Six elements of a strong financial close

A unified, standardized data structure is the cornerstone of financial efficiency. Organizations that eliminate fragmented data sources and manual reconciliation efforts gain real-time access to financial insights, fostering faster and more informed decision-making. By ensuring consistency and accuracy, companies can also enhance financial transparency and agility.

Leading practices for a united data structure

• Adopting a global reporting and data standard
• Leveraging automation and machine learning to enable efficient reconciliations
• Implementing real-time financial reporting with advanced self-service capabilities for management and operational reporting

• Document the current state
• Discuss reporting issues with teams/end users
• Define current and future report use cases
• Develop data definition and segmentation rules

A streamlined technology ecosystem helps promote operational efficiency and enhances adaptability with a scalable platform. Leading organizations invest in platforms that integrate these cutting-edge technologies while maintaining cost efficiency. Further, focusing on the architectural simplification of the technological landscape not only enhances efficiency, but better positions finance teams to support strategic growth initiatives for the organization.

Leading practices for technology systems

• Building a high-quality data structure that is harmonized through auto mapping and derivation logic
• Streamlining allows for scalability and future-ready systems to support technological evolution and emerging advancements
• Real-time connectivity ensures quick and efficient transaction capture, enabling continuous, up-to-date financial insights

• Document the current technical architecture
• Document uses for both current and possible future technology systems
• List current challenges and gather different points of view (POVs) from stakeholders, such as end users, report receivers, CFOs, and leadership to ensure a complete overview

The financial close process is evolving from a traditionally manual, time-consuming task to an automated, continuous cycle. Organizations at the forefront of this shift are implementing near-touchless close processes that improve accuracy, compliance, and efficiency. This transformation not only enhances reliability, it can help free up finance teams to focus more on value-added analysis and strategic decision-making.

Leading practices for a continuous process

• Reduce complexity and enhance governance and controls structures with defined owners and assigned due dates
• Utilize digital tools like apps and dashboards to track close processes and reduce reporting timelines

• Document challenges within the current close process
• Document the requirements of standard closes, including commentary requirements on profit and loss (P&L) and balance sheet (B/S)
• Measure and document the time to complete steps in the process

As finance functions become increasingly data-driven, governance is critical to ensuring accuracy, compliance, and operational efficiency. Organizations with well-documented financial processes—including clear ownership, timelines, and deliverables—are better positioned to maintain high standards of control. A disciplined approach to governance can also help strengthen financial integrity, reduce risk, and foster a culture of accountability.

Leading practices for data

• Create well-documented processes and comprehensive training with clear owners, timelines, deliverables, and controls
• Get organizational support for training, governing, and data quality reporting
• Implement advanced tools for data creation, storage, consolidation, and user access

• Establish a library of current process documentation
• Gather different POVs on the state of processes and governance, including inputs from end users through leadership levels such as CFOs
• Document challenges that exist today in process and governance

Advanced analytics and artificial intelligence are revolutionizing financial insight generation. By implementing well-defined metrics, real-time analytical tools, and even artificial intelligence (AI)-driven predictive modeling, organizations can get on-demand business insights to gain deeper visibility into financial performance and future trends that enhance decision making. AI-powered tools can also help finance anticipate potential challenges—such as testing supply chains or optimizing financial planning scenarios—enabling leaders to act proactively. Access to on-demand insights means that finance teams are not just record-keepers but strategic partners driving business success.

Leading practices for analytics

• Establish clearly defined metrics with documented processes and benchmarks
• Implement on-demand analytical tools to provide real-time insights

• Document the organization’s current analytics landscape, including what works well versus the remaining challenges
• Document the future needs of analytics, such as M&A strategy, speed, or deeper market analysis

In a rapidly evolving business landscape, finance functions should build platforms that remain agile to changing needs, adaptable to emerging business models, and responsive to new opportunities. A technology-driven approach to financial operations promotes efficient integration with emerging business models, M&A activities, and evolving regulatory requirements. Organizations that architect platforms for interoperability and enable flexible integrations with new systems by embedding adaptability into infrastructure can position themselves for sustained growth and navigate the complexities of the future of finance.

Leading practices for agile platforms

• Govern technology that adheres to standard maintenance and upgrade schedules
• Ensure the technology landscape is designed for connectivity with other technologies
• Ensure a platform has the flexibility to integrate with new technologies, such as those from M&A acquisitions

• Understand the current technology landscape and its challenges
• Validate the governance of current maintenance cycles and asset upgrade schedules
• List out the possible future needs and the need-gaps in today’s technical landscape