Spring training is in full swing. It used to be that finding baseball talent required a seasoned eye and an instinct honed by time. For decades, professional scouts traveled the country -– and in some cases the world -– watching up-and-coming players for signs of the skills that would propel them to major-league superstardom. Scouts learned to sort through average prospects using traditional measures of talent and conventional wisdom, and pair phenoms with the teams that could best use their skills.
Then, in the 1960s, everything began to change. The rise of sabermetrics, or computer-aided analysis of baseball performance on the field, not only started displacing scouts in the recruiting process, it demonstrated that the measures of talent historically relied upon by baseball insiders were not as indicative of future success as they had previously been thought. As a result of this insight, traditional metrics such as batting average and runs batted in (RBI) today are less important than measures that lead to runs or team wins in the scouting process.
Increased use of analytics in baseball has led to tougher competition and a smaller margin for error -– even among the best athletes in the sport. But for all the advantages sabermetrics offer, they have had the opposite effect on the prospects of professional scouts. Their unique, and often subjective, perspective holds a diminished place in the recruiting process today. In a January article run by USA Today Sports , Bob Nightengale wrote, “Teams are relying more heavily on analytics and sabermetrics than at any time in baseball history, with teams treating veteran pro scouts as if they’re old eight-track car stereos, needless in today’s game.”
Baseball is not the only “sport” being materially altered by a greater reliance on data. Corporate competition is changing rapidly in the face of modern analytical capabilities. Just take a look at the growing phenomenon of Industry 4.0, the next phase in manufacturing, considered by many to be the fourth industrial revolution. Plentiful cross-functional data will influence how connected, integrated enterprises gauge performance and their decision-making on what’s best for them.
Despite the impact baseball analytics has had on pro scouts, that is not a reason to ignore data’s potential -– once a capability becomes available and is applied to great effect, there is no turning back the clock. The same holds true for business and manufacturing analytics. As more data becomes available, companies need to be receptive to the revelations of analytics -– even when they contradict traditional wisdom.
The question that must be answered, however, is what the balance of talent and technology needs to be moving forward in any organization or function leveraging the power of analytics. It is impossible to deny that data and analysis play a strategic role in any business. But some responsibilities will always need to be addressed by a human with the right background and skills to apply data