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K-C selects Terra Technology’s MDS to improve shipment forecast accuracy, reduce safety stock

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K-C selects Terra Technology’s MDS to improve shipment forecast accuracy, reduce safety stock

April 19, 2010 - 20:47

NORWALK, CT, April 20, 2010 (Press Release) -Terra Technology, the most-trusted provider of innovative supply chain solutions for consumer products companies, today announced that Kimberly-Clark Corporation, manufacturer of some of the world's most recognized consumer brands, has selectedTerra's Multi-Enterprise Demand Sensing(MDS) to further enhance shipment forecast accuracy, improve service levels and reduce inventory costs. In a recent pilot using POS data from the largest retailers in North America, the software improved shipment forecast accuracy by 40 percent.

Gene Arnold, Vice President Sales & Operations Planning, Kimberly-Clark, said "Kimberly-Clark selected Terra Technology's Multi-Enterprise Demand Sensing to better synchronize a strategic monthly shipment forecast process with daily order execution. MDS enables us to utilize customer data along with our own order and shipment history to optimize a short-term forecast. The shipment forecast accuracy benefit in this horizon is expected to enable a meaningful reduction in safety stock inventory."

Robert F. Byrne, president and CEO of Terra Technology, said, "We're thrilled that Kimberly-Clark has selected Terra to help them improve accuracy and reduce inventory. Ongoing shifts in consumer preferences have created problems for traditional forecasting systems which rely on sales history and we think increased use of retailer data will offer significant benefits to consumer products companies in this and other ways."

According to AMR Research, "Downstream data can reduce demand latency by 90%, improve out-of-stock sensing by 2% to 4%, and improve revenue 1% to 3%. Investments in downstream data have returns in months, not years, in the area of sales account team reporting and OOS sensing."

Terra's Demand Sensing software analyzes daily demand signals, applying advanced mathematics to downstream data and decreasing shipment forecast error by up to 50 percent. More accurate forecasts enable better planning, lower inventory and manufacturing costs, and improved service levels.