The sight of a traditional factory floor full of rumbling equipment doesn’t exactly give off a vibe that says “nimble.” Faced with large fixed investments and years-long lead times to implement new technologies, some manufacturers have been slow to bring smart, data-driven technologies to the factory floor. But that’s beginning to change. Product makers are finding themselves with no alternative but to become far more agile to satisfy shifting consumer demands and preferences.

In the DXC Technology white paper “Manufacturers Wake to the Potential of Digital Technology,” Andrew Mullin, DXC’s CTO for manufacturing, Australia and New Zealand, says that companies recognize the need to make products in greater variety while managing the classic levers of cost, quality and schedule. “Manufacturers that are serious about optimizing their supply chain and value chain performance will have to reengineer at least some of their production processes,” Mullin says.

Make better use of shop-floor data

A key to the reengineering process is the ability to capture and make better use of data from all parts of the supply chain. Being a digitally savvy manufacturer means that shop-floor data can be turned into business-critical information, where analytics provide a far greater understanding of customer trends, as well as influencing product design and marketing. Here are just a few ways better data use can make a difference:

Cost-structure optimization. A processing and distribution company needs to understand the cost of production based on country-specific procurement costs and factory-specific manufacturing costs. This kind of analysis can help a manufacturer identify cost overruns and extrapolate its findings to other product lines and other manufacturing locations.

Inventory management. Data-driven manufacturing can bring together historical data, service level concepts and inventory process changes to deliver improved customer service and reduce inventory levels. For larger manufacturers, reducing a metric such as the number of days in inventory by even one day can result in saving millions of dollars annually.

Freight transport optimization. Creating unique shipper profiles can enable a company to predict capacity based on how freight is tendered. This can be used to build an automated model that selects the best shipper for pickup, delivery and line-haul operations.

Equipment downtime cost evaluation. This process marries historical data, service records and real-time sensor data to predict failures, helping manufacturers avoid unexpected operational downtime due to unplanned outages, which improves efficiency and safety. Predictive maintenance has the added benefit of extending equipment life and improving order fill rates. This process alone can yield a 5 to 20 percent increase in operational efficiency.

The fundamental measures of manufacturing success haven’t changed. Companies still need to produce quality products, on time and within budget. But as lot quantities shrink and variations increase, companies will need to get smarter about the way they plan and produce their wares.

For more from DXC experts on the digital revolution in the global manufacturing sector, read our paper, “Manufacturers Wake to the Potential of Digital Technology.”