The journey so far
In 2019 two fairly significant things happened which would change my life – the birth of my daughter, and the creation of the ICAEW’s Data Analytics Community. While these two events are totally unconnected (and I was unaware of the latter at the time), they do have one thing in common, in that they have both grown rapidly! Fast forward to 2022 and both are approaching their third birthdays; while my daughter has clearly transformed my life, the impact of the community on me is quite simply that without its rapid growth and a desire to tap into its enormous potential, I wouldn’t be sat where I am now, as the ICAEW’s new Head of Data Analytics and Tech.
As I continue to settle into the role there will be time to consider my vision for the community in due course (and a little more on this below), but as an opening gambit, I wanted to talk about two topics which are of great importance to me in the world of analytics, and will undoubtedly form part of this vision: Digital Upskilling, and a branch of analytics commonly known as ‘Accessible’ or ‘Self-service’ Analytics.
‘Accessible’ or ‘Self-service’ analytics
Once upon a time (and quite definitely when I started my analytics career not all that long ago), analytics was seen as the preserve of the specialist. We used tools that required programming, scripting and coding skills, and it was for us to build and run the analytics solutions, the results of which would be (mostly) gratefully received by our colleagues. Coming from an audit background, this generally took the form of journals testing or other analytical procedures where we’d agree a list of tests with the audit team, we’d obtain the data, process it, run the tests and collate in a spreadsheet for them to review and follow-up on. So far, so very conventional.
In the last few years however, there has been a change to the model with the advent of tools that make analytics substantially easier. They don’t require coding skills at all, instead working on a more visual, workflow basis where you can quite literally ‘see’ the journey that your data goes on during its analysis. With drag and drop interfaces, these tools open up the world of ‘accessible’ or, for the avoidance of confusion, ‘self-service’ analytics. In other words – provide the tools to the business, and with nominal support, the business can service its own needs. Not only does it offer a raft of opportunities to analyse data quickly and easily, but it also can lead to the development of automation solutions, saving both time and effort. Suddenly, tasks that might have taken hours, days or weeks, can be built into a workflow and run in a matter of seconds.
This all sounds great of course, but there’s a lot to unpack and a big role for the Data Analytics Community to play in supporting the journey. One of the biggest challenges is the inherent misnomer in suggesting that users can be entirely self-sufficient in using such tools. Training, guidance and support are still needed – somewhere for like-minded people to share and discuss the problems and potential solutions. The community has a role to help establish the framework in which such tools are used in our profession, as ultimately we have standards to adhere to and the risk of self-service analytics is that we create a ‘wild west’ culture where these tools are used without any oversight or rigour. There is also a need to recognise the scope of such self-service tools. Specialists will still have a part to play in developing the more complex solutions, using tools like Python, R, SQL and the rest. I’m very keen that the Data Analytics Community helps its members make the right decisions about what the best tool is for the job, and who is best placed to build it.
This also leads onto another topic that I’m particularly passionate about: Digital Upskilling. Put simply, this is the idea that everyone needs to have a basic level of digital literacy in order to support their personal progression, and the progression of the businesses and industries they work in.
In my previous role I was a huge advocate for sharing knowledge around technology solutions. And the ICAEW has made some progress already in this area, with recent changes to the ACA, the introduction of the Data Analytics Certificate, and an extensive range of CPD courses through the ICAEW Academy, including our “Finance in a Digital World” programme. But there is so, so much more to do, and the Data Analytics Community has a huge part to play in this. It is important that we spread the word about all that is great and good in the digital world, ensuring everyone has a solid grounding in a core set of digital and analytical skills that allow them to understand the world around them and not be left behind. So, a big focus for the community over the coming months will be ensuring that we have up-to-date content reflecting the latest trends in the world of analytics and technology, that presents potentially complex concepts in a way which is digestible for all (starting with our ‘Cloud Computing’ webinar next month).
Again, this is not to remove the need for data specialists at all; far from it, I’m keen that we showcase the cutting edge solutions that require advanced skills to be able to build and run. It is also quite categorically not suggesting that every accountant needs to know Python. It is important to me that accountants remain accountants, doing what we do best, but being able to leverage a core set of analytics skills (many of which will be innate to finance professionals) and understanding of technology that enhances, not distracts, from the important work we do. Furnishing the ICAEW’s members with this essential knowledge will form a key part of my role in the coming months and years.
These are just two of the areas I’m keen to focus on as we move forward with the Data Analytics Community, but there are just so, so many more burning topics in the world of analytics and tech. And crucially, I can’t cover them on my own, which is where you come in.
Currently we have a small advisory group, but with the size of the community, we are keen to ensure this is fully representative of the breadth of community membership – in terms of sectors, roles, geographic location and analytics experience. I’m also very keen to ensure we are delivering the content that our members want and need. So with this in mind, I have two main asks:
- What topics would you like to see us producing content on? Do you want a focus on the ‘fundamentals’ of data and technology? Or deep-dives into more complex areas? What specific topics do you want to hear more about?
- Would you like to contribute towards the success of the community by being part of our advisory group? There is a small time commitment, typically to attend quarterly advisory group meetings and engage in periodic discussions on content themes, sharing knowledge and insight drawing on your experience, with scope to be part of the team producing content should you wish to be more involved.
If you’d like to respond on either of these asks, then please contact the Data Analytics Community, I can’t wait to hear from you.
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