Agile methodologies originate from the software development sector, where development teams work in a more collaborative and cross-functional manner to deliver a product that is developed with an iterative approach and is continually improved to meet the requirements set out.

This is a methodology that is the exact opposite of the waterfall method of development, where an elaborate plan is established at the beginning based on user requirements and the project is executed by subject matter experts, the aim is to deliver a solution in one go with minimum possible change requests and by following the specs to the exact detail.

Manufacturers irrespective of their industry segment and geographical spread are facing challenges in all areas of their business, the sheer uncertainty which exists in the market due to global trade wars, international conflicts, heightened regulations, local and regional restrictions, and changing tariffs are all contributors to this unprecedented level of chaos.

There are, however, industry-specific, people and technology-related challenges as well, there is a clear and growing knowledge/skill gap between the existing old-school workforce and the new more digitally adept one. Understanding what technologies to implement to further the company’s vision and doing so with minimum disruption is another challenge. Competition is tighter than ever, digitization is being pursued by each and every manufacturer, which means improvement in efficiency and profitability are critically important. Even in relatively stable batch-type discreet production facilities, customer demands for personalization and customization are leading to a larger than ever product mix.

Unplanned downtime is the single biggest enemy of productivity.

Forbes estimates the cost of downtime alone is over $50 billion each year for industrial manufacturers. This is more than substantial and can often be the difference between a company making or losing money. The article points toward predictive maintenance gaining prominence to significantly reduce downtime, to learn faster and predict failures long before stoppages can ever happen.