Manufacturing professionals continuously strive to improve the financial results for their organizations, but it is often a struggle to get financial information that causally links to operational resources and processes. The struggle is most intense and confusing for the many smaller and incremental decisions made daily or weekly to implement routine improvements.
The primary problem is that financial data normally is far from being as granular and timely as operational data. The future is arriving, however. If manufacturing professionals demand, the future could include financial data that is responsive to and supportive of operational decisions in real time.
Picture this scenario: An Internet of Things (IoT) sensor picks up an equipment performance anomaly. The anomaly is transmitted to the manufacturing operations management (MOM) system, other sensors are instantly queried, and the anomaly is evaluated as having a significant—but not imminent—probability of failure if maintenance is not performed.
There are several options to choose from: Stop the line now for maintenance, wait a few hours to see if a line stoppage occurs for other reasons, wait until the end of the shift to fix the issue, or wait for failure. Which course of action is most cost-effective? Each scenario involves a different set of costs for lost production, extent of damage, repair parts, amount of downtime, product quality impacts, late deliveries, etc. What is needed is a financial system that can rapidly provide the costs of each scenario, use the MOM calculated or judgmental probability of failure for each scenario, and provide the risk assessment with cost impacts to support management’s decision-making.
The capabilities of the MOM system and IoT sensors are typically available within the manufacturing system. The linkage to such granular financial data and the integration between financial and operations systems is much more novel. Even more unique is financial data that comes from a system or data source agreed upon by both finance and manufacturing. How can this type of coordination and financial data be made a reality?
First, finance needs to recognize that “one version of the financial truth” is not a reality. Truth for external financial reporting is found in regulatory accounting standards. Truth for internal decision support must be based on causality, the cause-and-effect relationships between resources, processes, and the intermediate and final outputs. This is known as a managerial costing model.
Second, a cost model must be built that reflects the operational model—without the distortions caused by external financial reporting standards. This means cost data is collected that reflects the use of resources. The nature of the consumption (and cost) relationships, normally fixed or proportional, must also be clearly reflected. This will allow marginal and incremental costs to be rapidly calculated. The term “reflect” is used as an analogy to the clarity of a mirror.
Third, the managerial cost data must be available when the decision needs to be made, and it must be trusted throughout the organization. No time for a special study or analysis; and the decision-maker must be confident a decision made on this cost data won’t cause his or her judgment to be questioned later.
The cost modeling to create this type of model is not part of many finance and accounting departments’ portfolio of skills and abilities. Manufacturing professionals will need to push for this type of information. However, advanced costing methodologies such as resource consumption accounting (GPK) and quantity-based, pull-oriented activity-based costing have been around for decades.
Note: This column was inspired by a prototype production project using Siemens’ MOM software and MindSphere platform and Alta Via Consulting’s proEO managerial costing software as part of the Siemens MOM Expertise Alliance Center (MEAC) initiative. See a graphic above and a presentation from Alta Via and Siemens.
>>Larry White, CMA, CFM, CPA, CGFM, firstname.lastname@example.org, is executive director of the Resource Consumption Accounting Institute, which trains and advocates for improved cost information connecting operations to business performance.