Enterprise organizations are now realizing the benefits of employing analytics AI (artificial intelligence) to better leverage automation. These organizations are now using AI to learn and reason with the data and information they are gaining from it, in an effort to predict future needs and oftentimes address them before they even arise.

In a recent interview with Mark Newman, Chief Analyst with TM Forum, Shankar Arumugavelu, SVP and Global CIO of Verizon discussed employing analytics AI and Verizon’s strategy towards automation and predictive analytics.

In his interview, Shankar explains their journey to analytics AI and automation as it pertains to Verizon being more proactive with their 143,000 cell towers and 155 million user endpoints by better leveraging over 20,000 data pipelines from over 900 data sources.

What can we learn from this interview?

To move from a culture of diagnostic analytics to a predictive, and even prescriptive one, takes focus and alignment from the entire team. In Verizon’s case, he shares their 4-year journey to leverage predictive analytics at scale by aligning their Center of Excellence comprised of data scientists, data engineers, machine learning (ML) engineers, and data governance team members on the same goal.

In addition, this shift to analytics AI and automation required them to leverage more data. While their data sources were very valuable, leveraging external 3rd party data was also important with predicting events and impacts to sales, operations, coverage, and more. As Shankar shared, “data is more powerful with more data.”

To reach predictive analytics and automation, enterprises need transparency to all of the data throughout the organization. It’s no longer acceptable for sales to only access sales data, or supply chain logistics to only access logistical information. Transparency with all data is key to learning and automating processes.

And finally, Shankar shares how Verizon moved from an artisanal analytics platform to predictive AI leveraging Machine Learning and natural language processing (NLP). Leveraging ML and AI allows for systems and processes to handle issues and events no longer requiring human interview. In fact, with automation in real-time, they are able to improve the outcome of their efforts.

If your organization is considering analytics AI with automation, Live Earth can help. Contact us today to schedule an initial use case discovery workshop.