Finance organisations are transforming; slowly but surely. This change has driven to a large extent by the disruption in the business environment, whether caused by emerging technologies, changing demographics, new business models, or convergence of industry sectors.
Future-ready finance functions have disrupted the finance operating model with use of extreme automation, delivering new and better insights and analysis with a simpler organization with skills and talent for the future and all of this built on a strong foundation of data management, quality, & governance and strong focus on risk, governance, compliance & controls.
Many of these emerging technologies are fast changing from ‘technologies to watch’ to ‘technologies to deploy’. We see eight disruptive technologies playing the biggest role; data management, cloud ERP and EPM, blockchain, robotic process automation, machine learning, cognitive technologies, natural language processing and digital analytics and delivery. A well-architected use of these disruptors will enable extreme automation and allow the finance function to transcend its traditional role and take on a business partnering role that delivers significant business value through insights generation and enhanced risk management, while significantly reducing costs.
Today most finance functions spend time analyzing historical information generating descriptive analysis (what happened) and diagnostic analysis (why did it happen). These activities can be fully automated, leaving finance teams with time and resources to focus on the predictive analytics (what will happen) prescriptive analytics (what should we do about it). For instance, as part of their planning process using predictive analytics, we can now help companies deliver accurate forecasts created automatically through machine learning and external signals. Leveraging thousands of external signals allows us to spot patterns and perform sensitivity analysis to understand key drivers for revenue, margin, and earnings. These models can significantly enhance accuracy while also be linked to real-time, updated data streams to enable rolling forecasts. As companies mature towards prescriptive analytics, they can start generating hypothesis for strategic scenario analysis of revenue and profitability, advanced customer and market analysis and so on.
While companies see the ‘art of the possible’ with this transformation, most of them struggle to succeed at implementing the most important, future oriented initiatives. As per KPMG’s Future Ready Finance 2019 survey, only 28 per cent of organisations see their current initiatives as a great success, with the two most important initiatives of using data and analytics and extreme automation having even lower success rates. It shows that the digital transformation of the finance function is less about technology and more about data and people – the two key components that can make or break it.
Dealing with the avalanche of data, both from internal and external sources, by fixing the fundamentals is the essential first step. As per this survey, data quality is the biggest challenge to improving analytics capabilities, followed by ability to integrate analytics tools to legacy systems. Both are critical pre-requisites for delivering predictive forecasting and advanced analytics. Once this is fixed, organisations can focus on the business problems they can address using these data and analytics capabilities.
Automation also needs to be accompanied by a transformation of skills and talent to enable the finance function to take on the more value-added activities. However, very few organisations, as per this survey, have been able to adapt their skill bases to operate in this more automated workplace environment. Existing staff will require fundamentally different skills, including data and technology skills, new behavioural skills and process and exception management skills in addition to stronger core finance skills.
In summary, finance organisations must develop a roadmap to be future ready, focussing on (i) transcending the role to enabling business decision making and driving enterprise performance; (ii) thinking like a venture capitalist enabling innovation and disruption; (iii) establishing a digitally enabled service delivery model; (iv) driving the adoption of advanced analytics and automation technologies; and (v) taking a comprehensive and flexible approach to talent.
(A version of this article appeared in The Business Standard on December 29, 2019)