As new technologies like AI, Power BI and data analytics tools continue to develop, it is essential that businesses stay on top of changes, those that don’t risk becoming uncompetitive and out of touch. This article shares highlights from the FITT forum where guest speakers, listed below, joined Louisa Matheson to talk about some of the key technological changes happening within the accountancy sector, including:
- Software Evolution: Is Microsoft Excel still the cornerstone of financial analysis, or are there alternatives we should be embracing?
- Data Analytics Strategy: The strategies to embrace and harness data analytics, including best practices and considerations to address
- The AI Revolution: The real impact of AI on the sector, including what is changing and where AI can aid our business
Speakers and panellists
- Mark Proctor, Director at – (2:05 in the recording)
- Andrew Codd, Founder and Lead Producer at – (7:57 in the recording)
- Chris Reeve, Company Owner and MD at Gascoynes Limited – (17:56 in the recording)
- Clive Webb, Head of Business Management at ACCA – (25:23 in the recording)
- Sandra Jacquinot, Finance Training & Development Manager at Cambridge University Press & Assessment – (33:53 in the recording)
- Jenny Blewett, Finance Digital Transformation Lead at Cambridge University Hospitals NHS Foundation Trust – (46:00 in the recording)
- Tom Jamison, Managing Director of Abbeygate Accountancy – (54:53 in the recording)
- Marie Speakman, Freelance AI Consultant – (1:04:50 in the recording)
- James Best, Global Tech Forum at ACCA – (1:10:39 in the recording)
You can watch the recording of the session by clicking the button below:
Find key points from the forum below.
EXCEL AND OTHER SOFTWARE:
Is Excel the number one tool for those working in finance?
- Yes, it is currently the most used tool due to its flexibility, usability by all, and ability to put the power in the hands of the accountant
- Can we live without it? Yes, but only by removing the problem it is trying to solve or finding another way to solve the problem
- Excel has become the second-best tool for everything. There are better and more advanced tools for specific tasks out there, but each of those comes with a cost and would require multiple skills and platforms. However, you do not need specialist skills to use Excel
Will Power BI and Python replace Excel?
- Power BI is an extension of Excel whilst Python is being used with Excel, not replacing it
- It comes down to platform choice and what is right for a business
Will AI make spreadsheets obsolete?
- AI is helping spreadsheets become more detailed and accurate rather than replacing them
- Traceability is still essential that spreadsheets can provide and AI cannot
- AI will supplement but not replace
Is Excel dead and should we invest in other software?
- No, Excel is still one of the easiest tools to use and has widespread use in so many different businesses
- However, because of this and its many functions, it could be holding people back from higher levels of data analytics
- Therefore Excel still has a role but people may benefit more from using other more specialist programmes
- Use other tools as well as Excel to complement decision-making
How do we keep up with changing technologies?
- Expose yourself to conversations about technologies, hear what people are using and what is working for them
- Try things out that you hear and put them into practice
Do accountants need to be data scientists?
- Accountants need an appreciation and understanding of what is possible, but they don’t need to be experts
- Play to the strengths of accountants and bring in data scientists when it is necessary – a blended approach
How to adapt to new software
- Ensure it is a progressive step for your business and that staff are ready for it
- Make allowances and expect human error at the beginning
- Offer training and support and involve staff in the decision-making and implementation process
- Expect it to take between 3-6 months to become fully integrated and accepted in the firm
- Bring in software providers to help with the training
- Use existing software to its maximum
Over-reliance on Excel
- Excel is still by far the most popular tool of choice for budgeting and forecasting
- Migration is needed to understand what you are using a tool for, how to use the right tool in the right circumstance and where to bring in new tools with Excel
- Need to move away from Excel for predictive analytics as there are much better programmes out there that can do this
DATA AND DATA ANALYTICS:
Data analytics and where we should go from here
- Data analytics is about using the past and answering why to tell the narrative of the future with more confidence
- Business leaders increasingly want interpretations of the future and data analytics to model what happens next and a range of scenarios
- AI is used to extract trends and data but it is important that the finance professional understands the validity of the output. This is where the value of an accountant is added
- AI is never going to be 100% accurate as there are too many variables, so it is about what level of confidence in the data do we need to ensure we can make correct decisions
- We need to be aware of the capability of accountants understanding of the data they need to demonstrate – from a basic understanding and an expert level
Is data analytics going to become even more essential for accountants and their teams and if so, how?
Reporting and performance are increasingly not just about financial measures but instead about concepts like value
For example, businesses need to not just think about financial returns but also sustainability issues and social mobility and how that is going to affect the operating model
- Businesses can use data analytics to be more holistic and incorporate these into the way businesses think, it is not something Excel can currently do
Cambridge University Press & Assessment’s data strategy
- They have found that the challenge is not in knowing how to use the systems, but in understanding the data, where it is from, if it is accurate and how much it needs cleaning up
- This is particularly the case if data has come from many sources
- They used advanced software tools to clean all the data and have the data in one central repository, a ‘data lake’
- The challenge comes in ensuring staff have the knowledge and skills and use the technologies available to them as they are evolving all the time
How have staff upskilled in these areas?
- Learning is a continuous journey, it is about making people aware of what is happening and embedding a culture of continuous learning
- Offering training for what staff need to do their job, not complicating things by showing them more than they need to know
- Having flexibility around learning and explaining the benefits
- Encouraging learning from each other and using tools available to you such as YouTube and Chat GPT
THE AI REVOLUTION:
How using AI can benefit clients
- Some companies are quick to try and adopt lots of new technologies at once but this can become overwhelming and mean none are adopted properly
- Businesses can use AI to make the onboarding of clients smoother. For example, using AI-created videos or connecting AI to booking or CRM systems
- Automating administrative tasks frees up more time to spend with clients
- AI can also be used to improve virtual communications with clients, like turning off background noise on video calls and automatically transcribing notes from meetings
- Chat GPT and other systems can help create PowerPoint presentations and Excel outputs, again freeing more time that can be spent with the client and driving more profit or developing and training your team
- Chat GPT can speed up and improve communications such as emails, as well as help grammatically
- AI can help with marketing such as blogs and brand storytelling
- However, a danger of using a lot of AI within the workplace is that younger staff new to the role might not have the skills and knowledge to appropriately interpret the output AI produces. AI often does not show the working out or the understanding behind its output which is essential for new staff to learn
What will be next for AI in accounting and finance?
- More and more firms and roles within firms will be using it and those that are not are going to struggle
- There will be specific roles to handle automation in-house because the pace of it is changing so quickly. This presents an opportunity for consultancy roles
- Things will continue to get more and more digital and paper trails will disappear
- Businesses need to start investing in what their future will look like and planning their AI strategy
Use cases of AI
- It is helpful for accountants to appreciate the capabilities of AI, understand the question that needs to be answered and the problem that needs to be solved, as well as know what a good output looks like
- Data scientists have the skill sets and capabilities to develop a solution but accountants have a collaborative approach and an understanding of limitations
- Accountants can use AI to drive insight into their decisions, for example in budgeting and forecasting and in cash collection analysis
How can AI help with decision-making and forecasting?
- AI can be effective at using collective wisdom and combining different data models to create accurate forecasting and predictions
- However, high-quality, and substantial data is needed to achieve this
- The human perspective is still important and is something that should be considered alongside the use of AI as that often impacts buyers’ decisions, not just data