It is called the “fall forward” effect. Much like “The Wave” at a sporting event, participants lean far forward on their chairs in near unison. The entire room shifts at once to identify themselves within the organization’s network map, each employee seeking to understand their level of connectivity and importance relative to their colleagues. This was a real moment of truth for the Fortune 100 (F10) company focused on making training more relevant and nimble. With 25,000 employees operating in a rapidly changing industry, the talent development team needed to address the ever-changing business landscape. To do this, they were seeking to improve their High Potential Leadership and Development programs with data-driven results.
This proved to be a greater challenge than they imagined, despite overwhelming support from senior leadership to try anything new. F10 experimented with educational apps, network analysis, crowdsourcing technologies, manual group creation, and external design thinking consultancies. Over the years, it dabbled in a multitude of innovative solutions with varying degrees of success. But nothing helped to improve and sustain critical measures across the board or could be used as a solution that would be universally adopted by all teams.
Eventually, one of the program leaders came across a data science approach. Leveraging network science, big data, machine learning, and artificial intelligence algorithms, program participants could be understood within the context of teamwork, collaboration, and connectivity. This data science was the right approach for F10 because it complemented its big data and network analysis results-driven culture. While past vendors had been employed for specific analysis, none had delivered or answered the “now what?” once the data had been analyzed. The data science offering was designed around the data with practical solutions for easy implementation. In addition to creating high-performance groups, the data science solution identified each person’s networking journey, allowing participants to connect in areas of interest, as well as expand their networks.
As a large, conservative organization, the data science approach was a slow, controlled integration. Highlighting the importance of networks and data to future training and success, the data science solution was introduced during an employee training event. With interest piqued, attendees saw a personalized network analysis for each employee involved in the session. Hence, the “fall forward” event. Further distilling this output, trainees were intentionally networked with their peers in successive learning rounds. During these sessions, data was paired with specific content or educational modules to enhance effectiveness and long-term potential. Leveraging their data, connections, relationships, and learnings, employees then had the opportunity to develop their strategic network plan to personalize the enhancement of their career.
Results
As a result, all metrics across the board for the corporate and development training programs improved as much as 11 percent year-over-year. Based on the overall quality of class programming to the applicability of learnings in the workplace, data science was considered a great success and continues to be expanded across the organization.
As the original class continues to progress within F10, some of the classmates have been given access to the data science solution. These employees are tracked as they continue through their training curriculum. This ensures that they are making the right connections to drive success for themselves and the organization.
Brandon Klein is a partner at Collaboration.Ai, intelligent high-performance team creation for the connected age. The company’s People Science Engine coupled with Design Thinking offers the opportunity to unleash the Power of People in an organization, event, meeting, conference or educational institution. Collaboration.Ai’s proprietary Artificial Intelligence tech leverages the whole individual to improve team dynamics and enhance network connections. For more information, visit https:collaboration.ai.
