It is a term used to generalise a wide range of analytical tools and approaches from mathematics, computing and domain specific knowledge.
Is it new?
No, the roots of data science pre-dates the introduction of the computer, however, its wider adoption has grown with increasing access to more powerful computers and availability of more diverse and comprehensive data.
How is data science different from business intelligence?
Historically, business intelligence focused on data collection, quality, and security and providing ‘hindsight’ using dashboard reporting. Data science significantly expands on this capability, using a broader range of analytical approaches and machine learning tools to derive insight and decision support from data. This creates opportunities to deliver new services which were previously uneconomic and, automate tasks previously performed by both skilled and unskilled knowledge workers with a higher degree of accuracy, in less time and at lower cost.
Why should I act now?
Data science is driving the next revolution in organisational productivity. Successful organisations are those who introduce a culture focused on efficient and effective collection of data, use it to develop insight and drive change based upon that insight. Very successful organisations are those who can automate the process, applying data science to revolutionise the way services are delivered.
Great, I’ll ask the IT or Business Intelligence team to follow up on this!
This may be the correct choice. However, they will find it hard to realise the benefits of data science unless the culture of the organisation changes; and this will need the full co-operation of the board, senior executives and middle management. Without strong senior level leadership, it will be difficult to deliver the necessary change in organisational culture.
So, what would the organisation look like in the future?
To fully grasp the implications of data science (alongside the internet of things and robotics) imagine an organisation with no people, only machines. Ultimately, that is the goal – unlimited capacity to meet customers’ needs, anywhere, anytime. Whilst that may not be feasible in your organisation now, it will be in the future. The immediate goal is to work out which parts of the organisation can best benefit from data sciences, and how the relationship with customers, employees and suppliers will change.
That’s a great vision, where do I start?
All great businesses have a clear vision and understanding of their customer’s needs. Data science can help you understand you customer’s better, and the risks and issues the organisation is facing in meeting those needs. If you don’t have a clear view of where you need to go, then data sciences will only get you to the wrong place faster. Only once you know what your customers need and where you must go, can you use data sciences to improve the effectiveness, efficiency and flexibility of services.
So, how can I buy this as a solution?
Whether you develop your own solutions or buy them based upon data science approaches is a strategic decision for the organisation. Whichever route you take, you will need people with an understanding of data sciences to work with the organisation to identify and evaluate the most effective options.
Data science presents a tremendous opportunity to improve productivity and performance within an organisation. It needs to pervade the organisation and, whilst it may start as a small embryonic team, the approach, skills and knowledge need to infuse into all departments. Acquiring and maturing data sciences should be at the top of every organisations list of priorities.