5. Ronke Ekwensi, Vice President – Data, T-Mobile
Describe your career to date
I am a Data and AI leader with more than 25 years’ experience in various positions across multiple industries. I am currently Vice President of Data at T-Mobile, where I lead the organization’s data transformation efforts bringing together data science, AI, advanced analytics, data engineering, governance, and data management to support the company’s stated vision of becoming data driven and AI enabled.
Prior to T-Mobile, I was Vice President of Data Management at Prudential, leading the organization that focused on building a robust data management and governance function for the company. In this role, I partnered with C-Suite executives to develop a data strategy and operating model that resulted in the establishment of the chief data office.
My data and technology background spans multiple industries, including telecom, financial services, insurance, biopharma, utilities, and management consulting. I consider myself a multi-lingual data executive that understands the language of data and artificial intelligence (AI), technology, business, and the regulatory and privacy landscape. I began my career at Hewlett Packard working in the sales office as a financial analyst. I have a doctorate degree from Northeastern University, with a focus on the philanthropic use of commercially collected data in the telecommunications sector.
How are you developing the data literacy of your organization, including the skills of your data teams and of your business stakeholders?
Our initial approach to data literacy was to first to focus on our data organization. We developed a talent strategy framework that identified the necessary job families and the roles within each job family. We defined vision and structure for our data resources, and identified the right mix of skills, to better structure existing teams and resources.
We created a career lattice to provide a growth path for our data professionals and build multi-skilled teams. In partnership with our HR organization, we identified certification requirements for each data role in the organization. We are now working with HR to deliver broad training on data and AI to everyone in the organization through Magenta University.
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?
Our focus on data and AI is to improve our operations, increase productivity, and drive increased revenue. We work with the heads of each business to identify use cases that will deliver measurable impacts to their organization. My team develops and deploys machine learning models to enable business use cases. We are leveraging generative AI for some of our internal customers’ use cases.
What are the key challenges to your data function that you are facing as its leader?
The technological components of the role of data leaders are highly complex as the speed of innovation is staggering. The foundational role of any data leader is to connect the organization’s data to enable rapid access for creation of data products, delivery of AI use cases, and experimentation.
Cultural challenges remain the biggest barrier to driving data: persistent data siloes, resistance to data sharing, and slow progress. It is important to focus on building the right operating model that fits the company’s culture to ensure that everyone has a common understanding of the value of the company’s data transformation efforts.
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