Take-it-or-leave-it is a business model that has been actively used in the manufacturing industry for some time now. Henry Ford used to famously say – you can have any color for a car model as long as it was black. The strategy proved to be profitable for discrete manufacturing since they enjoyed the process of amassing a make-to-stock inventory with minimal production differences. However this static model has given way to more personalized, made-to-measure manufacturing that relies on modern ERPS with automation for increasingly complex tasks and processes.

Increasing Demand for Personalization

Technology has had a huge role in changing this long-standing dynamic. With the emergence of social media, B2B e-commerce, social media and online portal for customer engagement B2B buyers are now more in touch with manufacturers. This increased level of personalized interaction has paved the way for more manufacturing options and customizable variants.

In an attempt to keep up with the rapid increase in made to measure components, manufacturers are turning towards modular design, late-stage assembly as well as mix and match components. Workflows and assembly lines are being reinvented to be more flexible and are being streamlined to make way for the intervention of smart robots who can help assist in dispatching large volumes of parts and components with various specifications.

The Need for Automation

Manufacturers who are still working within the confines of legacy systems are having a hard time keeping pace with competitors who are quick to adopt new technology as a means of survival. The key to delivering products that are customized is to have a well-oiled link between your supply chain and manufacturing. Quotation is another such avenue that when manually overseen leads to a considerable number of errors not to mention how time-consuming it can be.

In a perfect situation manufacturing quotation would be undertaken with the help of automation. This would also entail the generation of a bill of materials along with all other operations integrated. In the absence of a predictive, adaptive supply chain manufacturers can often face the following common issues.

  • Absence of transparency into what is to be expected since systems are not integrated.
  • Lack of consistency between engineering and manufacturing Bill of Materials (BOM).
  • Reduced visibility into available options, features and materials create hurdles to forecasting.
  • Product cost is higher than sale price.
  • Delivery dates may not be met.
  • Inability to meet favorable relationship with suppliers.

Making a supply chain that is much more productive calls for a link between sales, engineering and planning systems for thorough visibility into predictability. Also engineering BOM’s and manufacturing BOMs have to be in alignment with each other while being automatically generated by intelligent robots. Forecasts ought to be based on probability factors devised for various options, features and materials that need support.

In order to limit the burden faced by manufacturing you can retreat to the very beginning and reengineer design processes by considering what can be done better. A supply chain that has a bird’s eye view of demand factors and AI-assisted probability analysis to ascertain what materials will be required can help stay on top of the game. Just the right number of sub-assemblies can be constructed ahead of time as and when new deals are set in motion. This will make sure that client demands are achievable while keeping cost in check and maintaining quality.

Are you interested in leveraging a modern ERP for made-to-measure manufacturing? Our team at SolutionsX would be happy to help. We provide expert solutions for your organization’s ERP needs. With more than a decade of manufacturing industry experience our SolutionsX consultants are not only a point of contact but an ongoing personal guide in building and integrating a system that fits with your operations, goals and culture. Reach out to us at SolutionsX to find out more. 

2021-01-21T12:30:55+00:00