Adopting cloud technology enables small-to-medium enterprises to access raw business data in almost real time. 

Analysing this data – known as data analytics – is simply a way of gaining a better understanding of various aspects of an organisation that were perhaps once siloed in different sources. Analysing these complex scenarios and interdependencies yields insights, leading to better informed business decisions.

Accountants are recognising that they can use data analytics to discover trends, metrics, and insights from data. These, in turn, can be represented in pictorial or graphic formats using data visualisation – a way of communicating hindsight and insights to the organisation and supporting informed data-driven decisions.   

Data analytics and data visualisation are distinct concepts says, Lance Rubin CA, partner at The Outperformer. “Unlike with fish and chips – you can feel satisfied from one or the other or both – you cannot really get the benefit from data analytics without data visualisation.”

“Unlike with fish and chips – you can feel satisfied from one or the other or both – you cannot really get the benefit from data analytics without data visualisation.”

What’s it all about?

Each company will have its unique data and specific reasons for analysing it. Here are three key concepts:

Descriptive analytics: This is about summarising what has happened in an organisation and what is happening.

Predictive analytics: This is using data, machine learning techniques and statistical algorithms to determine the likelihood of future results based on historical data.

Prescriptive analytics: This applies filters and sharp focus to answer particular questions precisely and accurately.

Is analytics for everyone?

Data analytics and data visualisation are useful for firms that have a workflow running predominantly in the cloud. Some businesses are particularly suited to analytics and visualisation, says Warwick Russell CA, co-founder of SMEtric Insights: “Businesses with lots of data, or businesses using a number of different systems and who want reporting all in one place, rather than having to dive into each system for reports and/or export report into Excel or CSV files to then put together.” 

Data analytics, which underpins visualisation, can provide SMEs with both big-picture and granular insights. “Visualisation with the right design and purpose can be used by any organisation to look at key business drivers,” Rubin says. For these techniques to be useful, an organisation needs to recognise the value it can unlock from the data.

Where does the data come from?

Rubin notes that raw data can be sourced from three interrelated areas:

• internal accounting (Xero, QBO, MYOB, SAGE, etc)
• internal operations (practice management, inventory, CRM, payroll, other operational workflow tools, such as WFM, SimPro, Unleashed, Deputy)
• external data (website traffic, social media, competition pricing data or relevant information such as exchange rates or even the weather).

Smaller businesses can connect their accounting platforms with affordable, cloud-based workflow solutions and access data from various areas of the business beyond basic accounts. “The usefulness of the data analysed is notably improved by accessing and integrating the operational data,” says Cameron Lynch CA, founder of Etani Business Platform.

How should analytics be set up?

Analytics can be grouped into dimensions. Here are six key factors for organising data analytics and visualisation for excellence: 

1. User profiles and requirements: What are the user or customer needs? The starting point is a candid and complete understanding of current and anticipated stakeholder need - the client’s needs in order to influence and guide decision making and from a staff perspective, an exploration of what’s being done currently and why.
2. Data governance and quality: Maximising the value (accuracy, completeness, consistency) of data through analytics makes it an invaluable asset. Data quality should be addressed at the source, even if it means staff training or process redesign.
3. Demand management and prioritisation: Avoid devoting too many resources to the customers who shout the loudest. Establish clear priorities guided by business strategy and effective customer segmentation.
4. Solutions development: Adopt a collaborative approach to deciding key stakeholder needs and triggers.
5. Leadership and resourcing: Leadership needs to embed analytics and visualisation in the business strategy and organisational structure, as well as staff skills. It requires a commitment of time and energy.
6. Technology platform: The right technology and infrastructure are essential to maximising impact and effectiveness:

• adopt software-as-a-service or a cloud-based platform
• define specifications before buying
• don’t get feature happy – focus on user profiles and needs
• aim for controlled self-service
• develop a mobile-first mindset.

What are the pitfalls?

“The biggest barriers companies face in extracting value from data and analytics are organisational; many struggle to incorporate data-driven insights into day-to-day business processes,” write Nicolaus Henke et al in McKinsey Global, 2016. “Another challenge is attracting and retaining the right talent – not necessarily data scientists but business translators who combine data savvy with industry and functional expertise.”

Good visualisation requires quality client data, access to software APIs, and staff who are willing to share data. You may need to enlist the assistance of a CFO or management accountant who can spot if any data doesn’t make sense. Some staff may need to be persuaded that sharing data will free up their time to act on the insights, improving the overall value of the data.

How should visualisations be presented?

While analysing data may come naturally to number-loving accountants, data visualisations can unlock their creative juices. Visualisations are crucial to helping clients who are not numerically minded understand what the data can tell them. Russell recommends keeping visualisations simple by utilising easily distinguishable colours; or, for an excellent user experience, engage a good graphic designer. 

Colours that reflect the client or business’s colour palette are also powerful, Rubin says. “For most business owners, simplicity is the key, so looking at the most important insights and how colours can be used to draw attention is helpful,” he says. “Of course, this takes a level of understanding of the business, their performance levers and the individual stakeholders reviewing the data in question.” 

Explore creative ways to present and engage with data differently based on the situation, he says.

What are the benefits of data visualisation?

A little good data visualisation goes a long way. Here’s what three experts in the field have to say on its impact:

Professor Erik Brynjolfsson, MIT Sloan School of Management: “Companies in the top third of their industry that use data-driven decision-making were, on average, 5 per cent more productive and 6 per cent more profitable than their competitors.”

Lance Rubin, financial modelling expert, The Outperformer: “Decision-making is best served visually [to many non-financial leaders] and data visualisation is a key part of serving hindsight and insight in a way that is consumable to non-accountants or business owners.”

Warwick Russell, co-founder, SMEtric Insights: “You can see what’s happening at a glance so you can spend more time acting on the numbers than trying to find or interpret the numbers from Excel spreadsheets. Staff can be given different levels of access to relevant dashboards. They can see what they need to see, more easily understand it, and have greater confidence in making decisions.”