Data and Systems in Accounting and Finance for 2019

Natasha Vatner 22.03.2019

In today’s technology-driven world, now is the time to really hone on the niche skills that will give you a competitive advantage in the marketplace. Here we explore the key data and systems skills that are in demand in the Accounting and Finance space in 2019.

This blog follows on from our last blog; 4 Key Skills in Demand in Accounting and Finance for 2019. If you haven’t had a chance to read this one, I suggest you do before diving into this blog where I’ll be addressing in more detail one of the key skills in demand for 2019; Data and Systems knowledge.

Data
In today’s technology-driven world, organisations have the power to amass large pools of data from multiple sources on an array of different topics: Anything from their transactions, the processes being used, how efficient their employees are, customer habits and even the impression they are making on social media. However, if these mounds of data are left unanalysed or in their raw state the whole process becomes a costly and fruitless vanity exercise to the organisation. 

For an organisation to drive any true value from their large pools of data they need to have a team of people who not only understand the 'why' behind the numbers, but also understand the business. It is the point at which data and decision-making intersect where accountants are playing a critical role. If a business wants to start having better conversations or interactions with their customers, they’ll need to have a much deeper context around their data, which is where the finance teams come in. They should know what the most profitable lines of business are, where there might be a concentration of customers, what are the biggest costs or risks are, and what the key drivers are. In reality, a well-oiled finance team should be able to use the data available to find key insights that might not be entirely apparent to business leaders.

If you are an accountant, it is incredibly important that you start getting comfortable with a data-driven culture. That shift involves not only learning about data tools but also continuing to learn about the business through conversations with other departments. This is how you will be able to start turning information into actionable insights.

accounting and finance salary guide 2019If you are stepping into a role that involves the utilisation of data here are three ways you can help improve your teams’ approach to harnessing the data available:

  1. Determine the best metrics to track. With large pools of data, this task might seem overwhelming at first. My advice would be to start small and at the bottom. Develop goals for how the data will be used to improve foundational processes like month end reporting. Once you get the foundation right the next steps will be a lot easier to analyse and measure. It is all about providing context that is usable for business leaders. 
  2. Make sure the data you are using is “clean” and valid. While it might seem obvious it is amazing how much data (even that, which has come from sophisticated software might have flaws).  It is important that you make sure the information received is accurate and relevant. This means confirming that the data you are using has, for lack of better words, been scrubbed and cleaned. Using bad or dirty data can have detrimental impacts on your analysis and very easily steer you from making bad suggestions. This is also where your understanding of the business units comes into play because having not only an overarching view but also a specific understanding of certain areas, will help you quickly determine if the data is clean and valid.
  3. Don’t be scared by the term Big Data. I know Big Data can sound daunting especially when you are just stepping into a role where you feel people are depending on your analysis to help drive better business decisions. And while there will be times in your career when you are expected to analyse a large pool of data it is also equally important to remember that you won’t always need a lot of data, or a data centre, to do qualified data analysis. The validity, quality and chosen metric all play a part in determining the appropriate sample size.

Systems
While it is all well and good to understand what data, you want to use and what metric’s you want to analyse without the right tools or lack of understanding of how they can help you it will be very difficult to conduct a thorough analysis. Gaining valuable insight may sometimes only be a few keystrokes away or right under your nose. Take it upon yourself to learn about the software your company is utilising, the reality is not everyone will, and by doing so you will set yourself apart from your colleagues.

I hope you found this article helpful. Please don’t hesitate to reach out if you have any comments or would like to know what opportunities are currently on the market.

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