“The problem we’re trying to solve is that there are rich teams and there are poor teams, then there’s 50 feet of crap, and then there’s us. It’s an unfair game … Like we’re looking for Fabio. We’ve got to think differently!”
The central lesson from the above quote, voiced by Billy Beane in the movie “Moneyball,” is that analytics can be used to level the playing field and gain competitive advantage. In a competitive market, the ability to identify, retain and develop talent can make or break an organization.
Prior to the 2002 Oakland Athletics and team General Manager Billy Beane, the conventional wisdom in identifying talent in baseball accepted a misleading set of metrics — stolen bases, runs batted in and batting average. By employing new metrics based on validated statistics instead of tradition, the Athletics went from being cellar dwellers to contenders. “Sabermetrics,” a form of analytics, is now common practice in baseball for talent identification and management.
The science of predictive analytics also has the potential to revolutionize talent identification and development in a business environment. When combined with next-generation learning platforms, predictive analytics can go further by providing firms with new opportunities for enhancing teamwork, collaborative learning and organizational development.
Traditional business intelligence provides data after the fact. Predictive analytics provides a lens into the future by uncovering hidden patterns and forecasting future outcomes. This ability opens up an entire dimension for optimizing organizational capability and competitiveness.
Predictive modeling starts with a set of machine-learning algorithms. To put it simply, machine learning takes an existing data set as a starting point, sifts through it for hidden patterns, then uses the patterns to generate predictions about the future. But instead of relying on HR-related systems for data, learning platforms represent an untapped source for deriving insights into employee strengths and weaknesses.
Leading companies already provide their employees with opportunities for online training and professional development. Organizations that leverage predictive analytics within their learning programs have the opportunity to take talent management to the next level.
Imagine a team of managers collaboratively needing to solve a negotiation problem in the context of an online or hybrid training program. Do certain behaviors and interaction patterns reveal managerial strengths and weaknesses?
Another central lesson from the “Moneyball” story is that traditional metrics overvalued stars and undervalued performers who advance team goals. Using machine learning techniques similar to those employed by online retailer Amazon to identify and rate customers based on their purchasing history, organizations can identify hidden talent and grow that talent to match their needs.
The most exciting area of development in predictive analytics is using data to advance collaboration skills and teamwork. The highest performers by nature are team-oriented and thrive in collaborative environments. But because they often don’t call attention to themselves, high performers can be undervalued and often go unrecognized.
Using data mining in the context of learning programs can help identify hidden talent within the organization. Conversely, employees who lack high-performance skills can receive feedback and training opportunities as part of a well-crafted talent management program.
With challenges in the current global financial climate, organizations are searching for ways to optimize their performance and remove ambiguity around employee performance. Analytics is a way to quantify what in most organizations is based on subjective perspectives. Predictive analytics allows companies to build a new culture of leaders based on teamwork, collaboration and creativity.
The untapped potential within an organization can be immense. Finding those opportunities by harnessing the power of predictive modeling is the key to guiding an organization to the highest levels of success.
Alfred Essa is director of innovation and analytics at Desire2Learn, a provider of enterprise e-learning products. He can be reached at editor@CLOmedia.com.Filed under: Leadership Development, Measurement