Improve your supply chain

A study of global chemical industry best practices provides insights on how.

By Christopher F. Lange

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The variety of tools and approaches used for demand planning points to a range of sophistication and effectiveness — and indicates that there’s often an opportunity for improvements that could have significant benefits. As many in the chemical industry know, weak demand planning ripples throughout manufacturing and the supply chain and ultimately makes the achievement of superior performance a challenge.

Supply and materials planning. Chemical companies continue to make progress in the effort to bring increased flexibility to manufacturing through two fundamental practices: the standardization of formulations across facilities, and the retention of decision-making about what facilities to use to produce particular customer orders (as opposed to having the customer make that determination), the research shows.

In the 2007 study, 60% of respondents said formulations are consistent across all plants, and 22% said sourcing decisions are handled by the producer. Thirty-seven percent noted that formulations are consistent across some but not all locations, and 67% indicated that they control some but not all sourcing decisions. And on the low end of the flexibility spectrum, 3% of respondents said that their formulations aren’t consistent across facilities, and 11% indicated that their customers determine production locations.

Overall, this picture shows progress since the 2005 study, in which only 45% of participants reported consistent formulations across all plants and 20% indicated that sourcing decisions were at their discretion.

Demand/supply balancing. In this area, often known as supply and operations planning (S&OP), chemical companies have seen some improvements in the last two years. For example, in terms of collaboration, 53% of respondents in 2007 said that related business units routinely share demand/supply data, up from 41% in 2005.

Thirty-seven percent indicated that they share such data periodically, and only 10% said that there’s no such communication between business units.

The breadth of participation in the S&OP process also has increased since 2005, with more than 70% of all respondents indicating broad functional representation on the S&OP team, with members coming from areas such as customer service, commercial, finance and supply-chain management.

At the same time, however, there’s clearly room for improvement. In looking at the “frozen period” used for S&OP, 45% of respondents cited one month and 24% said they use a shorter period — but 28% indicated that they had no frozen period in effect. Not surprisingly, given these varying approaches, the volume variance experienced by respondents covered the full range from 0% to 100%.

Meanwhile, the execution of the S&OP process is not uniformly strong among respondents. More than three-quarters reported having reliable accurate data feeding frequent responsive S&OP processes, but 17% said they were working with unreliable inconsistent data. In addition, less than half the respondents reported having optimization capabilities or frequent audits to improve their processes.

Production scheduling. Production scheduling appears to be an area where there’s relatively little opportunity for major improvements. Many respondents said that their companies have integrated scheduling technology, that they have been using those tools for five or more years, and that they are at least moderately satisfied with those tools. Many noted that they are able to re-plan on a weekly basis and the process takes less than a day.

For both unplanned transitions and schedule variance, companies appear to be hitting their targets. Across the study population, unplanned transitions — that is, changes to products or campaigns that were not in the plan one month earlier — were targeted and realized at about 20%. For schedule variations — that is, times when operations deviate from the production plan — targets averaged 20% for make-to-stock and 24% for make-to-order. Actual results were 25% and 28%, respectively.

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