Inventory, food cost and the end-to-end supply chain have unique management needs related to food service. When you implement an ERP system, it should support processes to manage suppliers and food distribution, allowing for full traceability.
The ability to manage your current inventory levels and understand what and where products are in the supply chain can help produce more accurate forecasts – leading to better contract terms with suppliers. The ability to modify your menu, pricing and recipes is fundamental to provide maximum flexibility… an advanced ERP will allow you to easily make these changes by various levels of your store/restaurant hierarchy. Since you may need to manage multiple systems to oversee various aspects of your supply chain, it is essential to have a strong integration framework in place to support a seamless workflow and transfer of data,
Integration and Master Data
Having all your required application functionality and features in your ERP would be ideal, however the reality is there are often many additional systems and third-party applications that are required to meet business needs. This includes integrating data from the store’s POS/BOS, collecting marketing data from external systems, and product costs from vendors.
All of these systems and the data must be properly integrated in order to synchronize your systems and business processes. A best practice is to define an integration strategy and work towards implementing an integration architecture using an ESB – Enterprise Service Bus. The “bus” serves as a central nervous system connecting each of your systems in a real-time de-coupled manner.
The ESB is a variant of a “hub and spoke” integration architecture, where each of your systems is connected via a centralized integration point. This architecture allows for more flexibility when adding new systems or changing existing ones that need to be integrated.
Going hand in hand with the proper integration systems is the mastering of the data. The ESB integration architecture ties your systems together and the master data management (MDM) concept unifies your data across these systems. Since having multiple systems often means having multiple lists of data you can easily end up in a situation where you have varying list for customers, vendors, inventory items or stores.
MDM is meant to implement the processes, tools, and governance to keep your key data synchronized. This often means more than simply implementing an MDM tool… it requires policies and guidelines to be implemented throughout your organization on how master data should be processed.
The best practice is to work incrementally and start with one key data area – such as customer or product – and work toward an MDM solution for it. Once you feel that the data area is mastered (meaning you can manage synchronized changes, removals, and additions to products across your organization) you can build on this platform and tackle the next data area.
Business Intelligence, Big Data and Analytics