What is the Profitability Analytics Framework
PACE's Profitability Analytics (PA) Framework is a process designed to produce high-quality internal decision-support information that supports decision making throughout the organization – from the C-suite to the shop floor and direct customer contact points. It is built on a holistic view of revenue management, managerial costing, and investment management within an organization.
The PA Framework goes well beyond traditional financial accounting, reporting, and analysis. It incorporates modern revenue management techniques, modern managerial costing focused on internal decision support, and new views of investments as both tangible and intangible.
The PA Framework is built to support and enhance the strategic planning framework of an organization and ensure management accountants are actively engaged in the creation of strategic plans by providing data, information, analytics, and insights well beyond traditional financial reporting.
The PACE PA Framework is designed to support internal decision making within an organization’s larger strategic/risk management envelope and expand the range of influence of management accountants by making it clear that they have an essential role supporting internal customers throughout their organization to optimally achieve strategic objectives.
Overview of the Profitability Analytics Framework
Benefits of Using the Profitability Analytics Framework
Use of the PA Framework helps explore issues such as:
• The management accountant’s role in:
-defining and evaluating customers, markets, and competition to develop market strategies.
-defining and adjusting internal resources, capacities, capabilities, and competencies to meet strategic goals.
-creating and using causal nonfinancial, operational models to support all the organization’s value-creating activities—both revenue and production/service delivery.
• Causal financial modeling that applies the principles of causality in revenues and costs in order to clearly reflect economic reality for internal decision support.
• New approaches to forecasting and planning for internal decision support based directly on the organization’s strategy, processes, and resources.
• A pathway for FP&A functions to expand their partnerships and develop more systematic approaches to modeling and collecting data for internal decision support.
• A more holistic approach for improving financial metrics and plans for managing, evaluating, and improving customer value.
• A more holistic approach for improving financial metrics and plans for managing, evaluating, improving, and investing in resources and assets—both tangible and intangible.
• A more holistic approach for improving financial metrics and plans for managing, evaluating, and improving an organization’s processes and operations from production and service delivery to support, administrative, sales, and marketing.
• The measurement of outcomes in both quantitative and financial terms to isolate and understand causes and effects, which in turn will enable effective adaptive and corrective actions.