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Getting Rid of Guesswork – Taking the Moneyball Approach to Business

Financial services is a sector built on risks that have to be balanced out with reward. It’s an industry, however, that has always underpinned the “gut instinct” decisions that drive the industry with data science. Finance, after all, is no place for guesswork.

Posted: 28th May 2020 by
Jil Maassen
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With the entire industry currently under pressure due to uncertainty, data must lie at the core of every decision any business makes if it wants to succeed. In fact, research from McKinsey tells us organisations that leverage customer behavioural data and insights outperform peers by 85% in sales growth and more than 25% in gross margin. Jil Maassen, lead strategy consultant at Optimizely, offers Finance Monhly her thoughts on how data experimentation can be used to drive financial services forward.

The game-changing nature of data

One of the best examples of risk and reward, based on data science, comes from the world of baseball. Back in 2002, Billy Beane, general manager of the unfancied Oakland Athletics baseball team, spawned an analytical arms race among US sports teams. Working under a limited budget, Beane used obscure stats to identify undervalued players — eventually building a team that routinely beat rivals who had outspent them many times over.

Data analytics turned the game on its head by proving that data is an essential ingredient for making consistently positive decisions. The success of the bestselling book and subsequent Oscar-winning film, Moneyball, based on Beane’s story, took data analytics mainstream. Today, financial services companies are applying a “Moneyball” approach to many different aspects of their business, especially in the field of experimentation.

Data analytics turned the game on its head by proving that data is an essential ingredient for making consistently positive decisions.

We live in testing times

Experimentation departments for the purposes of testing, also known as Innovation Labs, have been growing at a prolific rate in recent years, with financial services seeing the highest rate of growth according to a survey by Capgemini. By the end of 2018, Singapore alone had 28 financial service-related Innovation Labs. Alongside this, research from Optimizely reports that 62% of financial services companies plan to invest in both better technology and skilled workers for data analytics and experimentation.

Areas such as fund management are no strangers to data analytics. But since the fintech disruptors arrived on the financial services scene, legacy banks are now using data in combination with experimentation to evolve other elements of their business and remain competitive. Many have found that this is helping them to address common concerns, including how to improve customer experience and successfully launch products to market. So much so, that our research found that 92% of financial services organisations view experimentation as critical to transforming the digital customer experience. In addition, 90% also consider experimentation key to keeping their business competitive in the future.

Eat, sleep, test, repeat

However, experimentation takes patience. As Billy Beane said when his strategies didn’t deliver right out of the gate: “It's day one of the first week. You can't judge just yet.” He was ultimately vindicated. Like any new initiative, experiments can fail because of cultural “organ rejection.” They require taking short-term risks that don’t always work, all in service of long-term learning. It’s the job of Innovation Labs to take these risks, and often, one for the team, by being prepared to fail.


The point is, when you're transforming something and making massive change, not everyone is going to understand right away. The best way to convince people that your theory is correct is to show them — not tell them — you're right. Experimentation initiatives in business, and especially in financial services where risks and rewards have high impact and return, allow new ideas to be proven right before they play out in front of a paying public.

Founded in facts and stats, experimentation promotes an ethos that is key in adopting new technologies and utilising data analytics to build roadmaps for the future. As the amount of data companies have access to increases, the ethos of experimentation will only become more important for predicting and changing the future for the better.

Experimentation is about measuring and learning and repeating that process until optimum results are achieved. The final word in this regard should perhaps go to Beane himself; “Hard work may not always result in success. But it will never result in regret.” His story is something that all financial services organisations can learn from.

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