The growing demand for customisation and the increasing need to reduce inventory are pulling manufacturers in two very different directions. But, by using big data analytics correctly, smart companies can ride both trends.
“Any customer can have a car painted any colour that he wants so long as it is black,” Henry Ford famously said. The great industrialist would be shocked by today’s demand from consumers for personalised products and services.
A survey conducted last year for Deloitte revealed that around two-thirds of those asked were aware of the possibility of customising products such as clothing (64 per cent), furniture (63 per cent) and fashion accessories (61 per cent) while the figure for footwear was 56 per cent.
Mass customisation is putting huge pressure on supply chains as companies work to ensure they can offer customers sufficient permutations of a particular product and a variety of delivery options. Meanwhile, firms in all sectors are also looking to reduce inventory to avoid tying up capital in stock.
It’s a dichotomy that Sara Gifford, chief solutions officer at Quintiq, a leading provider of supply chain planning and optimisation software, sees first hand.
“The ability to optimise data in real time to change your plans as you react to customer demand is critical as it allows you to drive down inventory, even when offering increased possibilities for customisation”
“Food and beverage manufacturers are particularly affected at the moment,” she says. “Take brewing. Some of the big household names in beer have acquired new microbreweries. The microbrewery market is exploding right now and it’s highly profitable, but acquiring a niche brand requires a complete change in the way in which these large companies approach production.
“They aren’t going to give up on their well-established money makers, so they have to work out how to add into their production suites much smaller rounds of a specialist product.”
For a growing number of manufacturers mass customisation introduces similar complexities as they have to consider how to schedule the different resources that are needed at various points in the production process of a wider a range of products.
Option one is to ensure they have what they need by simply increasing the inventory, but this is costly and reduces their ability to respond quickly to changes in the market. The second option involves having minimal parts and accessories ready and waiting for use. This cuts inventory costs, but it reduces the opportunities for customisation as the product nears completion in its journey along the production line. Stocks are more likely to run out, too, threatening lead times.
Meanwhile, customers are also increasingly demanding and impatient with delivery times.
“The ability to optimise data in real time to change your plans as you react to customer demand is critical as it allows you to drive down inventory, even when offering increased possibilities for customisation,” says Ms Gifford. She points out that following the excitement a few years ago over the emergence of big data, attention is now turning to what can be done with this data.
“Analytics is the key,” she says. “You’ve got those ones and zeros sitting on a machine, but now what do you do with them? Companies have all of this data drawn from the production process. This might include the way in which various intermediate inventory points flow through their supply chain. With effective analytics you can interrogate your big data and get usable information.” Read more...
For more information please visit www.quintiq.com