The use of analytics by finance and accountancy professionals is not new. Many finance teams have been using data to report on trends and past performance since the 1980s. However, the volume of data that we, as a society, create and the availability of computing power to process and analyse it means that we can do much more than just look at past trends. In times of rapid change business leaders are seeking insights into what might happen rather than just focusing on what has done so.
Using case studies and interviews, as well as a survey of ACCA and CA ANZ members, the report explores the opportunity and the reality of analytics for the finance function. These case studies and insights draw on a range of experiences from both small and large organisations across a range of locations and sectors.
In our report we focus on four types of analytics. In looking back, we focus on the descriptive (what has happened?) and the diagnostic (why did it happen?). And in looking forward, the predictive (what will happen next?) and the prescriptive (what action should be taken?).
For many finance teams the core function has been descriptive and diagnostic analytics. Understanding what has happened in the past and how the organisation performed against its objectives.
As organisations increasingly focus on the 3Ps (people, profit and purpose) in defining their strategies so measuring a broader range of performance targets becomes important (ACCA and PwC have explored this in their report Finance Insights – Reimagined). The use of more predictive and prescriptive analytics to look forward across this broader range of measures is becoming essential for organisations. Finance and accountancy professionals need to grasp this and to ensure that they have the relevant skills to do so.
We need to recognise that the data that we need to work with comes from a variety of sources. It may be structured data, or unstructured data such as video, audio, text and email. Any information that helps us understand organisational performance and the behaviours of our customers. Finance professionals need to play a full role in data governance and data accuracy.
The use of machine learning algorithms applied to the data sources can give us insights into the future. However, we need to make sure that we have the skills to understand the narrative that is being suggested to us.
Developing these skills is essential. They are a combination of technical and professional skills:
- Finance and accountancy
- Data literacy
- Data extraction
- Application knowledge
- Problem solving and critical thinking
- Visualisation
- Storytelling.
It is important that the finance and accountancy professional continuous learns as each of these areas evolves. ACCA’s Certificate in Analytics provides an opportunity to develop these skills.
The ACCA Certificate in Data Analytics
The ACCA Certificate in Data Analytics is aimed at business professionals who wish to develop their understanding of data, and the skills and techniques available for data analytics.Â
Using real practical business examples, learners are able to develop an understanding of how data analytics and data modelling can be used to garner business insights.
Learners will learn about big data, the various sources of data, types of analytics, and become familiar with the range of tools and techniques required to extract, manipulate, interpret and present data. They’ll also learn about the need to be both sceptical and ethical when working in the data analytics field.
Many of the data tools introduced in the certificate are widely and freely available, such as spreadsheet or database software. Learners will also be introduced to popular statistical and programming tools such as SQL, R and Python, as well as an introduction to artificial intelligence and machine learning.
