Putting analytics into practice
A recent ACCA Caribbean webinar featured data analytics professionals from the Big Four – Deloitte, EY, KPMG and PwC – as they explained how finance functions of the future will harness new technologies for profit. of the whole organization. But to do this, they will also have to change the way they operate.
“In today’s environment, finance functions and CFOs are set to transform,” said Indar Ramcharan, senior executive at EY. “They will no longer just be required to provide financial reports and process transactions.
“The demand is much more than that; they are supposed to look to the future, using data analysis to gain insight into a longer-term strategic direction. “
Ramcharan suggested that there are three pillars for data: management, governance and integration. But he cautioned against the risk of implementing a data transformation project in an ad hoc manner, calling on organizations to migrate to a single IT platform, which could be much more efficient.
An EY survey, Ramcharan explained, revealed the top priorities for finance functions considering a data-driven transformation:
• Increase the way 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
• Make strategic decisions on what will be sourced, recruited, retained and / or developed to transform financial talent into a sustainable workforce
• Make significant changes to the operating model and competencies of the finance function, using a top-notch model of internal and partner resources / assets
• Reduce finance function costs through new technologies, automation and acting as a global custodian of cash and profits
Obstacles to progress
PwC CEO Alphonso Williams highlighted some of the challenges organizations face when considering adopting analytics. These included inadequate skills, digitizing the current process rather than rethinking the process, and a lack of clear goals. “Your five million dollar project can turn into a twenty million dollar project very quickly,” he said.
Inefficient use of technology, multiple unconnected and rigid systems, and poor implementation were also cited as challenges that must be overcome before data analytics can be deployed successfully.
Ariel Esteban Giminez from Deloitte said: “There isn’t just one way to approach analytics transformation – you can do it from a technology perspective, from a process perspective. and from a human capacity perspective, but you often see everyone in an organization doing analysis in different ways, using different tools, using different methods and techniques. It is not efficient.
His advice for finance functions includes:
• Ensure financial processes aren’t silos – address your analytics needs, demands and initiatives as part of an enterprise data governance / analytics transformation program
• Actively participate in corporate data governance / analytics / innovation programs – discuss and tailor possible analytics boosters to financial requirements / needs
• Benefits don’t just come from tools or new software: understand data governance initiatives and their impact
Finally, Albert Wilson, director of KPMG, argued for a wider use of dashboards, which can do “more with less” and help organizations visualize their data.
• Empower teams through data and analysis
• Provide more in-depth performance information
• Get more with less
• Become a unique source of truth
• Reduce hierarchical lines
• Improve performance through business insights and analytics
Difference between success and failure
Transformation programs often fail. According to Wilson, the reasons for the failure are as follows:
• lack of initial planning
• lack of executive sponsorship
• poor understanding of user needs
• poor visual design
• inappropriate technological platform
• lack of maintenance and planning for future improvements
So what must finance professionals do to ensure success? Wilson suggested a six-step program:
• Define direction and plan
• Collect needs and prioritize investment opportunities
• Design and prototype
• Make the investment and build
• Test and validate
• Deploy, develop and maintain the solution
Source: ACCA Accounting and Business magazine