More and more companies are using data in transversal ways, so it is essential for organisations to hire professionals who possess both analytical and business skills. For professionals of this profile, leadership capacity is also a must. This was one of the main conclusions of Data + Decisions 2019, the second annual conference of the ESADE Institute for Data-Driven Decisions, where various experts discussed the importance of analysing data to make better business decisions.

“We are starting to see the democratisation of analytic transformation,” declared Manu Carricano, Director of the ESADE Institute for Data-Driven Decisions. “In this new phase, cultural change will be essential. People, and the hybridisation of their competencies, will be at the centre of this change. At the same time, it is important for analytics professionals to develop strong business skills. Moreover, both strategic and tactical decisions have to be made on the basis of models and evidence.”

With the aim of defining the skill set of professionals and companies that work with data – and in particular, the skills most valued by the sector – the ESADE Institute for Data-Driven Decisions presented a methodology called the Data Literacy Index, which was created with the support of the Outliers Collective. This innovative technique, presented in a pilot format, provides a multi-level vision of the maturity of people and companies in terms of key competencies for analytical transformation. The technique promises to help companies and workers understand what aspects they should focus on developing.

Leadership, management and mathematics: the keys to success in business

As companies progress in their analytical transformation, leadership skills – strategic vision, governance, leadership, influence and ethics – become increasingly important. Other competencies valued by the sector include decision-making capacity – which includes the ability to transform data into action and to anticipate multiple scenarios – and mathematical and statistical knowledge in areas such as machine learning, statistical models, data analysis and algorithms.

The respondents surveyed as part of the pilot project agreed that they needed more training to develop the necessary skills for working with data. José Miguel Ibáñez, Big Data, Analytics and Data Science Lead at HP, commented: “Data are a language that will soon be used by everyone. We need to learn to understand what people are trying to say with the data they generate.” Louis Dorard, founder and chairman of the PAPIs.io international machine-learning conference series, commented: “The difficulty is not developing data-management models but learning how to integrate these models to solve people’s problems.”

Art Langer, Director of the Center for Technology Management at Columbia University, highlighted the need to experiment, innovate and take risks, even if they could lead to mistakes. “Data should not be used to do the same process in a new way,” he argued. “They should be used to innovate.”

The conference also featured the participation of Uri Simonsohn, Professor in the Department of Operations, Innovation and Data Sciences at ESADE Business School; Diego Villuendas, Head of Data and Analytics at SEAT; José Miguel Ibáñez, LFP Big Data and Analytics Manager at HP; Andrea Taverna, Operations Research at Zalando; Patricia Junyent, Business Analytics Country Manager at Rebold; Javier Lombana, Customer-Facing Data Scientist at DataRobot; Julián Rincón, Behavioural Economics Global Lead at BBVA; Xavier Guardiola, Data Science Team Lead at King; and Iasa Monique, Creative Strategist at Domestic Data Streamers.