It’s the disrupter behind the disruptors and the decade’s ‘sexiest’ industry. But data science is more than a buzzword. From stock trading to facial recognition, data science is behind the wheel of countless solutions once driven by human capabilities – and it’s not slowing down.
Wherever there is data and patterns to be discovered, there is a need for data science – and the continuous chain of data and resulting insight makes for a self-sustaining ecosystem.
In today’s digital revolution, it is seemingly impossible for organisations to stay ahead of all available information. They need smart technologies that sift through, analyse and bring relevant information to the surface – right to the people who can make sense of it. True data science is not about creating or having more data, it’s about equipping organisations with the tools and resources to manage and use it effectively– in a way that drives business results.
Data science is a dynamic, multifaceted field – a blending of technology and human insight. To unleash the power of data science, therefore, organisations must take a dynamic approach – specific to their goals and needs. Organisations must evaluate what they want to achieve and then explore different strategies. For some, data science means investing in the right people – building and refining integrated, in-house data science teams and embracing a data-driven transformation. Others are investing in the right tools – relying on outside consultants and experts to lead the way.
Data scientists are a hybrid breed – combining the technical expertise of a data analyst with the business acumen of an entrepreneur. They delve through disparate data sources to uncover hidden insight and recommend ways to apply data to gain a competitive advantage or address a business problem. Data scientists must bridge the gap between the organisation’s technical infrastructure and wider business goals and integrate the functions and responsibilities of every member of the C-suite.
Organisations, however, cannot expect it all from a single “Chief Data Officer”. Data science is a team sport. It requires a diverse roster – one that combines a variety of skills – from analytics and data management to design and entrepreneurship. Data science teams must have employees who can collect the right data, but also those who ask the questions needed to drive business outcomes. They need members who can understand that data and present it visually to other parts of the organisation and others who can support privacy and security efforts. These skillsets might already exist within your organisation, perhaps in unexpected places. Pulling it all together requires businesses to rethink their existing teams and to be open to new ways of doing what’s been done.
A data-driven business approach impacts every aspect of the organisation – from operational procedures and internal logistics to the efficiency of product development. It’s up to business leaders to ensure that all teams are prepared for the trickledown effect of this data transformation. As data reveal new insight into areas where operational efficiencies can be achieved, CEOs must embrace emerging opportunities and encourage support from within the wider businesses. This includes promoting the continued integration of and collaboration between the various C-suite roles.
Taking a new approach to data may usher in a broader cultural change within your organisation. Executives and wider teams may have to adjust to operating under a new set of rules and leaders must ensure that teams are open to doing things differently.
Technology is no longer the sole domain of the CIO or IT department – it’s a critical component of almost every position in today’s digital economy. Ensuring that the entire organisation embraces this transformation is critical to realising the revolutionary power of data science.
Data science is no longer just for major enterprises. Every business, from a global brand to a street corner market, generates data that can be used in meaningful ways. While not every organisation is capable of rounding up an in-house data science team, new tools are making it easier and more affordable than ever to collect and analyse data – levelling the playing field for smaller and less data-focused organisations.
This excerpt is from Business Spectator. To view the whole article click here.