Data.
Almost every action you do today will generate data. And that data is being automatically and continuously collected.
Thanks to the evolution of technology, including portable smart devices and the internet, we are constantly connected all the time and from anywhere in the world and, as a result of that interconnectivity, enormous volumes and variety of data is created.
However, this data only forms part of a business equation; it is not information alone. Today, many accountants, including myself, integrate analytical skills alongside accounting knowledge and experience to explore and translate this data into meaningful information. No longer are accountants, hiding quietly in the background, using spreadsheets to unsociably crunch numbers all day for retrospective reporting from the confines of bland, probably grey coloured, cubicles.
In actual fact, accountants, through data analysis, are your business advisors and decision-making partners.
Working alongside different areas of business in real time, data analysis by accountants can assist decision-makers understand what findings mean and the various options available, leading to better informed decisions to make the most of potential opportunities. Data analysis can also support risk management by reducing inherent degrees of uncertainty, not only limited to financial impacts but can extend to areas such as health and safety impacts, reputational impacts and the threat of obsolescence or disruption.
But what is the potential value of the data collected? How does one leverage this information rich data to formulate valuable strategic insights and competitive advantage? How can an organisation foster a culture of behaviours and beliefs centred around data?
Data collection, infrastructure and management
- Define your goals. What are your requirements? What information will be meaningful and informative for your organisation and perhaps your stakeholders?
- Make recording simple. The recording of data within a database / infrastructure should not be a cumbersome process. An off the shelf product such as Excel may meet simple needs for data recording.
- Establish a sharing process. Cloud computing infrastructure and permissioned networks can allow authorised persons to access data and view information at any time.
- Build a data team. This team should manage the recorded information, conduct monitoring and maintain general data integrity. Appoint a frontline manager who can develop and implement recommendations and act as a liaison officer for the data and any general questions, discussions and suggestions from team members across the organisation.
Data quality and analysis
- Paralysis by analysis. Don’t fall victim to the common pitfall of information overload! If the data is not necessary or relevant, don’t record it.
- Junk data in, junk data out. High quality data is imperative. Consider the reliability of the data source(s). Is the data accurate, complete and timely?
- Ability to analyse data. Data can be both unstructured and structured. Unstructured formats will require filtering, cleansing, and standardising before it can be useful to provide commercial insight.
- Discover patterns. Does the output of data analysis show trends or patterns that can be quantified? Can those patterns be linked to associated causes (traditional causes like seasonal and economic, or radical causes like a social media influencer who recently included your product or service in a TikTok reel?)
- Indicators. What indicators will be used to monitor and assess progress or change? It should be easy to recognise when success is realised, and the efforts that were needed to achieve the results.
- Don’t just look at weaknesses. Make sure you assess your strengths too in order to maintain a competitive edge! It doesn’t take long for others to notice and try to replicate successful practices.
Data communication and sharing
- Visualisation. The method in which findings from the data are communicated is equally as important as the data interpretation itself. Graphics, charts and dashboards are a powerful way to communicate a message and should be visually appealing and easy to understand.
- Share information regularly. Data should be shared regularly across the organisation, including what the information means. Communication from the data team can help the wider organisation understand what the information is saying and how it is used or affects their daily work.
Data culture
- C-Suite commitment. Encourage your executives to support data driven decisions through ongoing conversations and taking initiatives based on information derived from data.
- Get excited. Champion a data driven culture to achieve team member participation and buy in. Celebrate achievements, milestones and recognise those whose efforts are paying off to motivate the wider team.
- Repeat and refine. Data collection, management and communication will be an iterative process. Invite others to share their experience and thoughts to help engage your team members.
Final comments
Of course, intuition and ‘hunches’ have their time and place, but I believe it would be foolish to ignore data. Expensive AI or data mining programs are not necessarily required to extract information from data; you can start making data driven decisions using small data sets that will grow and evolve for the needs of the business over time. It also goes without saying that any decisions made should be ethical, and support and align with the organisation and stakeholder values.
As published in QLS Proctor and Lawyers Weekly.
Finance & Data Manager
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