A Genius Approach: Built-in Engineering Rules Prevents Problems

4 minute read

Upland Admin

Albert Einstein said intellectuals solve problems, geniuses prevent them. Built-in engineering rules allow customers to define rules on any event or action that occurs in the supply chain.

Sadly, few supply chain technology solutions have these rules built-in to the underlying technology, leaving the customers to suffer serious consequences. No matter how much standardization one might attempt, every company’s business process has nuances. Even identical processes between companies are managed differently.   Even if the management of identical processes are the same, the skills of people who manage differ. Ultriva provides a mechanism to support and axiomatically address these nuances at every level.  Rule-based functionality crosses at different functions, such as rules for inventory health, exception alerts, shipping schedules, acknowledgement, rescheduling, and shipments.

Supply Chain Management software users must be able to define these rules, otherwise the behavior of the application will be like the MRP/ERP where customers have to go and pull reports, analyze them, figure out exceptions, and then take ad hoc actions.   Most other demand-driven supply chain solutions are impotent without the ability to define these rules.  Typically, most of the applications come with pre-packaged rules which fit in to some standardized work flows. The problem arises when the nuances explained above cannot be addressed by these rules. This leads to expensive customization of the software to support those business issues; ultimately this customization also leads to the same problems faced by ERP systems – stuck on an older version due to customization.

The rules can be defined even on the non-happening of an event, such as a rule being set where the users are notified if an item is on-hand for longer than defined period.   Establishing this type of rule allows a company to realize significant cost-savings.  In the software architecture it is easy to trigger a rule when an action happens. However most of the critical exceptions happens when an action does not take place.  When a supplier failed to ship on the scheduled date or the supplier neglected to acknowledge a purchase order within 24 hours are frequent situations that might be called a “non-happening” event.  Additional examples include when material is supposed to be consumed within 3 days but does not happen or notification is needed before a part expires.

Other types of rules include shipping rules to match with supplier shipments (such as once in three days or every Friday or once in two weeks), categorizing parts as Red, Yellow and Green based on the on-hand threshold and identifying non-conformity based on supplier’s performance levels. The ability to apply shipping rules to supplier shipments is most important because some suppliers do not ship on exact lead time, rather on a specific day of the week. A supplier who ships every Friday cannot stick to the specified days of lead time unless the orders are released exactly the correct incremental days before a Friday. Without the shipping rules in place, the supplier performance will never be accurate.

As a new business process flow is added in Ultriva, a rule could be automatically created to correspond. This level of flexibility in the architecture allows Ultriva to add new modules very quickly without the need for customers to customize the application.  When Ultriva added the QMS module to support Non-Conformity/Corrective action business process, these business rules became automatically available to the users. Without further cost or effort, customers used these rules to notify the suppliers of non-conformity as well as monitor corrective action processes.  Similarly, when Ultriva developed the RFQ module it was easy to put rules around iterative RFP/RFQ processes.

A rules driven approach to supply chain management has bottom line benefits, including improved productivity due to immediate and proactive availability of information to minimize or mitigate risks.

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