A recent ACCA webinar on in the Caribbean featured data analyst professionals from the big four firms – Deloitte, EY, KPMG and PwC – as they explained how the finance functions of the future will harness new technologies for the benefit of the whole organisation. But to do so, they will also need to change how they operate.
"In today’s environment, finance functions and CFOs are expected to transform themselves," explained Indar Ramcharan, a senior manager at EY. "They will no longer just be required to provide financial reports and process transactions.
"The ask is much more than that; they are expected to look into the future, utilising data analytics to drive insight for more long-term strategic direction."
Ramcharan suggested that there are three pillars for data: management, governance and integration. But he warned of the risk of implementing a data transformation project in an ad hoc manner, calling for organisations to migrate to a single IT platform, which could be many times more efficient.
An EY survey, Ramcharan explained, revealed the top priorities for finance functions considering a data-driven transformation:
• Increase how finance works cross-functionally as part of an extended ecosystem to enable business models and value creation
• Improve data and analytics capabilities to transform forecasting, risk management and understanding of value drivers
• Take strategic decisions on what will be sourced, recruited, retained and/or developed to transform finance talent into a sustainable workforce
• Make significant changes to the finance function operating model and skill set, utilising a best-in-class model of internal and partner resources/assets
• Reduce finance function costs through new technologies, automation and acting as overall custodian of cash and profit
Barriers to progress
PwC senior manager Alphonso Williams highlighted some of the challenges that organisations face when considering adopting analytics. These included inadequate skills, digitalising the current process rather than rethinking the process, and a lack of clear goals. "Your five-million-dollar project can become a twenty-million-dollar project very quickly," he said.
An ineffective use of technology, multiple unconnected and rigid systems, and poor implementation were also cited as challenges that need to be overcome before data analytics could be successfully deployed.
Deloitte’s Ariel Esteban Giminez said: "There is no one way to address analytics transformation – you can do it from a technology perspective, a process perspective and a people capabilities perspective, but you often see everyone in an organisation doing analytics in different ways, using different tools, using different methods and techniques. That is not efficient."
His tips for finance functions include:
• Ensure that financial processes are not silos – approach your analytics needs, requests and initiatives under the frame of a corporate data governance/analytics transformation programme
• Actively be part of corporate data governance/analytics/innovation programmes – discuss and tailor possible analytics boosters to finance requirements/needs
• Benefits not only come from tools or new software – understand data governance initiatives and their impact
Finally, KPMG manager Albert Wilson made the case for wider use of dashboards, which can achieve "more with less" and help organisations visualise their data.
• Empower teams through data and analytics
• Give deeper insights into performance
• Achieve more with less
• Become a single source of truth
• Reduce reporting lines
• Improve performance through business insights and analytics
Difference between success and failure
Transformation programmes often fail. According to Wilson, the reasons behind failure include:
• lack of upfront planning
• lack of executive sponsorship
• poor understanding of user requirements
• poor visual design
• inappropriate technology platform
• lack of maintenance and planning for future improvements
So, what should finance professionals do to ensure success? Wilson suggested a six-stage programme:
• Set the direction and plan
• Gather requirements and prioritise investment opportunity
• Design and prototype
• Make the investment and build
• Test and validate
• Deploy, scale and maintain the solution
Source: ACCA Accounting and Business magazine