Costing and profitability management for competitive advantage

Key components of an effective CPM program

High-quality data sourcing
As organizations strive to model complex allocation processes for more accurate visibility into profitability metrics, expanding data sources and volumes are uncovered. Merging and harmonizing large data volumes from disparate sources, as well as implementing analytics and visualization tools, can create additional challenges.

Modern data management designs for cost allocation models should link product, service, and customer transactional attributes to financial data. Maintenance and monitoring of source data quality are paramount to ensure that model integrity is preserved. For example, to accurately calculate product line profitability, there should be data around quality issues, and resulting rework costs, of each SKU within a product line. If this data source is inconsistent, the resulting costing measurement will be inaccurate. In order to overcome data deficiencies and ensure consistent measurement, the source data will need to be improved or more rigorous transformation and modeling will be required.

At the end of the day, linking the cost pool to well-sourced allocation drivers is what determines optimal costing and profitability solution outcomes.

Allocation methodology and execution
Restructuring or upgrading an existing ERP, or migrating to a new one, usually gives rise to an allocation methodology change. Though profit and cost centers may be adequately predefined in an organization, there are cases where a simplification or standardization drive precedes any change. This eliminates any redundant cost or profit centers from the system. The company can then reassess the remaining cost centers and evaluate whether they fall into any mentioned categories.

Effectively sourced driver data for allocation calculations for each dimension can be companies’ most effective catalysts for refining costing and profitability accuracy. Cost and profitability drivers are the metrics that explain how expenses and revenue are derived, their origin, and the levers that may be available to influence them. Allocation drivers are predefined rules within an organization that translate how a product or service will be charged out to each function, cost center, business unit, product grouping, or SKU, as examples.

For instance, in a case where a group manager may be driven by the objective to minimize charges and report profitable results, organizations may need to choose allocation drivers that are predefined and consistent across the organization so as not to unduly burden or benefit any individual business segment.

Beyond the mechanical implementation of an allocation methodology, reaching a consensus across organizational stakeholders can be a significant effort that requires dexterity in arbitration. Decisions made in how costs are allocated have a direct impact on the profitability of business segment owners. It is the implementation team’s responsibility, as well as that of future CPM owners, to negotiate these challenges and reach common agreement across the organization.

Cost allocation approaches

Reporting, analytics, and data-driven decision-making: Key metrics
The key component of any successful CPM program is providing stakeholders with analysis and reporting to aid effective decision-making. As with many reporting solutions, these could be visual, narrative, or financial in nature. Since allocated data volumes are usually large, many of the decisions could also be guided by algorithms and machine learning. An effective example of this would be SKU prices on e-commerce portals and bidding websites, where elasticity and price thresholds may be built into the algorithms.

Agnostic of tools, an effective reporting strategy ties together the source cost pool data, drivers or allocation methodology, and postallocated data for a synthesized view of the financial results.