Why analytical thinking trumps coding

Recent years have seen ‘Big Data’ continually featured in tech and business headlines. But for every story filled with optimism about the promise of data, there are just as many bemoaning the lack of skilled workers who can understand and use it effectively.

While the UK Government’s recent focus on – and support for – STEM subjects has been widely covered at the broad educational level, this hasn’t necessarily translated into meaningful conversation about addressing the critical data ‘skills shortage’ that’s being reported across the business community.

The importance of data in running and growing an effective business – and particularly in gaining faster, deeper market insight and competitive advantage – has been unequivocally recognised. Now the question is, where are the data workers who can make this happen? How many legions of millennials are flooding into the workforce with in-depth data skills?

These are the questions that many businesses are asking themselves, and as a result, data scientists have never been in such high demand. In fact, US-based online employment analysts at Glassdoor recently announced that data scientist is currently the best job in America, based on pay, career advancement, and treatment in the workplace. The only problem seems to be that there aren’t enough data scientists to go around.

But is that really the issue, or have businesses rushed to address a three-dimensional problem with a one dimensional solution? Are they fundamentally missing the real problem they face?

Analytical thinking vs coding

There’s no doubt that the capability to set-up, manage, and fix vast and ever-growing corporate databases is a job for an experienced technical professional. Coders, programmers, and systems architects with experience in data warehousing and developing IT systems will always be of vital importance. However, many businesses are rushing to deal with the exponential growth of their data without considering what is truly needed. While the maintenance and broad management of data is a job for the technical experts, we’ve reached a point where it’s no longer possible to leave analysing data to a few, rarefied specialists.

For the most part, today’s organisations are obsessed with hiring people with very specific digital skills. While these are undoubtedly important, far more important are the common approach and thought processes that underpin each of these skills. At their core, these technical disciplines rely on a methodical, analytical way of thinking. This is what companies should be looking for in potential employees and graduate recruits, at the same time as encouraging and nurturing it in existing staff. What’s more, this should be the case across all departments within an organisation, from HR through finance to marketing. Every line of business needs analytical thinking.

This pivot towards recruiting a broad mind-type, rather than a list of specific skills, opens up new benefits at the same time as addressing issues. The first and most obvious question is whether hiring analytical thinkers who may not have extensive programming and coding capabilities will really help to address a business’s data requirements. The short answer is yes.

Self-service serves businesses

The growth of self-service analytics tools in recent years has meant that coding is no longer a requisite skill for anyone and everyone who interacts with data. Legacy systems used to assume a level of technical proficiency of the user, but the latest generation of data solutions delivers a user-friendly interface – often drag-and-drop – that removes the need for coding.

With that potential hurdle addressed, the entire hiring dynamic shifts. These self-service tools enable businesses and recruiters to look at a far wider pool of candidates for any role, allowing them to consider factors outside of specific coding languages. Rather than a blinkered, tunnel vision approach to candidate selection, organisations can look at related experience, personality, and even raw intelligence. This in turn means that they’re far more likely to uncover the star hires that deliver business impact, rather than being constrained to a far smaller pool of applicants with experience in specific coding languages.

The shift away from reliance on specific people with specific technical capabilities also preserves the sense of agility that the modern business world demands. What happens if the business changes in the next 12 months, and a skill you’ve hired in is no longer relevant? Far better to hire a wave of recruits with an overarching methodical mentality than a group who can parse a specific coding language, but perhaps don’t have the wider analytical underpinnings you need. It’s far more important to have a logical mental workflow, know what data is most important to the business, and understand the particular business questions that need addressing.

The ultimate knock-on effect of looking for people with this analytical mindset is that you’ll bring a richer, more diverse mix of people into the company, united by a systematic approach to business.

The future of analytics is bright

Leading educational institutions – including Imperial College London and the London Business School – already offer modules, and even entire courses, in business analytics and related fields. This, in turn, is driving change in the corporate world, as the newest generation of MBA students and business leaders arrive with an analytical approach and an understanding of the value of analytics already in place. Experian’s latest global data quality research found that 84 per cent of respondents believe data is an integral part of forming a business strategy. The only surprise with this percentage is that it isn’t higher!

The data-driven culture that many companies talk about no longer means that everyone should know SQL Server, Python or R.

It means that every member of the business should understand that each of the firm’s decisions are made based on data, and that frequently interrogating data and making business decisions accordingly is how a company succeeds.

Stuart Wilson, VP EMEA, Alteryx, Inc.

Image credit: Shutterstock/Sergey Nivens