How ACCA members can learn/acquire analytics skills and What is ACCA doing to help member learn data analysis?

There are several ways that ACCA supports the development of these skills.  The Professional Insights report Analytics in Finance and Accountancy is a good start point and there are a number of supporting resources to this.  ACCA has two certificates that provide context, the Certificate in Digital Innovation for Finance provides an overview of how technology can be used in a finance function whilst the Certificate in Data Analytics provides more specific context in this area.  ACCA also provides more country specific CPD activities that are detailed on our website.

What are some of the courses that an accountant can take to acquire these data skills?

In addition to the courses referred to in the previous answer you can consider using vendor specific courses which are now often available on-line and as part of software licence agreements.  Consider those provided for PowerBI, as an example.

As an ACCA member, what courses are there (which are valued for money), to upgrade our skills in AI or Data Analyst. Do I need to learn programming?

Please refer to the two previous answers.  In ACCA’s report, the Digital Accountant – Digital Skills in a Transformed World we discussed the skill sets that an accountancy and finance professional needs and how to develop them.  The relevance of programming to an accountancy professional will depend upon job role and expectations.  We consider, in the report referred to, the need to have an appropriate level of awareness of programming techniques so that you can have a relevant conversation with a data professional and be able to define the queries needed.

How do you respond to the growing issue of privacy invasion by companies analysing and collecting data? Some companies are very weary of this.

Data privacy is an issue.  As consumers we need to understand what we give permission for when we submit data to organisations.  This is a challenge and many consumers do not understand what they are giving permission for.  Trust and the ethical view need to be at the core of the accountancy professional’s response to this.

To what extent do accountants and auditors need to get skilled in tools such as Python, R and SQL?

There is no specific answer to this question.  It depends upon the role that you fulfil in an organisation.  For those accountants working in finance functions, especially finance business partners, it is important to consider how the data that you have access to (data from across the organisation) can be used to address problems and provide insights.  This requires a level of awareness of the data model of the organisation, how data is governed and the tools that can be used to interrogate the data (the art of the possible).  In addition to the reports mentioned in previous answers, ACCA and PwC’s report Finance Insights – Reimagined considers the implications of this.

As a qualified accountant of many years’ experience, how do you transcend to analytics / Data Science and how do you go about getting the practical experience for same?

The best source of practical experience is from learning from others who have the relevant expertise.  This may be a challenge if your organisation does not have in-house capabilities, but you can consider using local networks to support your skill development.  Skill development is made up on on-the-job experience, coaching and direct learning (such as courses); you should consider how you can use all three to your advantage.

What sort of personnel skill set in analytics will be needed in the internal audit team of a service company in the oil and gas sector?

It is hard to be sector specific, however, there should be an expectation that teams have the relevant skills to understand and critique the data model of the organisation, perform queries and understand how data can assist in techniques such as continuous monitoring and continuous auditing that can be used to support the objectives of the team.

For the smaller companies how the Data Analytics can play a larger role considering the budget constraints and expensive analytic systems

For smaller companies the use of Cloud-based applications provides opportunities for data analytics through the use of add-on applications that are available through the appropriate application ‘store’.  In our report, The Passionate Practitioner, we outline this.

For mid-tier organisations applications such as Microsoft’s PowerBI provide opportunities to develop analytics capabilities.

The extent of big data analytics and digitalising the business depends on the nature of business and industry - opinions?

This is correct as clearly industries will vary and the nature of data that is collected will differ according to where the organisation is in a supply chain.  However, big data can embrace embedded sensors in equipment that is linked by 5G or Internet of Things technologies.  It can also embrace data such as traffic flows and weather forecasts.  We should not be limited in our thinking.

I’m in the healthcare sector, with big data using predictive analysis there is the centralisation of data. Doesn't this present a risk in terms of security and integrity of the data

Any industry that captures personal data needs to ensure that it is protected.  The more sensitive the data the more important that it is to protect it.  With the increase in remote working there is an increased emphasis on cyber security and cyber risk management.  This is correct and threat actors are ready to exploit the vulnerabilities that this creates.  Good cyber security starts with the actions of the individuals as well as the application of appropriate technologies.  Organisations need to be mindful of this.  This topic is explored in the ACCA / CA ANZ / Macquarie University report Cyber and the CFO and an online CPD course is also available.

How much can value does predictive analytics really add to key decisions. I am thinking about the importance of unpredictable or uncontrollable factors such as covid19, government decisions on spending/tax, unknown fashion trends, etc.

One of the key elements of predictive analytics is scenario modelling which has come to the fore as a technique in the pandemic as finance teams look to be able to inform decision making in these complex times.  This requires the use of data to explore options and variable factors, such as the interventions of governments.

It seems to me that the use of predictive analytics would best be used taking unstructured data and relating that to existing historic data to perhaps predict events that will affect the organisation going forward and therefore being able to take action to mitigate any adverse effects or to position the business to take advantage of a predicted future opportunity.

The past is never a predictor of the future.  However, using trend analysis and unstructured data, such as customer reactions and profiling, can give insight as to potential future courses of action.

How can accountants working in developing nations with limited advances in analytics,  gain capabilities beyond using Ms Excel for data analytics?

Yes.  There are programmes, such as those run by Microsoft, that facilitate the digitalisation of the developing nations.

Any considerations for developing proxies for measuring the natural capital datasets in order to improve or enhance holistic analytics?

In ACCA and PwC’s report Finance Insights – Reimagined we discuss this specific issue and the data sources and models that can be used.

How important is it for us to learn a programming language ? And which one is most suitable for us Finance folks please?

Programming languages are important for accountancy and finance professionals.  Which language is dependent upon circumstances, however, you should look to those such as SQL, Python and R.  However, you should also consider a familiarity with the capabilities of tools such as PowerBI and Tableau as well given the need to manipulate data sets.  The tools often embrace some of the required programming capabilities through end user interfaces.

Most companies are not investing in analytical tools for finance team who are deemed to be backend or non profit producing....is there any way to influence this thinking? Especially companies that have commercial teams.

In our report Analytics in Finance and Accountancy we look at the business case and how finance teams can construct this.  Finance teams also need to establish their position as key players in decision making, as individuals who work across the organisation – this is considered in the ACCA and PwC report Finance Insights – Reimagined.

Can you give an example or two of what  useful data businesses can get from Trip Advisor or GPS?

Trip Advisor, as is quoted in our report, can provide data on customer sentiment and the need to react to this in terms of pricing and so forth.  GPS data can be used in the modelling of businesses to understand where demand may exist, also speed to deliveries and traffic flow issues.  In both instances finance teams need to think laterally about the problem that they are looking to solve and identify the cause rather than the symptom.  From this they need to understand what data they have to identify insights and recommendations.