IBP is an empirical science that resolves problems in conventional economic science to provide analytical power comparable to Newtonian physics, especially with respect to predictive modeling and explanatory analytics based on causal analysis. IBP is formally defined in terms of the Law of Universal Marginal Value and the Three Laws of IBP. The Law of Universal Marginal Value addresses problems in conventional economic analysis by defining Opportunity Value™ as the optimal, net economic impact of an action or decision.
The Three Laws of IBP build on the concept of Opportunity Value to establish a formal basis for economic analysis and a principled design, engineering, and management framework for building and operating a new generation of high-value solutions.
Opportunity Value is essential because it is the only way to understand the interacting effects of decisions and actions. This understanding is the core of IBP. Economic decisions based on metrics other than Opportunity Value are fatally flawed and should never be used as the basis for any form of business management solution. To be explicitly clear, any “planning solution” or decision analysis that uses Marginal Value and/ or Contribution Value based on conventional economic definitions is *WRONG*! Similarly, using any form of cost analysis for planning decisions is a fatally flawed paradigm. For emphasis, *EVERY* IBP solution requires accurate analysis of Opportunity Values.
This is an important consideration with respect to Enterprise Optimizer® in the sense that it is the only commercially available software application capable of calculating Opportunity Values.
The next few paragraphs should provide further clarification for those with a sophisticated understanding of quantitative analysis methods.
First, it is important to resolve misunderstandings regarding how Opportunity Values are calculated. Opportunity Values are not merely the “shadow prices” or “reduced costs” from a linear optimization. If the representation used is not suitable for IBP analysis – e.g., if the representation is not driver-based, causal analysis, shadow prices/ reduced costs do not correspond to Opportunity Values. Similarly, if the representation does not include “Balance Sheet constraints” or relevant domain specific constraints, shadow prices and reduced costs do not correspond to Opportunity Values.
Very simply, it is not the case that all linear optimization solutions are capable of generating Opportunity Values. Very few LP representations are suitable for analyzing Opportunity Values. The only representations that are suitable are custom built. Other than River Logic, there are no commercially available LP solutions capable of calculating Opportunity Values without extensive customization by highly skilled experts with considerable experience.
More importantly, there are additional considerations that require River Logic’s support for “knowledge engineering” in order to correctly determine Opportunity Values. To understand the importance of this issue, it must be remembered that shadow prices/ reduced costs are accurate for only the next infinitesimal quantity. To illustrate, for any given activity, the shadow price/ reduced cost associated with that decision is only accurate for the next very tiny amount of that activity.
It’s difficult to imagine how this applies to the real world. For example, if the Opportunity Value for a two liter bottle of name brand cola is $0.50, what does this imply? Is it possible to increase the production of two liter bottles of name brand cola by a single unit? If so, is it possible to transport a single two liter bottle of name brand cola? It is probably not possible to do this. The minimum unit for transportation is almost certainly a unit of measure such as a case or a pallet or a truck load.
In other words, in order to properly calculate Opportunity Values, the model *MUST* be constrained in such a way that Opportunity Values are calculated in terms that are appropriate for the units of activity. Thus, in order for a “planning solution” to be a legitimate IBP solution, it must incorporate an extensive amount of domain specific knowledge.
If you have not thought about these issues until now, you might be overwhelmed by the magnitude of the problem. You might despair and abandon hope of ever being able to capture all the domain knowledge needed to build even the most basic Integrated Business Planning solution.
Fortunately, River Logic addresses the problems in such a way that it is relatively easy to build IBP solutions. In general terms, River Logic provides three distinct processing structures that support the development of IBP solutions: numerous proprietary modeling structures for capturing context-sensitive domain constraints (Attributes, Constraint Sets, etc.), an extensive “Factor/ Add” data manipulation structure with a corresponding Truth Maintenance System (TMS), and an embedded scenario management structure that automatically tracks and analyzes a Base Case, the Current Solution and the Previous Solution.
River Logic’s proprietary capabilities explicitly address the challenges associated with creating high-value IBP solutions. River Logic’s proprietary business modeling structures reduce the time and cost required to capture expert domain knowledge by at least 90%. In addition, many of River Logic's structures are not merely useful from an efficiency perspective. They provide proprietary representations that are required in order to accurately represent domain constraints.
Examples include Pooling Constraints, Ratio Constraints, Attributes, Attribute Relationships, Constraint Sets, customized Variable Types, non-linear response functions, and more. Without these capabilities, it is not possible to represent real-world IBP problems. In other words, it is not possible to calculate Opportunity Values without the support of River Logic’s proprietary capabilities for representing real-world domain constraints.
In addition, River Logic’s proprietary “Factor/ Add” structure provides unprecedented capabilities for manipulating model constraints in order to constrain a given scenario. For example, once a “base case” is validated, River Logic’s factors and adds can be used to lock any portion, arbitrarily manipulate any other portion of the model, and constrain the model in such a way that accurate Opportunity Values can be calculated for every possible action or decision.
River Logic’s TMS capabilities are required because the necessary manipulations are often complex and require expert knowledge. For example, it is not trivial to apply a constraint across multiple time periods or markets. The extensive knowledge base in River Logic’s TMS dramatically simplifies this processing and helps insure correct results.
The final River Logic component necessary for calculating Opportunity Values is the embedded scenario management structures and analysis capabilities. Every River Logic model inherently includes three scenarios, a Base Case, a Current Solution, and a Previous Solution. As part of every River Logic solve process, the scenarios are updated and many analyses are performed. At any point, a user can lock the Base Case to the current solve.
Thus, in summary, Enterprise Optimizer® can always calculate an Opportunity Value for any decision or activity as follows:
With this approach, River Logic can always be used to build an IBP solution. The key points to remember, and where appropriate, to stress, are these:
Editor’s Note: This post was originally published June 10th, 2011 and revised September 30th, 2018.