Digiterre’s Rajesh Jethwa is named in the top 30 of the 2023 CIO 100
It’s easy to feel overwhelmed by the hype surrounding big data which can feel like an overwhelming flood at times. Many organisations, though, are not barricading themselves in; they’re seeing the potential benefits, making waves and grasping the business opportunity.
See it at its simplest as data with high volume, high velocity and high variety. It observes and tracks what happens from various sources that can include anything from business transactions or social to information from machine-to-machine or sensor data. This creates huge volumes of data. It streams in high speed and requires processing in a timely way to produce near or real time results. It also comes in formats which may be either structured, numeric as in the traditional database, or in unstructured text documents or in video, audio or email formats.
Its value is forecast to be worth £322bn to the UK economy alone by 2020 (Source: SAS and Centre for Economics and Business Research). Not only is its volume and value huge, but its growing exponentially, fuelled by the growth in digital platforms and processes, used in business process management, to the boom in multimedia, dependent on smart devices and social media.
Whilst small data is ‘small’ enough for human comprehension, ‘big’ data trumps small data and relational databases that have existed since the 1970s in many different ways. It’s:
The outcomes of these technical benefits feed through to commercial benefits that can touch all parts of a business:
Big data’s use with financial data can identify growth opportunities, previously unseen. Whilst marketing departments are clearly involved, finance departments are also in a good position – and have better access to data – to analyse cost to serve across multiple dimensions of a business – such as products, customers, services, channels – and to analyse pricing strategies and where to optimize profitability and growth.
Big data validates the assumptions that go into business forecasts, and allows commercial and finance departments to come up with more accurate views of how events in the market and internally will impact the company’s performance and thus its competitive position. A data-driven finance department can better look forward and identify leading indicators.
Tools such as Hadoop and Cloud-Based Analytics can bring cost advantages to businesses with large amounts of data being stored. More efficient ways of doing business brings major advantages. For example, retailers can optimize their stock more easily based on big data predictive models generated from combining multiple data sets, such as from social media, web search trends and weather forecasts.
Better understanding of current market conditions can be achieved with the use of big data. For example, by analysing customers’ purchasing behaviours a company can find out faster and more accurately the bestsellers and adjust its supply chain and planning accordingly. Similarly, by knowing the trends of customer needs and satisfaction levels faster and in more depth, products and services can be developed that better meet customer needs and wants.
For a bank, for example, from the analysis of historical customer data collected through banking interactions across the channels, customers’ motivations can be better understood and improvements made to customer engagement and comms through greater personalisation. Customer interactions can be enhanced with both self-service devices (such as ATMs, ASDs, ASSTs, reception booths) and with bank staff. The greater the knowledge staff have of their customers, the better prepared they are to meet increasingly growing and complex needs. Spending potential can be analysed and product requirements understood and new business opportunities identified for the medium to long term.
As important as realising the benefits of big data are the caveats and watch-outs from progressing big data strategies. What’s becoming clearer is the appetite for greater correlation of increasing volumes and streams of dynamic data could be held back, unless systems are utilising more machine learning and artificial intelligence to do this complex work autonomously and in real time. Furthermore, certainly for financial services organisations, there’s also a requirement to allow customers to see the value to them of sharing more of their data with their respective financial institutions. Trust needs to be won and carefully protected especially when customers agree to share personal data from their social media activity. With big data, even more importance will be given to data security, data regulation and data breach prevention, so regulatory technologies are now being seen as ‘business as usual’. Compliance with emerging data protection regulations could also in turn, be less a hindrance and more of a benefit as a catalyst for customers to feel more comfortable sharing personal data with their financial services provider.
But don’t barricade yourself in – grasp the opportunity!
By: Rajesh Jethwa
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