The importance of data analytics in the accountancy and finance industry is growing year on year. What was once viewed as something that would threaten to leave accountants’ roles obsolete, has instead aided them to deliver better-informed advice and strategy for clients. Chartered accountants have more time to interpret data, look for trends, and offer predictive and prescriptive analysis now machines are doing the laborious numerical legwork. Technology is amplifying the role of humans instead of taking over from them.
This article shares highlights from the session where guest speakers, listed below, joined Gareth John to discuss how data analytics is changing the role of accountants, what the future of accountancy looks like, and what businesses should do to keep up to date and benefit from data analytics.
- Paul Wardle, Account Manager at Inflo
- Steven Drew, Head of Products & Markets at AAT
- Mike Willis, Programme Director at Cambridge Judge Business School
- Christopher Argent, Editor of GenerationCFO
- Representatives from the awarding bodies AAT, ACCA, CIMA and ICAEW
You can watch the recording of the forum by clicking the button below.
The Role of Data Analytics in the Audience
To get an indication of how technologically developed the audience were we asked a couple of poll questions before we started:
Question 1 – How far along the journey of adopting general accounting technologies such as cloud accounting, bookkeeping and tax software and automated apps are you, with 0 being not started and 5 being fully adopted to the maximum extent?
In response, 64% of the audience said 3 or 4 (no one said 5) with only 16% saying 0 or 1. This shows that most felt they are well advanced with adopting general accounting technologies. This is not surprising given the high profile recently achieved by the likes of Xero, quickbooks, Receipt Bank, GoProposal and similar platforms.
Question 2 – How far along the journey of adopting specific data analytics technologies and tools are you, with 0 being not started and 5 being fully adopted to the maximum extent?
This time only 41% said 3 or 4 (again no one said 5) and a significant 40% saying 0 or 1, indicating that for many employers progress in the adoption of data analytics is well behind where they are with more general accounting technologies. It is however clear that there is an increasing appetite for information and guidance in this emerging area. It sounded like the content of the session was going to be really useful!”
Introduction to Data Analytics in Accounting
Data analytics benefits three main areas:
- Better business insights
- Enhanced decision making
- Improved quality and efficiency of work performed
Paul Wardle from Inflo, the financial data analytics auditing software solutions, shares his views on the current state and direction of data analytics. Inflo is designed and built by accountants for accountants to enable the industry to use data to drive better decisions, have more accuracy and effectiveness, as well as develop advisory opportunities. Accountancy has gone through unprecedented change over the past ten years, driven by technology and data analytics.
Paul highlights that the skillsets of accountants are changing. The future accountant needs to make better decisions with more informed choices from data. Programming knowledge, R or Python, and SQL Scripting are useful for accountants to learn. Future accountants have similar roles and aligned skillsets to data analysts, as data analytics and AI are influencing what they do on a day-to-day basis. Accountant’s jobs are evolving to put data in a meaningful way to shape thoughts and decisions.
Artificial intelligence is fantastic but it is hybrid knowledge that benefits accountancy. Using an accountant’s knowledge and experience of a business, as well as their professional skepticism is essential. Inflo makes it easier for accountants to spot anomalies in data and use machine learning to recommend ways to start looking at risk. As well as measure data performance with visual KPIs to help businesses add more value to their existing services.
Thoughts from the Panel
Is tech such as AI and Data Analytics rendering accountants obsolete, or quite the opposite are they putting accountants in the strategic driving seat?
Christopher Argent: Accountants are not going to be made obsolete. Humans tend to overestimate the power of technology but we are also in a position to underestimate it, particularly with AI. People either feel as though everything needs to be automated and roles changed accordingly, whilst others feel nothing should be done. Businesses need to look at technology and capabilities, a computer is not going to completely take over a role, but instead, AI solutions will aid a single process or task. We need to get closer to the problem and drive it internally to understand data analytics in accounting.
How do you think technology is changing the skills sets accountants need to drive value in their organisations? Is technology creating a generational divide?
Steven Drew: The way in which we see accountants now is outward-looking, forward-thinking, and more likely to engage with clients. Rather than being about compliance and data entry, it is more around developing advisory skills and personal skills to build relationships. As well as communications to effectively visualise and present data to make information more impactful. Accepting the role of data analytics is more about mindset than age. People who are more proactive and are looking for opportunities will be the ones who benefit most. There is a role for everyone but it is about seeking opportunities and embracing the tools that can make businesses more effective.
What are your thoughts on the current state of analytics adoption?
Mike Willis: Accounting and reporting are a trust activity where humans and judgment are needed. Mike agrees with the idea that the human side is still dominating the industry and will do for a while. Adoption is driven by the forces that are shaping the costs and benefits of data analytics. Data analytics has been used to predict behavior in retail for years, why then is the adoption in accountancy lagging behind? Mainly due to the fact retail is extremely competitive and there is data available from millions of customers. The huge amounts of data available and the lack of understanding to unlock what it is truly showing is driving data analytics in accountancy.
‘Data analytics’ seems like ‘sustainability’ in that it covers a huge ocean of different aspects. Can you suggest any smaller ‘buckets’ to help apply and use data analytics?
- We need to better understand our role in data analytics and therefore need to be more data literate. Training in this would help accountants see the opportunity in data analytics.
- Accountants should use their knowledge of businesses and finance to bring context to the questions they are trying to answer in a data analytics project. Questions do not need to start with data but use data to answer the questions.
- Messages can get lost without effective communication and visualisation. Accountants need to learn the fundamentals of data visualisation including what works and what doesn’t.
- It is about working together as a company towards supporting business decision-making. Financial colleagues provide financial information, whilst a marketing team provides information about research and insight from the customers. They come together as part of one mix.
- Always ask the question ‘so what?’. Try and bring together analytics, financial information as well as customer insight, and share it in the organisation to identify risk, opportunity, and ways to be more efficient.
- Descriptive analytics tools: This includes using visualisation as an explanatory to describe the state of the world and communicate. For example using visuals to explore and understand a data set through looking for relationships, trends, and patterns. Accountants, therefore, need to understand how the brain processes visual queues so to create a visualisation that tells the story and communicates effectively.
- Predictive analytics tools: This includes trying to make a prediction, using a subset of variables to explain what is the ultimate outcome.
- Prescriptive analytics tools: An algorithm that is making a recommendation or decision.
You don’t need to be a data scientist to participate in the world of data analytics, a lot of people can pick it up and become well versed in these principles.
At what levels of an organisation should data analytics be a consideration?
Christopher Argent: Top to bottom, there are people potentially coming in at the bottom who are more tech-savvy than the leadership team. We are starting to see trends around reverse mentoring, with the younger generation pushing conversations around apps, AI, and tech. There is a need for senior leadership to acknowledge the shift in this market from a talent point of view. As well as to understand the power of data analytics, the process, and the investment that is required.
What are the key skills required to make the best use of Data Analytics tools?
Steven Drew: Part of the changing role for accountants is to look outside. A key part of this is context, yes we need to develop advisory skills and relationships but we also need to understand the organisation. Staff need to know what the business is trying to do, the products, the customers and using that to develop opportunities.
Mike Willis: At one level there is being able to formulate questions and answer them using data tools. At another level it is about understanding the more complex algorithms, what can they do, and what they cant do. Survey evidence suggests there is a gap between what data science teams can do and what executives think they can do. We need to close this gap by gaining an understanding of what the algorithms can do. Having a basic understanding of writing code can help with this, as well as becoming more data literate and skeptical consumers of analytics technology.
Do you think accountants need to understand Python or SQL at a level?
Christopher Argent: This isn’t about being a data scientist, what are we gaining from learning Python or SQL? We need to understand that algorithms are not perfect and they have performance levels. If you want to understand how these projects run and want to be more data literate, then a basic understanding SQL or Python will help you empathise and be part of these projects. However, the goal is not to become a data scientist. Your job is still in finance and this is just to augment it.
Steven Drew: No, I would prefer the accountant to focus on developing their skills around finance. Yes, there is a need to have some empathy with data scientists’ roles but it is better accountants focus on understanding the information, helping to engage and work as a collective.
What are your top tips for leaders to prioritise and consider?
Mike Willis: There is no one size fits all approach to data analytics. Large corporations need to think carefully about data analytics adoption throughout the business. Smaller organisations however can let this evolve and they can choose what works for them.
Steven Drew: Keep it simple and focus on using this information to support business decision-making and strategy. Embrace the change. Qualifications are important but are likely to become outdated quickly. There is therefore a need for professional bodies to develop their qualifications but also businesses need to focus on CPD. This will make sure staff know what is out there and what works for them, and develop a well-rounded skillset that adds value.
Christopher Argent: Embrace data analytics and see it as an opportunity for augmenting your role. The profession is changing so start the journey and go with it. The journey starts with the nontechnical, including understanding the fundamentals, data literacy, data analytics, and theory concepts. First, figure out what accountants’ role is in data analytics before understanding a data analyst’s role.
Comments from Awarding Bodies Representatives
Adam Brit: In 2016 we were under pressure to change the qualification or introduce a new qualification for data scientists. The message was that the role of professional accountants was limited and in the future and there wouldn’t be any. In 2019 those same people said the future of accountancy is about data storytelling and using technology to benefit what accountants do. Technology should therefore be embedded in what trainee accountants are learning.
The role of a professional accountant is around enrolling trust in data, and technology has a part to play in that. For example to manage the volumes, sources, and visualisation for data storytelling. Professional accountants’ role is to act as an informed buyer when looking at technologies. They do not need to have coding skills but instead need to understand what the technologies are doing and ask the right questions.
Accountants should also be enabling trust in data, this can be achieved with professional skepticism. For example, looking at whether sources can be trusted, asking what is data saying, can it be matched with other sources? Accountants’ ethical code and the ethics of data analytics are just as important as understanding it. Furthermore, communication is essential as well as staying up to date. Data analytics is a phrase that has a meaning at the moment but this will change over time. What we have discussed becomes increasingly important as the extended role of reporting and assurance around sustainability comes in. This conversation will therefore likely have a different slant in a year.
Clive Webb: This world of technology is going to continue to change. If we purely stick to financial data in the way we look at this, we are starting to absolve where the decision-making is going to come from. Accountants have to realise it is not just about financial data, but about non-financial data and customer sentiment. Technology is the business model of the future and the reality of today which the pandemic has only escalated.
Continuous education and evolution of the qualifications are important. Organisations need to embrace this and take continuous education opportunities to be the educated communicator. But companies need to take the time to understand how technology is driving the business as that gives you that data model. By understanding the data model then you can understand the business objectives and can problem solve. How to use data to forecast and scenario model is essential for businesses to predict outcomes.
Tim Rutt: We have gone from analog to digital and as a result huge amounts more data is out there. Big data is not necessarily better, it is about how we make sense of this data. An accountant’s job is to make sense of data in order to maintain relevance in society. Particularly as there is now more data to measure and make use of, including sustainability, governance, and society.
For accountants, it is about owning and understanding the algorithm (not writing it) and predicting the future. Tim agrees that competencies are changing to be about building empathy from interactions with stakeholders. As well as co-creating value from being out there and making connections.
Accountants should, therefore, be reframing and trying to develop critical reflexive forms of analysis. As well as questioning assumptions, where beliefs are stemming from and challenging them, how we can think about things differently, and educating to ask better questions.
Anthony Clarke: There has been a clear message from clients that they still need people to understand the numbers. As well as have the confidence to interrogate and draw conclusions from the data they are seeing. Wider skills and behaviors and accountants being curious and having professional skepticism to derive conclusions from the data and communicate that with clients is still essential.
The need for lifelong learning is important in all elements of accounting but particularly in data analytics. The area of digital literacy is fundamental to the accounting profession. First Intuition has teamed up with FUTURE FINANCE TRAINING LTD – a like-minded and internationally recognised CPD training consultancy to design and deliver continuous professional development courses the First Intuition way.
For developing you knowledge on data analytics, we recommend:
The Power of Digital Technology, AI, Machine Learning & the Value of Data 21st April – 9:30am to 12:30pm
The Impact of Digital Technology on Accountants today & in the future 13th May – 9:30am to 12:30pm