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Business Management

Scott Schlesinger (US) - Do Companies Have the Skills to Make Better Decisions?

Predictive analytics can help companies see into the future, reducing uncertainty and increasing return on investment. But is it a tool for marketers or technologists?

Uncertainty can be expensive. Whether it affects the future performance of a product or the viability of a new market, doubt represents a risk to the business. Bad decisions tend to generate a poor return on investment, but the increasing availability of data has improved the quality and accuracy of decision making and in some cases is helping organisations to see into the future. The influence of social media, enabling ever richer customer data, combined with the impact of digitisation, right across the value chain, has sparked a new wave of predictive, data-driven decision making.

The increase in the breadth and depth of useful data is one reason why more and more businesses are turning to methods such as predictive analytics as a way of gaining business insight, and a strategic advantage. For example, media and entertainment companies are starting to understand how data can help to improve box office revenues for new movies by altering the date, the location and even the time of day that the film is released. Set against other historical data, including the revenue streams from similar movies starring the same actors, and how films of a similar genre have performed in the past, analysts can model future outcomes and determine the best conditions for release.

How should companies harness this ability? The line of approach depends a great deal on where the power resides. Which department should control the budget, IT or marketing? Predictive analytics involves statistical modelling, data mining and other complex quantitative techniques. Technical skills, argue some CIOs, should be the responsibility of the CIO's office, particularly since most of the tools used to analyse data are technology driven. But this assumes that IT-focused employees are cognizant of the many competing demands of the business, can assimilate this information at a strategic level, and are customer focused in a way that enables them to translate the data into real benefits for the business. Are IT folk as aware as other employees of the reasons why some customers are targeted in a particular way at a certain point of the sales cycle? If they aren't, they might not be as quick to spot a pattern that either corroborates an established strategy or points the way to a different approach.

Interpretation of data is as much an art as it is a science. Although advanced statistical and quantitative techniques are needed to spot unusual patterns, it takes a certain amount of creativity and strategic awareness to turn data into insights that can be acted on. That requires not only a strong culture of using data-driven methods to reach business decisions, but also personnel who are comfortable with solving both technical and business problems. This raises a barrier. Marketing departments tend to be filled with creative people, usually with a holistic view of the organisation's objectives, but often little grasp of how complex mathematical modelling can help them to achieve those objectives. Conversely, as a discipline, IT tends to attract more introverted, technically gifted, yet siloed people, who sometimes lack the creative edge to turn data into knowledge. Crudely put, technicians know how the tools work, but not how to apply them.

This is changing, of course. Today's CIO plays a far more strategic role than ever before and must add value to the business as well as manage technology. But beneath the c-suite is a skills gap. The short supply of both technically-proficient marketers and business-focused technologists threatens to undermine companies' ability to make accurate data-based predictions. In the short-term, organisations might conceivably ask where the budget for predictive analytics might sit. But in the long-term, the focus must switch to more holistic recruitment, which recognizes the fundamental shift in thinking that data-driven decision making requires.

As the breadth and depth of data continues to grow, demand for broader-skilled employees will continue to outweigh supply. Education and training must prioritise multi-faceted learning to address the gap, while companies must break down internal silos that serve only to propagate damaging stereotypes. Collaboration across disciplines, regardless of background, is the only solution. Marketers must become better technologists; technologists must become better marketers. If organisations wish to tackle uncertainty with data, they must first learn to integrate their thinking.

By Scott Schlesinger, Head of Business Information Management for North America, Capgemini

 

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