What talent are you chasing for your DS and Analytics teams to leapfrog competitors? The best data architects/modelers, or the best framers/storytellers? Or a combination?
Companies are increasingly engaging in innovative corporate strategies and challenges that stand to greatly benefit from academic inquiry. Firm boundaries are constantly being reconsidered by both digitally native firms (like Google and Amazon) and more traditional firms (like Comcast and McDonald’s) alike. New technologies and applications, such as ML, blockchain and AI are influencing corporate data and analytics strategies in ways that are only partially understood. It’s critical that enterprises foster a true, learning-based conversation around the effective use of such technologies and the framework that should govern their use. By no coincidence, there is an increasing number of corporate/academic alliances that provide scale and scope to address the need for better, data-driven decision making. Many companies have fundamentally shifted how academics and industry are fostering collaboration to streamline business value, talent pipelines and innovation. Key components shaping this trend are the need for unicorn talent integration into teams, selecting the correct rabbit holes/questions to answer, and fostering an adaptive business culture. Companies are recognizing that a handful of artful storytellers are the last puzzle piece needed to maximize the investment in DS unicorns, data lakes and terabytes of data.
Gain insight into how organizations are successfully utilizing academic partnerships to:
• Create collaborative data sharing and analytic inquiry approaches beyond technical infrastructure
• Leverage learning partnerships in talent investments
• Challenge corporate culture and status quo
• Balance quick wins vs. long term projects
• Influence IT capital investments/ROI
Executive Director, Wharton Customer Analytics
The Wharton School, University of Pennsylvania