Buyer’s guide: Data analytics key for finance function

Buyer’s guide: Data analytics key for finance function

Uptake in automation and AI accelerates as pandemic inspires instrumental changes in the way organisations use data

Buyer’s guide: Data analytics key for finance function

More finance departments are looking to tech advances in order to help determine future strategy – a task that has become much more complicated given the unpredictable direction of markets and the data that has produced.

As such the adoption of automation and Artificial Intelligence (AI) has gained speed in 2020 says Chris Duddridge, UiPath’s area vice president & managing director – UK & Ireland, as “industry leaders have come to see that automation solutions that combine the two, as well as related technologies such as machine learning  and OCR can help them solve old challenges and drive sustainable growth, minimise business risk and foster innovation through technology.”

Once the privilege of the few, a range of price points to suit varying budgets has made the uptake of Robotic Process Automation (RPA) more accessible to small and medium-sized firms.

Widescale adoption has meant the technology has had to scale up quickly, with early implementers now looking to upgrade their software for the latest tech on the market.

Chris Huff, chief strategy officer, Kofax, explains: “RPA was always referred to as the ‘bridge to AI’ and I think many early RPA adopters have crossed that bridge. Early adopters are now proficient and ready for ‘RPA Plus’ to handle areas where ‘RPA Only’ struggled. Those areas were primarily around exception handling, human-in-the-loop requirements and unstructured data and document handling.

“To address these RPA capability gaps, users are seeking low-code workflow transformation platforms with embedded RPA, document automation and analytics. Based on Gartner’s #1 2020 Tech Trend – Hyperautomation, it appears RPA-early adopters are moving on to integrated low-code Intelligent Automation platforms providing embedded RPA, Workflow, Document Intelligence and Analytics.”

Igniting productivity

While demand extends to all sectors globally, there are some reservations about the threat of RPA and ML to the workforce.

“The flipside of automation is the fear that it could lead to job losses.” says Philip Rooney, CEO at DataJavelin. “One of the unusual features of the 2008 financial crisis was that, for the most part, employment stayed high, and eventually increased to record levels. However, in the meantime, productivity growth has been sluggish. Companies may try and improve productivity though automation. In the past improved efficiency has led to job creation, but it is plausible that machine learning may make some roles obsolete and see unemployment grow.”

As the conversation around productivity is further explored due to a distributed workforce, a report from Xero shows that only five percent of the jobs that exist today consist of activities that are fully automatable.

“It’s important that we try not to compete with machines, and instead look to boost the unique human capabilities that set us apart,” says Damon Anderson, director of operations, Xero UK & EMEA.

“In the coming years, AI and automation will continue to be adopted for basic or repetitive tasks. These technologies will give valuable head space and critical thinking time back to accountants and bookkeepers – allowing them to take on a more advisory role within a business,” he says.

With this in mind, Xero launched Xero Tax earlier this year. A cloud-based tool, the new tax technology enables firms to file tax and manage accounts from any location, at any time. Not only can accountants provide a remote service to their clients, it frees up time to provide support in other areas like access to capital.

Investment versus risk

Despite data analytics software becoming more affordable in the last number of years, return on investment is certainly a question you will be asking yourself says Inflo.

“Direct versus indirect return on investment, the use of data and data analytics in compliance services is not just about direct ROI on hours saved,” says Inflo CEO Mark Edmondson. “Taking the indirect approach, accountancy teams will naturally work in a different way, an advisory style of working whereby accountants sit with their clients and understand what is going on in their business instead of a mainly checklist driven methodology.”

Kevin Sheetz, CEO & co-founder, Powerlytics agrees that “a singular focus on cost will often drive a sub-optimal result.”

Often, struggling to remain relevant in an ever-changing market poses a far greater risk than an initial investment in automation technology.

“In a digital world, macro level issues such as trust, privacy and the availability of data are challenging the fundamentals of established professions,” adds Edmondson. “The biggest issue for the accounting software market is how technology can augment the accounting profession of today, to become the accounting profession of tomorrow.”

For Inflo, the evolution must centre around two core principles; modernisation of traditional accounting services to respond to stakeholder needs and creating new services to meet stakeholder needs.

“This includes traditional services such as external audit, where reviews in the UK and overseas have highlighted the disconnect between the services currently delivered and the expectations of those outside the profession.”

Future trends

As the market progresses quickly tech providers are constantly bringing new innovations to keep up with demand.

For UiPath, this will mean putting more emphasis on low-code capabilities that allow users to easily create new business applications fast.

Equally important is driving adoption and accessibility in the democratization of RPA training and last year the company launched its Automation Ready Workforce program in partnership with Chartered Accountants Ireland.

“We’re determined to empower accountants and support them to develop RPA skills so that they can design, build and work alongside software robots,” says Duddridge.

Meanwhile, Powerlytics has seen the greatest shift from descriptive to predictive analysis, a trend that has experienced growth in 2020 due to the pandemic.

CEO & co-founder Kevin Sheetz comments: “New tools and techniques have driven this push from simply using data to understand historical and current situations toward using advanced modeling technique and ML to assess future economic conditions, areas of risk, and potential opportunities.”

Another area that is gaining traction is probabilistic techniques in which organisations can build their own sophisticated models to get a greater understanding of any problems rather than just raw predictions.

Digital transformation in a post-pandemic world

The limitation to ML software is that its trained entirely on historical data and therefore can’t predict outcomes that have never been seen before.

For many vendors, having the data from the previous financial crash meant that they could identify any trends and apply those to the current market.

“Once the pandemic hit, we quickly took action and created a foundational model to determine which of our data variables best indicated the degree of consumer impact from the 2008 recession and which variables best predicated the strength of their short-term recovery (one year after the recession) and long-term recovery (through 2019),” says Sheetz.

While the global impact of the pandemic may have been unprecedented, tech software now has the data to react to similar crises going forward.

Kofax’s chief strategy officer believes that the pandemic has accelerated digital transformation, which is largely addressed with automation and AI.

“Finance holds an immense amount of data with the potential to help many areas across the organization, meaning the pandemic has created the opportunity for accounting leaders to step up,” says Huff.

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