January 6, 2016

What Does 2016 Mean for Data Science?

Mike Weston


I don’t imagine many people outside the tech bubble realize how much their lives were impacted by data science in 2015. Amazon (NASDAQ: AMZN) recommendations, marketing campaigns, IoT tech, Uber, Siri, price comparison sites, gaming and image recognition, are all fueled, to varying degrees, by data science. Plenty more is going on behind the scenes. However, it would be a stretch to say that data science is ‘mainstream.’ The profession still has much more to prove. 2016 will undoubtedly see a series of interesting developments, both in the application of data science and changes to the industry.

In finance, the algorithms that underpin these systems are largely powered 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 personalization 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 prioritizing 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.

I strongly believe that 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 full name. The personalization that information from social media platforms enables has opened the door to a huge swathe of new marketing opportunities.shutterstock_data_scientist_lassedesignen

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 personalized 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 personalization 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 some strong head winds. First, a new “Safe Harbour” agreement seems a long way off. In October, the US Senate passed The Cybersecurity Information Sharing Act. The 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 EU confidence around online privacy standards in America.

These decisions taken together, along with the Microsoft (NASDAQ: MSFT) judgement (more on that later), have created a situation 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 center 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 be appealed, therefore, expect this issue to rumble on for the rest of the year.

Third, save for the creation of a “killer app,” the IoT is not going to gain widespread adoption in 2016. The trend is likely to hit the “trough of disillusionment” as hype dissipates and manufacturers focus on creating more useful products. Similarly, smart cities are not going to explode into existence in the next twelve months. The technological and financial challenges inherent in creating a truly “smart” city are staggering.

Despite these hurdles, there is plenty to be merry about this year if you’re a data scientist. 2015 was a breakthrough year and the next 12  months should see impressive growth for the sector. The profession as a whole will continue to get stronger as more people join its ranks, existing practitioners get more experience and new techniques are developed. Mike Weston

About the author: Mike Weston is CEO of the data science consultancy Profusion. He previously worked at Digital Oxygen, Silverpop wunderloop, and Lyris. Mike was educated at the University of Auckland and has spoken at events in the UK, United States, and across Europe.

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