Key Takeaways

• “A composable paradigm is designed around modular technology solutions and best-fit vendors that deliver specific finance capabilities.”

• “CFOs don’t have to choose between being efficient or being innovative. Composability enables finance to do both by driving standardization in core capabilities and differentiation in value added capabilities.”

• “Enable a technology governance that supports experimentation and a fail-fast culture in innovative technologies, such as AI, while sticking to traditional implementation approaches in stable technologies such as ERP."

• “Think top down by identify where innovation is most urgent in finance and encourage experimentation. Execute from the bottom up  by building the foundation and promoting composable thinking across the organization to accelerate agility.”

Key Takeaways

• “A major challenge to AI use is a lack of comprehension that it is human-like, but not human. It’s important to be aware of what AI can and cannot be trusted to do in any context it is used.”

• “The tendency to believe that because AI can do some things like humans, it can do all things like humans creates inflated expectations from leadership but also resistance from employees because of fears about being replaced.”

• “Leading organizations address this cultural resistance by positioning AI as a coworker that helps people do their jobs better rather than doing their jobs for them. Such an approach increases AI success sixfold, and triples job satisfaction.”

• “AI is an enormous opportunity to increase productivity but also requires a radical change in how organizations function. This requires change from both leaders and employees. AI is an organizational capability not just a technology.”

• "To position AI as a coworker and mitigate cultural resistance, finance leaders should start small and clearly communicate an intention to prioritize productivity use cases and use newly available capacity that is freed up for value-add work.”

Key Takeaways

• “To enable a scalable delivery model, finance should reduce resourcing investments targeted at supporting niche, stakeholder-specific operational needs and should instead pursue portfolio-level value generation opportunities.” 

• “When it comes to process and technology, to effectively manage an increasingly complex and disruptive environment of digital initiatives, finance must stop delaying digital innovation in favor of ongoing process optimization efforts.” 

• “Top performing companies focus on ensuring that processes are sufficiently resilient to be able to adapt as digital innovations are pursued.”

• “Finance organizations should continue to expand their analytical scopes and usage of self-service reporting while working to enhance the decision-readiness of finance-owned data.”

• “Finance leaders should complement the function's expanding competency profiles by developing strategies to enhance kinship and belonging among key digital talent, to drive retention of critical new skills.”

Key Takeaways

• “Finance process improvement starts with setting a goal for what constitutes process excellence. This goal enables smart decisions on where and how to improve by effectively identifying what’s getting in the way of process excellence.”

• “Finance process excellence is achieved by the exploration of what technologies are in the market, as well as how machine learning and AI are enabling better decision-making by predicting outcomes and prescribing targeted actions.”

• “Many finance departments are finding Integrated Invoice-to-Cash Applications can use data to predict when customers will pay, and this informs targeted collections strategies that allow them to collect cash faster."

• “To truly benefit from technology-driven process improvement, every team needs to be familiar with the technology that is available in their process space, as well as technologies such as RPA and process mining that can be valuable tools in the automation and optimization toolkit for finance process improvement.”