Data Science

How will data science change in 2016?

2015 was a good year for data science. A cursory glance at any tech jobs board reveals the sheer breadth of companies looking for data science expertise. Technical terms such as machine learning are slowly entering the public consciousness. Many people still don’t realise how much data science touches their everyday lives, from Amazon recommendations to the algorithms powering their Uber app. With adoption of data science up across most business verticals, it’s natural to wonder how the sector will develop in 2016. My gut feeling is that it will be the year data science proves its worth on a spectacular scale.

Many of the systems in financial institutions are underpinned by data science. Indeed, the financial industry is one of the pioneers of data science techniques. Nevertheless, the adoption of data science has been far from uniform across all banking services. In 2016 I expect this picture to change. Better use of data and personalisation of services will move from the financial markets to retail banking. It will have a profound impact on marketing, customer service and product development.

Atom Bank has already announced its intention to use data models to predict its customers’ needs. It’s worth noting that Atom Bank’s model of prioritising mobile services over bricks and mortar branches is, in the long-term, likely to be adopted by most major banks in the UK. However, such a move will require large scale investment in IT infrastructure, something that is notoriously difficult to get right in financial corporations with bespoke legacy infrastructure.

Data science will inform the best marketing initiatives next year. Targeting has got much more accurate, thanks to a better understanding that collecting the right data goes way beyond an email address and a first name. The personalisation that information from social media platforms enable has opened the door to a huge swathe of new marketing opportunities.

By marrying information from traditional sources and social media, with other dynamic data sets such as weather, economic news, major events, and in-store activity (for retail), ultra-targeted and personalised marketing becomes a reality. The issue of joining the world of in-store marketing and online marketing could finally be solved, much like the difficulties around multi-platform marketing have been largely surmounted.

Underpinning the explosion in mobile advertising and ever more impressive personalisation is the surge in the number of marketers intelligently using data. Indeed, it is this growth in ‘data-savviness’ by marketers that will inform many of the major changes we are likely to see in 2016.

Use of data science within the insurance sector will also continue to take off. The most exciting area of development is the use of wearable technology to better monitor and assess health and wellbeing. Not only will this help to give health insurance companies more useful information, it will also have a growing impact within the HR and recruitment function of some pioneering businesses.

Don’t expect it to be plain sailing for data science in 2016, though: there are a number of head winds. First, a new Safe Harbour agreement seems a long way off. In October, the US Senate passed The Cybersecurity Information Sharing Act. This act should make it easier for US companies to share data with American security agencies. Given that around seven different US security agencies employing thousands of people could access and share this information, the result is to significantly erode online privacy standards in American.

These decisions taken together, along with the Microsoft judgement (more on that later), have created an environment where the US and EU are going in completely different directions on data protection and, by extension, data security standards.

The consequence of this fragmentation is likely to be serious disruption in the free movement of data across the world. For businesses, this means increased restrictions on how they manage and use data, resulting in higher costs both in relation to infrastructure and compliance.

Second, the Microsoft case should reach a conclusion in January. If the Federal Court in the US rules against Microsoft and allows the US Government to access data held in a data centre in the Republic of Ireland, we should expect serious repercussions. Cloud computing businesses will be the most severely affected and a dangerous precedent that other governments could follow could be set. Whatever happens, the case will probably be appealed, so expect this issue to rumble on for the rest of the year (and beyond).

However, these issues are unlikely to derail the strong development of data science over the next twelve months. More businesses are going to undertake innovative applications of data science, strengthening the profession by providing valuable experience and thought-provoking case studies. This will create a virtuous circle, prompting more people to become data scientists, increasing the talent pool and spurring more innovation.

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