What managerial insights about profitability per household can you extract from Exhibit 3?

a) Using ABC analysis, and the information in Exhibits 2 and 4, calculate the loss per household for the six customer profiles per Exhibit 4. Round your calculations to the nearest dollar. b) What are two specific management actions for each of the six customer profiles that would substantially improve the profitability? Calculate the impact of these actions to the nearest dollar.

Noting that excess capacity is charged back to active accounts, if AIMS scaled back to 3,000,000 active households and planned only a 10% excess capacity reserve for future growth, a large proportion of cost could be eliminated. Estimate how much of total cost for 1999 could be eliminated, based on facts presented in the case.

What are your overall recommendations to top management based on the customer profitability information?

American Investment Management Services (AIMS) Kim Davis, Executive Vice President of AIMS, sat in her 43 floorcorner office overlooking the Manhattan skyline, reflecting on the challenges facing the investment services business in 2000. Profits had come easily during the longest economic expansion of the century. However, signs of weakness in the economy, inancial market volatility, intense competition for high net worth customers, and the proliferation of complex technology-dependent products were all making her life much more complicated. AIMS had recently invested in new analytic tools to help think more strategically about its operations and customers. Kim wondered how much the new analytic approach would really impact business decision-making. Was intensive customer segment analysis a real opportunity or just another "shot in the dark?" AIMS is one of the larger investment services providers in the U.S., approaching $500 billion in assets in 2000. Of this total, a little more than half was in mutual funds and the balance in brokerage accounts. This case deals with customer profitability assessment for AIMS' 3.9 mion households, up from 1.8 million in just four years. Until 1999, AIMS had no system for measuring the profitability of any specific customer SEGMENTATION AMS spanned two separate and very different product lines (mutual funds and full-line brokerage services), but that was only one element of the complexity it faced. In addition to this product complexity, it also spanned three distinct "distribution channels" (Call Centers, Full Service Branches, and E-business), and a complex array of customers with diverse asset holdings, trading patterns, investment objectives and service requirements. There was no particularly sharp focus on what kind of households to add. The basic idea was high wealth, but that was not pushed exclusively at al Basically, AIMS wanted to do business with the same 2 million American households (over S1 million in invested assets) that 21 other major financial services firms were pursuing. In 1999, AIMS introduced segment analysis, starting with a four-way segmentation that mixed three different dimensions: asset holdings, trading activity and age (as a proxy for investment objectives). The first segment was any household with more than S500,000 in assets under management at AIMS ("High Net Worth," or "HNW"). Failing this test, the second segment was households trading more than 36 times in 1998 ("Active Traders," or AT"). Failing this test as well, the third segment was households where the principal customer was already retirement age (60 years old). Finally, customers failing all three of these tests comprised the fourth segment-all other, termed "Core" customers. "Core," with more than 70% of all households, was the largest segment. The primary role of any segmentation is to facilitate analysis leading to management actions tailored to the specific needs of defined customer subgroups. No particular segmentation is ever beyond dispute. Whatever approach is chosen necessarily emphasizes some distinctions and de- emphasizes others. But, the AIMS segmentation was particularly contentious on two grounds: 1) it segmented current customers rather than a market. It is as if Procter & Gamble were to segment the detergent market based on how many pounds of Tide are purchased; 2) the sequence specific classification scheme meant that labels could be misleading: for example, the segment Active Trader applies only to households which are not each HNW. And, "Retiree" applied only to households which were not each HNW or AT American Investment Management Services (AIMS) Kim Davis, Executive Vice President of AIMS, sat in her 43 floorcorner office overlooking the Manhattan skyline, reflecting on the challenges facing the investment services business in 2000. Profits had come easily during the longest economic expansion of the century. However, signs of weakness in the economy, inancial market volatility, intense competition for high net worth customers, and the proliferation of complex technology-dependent products were all making her life much more complicated. AIMS had recently invested in new analytic tools to help think more strategically about its operations and customers. Kim wondered how much the new analytic approach would really impact business decision-making. Was intensive customer segment analysis a real opportunity or just another "shot in the dark?" AIMS is one of the larger investment services providers in the U.S., approaching $500 billion in assets in 2000. Of this total, a little more than half was in mutual funds and the balance in brokerage accounts. This case deals with customer profitability assessment for AIMS' 3.9 mion households, up from 1.8 million in just four years. Until 1999, AIMS had no system for measuring the profitability of any specific customer SEGMENTATION AMS spanned two separate and very different product lines (mutual funds and full-line brokerage services), but that was only one element of the complexity it faced. In addition to this product complexity, it also spanned three distinct "distribution channels" (Call Centers, Full Service Branches, and E-business), and a complex array of customers with diverse asset holdings, trading patterns, investment objectives and service requirements. There was no particularly sharp focus on what kind of households to add. The basic idea was high wealth, but that was not pushed exclusively at al Basically, AIMS wanted to do business with the same 2 million American households (over S1 million in invested assets) that 21 other major financial services firms were pursuing. In 1999, AIMS introduced segment analysis, starting with a four-way segmentation that mixed three different dimensions: asset holdings, trading activity and age (as a proxy for investment objectives). The first segment was any household with more than S500,000 in assets under management at AIMS ("High Net Worth," or "HNW"). Failing this test, the second segment was households trading more than 36 times in 1998 ("Active Traders," or AT"). Failing this test as well, the third segment was households where the principal customer was already retirement age (60 years old). Finally, customers failing all three of these tests comprised the fourth segment-all other, termed "Core" customers. "Core," with more than 70% of all households, was the largest segment. The primary role of any segmentation is to facilitate analysis leading to management actions tailored to the specific needs of defined customer subgroups. No particular segmentation is ever beyond dispute. Whatever approach is chosen necessarily emphasizes some distinctions and de- emphasizes others. But, the AIMS segmentation was particularly contentious on two grounds: 1) it segmented current customers rather than a market. It is as if Procter & Gamble were to segment the detergent market based on how many pounds of Tide are purchased; 2) the sequence specific classification scheme meant that labels could be misleading: for example, the segment Active Trader applies only to households which are not each HNW. And, "Retiree" applied only to households which were not each HNW or AT