the case for Dynamic Enterprise Simulation™
Dynamic Enterprise Simulation establishes a framework for consistent understanding of enterprise complexity while gaining the mathematical blueprint for optimizing performance. DES decodes and maps the entire enterprise, unlocks business system data and provides in-depth assessment and forecasting.
This flow diagram indicates the key six steps in Dynamic Enterprise Simulation, and where the KUITY Data Mapping and Modeling Platform comes into play.
Dynamic Enterprise Simulation is not merely mapping data, although that is an early and crucial element of it. DES encompasses data harvesting, transformation, orchestration, intelligence extraction, modeling and simulation, and visualization.
This holistic understanding of the enterprise is critical to gaining control of the causal relationship set—identifying a few Key Performance Indicators will not tell you what you need to know. You need to understand the relationship between the underlying data and the Key Performance Indicators.
Once a dynamic and customized model of the causal relationships in the enterprise are in place, there is no shortage of opportunities for bottom line improvements.
- Model risk scenarios for different courses of action
- Simulate impact of changes to service fee structure to revenue and customer retention
- Validate economic assumptions and degree of impact to organization
- Optimize pricing strategy
- Optimize inventory allocation and distribution
Business performance at the speed of business activity
Whether they admit it or not, most businesses wing day-to-day decisions because the data they wish to use in decision-making is not current enough, accurate enough, or informative enough. While they may have some processes modeled and optimized and likely use spreadsheet modeling when contemplating a new business line, the daily operations of the business are largely a function of experience and a gut sense for what the outcome will be. This is because most analytics are static. The data must be manually gathered and consolidated and the models take a long time to tune. This static representation ensures the model will soon be out of step with current realities (sometimes even before it's completed), and is less likely to be trusted or used in the decision process. Because DES operates in a "live-mapped" environment, organizations can be confident that data used for analysis is current and accurate. Developing trends and sudden shifts can be captured and analyzed on the fly so that operational decisions can take advantage of this timely intelligence.
Now, instead of the guess work involved in predicting next year’s or next quarter’s revenue and earnings projections, management is able to gain statistically reliable projections. And, while most businesses have a slow rear view mirror with meaningful latency between actionable information and the timing of when action is required or expected, DES helps shorten and eventually eliminate this gap. Organizations gain confidence in their understanding of business performance, in a timeframe that enables them to take maximum advantage of the intelligence. Further, DES helps organizations gain understanding and reduce volatility (variability).
Our pioneering work in the development of Dynamic Enterprise Simulation and optimization models is infused into all our product and service offerings.