Generating an accurate forecast is central to many of the business processes driving the supply chain. The forecast drives, customer satisfaction, manufacturing and shipping costs, inventory turns holding expenses. Issues with the demand planning forecast will cascade and impact all parts of your supply chain.
Demantra Demand Planning utilizes a combination of business parameters, statistical models, causal factors and sales history to generate a best-in-class forecast using Bayesian Markov methodologies. The many configuration levers used to control the various capabilities of the statistical engine are challenging to configure optimally due to the sheer number of possibilities and parameter interactions.
As your business evolves through growth, acquisitions or market changes the demand planning process you implemented may no longer be an optimal fit for your current needs. Analyzing the state of your business combined with your business needs is the first critical step to improving your supply chain performance. An Analytical Factor Health Review includes an in-depth overview of the existing Demantra implementation, customizations, performance, key metrics, and business processes. After the review, we provide you with a detailed report highlighting areas where your demand planning process can be improved as well with costs and estimated business impacts. Recommendations can vary from simple process and configuration changes to wider transformations enabling key capabilities and business flows. The recommendation will be accompanied with an actionable plan on how to best tackle your changes.
We can perform an extensive assessment covering all aspects of your Demand Planning, Trade Planning,and other Demantra processes. The focus will vary to meet your goals and will include evaluation of system behavior, performance, accuracy and fit to current and future business needs.
