which is not salient to an expert has to be consciously processed (and then ignored) by a novice. And every second they are doing that they are not paying attention to the data.
So, the next time you are reviewing a report, dashboard, or graphic, consider how much ink was spent to build it.
#dataanalytics #peopleanalytics #hranalytics #iopsychology #datascience #datavisualization
Model of the Month: The Infrastructure-to-Appetite Ratio. How does data maturity impact #analytics sustainability?
Businesses think about the value they want from #data, but not as much about how its infrastructure impacts the energy it takes to get that value. And in the race to get data and insights we sometimes leave data maturity behind, accidentally inflating time-per-insight.
Analytics is sustainable when infrastructure and expectations evolve together, but there are a few maturity moments I believe mark common stagnation threats to data maturity. If appetite for insight continues to increase at these inflection points, it inflates the energy required to deliver value:
Faux Maturity: That first taste of data hooks us. We can run reports, generate correlations, and pivot to our hearts’ content. This increases what leaders want from data... and reporting volume explodes. But infrastructure cannot keep up with demand and human-hours bridge the gap. Many organizations get stuck here and accidently turn their analytics team into glorified data waitresses and correlation chasers.
The Illusory Peak: If data maturity increases, then legitimate data governance, metric standardization, and healthy mechanisms for moving and using data emerge. However, if appetite increases without continued maturity, this “peak” becomes overly time-intensive. At this level, some infrastructure is efficient (e.g., reporting tools), but many data activities are not (e.g., population mapping tables; data wrangling for research; data access strategy). To the senior leader, it FEELS like infrastructure is mature because they can get what they ask for but, in reality, there are huge amounts of manual hours spent keeping the data and insights machine running.
Commitment to data infrastructure and operational maturity cannot wane after a few big reporting or analytical milestones – it must be maintained and invested in as fiercely as increasing market share, bolstering revenue channels, and optimizing operating cost. The realities of the infrastructure-to-appetite ratio are critical to consider when creating a sustainable analytics function.
#hr #hrstrategy #iopsychology #hranalytics #peopleanalytics #businessanalytics #appliedresearch #dataengineering #businessintelligence
