Data analytics for the smaller firm

The latest Tech Essentials guide looks at the use of data analytics in smaller firms, with a number of case studies looking at its use in the field. I enclose an overview of some of the findings.

What is data analytics?

The guide starts with a helpful definition of data analytics, noting that accountants have been ‘using it for years’. Data analytics ‘is the process of collecting, organising and analysing large sets of data to discover patters and other useful information, which an organisation can use for future business decisions.’ With the explosion in available data and the inexorable move of accountants from compliance work to advisory, insights offered through data analytics are a growth area for the profession.

For the smaller firm

But this guide is about data analytics for the smaller firm – and many of those would say that big data and its associated analytics is for big firms only. The advice is to think about all data rather than big data – smaller firms still have access to large amounts of internal data (especially if you include unstructured data such as emails, texts and pdfs), but these firms also have access to huge datasets externally, whether open government data, or data on weather or footfall.

Where to start

The guide suggests a good place to start is to consider what questions you wish to find answers to, and then go looking for the data you need to provide the insight. This guide summarises that in a three-step approach.

First, ‘Strategy’ – what are the business problems analytics can help you answer; what are you looking to do? Second, ‘Assessment’ – what do you have and what do you need; are you looking to buy in or develop internally? Third, ‘Pragmatism’ – see what tools you need and what skills you have to develop or acquire. A top tip in this respect is to start with employees who are comfortable with data and use them as your ‘point people’.

Real life examples

The case studies outline firms who are leading the way in their use of analytics.

  1. The first study outlines how the firm mined its data to ascertain average fees and margins, calculate return on tech investments, support the transition to Making Tax Digital (MTD) and more. More specialised forecasting and planning tools are used to inform decisions inside the firm, enhance client services and highlight potential revenue opportunities.
  2. The second case study talks about innovating to accumulate, with the firm developing its own analytics tools. These enable it to analyse people performance, client performance and profitability. Analyses can show how much work is given away free, potentially highlighting inefficient working practices and opportunity costs.
  3. The third case study urges prioritising the essentials. These included the capacity to ask any questions of the data, seek value-added opportunities and retain ownership of the data. The firm decided to create a data lake of its own, with a strategy to pool all the data in one place. This firm also writes its own Python scripts to extract information from its database and to address issues with data.
  4. The fourth case study urges sourcing quality data, noting that without a data governance and clean-up exercise, the quality of data is often too poor to be useful if you want to reap the benefits of data analytics. This loops back to the third case study and the skills needed by accountants to extract and clean data before it can be used.

The guide also has a helpful glossary and a number of suggestions as to how to move forward.

The guide is available to members of the Tech Faculty as part of their annual subscription. There is more information about the faculty, including how to join, on our faculty joining page.

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