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Published: February 23, 2010
 / Spring 2010 / Issue 58

 
 

Virtuous Connections

To mitigate this situation, West and his team dug deep into Chem One’s sales records, analyzing each customer by its size, needs (for example, did it have a just-in-time system?), and strategic importance to Chem One, along with a few other variables. After this assessment and discussions with salespeople in the field, the team gave each customer a priority code. This code, in turn, dictated how its Chem One customer service representative would respond to its requests for rushed or changed orders. Immediately, unplanned deliveries were reduced significantly and customers were given a more realistic picture of product availability and shipment schedules.

That small fix led to another that was also related to orders and shipments. Chem One had always been proud of its automatic inventory system, which refilled warehouse shelves in an orderly fashion as product levels declined, ensuring that there was always more than enough — rather than just enough — product on hand to move out quickly as customers needed it. But in some warehouses, sales teams had developed rogue stock replenishment processes, hoping to protect their customers from delayed deliveries and product shortages. These processes had overridden the automatic system, wreaking havoc with Chem One’s manufacturing schedules. By eliminating these rogue systems, West was able to shift special ordering questions back to customer sales representatives, who could use their new segmentation programs to make smart decisions.

After cleaning up sales and ordering procedures in the supply chain, West had a relatively uncluttered pathway for improving production scheduling. Typically, manufacturing timetables had been based not on the capacity of the factory but on demand forecasts by salespeople. That had led to unrealistic schedules that did not take into account the time, resources, and plant space needed to make more complex items. To alter this inefficient approach, West implemented a system that included risk constraints — for example, the number of batches of lacquer that could be manufactured in a week was determined by whether the order contained one, 10, or 20 viscosity types. If the risk constraint was reached, the factory could not be scheduled to manufacture any more product unless management added another shift of workers. By adding this improvement to the other supply chain fixes already under way, Chem One could offer a higher level of shipment predictability. In turn, Chem One’s customers became more confident in the company’s ability to deliver on time and stopped making unreasonable demands, relaxing the supply chain still further.

This was just the beginning — in large part because Chem One’s supply chain is an extremely wide-ranging and intricate network. West went on to attack several long-running and seemingly intractable problems, orchestrating a set of solutions that ultimately simplified Chem One’s product line, reorganized its ordering procedures, and introduced a series of lean manufacturing procedures into the factories. The payback from these efforts was substantial, by all the most critical measures: Inventory on hand is down by 20 percent, to its lowest level in three years; shipment costs per ton are stable, even in a period of rising fuel prices; and stockouts have fallen by 50 percent.

Perhaps the most intriguing outcome of Chem One’s holistic supply chain initiative is that the resulting improvements and cost savings were far above the initial expectations. Although West and his team implicitly understood the potential influence of the virtuous circle concept on supply chain performance, they nonetheless forecast gains based on expected, discrete improvements in each individual aspect of the supply chain and ignored their carryover impact on subsequent links. In fact, the gains were exponential. And those gains demonstrated clearly that connecting the silos within an organization — particularly within a sprawling structure like a multinational’s supply chain — can produce tipping points that drive efficiency and generate cost savings in parts of the network that at first appear to have little direct bearing on one another.

 
 
 
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