Big Data: A Competitive Advantage or a Competitive Necessity?
Monday 1st October 2018
For several companies, data has always been a key asset; however, over the last decade it has become critical. The means in which data is analysed has become an important competitive advantage for a wide variety of industries.  To become and remain competitive, enterprises must seek to adapt advanced analytics, and adapt their business models, establish specialist data science teams and rethink their overall strategies to keep pace with the competition. With the amount of data now apparent within every sector and function of the global economy, should it be considered a competitive advantage or a competitive necessity?
 Hilary Mason, founder at Fast Forward Labs, claimed “The core advantage of data is that it tells you something about the world that you didn’t know before. As your competitors learn more, you’ll need to learn, too.” Big Data is a collection of data from traditional and digital sources which is available both in structured and unstructured form, the difference being that structured data is organised in a mechanised and manageable way.  The use of Big Data will become the basis of competition and growth for individual firms, enhancing productivity and creating significant value for the world economy by reducing waste and increasing the quality of products and services.
Advantage or Necessity?
Organisations look for the most innovative and impactful methods to gain an advantage over their competitors in an ever-changing market. Due to the recent rise of Big Data more organisations are looking to this as a means of getting ahead of their competitor.  As the pace of business continues to accelerate, forward-looking organisations are beginning to realise that it is not enough to analyse their data; they must also take action on it. Big Data provides opportunities for more measured decision making throughout most departments, including advertising, human resources, marketing and media.  It tells us who our customers are, how they spend their time, what kind of products and offers engage them.
With the amount of data available to organisations constantly rising, it is important to understand the difference between useful data and data which will be distracting. According to Max Shron, founder of Polynumeral,  “It’s not how big the dataset is, but how detailed (or fine-grained) it is.” The accuracy of the inputted data is vital in receiving results which will have a positive impact on decision making. Many companies aren’t in a position to put resources behind their analytics team and have opted to outsource their data. Some companies make the mistake of gathering the data and passing it to a data scientist before waiting for results. It would be more beneficial to include the data scientist prior to gathering the data as you can come to an agreement as to what kind of data is required and what can be built from the results.
Naturally, Big Data is associated with market leading firms within the digital economy such as Amazon, Google, Apple and Samsung. Jeff Bezos, founder of Amazon, was among the first to understand the importance and the new rules of data. His success is further proof that the digital economy and data holds the key to competing in a congested market. Bezos believes that to thrive in the digital economy organisations must  obsess about customers, invest for the long term, exploit your network of customers to grow further, and focus on delivering the best customer experience and the lowest price via an online platform.
Investment banks generate more data than any other type of organisation due to the large number of transactions entered into daily. In a move that indicates an awareness of this burgeoning market, Goldman Sachs recently announced plans to invest heavily in Kensho - a Big Data Analytics start up. Market leaders within the financial services must either embrace Big Data or be replaced by those who do. Investment banks  mainly use Big Data Analytics for potential areas for investments, identifying potential companies for mergers & acquisitions, research, fund/asset management, and trading. The availability of Big Data technology reduces the possibility of human error which gives rise to better decision making and predictions for investment banks.
 Big Data is not confined to the cluster of companies that we know, somewhat imprecisely, as the tech industry. Rather, it describes a particular way of acquiring and organising the information that is becoming increasingly indispensable to the economy as a whole. With the price of computers and data storage significantly falling, it is possible for smaller organisations to collect and analyse data that would have been too expensive beforehand. There are also tools now available that eradicate the need for a large investment in personnel and infrastructure. It is this increase in technology and reduction in cost which is pathing the way for Big Data to shift from a competitive advantage towards a competitive necessity.
Restrictions of Data
Data is now a vital component within the wider economy; it is therefore understandable that there are restrictions to its use. The introduction of the General Data Protection Regulation (GDPR) on May 25, 2018, which intends to give consumers better control of their personal data as it’s collected by businesses, was designed to preserve data privacy of the European Union’s own citizens.  The biggest way GDPR legislation is likely to affect data collection is that it will lead to an increased reliance on real-time analytics. With an instant turnaround, there will be less requirement to hold on to unnecessary data for a long period of time which may increase the risk of a GDPR breach.
 Another key question is how far personalisation should go, and at what point does data collection stray into invasion of privacy? In some instances, the use of Big Data can be very convenient for consumers; a simple example of this is the personalised suggestions on Netflix based on shows which were previously watched by that individual. Some airlines are looking into the possibility of using Big Data to be more personal on flights. Ideas such as offering a customer a certain drink as this is what they have ordered on their previous three flights. Some individuals may feel that this is a slight invasion of privacy, whereas others may enjoy the “improved” customer service. It is important that organisations know exactly where to draw the line.
 There are also many technological issues that need to be resolved to make the most of Big Data. Formats, legacy systems and incompatible standards often prevent the integration of data and the application of the more sophisticated analytics that create value. Large datasets, which are referred to as “silos”, often amass within different departments of an organisation. For example, Research and Development, Human Resources and Operations departments may each have their own collection of data. The data would be more beneficial if it was shared throughout the departments and better-informed decisions could be made regarding the understanding of customers and the understanding of the market itself.
The trustworthiness of data also bodes another problem in that the digital world can be somewhat anonymous.  If you do not know the provenance and integrity of information and data, how can you trust their veracity? It could be argued that unless the data is completely accurate, results and decisions may be partially erroneous. On the other hand, it is argued that with trusted data it is possible to find out information about the wider economy in much more detail than ever before.
“Europe-wide” Big Data Strategy
To fully understand the importance of Big Data as a competitive advantage for organisations it is beneficial to consider Big Data on a greater scale. On a recent visit to China, French President Emmanuel Macron called for a Europe-wide strategy regarding Big Data and has made it a priority for France.  To compete in Big Data, AI and other technologies, Mr Macron called for a European market including protections of individuals’ legal rights and a definition of what were legitimate commercial rights.
The United States of America is very much the leader in terms of Artificial Intelligence (AI) and Big Data; however, due to China’s greater population and access to data, their advances in technology should also be considered. Russian President Vladimir Putin has also emphasised the importance of Big Data as he believes the leader will become the “ruler of the world.”  It takes three things to be a world-class AI power: the most advanced algorithms, specialised computing hardware, and a good supply of the raw material that machine learning systems depend on – data.
Should Big Data be considered a competitive advantage or a competitive necessity? Big Data will become the basis for competition and growth and is used as a means of improving the quality of goods and services. It is simply not enough for organisations to analyse Big Data, they must also take action. Big Data provides us with information about who our customers are and what kinds of products engage their attention. With the amount of information now available, it is important to have the knowledge to extract data which will add value and avoid data which will simply act as a distraction. Big Data is often associated with the market leaders of the digital economy such as Google and Amazon; however it is not confined to the tech industry alone. Due to the reduction in cost of computers and data storage, smaller firms can also collect and analyse their data.
The recent introduction of the General Data Protection Regulation, which was intended to preserve data privacy of the European Union’s own citizens, has resulted in an increased reliance on real-time analytics. In terms of personalisation, organisations must ensure they know the difference between consumer convenience and an invasion of privacy. Organisations must also ensure their data is inter-departmental, rather than individual silos, in order to improve decisions and have a better understanding of the market itself. Data can be somewhat anonymous; however if the data is trusted, it can be extremely advantageous.
Big Data is considered a competitive advantage, although the shift to a competitive necessity is currently underway. With a rise in technology and a reduction in cost, even smaller organisations should be considering Big Data as a way of improving decision making.  As information becomes more readily accessible across sectors, it can threaten companies that have relied on proprietary data as a competitive asset. The next five years will be crucial for organisations and Big Data, and there is no doubt that it is fast becoming a competitive necessity.
Daryl joined FinTrU in October 2016 through our Fourth Financial Services Academy after graduating from Queens University with a BA (Hons) in Management and Business Studies.
Upon joining FinTrU, Daryl started work on a client outreach project for a Tier 1 Investment Bank and has since transitioned into the legal team. Daryl has worked on various regulatory projects including the EMIR/CFTC Variation Margin rules, MiFID II and is currently working as part of the Contractual Terms Risk Management team. As part of his role Daryl has drafted legal documents or amendments, whilst negotiating with clients and in his current role, he is responsible for the front to back risk management of all data contained in client contracts.
Daryl has completed all three modules of the CISI Investment Operations Certificate, studying an Introduction to Securities and Investments, UK Financial Regulation and Derivative Operations. Daryl is currently working towards a Diploma in Capital Markets.