The movie Moneyball tells the story of how Billy Beane and his Harvard-educated quant whiz kid protégé Paul DePodesta turned the Oakland Athletics into a team that consistently made the playoffs over a number of years. And they did it using data-driven decision making.
The Athletics were near the very bottom of the league in terms of their financial capacity to spend on acquiring talent. Through detailed analysis of every imaginable baseball statistic, the duo uncovered the true underlying drivers of success for a baseball team. They uncovered the massive inefficiency in how baseball talent is priced and were able to exploit this inefficiency to their advantage. Billy and Paul figured out how to gauge and price the true worth of every ballplayer.
Data-driven decision making improves performance
The morale of the Moneyball story is that data-driven decisions result in significantly better outcomes than gut feel, intuition, or conventional wisdom.
And there is research that proves that companies that rely heavily on data analysis are likely to outperform others.
Researchers at the Wharton School of the University of Pennsylvania studied 179 large publically-traded companies. They found that the companies that adopted “data-driven decision making saw measurable improvement in productivity and other performance measures.”
But most companies still use HiPPO and intuition-based decision making
Despite the fact that data-driven decision making positively impacts the bottom line, few housewares companies have switched to this form of decision making. Most companies still base decisions on management experience and intuition.
Most housewares companies use HiPPO-driven decision making. HiPPO stands for “the highest paid person’s opinion”. The term refers to those people who have the final word on any design issue on the basis that they’re the highest paid person in the room.
What’s more, the vast majority of marketers still rely too much on intuition. According to a recent Corporate Executive Board study of nearly 800 marketers at Fortune 1000 companies, marketers depend on data for just 11% of all customer-related decisions. In fact, when the researchers asked marketers to think about the information they used to make a recent decision, they said that more than half of the information came from their previous experience or their intuition about customers. They put data last on their list – trailing conversations with manager and colleagues, expert advice and one-off customer interactions.
Certainly, intuition grounded by years of in-market experience should always be listened to carefully, but it pays to augment even the best intuition with data.
In today’s volatile business environment, judgment built from past experience is increasingly unreliable. With consumer behaviors in flux, once-valid assumptions can quickly become outdated.
That’s why it is so imperative that companies embrace data-driven decision making.
What exactly is data-driven decision making?
If you do a Google search on the term, most of the search results relate to the use of data-driven decision making in education.
In the education world, data-driven decision making is defined as “A process of making decisions about curriculum and instruction based on the analysis of classroom data and standardized test data.”
The practice of data-driven decision making in education has exploded over the last five years as educators have discovered how powerful data can be when promoting school improvement. Data driven decision making has been credited with improving teacher quality, improving curriculum, promoting parental involvement, and narrowing the achievement gaps amongst various student populations.
For the housewares industry, data-driven decision making is the process of making product development and marketing decisions based on the analysis of consumer, marketplace, and competitive data.
But that doesn’t mean that you need to invest in analytics software and new computer systems to process Big Data to get started using data-driven decision making. Unlike Billy Beane and his team who had to plow through mounds of baseball statistics to figure out how to gauge and price the true worth of every ballplayer, the answers to your most pressing product and marketing decisions won’t be found in statistics or Big Data. The answers will be found by talking with and understanding the people who buy and use your products.