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Avinash Tripathi, Vice President of Analytics, University of Phoenix

Avinash Tripathi, Vice President of Analytics, University of Phoenix

Describe your career to date

I have amassed over two decades of experience as an analytics practitioner, driven by my fervor for transforming ideas into tangible outcomes. Throughout my career, I have adeptly steered teams in offering insights and implementing innovative solutions. Embarking on my professional journey as an analyst at WPP, a globally renowned company specializing in creative transformation, I witnessed the evolution of data and analytics from mere support functions to pivotal components within businesses. Recognizing the transformative power of data-driven decision-making, I embraced a pivotal role in shaping this paradigm shift.

During my tenure at WPP, my primary focus revolved around developing and executing data solutions geared towards optimizing advertising return on investment. Progressing into senior roles, I transitioned to a leadership position at a prominent global higher education company. Here, I strategically built and led teams consisting of data scientists, data engineers, and analysts. Our collaborative efforts formulated problem-solving approaches that not only enhanced efficiency but also contributed to substantial growth rates.

In my most recent roles, I played a key role in shaping the data-driven decision-making culture of two of the largest online educational institutions globally. Additionally, I took on the responsibility of crafting data strategies for these organizations. Throughout this journey, I have been privileged to offer guidance to organizations, aiding them in implementing data-driven initiatives aimed at boosting enrollment. My consistent approach involves unlocking insights from available data resources, yielding favorable outcomes.

What distinguishes me is the seamless integration of business acumen with technical expertise, allowing me to deliver solutions that revitalize organizations. Beyond my role, I am a sought-after speaker and contributor to industry publications and blogs, further showcasing my commitment to advancing the field of analytics.

Data literacy is a key enabler of the value and impact from data. How are you approaching this within your organization?

Looking back on my 20 years of experience in the field of data and analytics in the US higher education sector – which is valued at a $1.9 trillion worldwide, compared to healthcare at $1.7 trillion and IT at $3.4 trillion – I believe that my most significant contribution has been advocating for disruptive transformation. This transformation aims to address the changing needs of the industry by harnessing advanced analytics and real time data effectively.

Implementing disruptive transformation through advanced analytics poses challenges for any organization. In higher education, these challenges are compounded by sector-specific factors such as governance (regulatory), compliance, and talent. In this context, the impact of analytics is often constrained, and the insights derived are not fully integrated into day-to-day decision-making processes across the institution.

To address this, our organization is approaching data literacy through various initiatives. We are actively fostering a culture of data-driven decision-making by enhancing accessibility and usability of data for frontline managers. Equipping them with data visualization tools facilitates better understanding and interpretation of data. Additionally, we have instituted a comprehensive data literacy training program for all employees, complemented by open office hours to promote data democracy, accessibility, and a single source of truth. Our efforts also extend to measuring the impact of data literacy by tracking the use of data in decision-making and its subsequent business outcomes.

As one of the largest institutions in the world, our future plans include making data literacy a core competency for all students. We are exploring to introduce a data literacy course as part of our general education curriculum and integrate data literacy principles into various courses across the university. We firmly believe that data literacy is not just a skill but an essential competence for students to thrive in today’s data-driven world.

What role do you play in building and delivering conventional AI solutions, including machine learning models? Are you involved in your organization’s adoptions of generative AI?

In my multifaceted role in building and delivering conventional artificial intelligence (AI) solutions, my primary focus revolves around developing machine learning models for predictive personalization. This includes actively shaping personalized experiences through predictive analytics and automating workflows to achieve efficient personalization at scale.

My responsibilities encompass analyzing real-time user data to anticipate individual customer needs, refining machine learning models, and implementing workflow automation for seamless personalization.

I actively contribute to persona-based personalization by categorizing users into meaningful clusters based on their characteristics and behaviors. This strategic approach facilitates highly personalized content delivery, enhancing user engagement and satisfaction. Moreover, leverage natural language processing techniques to analyze and generate text content, contributing to personalized messaging and content creation.

An illustrative case study, recently published with Digital First Magazine, highlights the successful application of conventional AI solutions in the education sector. Through the analysis of anonymous website visitors, played a pivotal role in identifying and categorizing potential students based on online behavior. This initiative resulted in highly personalized outreach, improved conversion rates, and student satisfaction for a large online university.

As the CDAO landscape evolves, I emphasize a strategic shift towards delivering business value, addressing challenges in data culture, ethics in AI, and fostering a broader community of data-driven contributors. Building trust in the age of data privacy is crucial, and I advocate for the ACTED framework, promoting practices like anonymization, user consent, transparency, and data minimization to ensure responsible and ethical use of personal information in personalization efforts.

What are the key challenges to your data function that you are facing as its leader?

My primary challenge as the leader of the data function is to navigate new opportunities through data and drive substantial value to the organization. Prioritizing a data-driven customer approach is crucial in the education sector, given the heightened competition, economic uncertainties, and evolving student demographics that influence changing student needs.

To excel in this environment, higher education institutions must embrace a customer-focused mindset, prioritizing students’ needs and utilizing data to gain insights into their desires, thereby creating a relevant and impactful student experience. By reframing “students” as “customers” and transforming “data” into “insights,” we can shift the focus from the institution as a whole to recognizing each learner. This change empowers institutions to understand customers better, identify areas for improvement, and make informed decisions—a concept I’ve emphasized as head of data.

Despite substantial investments in becoming more data-driven, only a small fraction of organizations, including higher education institutions, have successfully scaled up their analytics capabilities to extract full value from their data. Specific challenges faced include fragmented data and governance, where data is scattered across departments, necessitating a framework for managing data to address privacy and security concerns.

Additionally, the perception of data analytics as a cost centre limits our ability to fully utilize analytics talent, hindering their potential contribution to driving differentiation and uncovering valuable insights. Effective communication of data analysis results, particularly to non-technical audiences, is crucial for organizational success, emphasizing the need to convey insights in a way that resonates with stakeholders.

Change management poses another significant challenge, as implementing data-driven change requires a shift in behaviors and thinking. Overcoming these obstacles will enable university to maximize the benefits derived from data utilization, effectively leverage analytics for decision-making, and ultimately improve outcomes. By addressing these challenges head-on, we can lead the way in harnessing the full potential of data in the higher education landscape.

Avinash Tripathi
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