This article was first published in the February/March 2020 International edition of
Accounting and Business magazine.

Did you, like me, think that when you passed your final ACCA papers a decade or two ago that you were set for life and would never have to study again? What we didn’t realise then was that the ground beneath our feet was shifting, and that standing still would not be an option.

As we enter the third decade of the century, it has become clear that professional accountants need to have a ‘growth mindset’. They have to recognise that, whatever their level of experience, the effort they put into learning today is what will put them ahead of the curve tomorrow. As we know from ACCA’s work on lifelong learning, the need to update never ends, as technology and data proliferation move inexorably on.

Back in the 2000s, as the digital era dawned, words and concepts that are now very familiar – artificial intelligence, machine learning, chatbots, facial recognition and the like – were not even in our vocabulary. With the use of technologies in everyday life exploding over the past decade, tech-savvy is becoming a key attribute at every level.

Historically a professional accountant was the go-to person for working the numbers or any type of data analysis on Excel. Analysts and controllers would play a key role in – and sometimes be the only custodian of – cost line analyses, which would be descriptive or diagnostic in nature. Descriptive analyses would indicate, for example, that maintenance costs of equipment had gone up, while diagnostic analyses would take it a step further and indicate why these costs had gone up.

Analytical sorcery

These days, such analytics are fully automated, reporting and presenting the data in user-friendly dashboards, while advances in data science are enabling companies to carry out much more complex predictive and prescriptive analyses.

In the above example of equipment maintenance costs, analytics are now able to predict equipment failure using statistical models. These models incorporate both financial and non-financial information, such as pressure, temperature and operating time, and allow equipment failure and maintenance costs to be quantified and predicted under variable conditions. These insights can be further developed into prescriptive analyses, which can recommend intervention before a piece of equipment actually fails. Maintenance costs are reduced and hardware breakdown managed before an expensive failure occurs. And all this numerical sorcery is completely automated; no human input is required.

Companies have harnessed data analytics tools in other ways too – to devise customer-specific packages, for example – while audit firms are using them to address fraud risk. In short, data science is at the heart of all today’s tech progression, and this has implications for professional accountants. Our skillset will simply not be sufficient on its own. To remain relevant, accountants working in any capacity in any industry need to keep up with the pace of change.

Having acknowledged the need to upskill, how do you go about acquiring such knowledge? The idea is not to turn all accountants into data scientists but to ensure they have the skills for the digital elements of their work. Regardless of their role, accountants need to develop a level of familiarity with data tools and sufficient data literacy to be capable of insightful exchanges with developers, data scientists and digital strategy experts. Such knowledge will also assist them in their role as business partners, interpreting the data and assessing its significance for the organisation.

The upskilling options

There are options at various levels, catering for a range of appetites, spare time and depth of pocket:

  • ACCA introduced a data analytics unit for its Ethics and Professional Skills module last year. All members can access it for free, and it counts as verifiable CPD.
  • Online ACCA courses and webinars on a range of particular topics are available – from introductory level to more in-depth learning.
  • ACCA will soon be launching a certificate in digital finance.
  • Many universities offer courses in data analytics, machine learning and artificial intelligence.
  • Learning platforms such as Coursera, Udemy and EdX also offer courses, and informal training videos are available on YouTube.


Much data analytics training is far from easy, especially for time-poor seasoned professional accountants, with rusty mathematical concepts and very limited knowledge of advanced statistics or coding. Many enrol with enthusiasm and good intentions only to give up after finding the content too complex, or failing to see the relevance to their current role. It requires a high level of self-motivation to sit through demanding material in these circumstances, so it is important to pick the appropriate course content and level for your particular needs.

The digital skills gap offers an unparalleled opportunity to stay relevant by adding these skills to your professional accountancy knowledge and experience. The fact that most people consider analytics course content too complex or too intimidating even to contemplate is an opportunity in itself for anyone with a growth mindset.

The reality is that the landscape of our chosen profession is rapidly changing and the choices we make now will determine whether we are the future of this profession or its past. The real choice here is between being part of the crew or part of the baggage.

Arshamah Motiei FCCA is SAP deployment manager, Eastern Hemisphere, at Schlumberger.