Intelligent ERP. This phrase is gaining momentum and it’s being spurred by Digital Transformation. Plastic Manufacturers are always looking for performance improvements to allow selling and producing more with fewer resources at a lower cost.
While Machine Learning, Artificial Intelligence and other advanced analytics offer exciting opportunities in areas where predicted outcomes can make a sizeable financial impact like:
- Using Machine Learning to forecast resin price and for sales forecasting
- Using Artificial Intelligence to predict remaining useful life of machines for timing of capital expenditures
- Using either analytics above for predictive machine breakdown avoidance and balancing time considerations such as, production schedules, promise dates, sales forecast, etc.
Often the data is available buried in some report but it’s sometimes a new relevant visualization (you know, the old charts and graphs) that bring outliers and other exceptions into full view (See Figure 1 below). And, it’s not always identifying bad use cases… in many cases, it’s identifying the positive outliers and understanding the myriad of process improvements, collaboration and other methods that have led to the overwhelming success.
Figure 1 – Geo Map Example Below (Source = Public preview of project codename “GeoFlow” for Excel delivers 3D data visualization and storytelling)
Microsoft is in an ideal position having spent the past five years to rebuild and re-platform their ERP system to support Digital Transformation through Azure services (including Machine Learning, Predictive Analytics and user oriented tools). And, the primary end user oriented tool, PowerBI has been integrated and embedded into this system (using role-based Workspaces) to bring these epiphanies front and center in Dynamics 365.
For more on how business intelligence is built directly into Dynamics 365, see our collection of Power BI blogs – http://ellipsesolutions.com/category/powerbi/