Case study Forster phamaceuticals case 28

Kathleen Grogan received her PhD in pharmacology ten years ago from Boston University. While there, she became very interested in the business side of drug distribution and hence stayed on for an extra 18 months to earn an MBA. After graduation, she went to work for Capo Corporation, a major drug manufacturer, where she managed the development of a new nonprescription antiallergy drug. Although the drug passed all Food and Drug Administration (FDA) trials and was certified for general use, Capo simultaneously developed a similar drug that was cheaper to produce and equally effective in treating most, but not all, allergy symptoms. Thus, Capo decided not to proceed with production of the drug that Kathleen helped develop. However, Capo was willing to license production and distribution rights to another company. Kathleen thought that this might be a golden opportunity, so she quit her job with Capo to found her own company, Foster Pharmaceuticals. The sole purpose of the new company is to obtain the license for, produce, and distribute the new drug, which Kathleen dubbed Sneeze Relief. Kathleen is currently working on the business plan that she will present at a venture capital conference to be held in New York. The main purpose of the conference is to match entrepreneurs with venture capitalists who are interested in providing capital to fledgling firms. Kathleen has spent a lot of time thinking about how her proposed companys receivables should be managed; she is concerned about this issue because she knows of several small drug manufacturers that have gotten into serious financial difficulty because of poor receivables management. Initially, Foster Pharmaceuticals would sell directly and exclusively to four retail customers in the Northeast (Exhibit 28.1 provides the sales mix). If demand proved solid, the company would expand into other areas and wholesale channels. Sales are expected to be highly seasonal: Allergy drug sales are slow during the winter months, but they pick up dramatically in the spring when plant pollen levels reach a peak. Business falls off again in the summer, but it picks up in the fall when the ragweed season begins. Kathleens sales forecasts for the first six months of operations are given in Exhibit 28.2. Assuming the fledgling company receives financing and begins operations, Kathleens sales forecasts for the first six months of the second year are provided in Exhibit 28.3. Kathleen does not plan to give discounts for early payment; discounts are not widely used in the industry. Based on preliminary discussions with the retail outlets (her customers) Kathleen forecasts the payment schedule, shown in Exhibit 28.4. She does not foresee any problems with bad-debt losses; the retailers she plans to sell to have been in business for a long time. Furthermore, she plans to carefully screen her customers, and she believes that these two factors will eliminate such losses. On average, Kathleen believes that 20 percent of receivables will contribute to profits, so 80 percent of receivables represent cash costs. Furthermore, the First National Bank of New England has indicated that its receivables financing would cost 8 percent annually. In spite of her optimism regarding bad-debt losses, Kathleen is concerned about the companys potential level of receivables, and she wants to have a monitoring system in place that will allow her to quickly spot any adverse trends that develop. Kathleens total sales forecast for the first full year of operations is 800,000 packages. Each package, which will contain 12 tablets, will be priced at $5. Kathleen has hired you as an outside consultant to advise her about receivables management. So far, you have developed a model that produces accounts receivable balances, average collection period (ACP), aging schedules, uncollected balances schedules, and quarterly carrying costs for the end of March and the end of June. The uncollected balances schedule permits managers to remove the effects of seasonal and/or cyclical sales variation and to construct an accurate measure of receivables payment patterns. Thus, it provides financial managers with better aggregate information than do such crude measures as the ACP or aging schedule. Kathleen anticipates that the venture capitalists will ask some questions concerning the interpretation of the receivables data, the sensitivity of the results to the basic assumptions, and strategies to reduce carrying costs of receivables Exhibit 28.1 Foster Pharmaceuticals: forecast customer sales mix Customer Sales mix Large retail chain 1 40% Large retail change 2 35% Regional drug store 15% Small grocery chain 10%

Exhibit 28.2 Foster Pharmaceuticals Partial sales forecasts for year 1 Month Sales January $100,000 February 250,000 March 400,000 April 600,000 May 450,000 June 300,000

Exhibit 28.3 Foster Pharmaceuticals Partial sales forecasts for Year 2 Months Sales January $200,000 February 350,000 March 500,000 April 700,000 May 550,000 June 350,000

Exhibit 28.4 Foster pharmaceuticals forecast receivables collection pattern: Customer 0-30 days 31-60 days 61-90 days Large retail chain 1 35% 50% 15% Large retail chain 2 25% 40% 35% Regional drug store 20% 35% 45% Small grocery chain 30% 55% 15%

Question

Write a case review that addresses receivables management. Your review should be approximately three pages.

Complete Case 28, Foster Pharmaceuticals:

Review Case 28, pages 193196, in your Cases in Healthcare Finance text. You will find a case spreadsheet model via the Student Spreadsheets link in the Resources area. (Select Case 28 to download the Excel spreadsheet.)

Write a case review that addresses receivables management. Your review should be approximately three pages.

CASE 28	Student Version					Copyright 2014 Health Administration Press
3/4/2017
	FOSTER PHARMACEUTICALS
	Receivables Management
This case focuses on the usefulness of the average collection period (ACP), the aging
schedule, and the uncollected balances schedule in monitoring a business's receivables.
The model uses sales forecasts and collections expectations to calculate ACP and to
generate both aging schedules and uncollected balances schedules. In addition, the
model calculates the cost of carrying receivables.
The model consists of a complete base case analysisno changes need to be made
to the existing MODEL-GENERATED DATA section. However, all values in the student
version INPUT DATA section have been replaced with zeros. Thus, students must
determine the appropriate input values and enter them into the model. These cells are
colored red. When this is done, any error cells will be corrected and the base case
solution will appear. Note that the model does not contain any risk analyses, so students
will have to create their own if required by the case. Furthermore, students must
create their own graphics (charts) as needed to present their results.
INPUT DATA:				KEY OUTPUT:
							End of Mar	End of Jun
Sales Forecast:				Accounts Receivables Balance:			$0	$0
Month	Gross Sales
January	$0			Average Collection Period (Days):			#DIV/0!	#DIV/0!
February	0
March	0			Aging Schedules:
April	0			0 - 30 days			#DIV/0!	#DIV/0!
May	0			31 - 60 days			#DIV/0!	#DIV/0!
June	0			61 - 90 days			#DIV/0!	#DIV/0!
Sales Mix Forecast:				Uncollected Balances Schedule:
Payer	% of Sales			January (April) remaining rec / sales			#DIV/0!	#DIV/0!
Large Retail Chain 1	0%			February (May) remaining rec / sales			#DIV/0!	#DIV/0!
Large Retail Chain 2	0%			March (June) remaining rec / sales			#DIV/0!	#DIV/0!
Regional Drug Store	0%			Quarter remaining rec / sales			#DIV/0!	#DIV/0!
Small Grocery Chain	0%
				Quarterly Carrying Costs of Receivables:			$0	$0
Assumed Collection Pattern:
Payer	0-30 days	31-60 days	61-90 days
Large Retail Chain 1	0%	0%	0%
Large Retail Chain 2	0%	0%	0%
Regional Drug Store	0%	0%	0%
Small Grocery Chain	0%	0%	0%
Other Inputs:
Periodic (quarterly) interest rate		0.0%
Contribution margin		0.0%
MODEL-GENERATED DATA:
Average Collection Period:
	Remaining Uncollected Balance at Period End
Payer	30 days	60 days	90 days
Large Retail Chain 1	100%	100%	100%
Large Retail Chain 2	100%	100%	100%
Regional Drug Store	100%	100%	100%
Small Grocery Chain	100%	100%	100%
End of March:						End of June:
Accounts receivables balance				$0		Accounts receivables balance				$0
Average daily sales				$0		Average daily sales				$0
Average collection period (days)				#DIV/0!		Average collection period (days)				#DIV/0!
Aging Schedules:
End of March:						End of June:
		Age of Accounts in Days						Age of Accounts in Days
Payer	0-30	31-60	61-90	Total		Payer	0-30	31-60	61-90	Total
Large Retail Chain 1						Large Retail Chain 1
Accts Rec	$0	$0	$0	$0		Accts Rec	$0	$0	$0	$0
%	#DIV/0!	#DIV/0!	#DIV/0!	#DIV/0!		%	#DIV/0!	#DIV/0!	#DIV/0!	#DIV/0!
Large Retail Chain 2						Large Retail Chain 2
Accts Rec	$0	$0	$0	$0		Accts Rec	$0	$0	$0	$0
%	#DIV/0!	#DIV/0!	#DIV/0!	#DIV/0!		%	#DIV/0!	#DIV/0!	#DIV/0!	#DIV/0!
Regional Drug Store						Regional Drug Store
Accts Rec	$0	$0	$0	$0		Accts Rec	$0	$0	$0	$0
%	#DIV/0!	#DIV/0!	#DIV/0!	#DIV/0!		%	#DIV/0!	#DIV/0!	#DIV/0!	#DIV/0!
Small Grocery Chain						Small Grocery Chain
Accts Rec	$0	$0	$0	$0		Accts Rec	$0	$0	$0	$0
%	#DIV/0!	#DIV/0!	#DIV/0!	#DIV/0!		%	#DIV/0!	#DIV/0!	#DIV/0!	#DIV/0!
Total End of March						Total End of June
Accts Rec	$0	$0	$0	$0		Accts Rec	$0	$0	$0	$0
%	#DIV/0!	#DIV/0!	#DIV/0!	#DIV/0!		%	#DIV/0!	#DIV/0!	#DIV/0!	#DIV/0!
Uncollected Balances Schedules:
End of March:						End of June:
			Accts Rec	Remaining					Accts Rec	Remaining
Payer	Month	Sales	for month	Rec/Sales		Payer	Month	Sales	for month	Rec/Sales
Large Retail Chain 1						Large Retail Chain 1
	January	$0	$0	#DIV/0!			April	$0	$0	#DIV/0!
	February	$0	$0	#DIV/0!			May	$0	$0	#DIV/0!
	March	$0	$0	#DIV/0!			June	$0	$0	#DIV/0!
	Quarter	Total	$0	#DIV/0!			Quarter	Total	$0	#DIV/0!
Large Retail Chain 2						Large Retail Chain 2
	January	$0	$0	#DIV/0!			April	$0	$0	#DIV/0!
	February	$0	$0	#DIV/0!			May	$0	$0	#DIV/0!
	March	$0	$0	#DIV/0!			June	$0	$0	#DIV/0!
	Quarter	Total	$0	#DIV/0!			Quarter	Total	$0	#DIV/0!
Regional Drug Store						Regional Drug Store
	January	$0	$0	#DIV/0!			April	$0	$0	#DIV/0!
	February	$0	$0	#DIV/0!			May	$0	$0	#DIV/0!
	March	$0	$0	#DIV/0!			June	$0	$0	#DIV/0!
	Quarter	Total	$0	#DIV/0!			Quarter	Total	$0	#DIV/0!
Small Grocery Chain						Small Grocery Chain
	January	$0	$0	#DIV/0!			April	$0	$0	#DIV/0!
	February	$0	$0	#DIV/0!			May	$0	$0	#DIV/0!
	March	$0	$0	#DIV/0!			June	$0	$0	#DIV/0!
	Quarter	Total	$0	#DIV/0!			Quarter	Total	$0	#DIV/0!
Total End of March						Total End of June
	January	$0	$0	#DIV/0!			April	$0	$0	#DIV/0!
	February	$0	$0	#DIV/0!			May	$0	$0	#DIV/0!
	March	$0	$0	#DIV/0!			June	$0	$0	#DIV/0!
	Quarter	Total	$0	#DIV/0!			Quarter	Total	$0	#DIV/0!
Quarterly Carrying Costs of Receivables:
End of March:						End of June:
Large Retail Chain 1			$0			Large Retail Chain 1			$0
Large Retail Chain 2			$0			Large Retail Chain 2			$0
Regional Drug Store			$0			Regional Drug Store			$0
Small Grocery Chain			$0			Small Grocery Chain			$0
Total			$0			Total			$0
										END