Presented by Larry White and Gary Cokins
Many organizations that use SAP are far from where they want and need to be with improving their performance. They typically apply intuition and externally oriented financial information, rather than information designed for internal decision support, when making decisions.
To address this problem a non-profit Profitability Analytics Center of Excellence (PACE) was created. PACE is based on a framework that integrates revenue management, capital and intangible investment management, and managerial costing. The framework provides a roadmap for finance to support strategy formulation, validate strategy with operational and financial models, improve the quality of strategy execution, and support strategy evaluation for continuous improvement. The result is improved forecasting and decision making.
Foundational to the PACE framework is the “causality principle” which is the basis of scientific insight, including decision science, as it applies to economic, financial, and operational decisions. Effective economic modeling is essential for all of the enterprise and corporate performance management tools.These include: a strategy maps and its companion balanced scorecard; product, service line, channel, and customer profitability analysis; capacity-sensitive driver-based budgets and rolling financial forecasts; enterprise risk management; supply chain management; and lean and Six Sigma quality management for operational improvement. Each method should be embedded with advanced business analytics of all flavors.
This presentation describes how to complete the full vision of the PACE framework.
This presentation by PACE practitioners will cover:
The Profitability Analytics Framework
Improving Finance and Accounting’s role in the strategic management process.
Improving the internal decision support perspective of financial information
Some methodologies and tools that support the Profitability Analytics Framework.
Q & A
Q: What has been one major lesson learned when attempting to implement the methodologies in the PACE Framework?
A: Cokins: A major lesson learned does not involve technology, software, or methods. It involves people. It includes these: (1) Resistance to change which is human nature. People prefer the status quo; (2) fear of others knowing the truth; (3) fear of being measured; (4) fear of being held accountable; (5) weak leadership. The lesson is what is needed are behavioral change management skills to get buy-in from executives, managers, and employee teams to apply advanced managerial methods and analytics.
A: White: When implementing profitability analytics and managerial costing methods, it is necessary to move beyond the widely but incorrectly held belief that financial accounting for required external financial accounting is a comprehensive and complete “one version of the truth”. Financial reporting is designed to support investment and credit decisions by external, arms-length investors. Internal decision support, the focus of profitability analytics, needs much more information, and that information must be causal and reflect operations.
Q: What is a tip for how to define key performance indicators (KPIs) for a balanced scorecard?
A: Cokins: An effective way to identify strategic key performance indicators (KPIs) is to first have the executive team create a strategy map with two to four strategic objectives in each of its four perspectives. Then ask “what metrics (i.e., KPIs) can be used to monitor the progress in accomplishing each strategic objective?” Ideally, the executive team should assign a target level for each KPI and identify a manager who should be held accountable to meet or exceed the target.
Q: When implementing an activity-based costing (ABC) system, how does one identify the activity cost drivers? And what if the data for them does not exist or is not easily accessible?
A: Cokins: Each work activity in the middle module of an ABC system should be defined with a “verb-adjective-noun grammar. An example is “process international invoices”. Then ask “What would make the quantity or volume of the ‘adjective-noun’ significantly increase or decrease?” So, for the example, the activity cost driver would be the number of international invoices processed.
Q: Management is often skeptical that the benefits will not exceed the effort and costs to implement the methodologies you describe in the PACE framework. How can one counter their position? Is there evidence of a return on investment (ROI) from implementing any of the PACE methodologies?
A: What this question is actually asking is this: “What is the incremental benefit from having better data to make better decisions?”
When an organization is considering implementing a method from the PACE Framework, it should think about the ROI from what they have today, In short, you cannot put a measure on the benefits of better data. An organization considering implementation of a method from the PACE Framework first needs to ask itself, "Given what we see our more fierce competitors doing, how long do we want our company to perpetuate making decisions with the flawed and incomplete data that our managers and employee teams are already grumbling about?"
I am not suggesting that a company pursue a method from the PACE Framework based on blind faith, but there is some conviction required that the PACE methods just make good sense to provide better data. The flip side is to take no risk and keep using the same existing methods. Reluctance to act may be what separates successful from unsuccessful organizations.
Q: What is meant by causality?
A: White: Causality means cause and effect which is the basis of the scientific method. Internal decision support information, both financial and non-financial, needs to be causal to reflect real impact. Internal decision support needs to be looked at as a decision science, not merely compliance with rules and standards. Examples of non-causal information are allocations of overhead, treating R&D as an expense rather than an investment, pretending equipment can be fully depreciated and therefore produces products at lower cost than new equipment, pretending many marketing and selling expenses aren’t part of product cost.….to name a few.
Q: How does the Profitability Analytics Framework incorporate ESG goals and objectives? (Environmental, Social, and Governance)
A: White: We believe the Profitability Analytics Framework will support information valuable to ESG goals, but we have not yet incorporated this dimension into the framework. We would be happy to hear from you if you are passionate about moving the framework in that direction. ESG goals clearly require causal modeling which is what profitability analytics advocates.
Q: When you say “monetize the operational model”, doesn’t the financial accounting system already do that?
A: White: Traditional financial accounting for external financial reporting is a (not “the”) monetary model of the operations of an organization. HOWEVER, the issue is: How causal is it? The PA Framework “causally monetizes the operational model” with the goal that the money reflects the characteristics of the resources and processes. Traditional financial accounting allows many compromises based on man-made rules (resulting from a social consensus process). Profitability analytics seeks to apply causality with little compromise up to the point were better modeling is not economically justified to improve decisions or support achieving an organization’s strategic objectives.
Q: You use the term “economic reality”, aren’t financial statements an economic reality?
A: White: Financial statements are a reality, and they have economic impact that is perhaps out of proportion with their real informational value. Many accounting conventions and rules do not support a realistic economic depiction of reality. How can R&D not be an investment in the future? Does depreciation really occur because the earth orbits the sun or is the level of use more realistic? Overhead allocations by simplistic methods are highly distorting for many decisions. Profitability Analytics views economic reality as a decision science, a reflection of the cause and effect relationships among resources and processes, not a set of man-made accounting rules.
Q: There are a lot of terms: cost accounting, managerial costing, management accounting, and now profitability analytics. How do we unravel the definitions?
A: White: Cost Accounting is the costing done to support required/regulatory external financial reporting.
Managerial Costing is costing done purely for use in internal decision support.
Management Accounting is the profession of accountants that work inside organizations and are employees (or employee like) of those organizations. as opposed to accountants in public accounting and auditing.
Profitability Analytics expands managerial costing’s focus on internal decision support to include revenue and investment activities.