Revolutionizing the finance department through the power of data science and automation

Over the past year, the pandemic required companies to quickly adapt to a new operating paradigm. But even before Covid, finance departments were facing growing challenges driven by ever increasing business and operational complexity.  With the vaccine rollout continuing and allowing countries to lift pandemic-related restrictions, the world is slowly but surely approaching something akin to normal. Many executives are using this time to examine their businesses and consider how they too can “build back better.”  Now is the perfect time for finance departments to digitally transform themselves.

Finance is responsible for one of the company’s most important assets: its money. It is tasked with looking after a company’s financial health by performing a range of critical duties, including administering payroll, managing budgets and cashflow, keeping meticulous records of the firm’s assets and liabilities, paying the right amount of taxes, and ensuring regulatory compliance.  Digital transformation of the finance department offers the ability to close, consolidate, and report faster and with increased reporting accuracy. It frees up resources tied to manual repetitive tasks, while reducing operational costs and increasing efficiencies.

However, there are three common obstacles to digital transformation within finance departments: 1) increasing data complexity, 2) lack of user-friendly accessible technologies, and 3) lack of skilled data workers.  Data science and automation are now critical to enable new forms of data interaction and usage, with education and upskilled a key ingredient to accelerate transformation.

On average, data workers leverage more than six distinct data sources, 40 million rows of data, and seven different outputs to do even a simple analysis.  Multiply this by the numerous analyses that each finance team needs to perform, and data challenges increase exponentially. 

In addition to increasing data complexity, many companies are stuck using outdated legacy systems which are too complex for average employees to use, or simple spreadsheets which are error-prone and lack proper controls.  According to IDC, $60 billion is wasted every year in the US due to data workers such as finance professionals spending hours and hours buried in spreadsheets.  The fact is, with the vast amounts and exploding complexity of digital data, there is only one way for an organisation to stay ahead: data science and automation.

This is a great opportunity for strategic CFOs and finance thought leaders to rethink the status quo and begin to digitally transform.  According to IDC, using data science and modern analytics allows finance departments to complete financial forecasts 74% sooner, make decisions 25% faster, and improve financial report accuracy by 16%.

By investing in more robust processes and leveraging easy-to-use modern technology built specifically for data science and automation, finance departments can better meet today’s challenges.  Thanks to the evolution of technology, a wave of smarter, more accessible data systems can be deployed by any organization to harness the power of data and automate manual processes to surface actionable insights.  Automated analytics workflows can empower organisations to speed up manual processes such as collecting and sorting the data needed for reconciliation and work more efficiently by freeing up staff to work on more creative or value-added work, such as identify future revenue streams. 

Plus, data science powers advanced analytics, which can help analysts spot unexpected connections within data sets — addressing problems such as fraud detection, audit investigations, and other types of advanced analytics where viewing the data in a connected way might reveal new insights.

Unfortunately, as more and more businesses recognise the power of data science, they are encountering another challenge: a lack of data scientists. Due to high demand, there is now a global shortage of data scientists within the labour market. According to Quanthub, this shortage grew to 250,000 in 2020.  With such a significant shortage of established data specialists, breaking down the digital divide and upskilling existing team is the next logical step to take advantage of today’s business environment.  Upskilling and empowering workers today can make up for the talent pipeline bottleneck, but businesses which do not take advantage of the data-driven insights available will be left behind.

Upskilling goes hand in hand with any transformation journey.  Any company in the midst of transformation must also invest in its workforce and their career prospects – not only to encourage a comparable investment from them in your business, but to make them feel more valued and digitally literate.  Empowering those closes to a process – those people who know exactly where the problems are – are the best placed to turn raw data into insights. Finance employees also possess key foundational skills, such as strong analytical abilities. 

The end-goal is to ensure that more people across the organization have access to useable data – an environment where employees can improve their own digital literacy. 

By fully embracing digital transformation, data science and automation, the finance department can substantially diminish process cost, while successfully redeploying talent to value-added activities. While the past year has been a challenge, the future is full of opportunity.