Modern factory equipment is embedded with smart sensors, and raw materials are now tagged with RFID chips. Finished goods are tracked in the warehouse, on the shelves at super markets, and sometimes even once they are purchased by the end consumer.
We generate, capture, and store an enormous amount of data today, but do you really use it all? How much of it do you tap into when you try to build intelligent manufacturing systems?
If used effectively, this data can help create a smarter order management system that reduces costs, delights your customers, and improves their overall experience.
Understanding the Role of ERP Tools in Predictive Order Management
When organizations think about becoming more efficient, their first thoughts are to upgrade their technology and invite ideas for innovation. Thats important, but to be successful, youll need to make your manufacturing processes more nimble, to match the scale and speed of the e-commerce environment. This can only be made possible by an ERP tool that is simple, integrated, and evolved.
Conventional ERP tools seem inadequate for organizations working in multiple geographies, sourcing from multiple locations, and doing business worldwide, electronically. As a result, they cannot create a predictive order management system. Here are three common components that you must ensure your ERP has before you embark on such a project:
- The Legal Structure ERP systems are designed to treat each of your manufacturing units as separate entities, which becomes a challenge when aggregating data for analytics. To facilitate the free flow of data, your ERP needs to follow a flat structure and treat your business as a single coherent unit.
- Demand Planning Traditionally, ERP tools use spread-sheet-like interfaces to capture a limited number of data-points and run statistical models to forecast future demand. This doesnt produce very reliable results, especially for manufacturers of low volume, high variation products. To improve, your ERP tools need to use Big Data and real-time analytics.
- Available to Promise You can significantly improve your customers experience when your ERP solution can tell you where your inventory is and when it can be delivered, with reasonable accuracy. Only ERP tools that factor in all the data that is available can produce surprising results.
Surviving Technological Disruption in the Digital Age
Predictive order management can tap into all of the data from your digital supply network analyze it, and produce valuable insights. As a result, it helps make supply chain management more efficient, order management more responsive, and customer interaction more intuitive.
While creating a good predictive order management system, you need to optimize your ERP tool and follow the Predictive Order Management Chain (POMC) model.Following this model will help you predict what your organization needs to do to better manage the logistics around manufacturing and delivering the final products when an order is received.
In the modern e-commerce business environment, such predictive order management systems are becoming the industry standard. To delight your customers, start thinking about how you can use Big Data and analytics to improve your order management capabilities, and your business as a whole.
The author wishes to thank Goran Lucic in the preparation of this blog.
Goran Lucic is an Engagement Director in TCS’ Consulting and Enterprise Solutions unit. In his current role, Goran helps organizations develop business strategies, capabilities, and executional roadmaps to adapt to constantly changing environments. Goran has 25 years of experience in business transformation engagements across geographies, delivering strategic IT and business technology advisory.