Organisations worldwide, including finance departments, are using data to boost the efficiency of existing processes, drive operational costs down, achieve strategic excellence, and monitor and improve performance. And according to a study by the Business Application Research Centre, they are gaining benefits from big data such as better strategic decisions, improved control of operational processes, an increase in revenues and reduction in costs.
Digitising transactional processes have productivity benefits associated with them and can also help create new datasets for analytics, which in turn enables finance functions to deliver new rapid insights. This can elevate the function’s relevance and value to the organisation. However, the right groundwork needs to be put in place for the transformation to take root.
The power of data
Data analytics is a broad term that encompasses a plethora of diverse techniques and processes which draws insights from financial and non-financial data to improve operational decisions that are critical to an organisation’s success.
By digitising fit-for-purpose processes with cutting-edge technologies, finance functions can provide organisations with easily accessible and transparent data and reporting.
This in turn will give organisations the capability for data-driven decision making, which will enable a more forward-thinking and agile finance function.
For example, when finance organisations automate their processes, they can free siloed data and allow for increased data sharing between all departments within the organisation.
With data analytics, KPIs can be identified, measured, improved, filtered and arranged according to what’s most relevant at any needed time.
Process digitisation can also increase workforce productivity, which in turn improves cost efficiency. Transactional processes, for one, stand to gain the most.
The challenge of data
One of the biggest data challenges faced by organisations is turning the deluge of raw data into actionable insights. CEOs and CFOs are looking for quick, easy, and automated ways to obtain them.
To truly extract value from their data, organisations must address the following challenges:
- Regulatory compliance
Finance functions must fulfil stringent regulatory requirements.
- Data security
Data governance measures can help mitigate risks common in finance such as hacking, unauthorised access, corruption, and theft. Top-tier big data management tools can help ensure that data is secure, protected and monitored.
- Data quality
Organisations want to do more than just store data. Extracting value from unstructured data sets requires collating and compiling various sources of information.
- Data silos
The inability to connect data across departmental and organisational silos is a major business intelligence challenge, leading to complicated analytics that stands in the way of big data initiatives.
- Data usage
American astronomer Clifford Stoll once said, “Data is not information, information is not knowledge, knowledge is not understanding, understanding is not wisdom.”
One of the biggest shortcomings of digital initiatives is the failure to use the technology. Despite all the hype about artificial intelligence, human intelligence is still required to interpret data, identify gaps in performance, establish root causes and actions, and to see that the actions are executed successfully. This requires much more than installing an app to fix.
Regardless of the challenge, organisations must thoroughly define their overall data roadmap — one that lays the groundwork for how data is handled and its role in helping the finance function address its issues and shortcomings.
The roadmap should include:
- Systems or structures to capture data
- A communication plan to obtain buy-in from employees so that they can understand their role in a data-driven organisation
- A plan to fill missing skillsets and capabilities to interpret and develop data-driven insights
- A strategic plan to collect, organise and use the right data in a way that will add value to the organisation
As different organisations have different ideas of what they want from their finance function, the roadmap will be unique for every organisation. Some organisations may want the finance function to be more proactive and focused on analysis or planning. Others may require their finance functions to be more transactional, or they may find a need to reduce transactional and reporting activities and shift it towards higher-value activities such as strategy or decision-making support. This may call for process reengineering.
By taking a strategic approach towards data, the finance function is well on its way to becoming a proactive partner that delivers value to the organisation.
However, while data and analytics is a great enabler, finance transformation also involves transforming systems, processes, the organisation structure and the culture of the finance function itself to be successful.
Discover the framework to implement successful finance transformation in our white paper, Winning Finance Transformation: Harnessing the Full Value of the Finance Function.