Negative Volatility

The percentage of industry or individual company volume sold during a period of time that is lost by a company, or by a set of suppliers, to another company or set of suppliers. Negative volatility is the sum of Get Out plus Decrease Use volume.
(See also Positive Volatility, Volatility)

Example 1:

In 1990, the cellular phone industry had a 51% increase in new customers.

Explanation: Positive Volatility is very high because of the number of new customers coming into the marketplace. We know nothing about Negative Volatility from this statement.

Example 2:

In the early 1990s, there was a trend in advertising to consolidation. More clients were reducing the number of agencies with which they did business. This consolidation offered the clients efficiencies and cost savings.

Explanation: Negative and Positive Volatility in the industry will probably be close because the clients' purchases seem to be stable and predictable, with the majority of purchase volume originating with the established Very Large and Large customers. Positive Volatility in the industry is no longer being driven primarily by unique features. Increasingly, customers are consolidating their purchases for the low cost they get from one stop shopping and, probably, for low price.

Example 3:

In the early 1990s, Hilton dropped Spectradyne, the hotel movie company. It replaced that company with On Command Video. On Command offered 60 movies at a time, compared to Spectradyne's 8, with the added feature of allowing viewers to start the movies whenever he or she wanted.

Explanation: On Command is offering a new unique functionality in the market. Total Volatility is likely to be high because this functionality offers substantial savings and revenue opportunities to the lodging industry customers. Since there is not a great deal of change among the Very Large and Large customers in the way of new entrants or exits from the market, Positive and Negative Volatility are likely to be close.

Example 4:

In the early 1990s, IBM's mainframe systems business was reaching maturity. Customers were buying fewer mainframes for fewer data centers. Price discounting in the industry had reached as high as 50% on some deals. IBM was cutting its cost structure.

Explanation: This is an industry where Negative Volatility would outweigh Positive and total Volatility is likely to be low. The Negative Volatility occurs because customers are leaving the industry due to fewer data centers buying fewer mainframes. Unanswered price discounts might be causing some Positive Volatility among existing players, but total Volatility is likely to be low unless IBM refuses to match falling prices. This appears unlikely since IBM is cutting its cost structure.

Example 5:

For years, big name auto insurers stayed away from the millions of drivers who had blots on their records. As a result, smaller specialized insurers stepped in to fill the gap.

Explanation: Positive Volatility is likely to be greater than Negative Volatility though total Volatility may be low. New competitors, the smaller specialized insurers, are entering the market to meet the needs of drivers who were previously uninsurable. Overall, however, the total purchase volume of these newly insurable customers is likely to be a small percentage of the total market. So, while Positive Volatility is greater than Negative, total Volatility is not high.

Example 6:

Keebler and Anheuser-Busch abandoned the snack food market in 1997. The salty snack market had grown in volume at 2.4% a year for several years. And during that time, Frito Lay continued to gain share..

Explanation: Total industry Volatility is likely to be low. There are few new entrants or exits among the Very Large and Large customers in the snack food business. There appear to be no blockbuster new products or substantial differences in prices that would create sizeable Positive Volatility. The market's low overall growth rate is likely to be the result of volume growth among the Very Large and Large retail customers. Frito Lay would have seen Positive Volatility, while Keebler and Anheuser-Busch would have had Negative Volatility. The Volatility in the market place would be balanced between Positive and Negative.

Example 7:

In early 1995, P&G decided to take back the low-price segment from Drypers. The company slashed its prices on its cheaper Luvs brand by 11%. Kimberly Clark followed. Drypers, in turn, cut its prices by 17%. Drypers still lost one-fifth of its market share.

Explanation: The disposable diaper industry was experiencing high Volatility. Positive Volatility would have been slightly greater than Negative Volatility. There are few new channels of distribution customers entering or leaving the market. However, the price reduction by the industry leaders might have brought new consumers into the market. Volatility within the industry itself would have been high due to the substantial change in relative prices. P&G had been in a Leader's Trap, along with Kimberly-Clark. As these leading companies reduced their prices, they recaptured some of the market share that low-priced Drypers had gained over the years. Volatility is high in the industry due to consumer turnover, as well. There are new consumer entering the market each year, creating the opportunity for Positive Volatility. There is Negative Volatility as consumers leave the market.

Example 8:

Tambrands market share shrank from the 90s in the l960s to about 52% in 1997. Its rivals introduced a barrage of product innovations and aggressive pricing. Tambrands products, by comparison, were outdated and had poor marketing.

Explanation: We know relatively little about Volatility from customers entering or leaving the market. We do know that Tambrands lost 40 share points over 35 years. While this is a substantial loss in market share for one company, the rate of that loss is likely to have left the industry with relatively low annual Volatility throughout the period.

Example 9:

In the early 1990s, competitors like Research Institute of America grabbed chunks of Commerce Clearing House's business with easier-to-use products at lower prices.

Explanation: We have no information on customers entering or leaving the industry. However, Research Institute has created Positive Volatility because of its ease of use and lower prices. Because Research Institute has done this over a short period of time, total Volatility in the industry is likely to have been high.

Example 10:

Kodak and Fuji feel vulnerable as photography moves into the digital age. Market watchers expect to see 1.8 million digital cameras sold world-wide. This number will grow sharply as quality improves and prices drop.

Explanation: Volatility in the industry is likely to be high as consumers adopt more digital photography. The photographic film market will see Negative Volatility being greater than Positive Volatility as consumers leave the market. The digital photography market will see substantial net Positive Volatility as the industry grows behind the impetus of better quality and lower prices.