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Day of the data: futureproofing skills will be essential

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By CA magazine

27 February 2020

Key points:

  • Futureproofing skills will be essential for firms seeking to survive the technological advances coming.
  • CAs need to be continuous learners to keep up.
  • CA magazine look at four ways to get – and stay – ahead.

Futureproofing skills will be essential for firms seeking to survive the technological upheaval to come. Robbie White, Director of Technology Programmes at BPP University, tells Anna Melville-James how CAs can stay current.

From AI and predictive analytics to automation and big data, the digital age is throwing up the tools to transform the accountancy profession. Whether through greater efficiency or new strategic insights, the Fourth Industrial Revolution is full of opportunity – but is the profession ready to make the leap to lightspeed?

“As demand grows in these areas, expectations are higher,” says Robbie White, Director of Technology Programmes at BPP University.

“Clients expect firms to grow above the market because they will have to support them by providing consulting advisory services and being able to audit whatever’s been applied.”

However, with a knowledge gap – research in 2019 by Tata Consultancy Services showed most employers have digital vacancies they doubt they can fill – and a lack of clarity on exactly where future competencies will be needed, there is a challenge to overcome. Hard and tacit skills are one prong of any futureproofing strategy, from computer-aided audit tools to coding languages and their application to business.

The key competence is that people are continuous learners – because if they aren’t, they won’t be able to keep up. It’s not optional. Robbie White

Yet, with digital innovation often outstripping application, tooling up brings its own challenges for employers, institutes and educators.

“There are always going to be skills that are developed and used for short periods of time, but then fall away,” notes White. “It’s interesting how some organisations use reverse mentoring, for example, getting people trained in recent knowledge to educate others who have a huge amount of experiential knowledge.”

The goal, then, is a long-term, agile approach that adapts easily to technological innovation and its wider implications for business culture and output. Softer skills, such as communication and team building, will remain as important as ever, says White, but with new resonance for moving with the demands of a restless digital landscape. The most precious skill though will be the ability to stay current:

“The key competence is that people are continuous learners – because if they aren’t, they won’t be able to keep up. It’s not optional.”

Futureproofing finance

Four ways to get – and stay – ahead

Data

“Our understanding of data is probably the most important thing for the future – it is fundamentally what drives decision making and how we use it and create value with it is vital for the next wave of professional services.

They have to be able to take that data and make sense of it for the businesses for which they provide guidance. Data skilling depends on the structure you work with – a person in an audit function looking to cross-skill will want to focus on things like data visualisation, for example. But students studying accountancy need to start with low-hanging skills that will be applied to everything, generally around data visualisation, quality, management and governance. As they build up competence and knowledge of specific tool sets, they’ll grasp where that data comes from and approach questions such as, ‘How do we wrangle that data to represent it in the correct way?’”

Business partnering

“Organisations are creating partnerships with large strategic vendors. These will be incredibly important in the future, not just around the relationship with each other, but also with their clients. Some existing partnerships have even led to pure acquisitions, because they are so important they need to be managed internally.

To keep up with the demands of the market, strategic decisions need to be made around where you want to partner and why. I’ve been working with firms looking at robotic process automation, blockchain and cryptocurrency, and many are unsure whether that’s something that they want to build, buy (acquisition), borrow (outsource) or bot (automate).

These relationships with tech firms are moving rapidly and people are going to have to be responsive to what’s happening in the market. But that’s much more transparent now. Before, everybody worked in isolation; in future, the key will be to collaborate and cooperate – while also working as two organisations for governance purposes – around customer focus.”

Machine learning and AI

“AI and machine learning will be embedded into a lot of tooling and functions in the industry. When you’re doing an audit, for example, and want to repeat the same audit on a different set, AI will make recommendations based on that. There are two sides to the skills here, though. People will need to build up a [technological] skillset, but then there will be an advisory function in professional services more to do with ethics and strategy.

Firms will be expected to understand how machine learning and AI should be used in an organisation. You can create an AI, but the deeper questions will be, ‘Should we do this – and why? What’s our rationale for approaching that problem with AI?’”

Cyber security

“Quantum computing will become a massive security concern. As it allows people to create more complex attacks, the ability to respond is critical. A proactive approach is ideally what everybody wants to move towards, but in cyber security that means thinking of what a problem might potentially be before it even happens – that’s really difficult for a business to cost objectively.

With such huge amounts of data there’s also going to be a point where we need to decide what’s important and what’s not – which comes back to our perception of it and its value – and it will determine how we create security protocols for different types of data.”


This article first appeared in the March 2020 issue of CA magazine.

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