Niagara Cutter to Reduce Inventories by 50% and Significantly Increase Turns with SmartForecasts Enterprise

Several years ago, Sherwood Bollier understood that he needed to get more control of his company's inventory levels and planning procedures. Bollier is president of Niagara Cutter, a privately-held manufacturer founded in 1954 with headquarters in Amherst, New York, and plants in Massachusetts and Pennsylvania. Niagara Cutter is a leader in cutting tool technology, manufacturing high quality tools for the metal cutting markets and selling its products to the aerospace and automotive industries, among others.

Niagara Cutter's business is very competitive. The company sells its products through industrial distributors, and although the distributors maintain an inventory of standard cutting tools for sales, Niagara Cutter's inventory and stock levels have become increasingly more important to order fulfillment. According to Bollier, “In today's market, you'd better have on the shelf exactly what your customers need, or they will find it somewhere else.”

The Challenge
This type of selling environment dictates that Niagara Cutter maintain enough inventory to satisfy high customer service levels. At the same time, however, Bollier recognized that to increase profitability the company needed to reduce inventory and reposition its assets. Niagara Cutter stocks about 24,000 separate product items. Niagara has concentrated on the “key” selling items, meaning that their demand patterns are normal and that they turn over on a regular basis. The rest, representing 95% of total inventory items, are only requested occasionally and demonstrate intermittent, slow-moving demand.

In order to maintain high service levels and reduce his total inventory at the same time, Bollier needed better forecasting and planning tools to help him figure out Niagara Cutter's inventory requirements. The company's manufacturing information system wasn't capable of generating a forecast, and the spreadsheets it was using to help in production planning were cumbersome and inadequate for the task. For this reason, Niagara Cutter didn't forecast very often, and when it did, there was no rigorous demand analysis and managers had little confidence in the results.

The Solution
Bollier found out about SmartForecasts on the Internet and initially purchased a basic version of the system to help forecast product demand and better manage his company's inventory. However, he quickly determined that what Niagara Cutter really needed was the SmartForecasts Enterprise edition with its new, patented technology to accurately forecast intermittent demand.

Intermittent demand occurs where there are few, if any, identifiable patterns in the demand history, and the demand data typically contain a large percentage of zero values with non-zero values mixed in randomly. This type of demand has been particularly difficult to forecast because the traditional forecasting methods available in most computerized systems assume that the data behave in a “normal” way with predictable trend and seasonal patterns, and these methods also ignore the special role of zero values in forecasting demand. Smart Software's technology is different. It makes no a priori assumptions about the behavior of the data, using empirical bootstrapping techniques to sample the demand history and running thousands of simulations of likely future outcomes to build each demand forecast.

According to Cyle Anthony, Niagara Cutter's production planner, the company is now able to forecast more frequently and flexibly using SmartForecasts. Some items, such as new products, are forecasted monthly, others quarterly, semi-annually, or annually. SmartForecasts also allows him to set customer service levels for each item. Key items are forecast at the 95% service level, while others are forecast at lower levels.

Anthony runs SmartForecasts Enterprise using demand history stored on Niagara Cutter's Daly & Wolcott MIS system. He uses SmartForecasts' special OLAP data management capabilities to “slice and dice” the data and quickly identify all intermittently demanded items. He then uses the system's intermittent demand forecasting technology to forecast these items, and he processes the remaining items using the software's other automatic forecasting techniques. Finally, he combines the two sets of forecasts and feeds the results back to the MIS system, where they are used to plan inventory requirements.

“We are very confident in the forecast results,” said Anthony. “We know that they have sound statistical value. That's not at all like it used to be.”

The Results
Niagara Cutter first started using SmartForecasts Enterprise at the company's Massachusetts plant. Within six months, SmartForecasts helped the plant achieve a dramatic reduction in inventory, reducing work-in-progress (WIP) levels by 75 percent.

Bollier now has his sights set on company-wide inventory reductions using SmartForecasts: “Looking ahead we expect to achieve a 50% reduction in total inventory resources and significant increases in inventory turns.”

Niagara Cutter maintains millions of dollars of inventory in raw materials, work-in-progress and finished goods. A significant decrease in inventories while maintaining customer service levels translates into increased cash flow and profitability. Niagara Cutter breaks down its inventory into three categories, and the table below shows where the inventory reductions are expected to come:

SmartForecasts Enterprise also has helped Niagara Cutter better understand its overall inventory requirements. At the company's Pennsylvania plant, SmartForecasts indicated that future demand was shifting from its uncoated line of cutting tools to its high performance, coated line of cutting tools. This enabled the company to reposition its inventory, eliminating obsolete items and making better use of its available assets.

Bollier is more confident in the information he has for decision-making. He and his top managers are so impressed with SmartForecasts' results that they are adding new manufacturing information systems from other vendors to aid in the company's planning processes. “Since we started using SmartForecasts, we've discovered new ways to drastically reduce our inventory and reposition our assets to increase customer service levels. We expect that trend to only improve in the future.”

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