How wonderful the new world of business is, thanks to the ability to collect and use intricate and far-reaching information on our customers, competitors, suppliers and staff. Big data - and the global connectivity it underpins - means we can check machinery functionality from thousands of miles away, conduct remote repairs on a ship that’s out at sea or monitor and measure the status of a pallet of goods with pinpoint accuracy, wherever it is in the world.
We can research our customers' buying patterns, social media related preferences and their interests. Before long, via wearable technology, a wealth of personal medical data will be accessible for analysis anywhere in the world. The huge data sets we can extrapolate internally and externally can be compared to create realistic predictions. This is the sort of development that makes strategic business planning and financial investment a great deal more solid. What could possibly be a downside to all this connectivity and the abundance of information through big data?
As the EU General Data Protection Regulation (GDPR) illustrates, top of the list of disadvantages to big data is the huge implications for privacy and security. Companies face a real risk of getting too enmeshed in analytical prowess, extracting and using data to grow businesses at the expense of having due regard for their customers' privacy. And when you start shifting customers around into boxes based on data profiles, you also increase the risk of something going wrong.
The €20m fines for data breaches after the GDPR goes live in May 2018 may be what’s needed to wake some companies up to the security risks of big data. How to contain and control data effectively clearly needs careful thought and planning - not least how to collect it in a way that keeps customers properly informed.
Even the industry giants are not immune from the danger of misusing the power that big data brings. The European Commission recently slapped a €2.4bn fine on Alphabet, Google’s parent company, after a seven year investigation into whether the company abused its position in the market to promote its own online shopping service unfairly. Big companies using their technical prowess to remove freedom of choice cheats consumers and puts smaller businesses to the sword. Added to this are concerns about just how much data companies like Alphabet have about the general public. Is there a way for regulators to keep control of the way in which big players stockpile and use data? The answer is not certain, as big businesses are often the organisations with the greatest ability to diversify, amend, or simply create new, unregulated technological advances.
The second thing that can go wrong with big data is its ability to make or break companies. For some organisations, it means big business potential. For others, it’s a step too far. For example, Alphabet have immeasurable data harvested from its users. They have invested in creating advanced services, often utilising artificial intelligence, that enable them to sell data sets to the public and private sector, and are in the driving seat in the race to identify and halt cyber-attacks, along with other globally significant applications of big data. Having ownership of a barrage of sophisticated data-rich services and products puts them far ahead in the new economy that big data has created.
Meanwhile, many smaller companies are overwhelmed by big data and are flailing to keep pace. And even those who have embraced its possibilities are finding that using it to inform business decisions and functionality is a lot more complex than it sounds. Integrating systems within big data projects can be a challenge, and the systems used to measure the success of initiatives often lag far behind the initiatives themselves. This issue is compounded if companies are running big data initiatives on legacy technology. All these factors mean that big data may increase the polarity between the giant companies and the smaller businesses who don’t have the skills or systems to compete.
Staying up to date with data science and data protection puts a substantial financial strain on companies, but it is now an unavoidable need. The third problem big data can bring - one that is, fortunately, avoidable - is losing sight of core company values.
In general, IT has moved to the top of boardroom agendas. While at one time the question may have been, 'how can IT support our staff and systems?', increasingly the question now is 'how can our staff support IT as the focal point of all business operations?' Increasing reliance on machinery and software puts companies in danger of losing the flexibility and resilience of human skills and personality. If your focus has switched entirely to big data, you may want to regroup and think again about the loyalty, resourcefulness and adaptability of your staff. This change of pace could be why so many technology firms are leading the swing back to more ethical and person-centric business practices, for example, creating and celebrating diversity in workforces. Global hi-tech firm CA Technologies has scooped numerous awards, not for its IT skills, but for its diversity and equality policies, introducing kinder working practices for staff. They also recruit on the basis of 'Bring What You Bring', celebrating ideas, passion, commitment and other human strengths, as opposed to data driven hiring systems.
It is certainly true these days that information is power. So, how do you make sure you can harness that power, rather than drifting into the three problems outlined above. Companies of all sizes have opportunities to unlock the value of big data – as long as they have the skills, intuition and ethical business practices available to them to harness it. This often comes down to having the best talent, not the best machinery and software.
One serious shortfall that currently affects all of the three issues outlined is that the talent pool is failing to keep pace with the rapid advancements of technology and data. This is especially true of data science and data protection staff, who are in perilously short supply globally. Countries across Europe - including Germany - are struggling to generate enough graduates with STEM (science, technology, engineering and maths) expertise to keep up with the demands of the new economy and technological advancement. At the end of last year, the UK Commission for Employment and Skills announced that 43% of STEM vacancies were proving hard to fill. It’s highly unlikely that by the same time this year the figure will have risen, despite all the efforts to plug the skills gap.German's saving grace could be a richer pool of talent created by Brexit steering European graduates away from UK posts.But meanwhile, after over ten years of strong business and jobs growth, the German economy is also feeling the ripple effect from having too few qualified recruits. According to the IAB think tank, an unprecedented 1.1 million jobs were vacant in Germany in the first quarter of 2017.
When hiring, you want staff with the acumen to harness big data for just about every business function, to inform and underpin profitable growth.
But this will never be a tickbox exercise. Getting the person who forms the right match with your company is often about having a hiring network to find talent with the right personal attributes who can bring the most to the role, because sometimes you need big hearts, big emotional intelligence and big interpersonal skills, to ensure that big data doesn't go wrong.
Selina Chung is an Endorsed content creator for the tech and manufacturing sectors. Always up-to-date with London, Berlin and Munich’s tech scenes. Whenever she is not ferociously tapping away at her keyboard, she can usually be found reading a book or practicing a foreign language.