by QA

It’s undeniable. New technology is affecting society, organisations and individuals. The digital age is defining the way organisations need to operate. They’re closing critical skills gaps with an agile approach – to lead, train and re-train their workforce.

In this new world, there’s an unprecedented need to adapt for business survival. So, many are choosing to lead by challenging industry norms. But when you go against the grain, how do you have confidence you’re making the right decision? That’s where data science comes in.


Big decisions, can mean big mistakes

Business decisions are typically made using a mixture of intuition, superstition and data-driven consideration. But intuition and superstition are based upon personal prejudices – despite our best efforts to remain objective and rational. We’re only human. Unfortunately, this means making mistakes. And whilst mistakes are an important learning opportunity in life – some mistakes are catastrophic, particularly in a business setting.

Without meaningful data to support our natural intuition, the risk of costly errors is significant. For example, well-managed workplaces using normal quality management methods have failure rates of 5 to 10 in every hundred opportunities [1]. Extrapolating this to large data sources – this failure rate in over a thousand opportunities would produce potentially invalid data, riddled with errors.

So it’s hugely important to process vast databases in the right way – to get accurate and meaningful insights for your organisation. So you can make better decisions.


Learning from data

Data Scientists and Artificial Intelligence and Machine Learning Specialists uncover hidden trends in data. These trends can be used to inform things like business strategy, product development and resource management. Analysing data can even answer a wide range of political, cultural and economic questions that helps organisations to grow.

For example – historically, it was up to a newspaper editor to answer questions like ‘What are people in the UK concerned about right now?’ But now, Google does it – by analysing the most searched for queries. Google records data (the questions, their answers and implied preoccupations), and connects it to global events.

Being able to do this, means Google can turn potentially speculative questions into concretely answerable queries, to gain insight by ‘learning from data’.

In today’s digital age, clues about the future lie hidden in the patterns that connect our daily interactions with the world.

Only machines can process and ‘learn’ trends within colossal data banks – but machines still require human interaction to accept or reject the findings. These humans are Data Scientists.


Data Scientists – a rare breed

Learning from data requires very particular skills. So Data Scientists have a rare selection of qualities and are therefore (unsurprisingly) in high demand. This makes them difficult and expensive to hire [2]. Currently, 80% of UK business are looking to hire a Data Scientist, or seek data consultancy [3]. And, technology giant, IBM, anticipates that Data Science will account for 28% of all digital jobs by 2020 [4].

The shortage of Data Scientists could be the result of the ever-expanding, practical skills needed to ‘predict the future’. Data Science builds on other skill-sets, but unfortunately these skills can’t be found exclusively in other professions. Few professionals have enough business knowledge to communicate valuable, actionable insights related to business strategy – whilst also having the ability to effectively automate analysis of gargantuan data sets. For example – few Programmers are Data Scientists – few Mathematicians are Business Analysts – few Business Analysts are Programmers.


Becoming a Data Scientist

Training as a Data Scientist is an intensive programme – of applied and theoretical learning in all of the above areas. Despite being demanding, it’s a rewarding specialty for both the Data Scientist and the organisation.  

The organisation is rewarded with a whole new way of seeing their business – it’s future and past. Data Scientists help others make important business decisions – informed by real trends that are measured, observed and qualified. They know they’re making a crucial, valuable contribution to their organisation’s success.

The enhanced business insight a Data Scientist brings will inspire new strategies and reveal failures quickly. You’ll move forward with confidence – to go against the grain, and challenge norms.



[1] Lifetime Reliability Solutions: Unearth the answers and solve the causes of human error in your company by understanding the hidden truths in human error rate tables [2019]

[2] Harvard Business Review: Data Scientist: The Sexiest Job of the 21st Century [2012]

[3] MHR Analytics [2019]

[4] IBM: The Quant Crunch [2017]