Measures of Performance

Transcription

1 Measures of Performance The Credit Research Foundation 4 th Edition

2 MEASURES OF PERFORMANCE CREDIT, COLLECTIONS, & ACCOUNTS RECEIVABLE By: Rob Olsen, CCE The Credit Research Foundation acknowledges its indebtedness to Rob Olsen, CCE, V.P. Chief Risk Officer, Wright Express Financial Services Corporation, Salt Lake City, Utah, for his dedicated efforts in the collection and interpretation of the information, and the production of this publication. 4th Printing, , 2001,1995, 1993 by Credit Research Foundation, Inc. Columbia, Maryland All rights to this book are reserved. No part of the book may be reproduced in any manner whatsoever without written permission. Printed in the United States of America. Credit Research Foundation 8840 Columbia 100 Parkway Columbia, MD

3 TABLE OF CONTENTS Foreword... 2 Introduction... 3 Using Appropriate Measures Of Performance Can Help...4 What Makes a Measure Meaningful?...5 Benchmarking Makes Performance Measures Valuable...6 What is the Right Measure?...7 Measures and Frequency of Use...8 Performance Measures...9 Collection Effectiveness Index (CEI)...9 Days Sales Outstanding (DSO)...11 Best Possible DSO Average Days Delinquent (ADD) 15 Sales Weighted DSO DSO Countback Method..19 True DSO...21 Days Average Collection Rate...23 Payment Pattern Analysis...25 Prior Month's Past Due Collected...27 Percent Over 60 Days or (Percent of Any Age Category)...29 Days Deductions Outstanding (DDO)..31 Bad Debt to Sales...33 Bad Debt Recoveries as a Percent of Bad Debt Loss...35 Actual Loss to Budgeted Loss..37 New Account Decisioning 39 Collection Productivity.41 Operational Measures Active Customer Accounts per Credit and Collection Employee...43 Active Customer Accounts per Credit Representative or Collector Operating Cost per Employee...47 Cost per Sales Dollars...49 Cost of Collections High-Funds Accounts High-Risk Accounts Check Turnover per Cash Applicator...57 Transaction Turnover per Cash Applicator...59 Transaction Turnover per Accounts Receivable Employee...61 Deduction Turnover per Cash Applicator and A/R Deduction Specialist 63 Operating Cost per Transaction...65 Collections Cost per Customer 67 Credit Authorization Rates...69 Credit Line Utilization..70 Appendix, Items Used in Measures of Performance Analysis...71 Glossary

4 FOREWORD As part of its program of keeping credit executives informed on the changes taking place in credit and financial management, the Credit Research Foundation is proud to present this dynamic reference on measures of performance relative to credit, collections, and accounts receivable operating criteria. This book focuses on commercial credit. However, many of the measures and their corresponding explanations can be applied to consumer credit. The Credit Research Foundation is a resource for credit and receivable managers to examine their performance through numerous programs such as its Benchmarking Survey, quarterly National Summary of Domestic Trade Receivables and annual Bad-Debt Survey. American executives pursuing excellence in the hyper competitive, corporate environment must stay informed of their customers' expectations and where they stand in relation to their competitors in satisfying those expectations. For credit, collection and account receivables executives, this requires the development of accurate measures of performance that allow intraand inter-industry comparisons of company performance in this vital area. Benchmarking provides an excellent tool for credit, collections and accounts receivable executives to develop and implement an accurate performance measuring process. The information obtained as a result can be incorporated into the planning process that allows companies to focus on satisfying the consumers more thoroughly and eliminating wasteful activities. 2

5 INTRODUCTION Used as a resource in determining and defining measures of performance by credit and accounts receivable organizations, this book should act as a guide or tool to illustrate the concepts associated with various tests of accounts receivable. If there is one thing that credit executives agree upon, it is that they cannot agree on which measures to use in evaluating individual, departmental, and company performance. In researching the myriad measures available, it was evident that choosing an individual or group of measures was a personal, company, or industry preference. Since many organizations cannot agree among themselves on which measures to use, the person with the most authority usually dictates the measures to be reported to management. Even though credit, collections and accounts receivable personnel report the requested data to management, most individually track other measures to "see how they are really doing." This book is not attempting to dictate, or even suggest, which performance measures are most valid and should be used. The purpose of the book is to serve as a reference guide to readers and provide them with a comprehensive collection of performance measures used in credit, collections, and accounts receivable, hence, allowing the individual to make educated decisions on what to use and why. This book is dynamic. As new measures or information on existing measures becomes available, they will be added to the book. The author encourages all interested parties to submit information so other professionals may have the most accurate information available. If there is any information in this book that the reader can clarify, they are asked to contact the author. Dynamic credit executives plan and direct the credit, collection and accounts receivable functions to increase sales and profits. While pursuing these goals, they use their decision- making capabilities to foster growth, optimize cash inflows and improve the quality of work performed by credit, collections and accounts receivable personnel. Using valid measures of performance is critical in this process. For many years credit and finance professionals, along with academic researchers, have been seeking a means of accurately measuring performance in credit, collections, and accounts receivable. Most of the measures that are currently in use have value. Unfortunately, they also have flaws. The challenge is to understand the individual measures and use them appropriately. The prudent credit professional will have a clear understanding of the importance of spending the necessary time and effort to understand the individual measures of performance and implement the appropriate measures to meet the needs of their organization. 3

6 Using Appropriate Measures Of Performance Can Help: 1. Identify areas of expertise 2. Identify areas of potential growth 3. Improve policies and procedures 4. Reduce errors or defects 5. Shorten lead time 6. Increase customer satisfaction 7. Reduce customer complaints 8. Increase customer retention 9. Improve financial performance 10. Improve employee morale 11. Focus employee training and support 12. Increase productivity 13. Increase cash flow 14. Reduce costs 15. Reduce bad debt 16. Perform fair individual and group evaluations Regardless of the measures chosen to evaluate an organization, they must be able to stand the test of time. The measures that make an organization look good today may not in the future. The goal is to identify and use valid measures that work over time, not just measures that work for the moment. If a measure is not understood it should not be used. It is difficult to explain or defend something that is not understood. Always use measures that accurately reflect reality, and then manage for improvement. 4

7 WHAT MAKES A MEASURE MEANINGFUL? A meaningful measure fills a need and meets a specific objective. If a measure does not accomplish a purpose, don't use it. If a measure is being used and the objective is not understood, figure it out. All productive activity has a purpose. Meaningful measures will support the organization's mission and help reach organizational goals. The measure used must have a standard. The standard can be a set value or a range. For example, if the controller of a company is using Days Sales Outstanding (DSO) as an overall measure of accounts receivable in relationship to credit sales, what is acceptable? Is the standard a set value such as 45 days, where any value below 45 days is acceptable? Perhaps the standard is a range such as 42 days to 51 days, where any value within the range is acceptable. Using a range as a standard has some benefits. In this example, the low-end of the range may reflect a credit policy that is too strict, while the high end may indicate policy is too liberal. A measure must be compared to some standard or it has no meaning. Standards may be set according to past organizational or industry values or trends. Choosing a range for a standard can provide the tolerance that is sometimes needed to allow for situations such as seasonal sales. Consistency is the next element of a meaningful measure. If the standard DSO calculation is used one month, Sales Weighted DSO cannot be used the following month. Likewise, the acceptable standard and the comparable standard cannot change monthly. It's true that measures need to be evaluated and updated from time to time, but the update should be completed on more of an annual basis than monthly. The effective implementation of measures requires action. This is similar to a guidance system on a missile. It has an acceptable standard (hitting the target). It also has a comparative standard (the course to the target). The missile is constantly comparing its current position (course) to its destination (target) and making the necessary corrections to stay on course. As mentioned earlier, the acceptable standard can be specific or general. Missiles used in the Gulf War demonstrate this point very well. Iran had a range for its acceptable standard. They simply wanted their Scuds to land somewhere in Tel Aviv. The Allied Forces on the other hand, had specific values for their acceptable standard. They did not just want their missiles to land in Baghdad, but they wanted them to hit the front door of a communications building. However, this example does not imply that specific values are always preferred to a range. An effective measure provides a benefit. One benefit could be the satisfaction of reaching a goal and realizing the implications of that success. The question could be asked, "If a measure provides no benefit, why bother using it?" Organizations should communicate all measures and standards to those individuals who are responsible for executing the action plan that will help the organization reach its goals. Measures of performance should be graphed or charted as part of the reporting process. The old adage that states, "when performance is measured, performance improves, but when performance is measured and reported, the rate of performance accelerates" is true. 5

8 BENCHMARKING MAKES PERFORMANCE MEASURES VALUABLE One way to maximize the benefit of using performance measures is to benchmark. Benchmarking is a method of linking key measures of performance between companies and identifying and learning best practices. It sets forth a means of comparing the data so individual companies can compare their performance to the high and low ranges of the contributing group as well as the best in class for each measure. Benchmarking is very powerful. Individual companies can work though the organization compiling the data to find out how the best in class has been able to do so well. The benchmarking process gives organizations a vehicle to improve in specific areas. For more information on benchmarking credit, collections, and accounts receivable, contact the Credit Research Foundation at (410) or write to 8840 Columbia 100 Parkway, Columbia, MD The key measures used by the Credit Research Foundation in benchmarking are as follows: 1. Collection Effectiveness Index (CEI) 2. Bad Debt to Sales 3. Active Customer Accounts per Credit and Collection Employee 4. Operating Cost per Employee 6. Cost per Sales Dollar 7. Days Sales Outstanding (DSO) 8. Average Terms Based on Customer Payment Patterns (Best Possible DSO) 9. Check Turnover per Cash Applicator 10. Transaction Turnover per Cash Applicator 11. Transaction Turnover per Cash Accounts Receivable Employee 12. Deduction (Adjustments) Turnover per Cash Applicator and Deduction Specialist 13. Operating Cost per Transaction 14. Operating Cost per Employee 6

9 WHAT IS THE "RIGHT" MEASURE? The right measure is the one that meets your organizational needs. To determine if a measure meets your organizational needs, logic dictates that you must first understand those needs. Once your needs are understood, you must then identify the most appropriate measure to meet them. This requires a thorough understanding of what the measure expresses. The right measure will express a value that complements and supports the objectives of the company, division, department or subgroup. The following questions will help you determine if the right measure is being used: 1. What does the measure express? 2. What do the results of the measure indicate? 3. Does the measure support the objectives? 4. Is the measure valid? 5. Is there a more valid measure that should be used? 6. Does the use of the measure's results comply with organizational goals and values? 7. Should the measure be used independently or in conjunction with other measures? To help answer these questions, the following information will be provided for each measure: 1. A definition of what the measure expresses 2. Formula 3. Advantages 4. Disadvantages 5. An explanation of sample data 6. Appropriate uses 7. Inappropriate uses Note: When calculating formulas that require the number of employees and that employee performs tasks in addition to the measure being calculated, you must allocate the employee as a percentage of the time spent working on the measure being calculated or the ratio will be inaccurate. 7

10 MEASURES AND FREQUENCY OF USE The Credit Research Foundation previously conducted a survey of credit professionals asking what performance measures were being employed to assess productivity in the management of the receivable portfolio. Respondents were provided a list of measures and were asked to select all that they use to measure internal performance. The following table represents those performance measures identified together with the corresponding percent of respondents who track, measure or calculate them. Not surprisingly, DSO remains the most widely used performance metric. It is interesting to note however, that based on this survey the CEI metric is being employed with greater frequency than prior surveys have reflected. As explained later in this publication CRF believes that the Collection Effectiveness Index is a far more appropriate measure for credit and collection performance than DSO and should be considered to at least supplement the DSO calculation as a measure of credit and collection performance. Performance Measure Percent Who Track, Measure or Calculate Days Sales Outstanding 93% Bad Debt to Sales 69% Average Days to Pay from Invoice Date 51% Best Possible DSO 43% Average Days to Pay from Due Date 37% Delinquent DSO (Average Days Delinquent) 37% Collection Effectiveness Index 34% Active Customer Accounts per Credit and Collection Employee 33% Collection Productivity 22% Prior Months Past Due Collected 20% Sales Dollars per Credit Rep or Collector 15% Sales Weighted DSO 15% Operating Cost per Employee 14% Cost of Collections 13% True DSO 12% % of Invoice Accuracy 11% Operating Cost per Transaction 9% Operating Cost per Transaction 9% Per Cent of Orders Automatically Approved by System 9% Total Credit and Collection Cost per Sales Dollar 9% Check Turnover per Cash Applicator 6% Transaction Turnover per Cash Applicator 5% Deduction Turnover per Cash Applicator and AR Deduction Specialist 4% Transaction Turnover per Accounts Receivable Employee 4% Cancellation of Booked Orders 2% Other 16% 8

11 Performance Measures Collection Effectiveness Index (CEI) Definition: This percentage expresses the effectiveness of collection efforts over time. The closer to 100 percent, the more effective the collection effort. It is a measure of the quality of collection of receivables, not of time. Formula: Advantages Beginning Receivables + (Credit Sales/N*) - Ending Total Receivables Beginning Receivables + (Credit Sales/N*) - Ending Current Receivables x 100 *N = Number of Months 1. CEI accurately measures collection effectiveness (amounts that are collectible and are actually collected). 2. Somewhat neutralizes the sales bias. This is because the formula uses Credit Sales in both the numerator and the denominator and not just the denominator, as do the DSO formulas. 3. CEI can be used to evaluate individuals, subgroups and overall groups. 4. It is a quick and simple calculation. 5. It is easy to understand. Disadvantages 1. CEI is relatively new and not well known. 2. It is not expressed in days. Traditionally, DSO has been used to evaluate collection performance. As a result of the longtime general use of DSO, credit and finance people are comfortable thinking in terms of "days" when evaluating collection performance. 3. CEI is insensitive to differing terms of sale or dating. 4. This measure covers up the behavior of delinquent accounts when other accounts are discounting their bills. An Explanation of Sample Data The following data and graph show that collection effectiveness averages about 73% on most months. However, March, April, June and July are about 77% with December the highest at 80%. December is the month during which the most effective collection effort was employed. 9

12 Month Beginning Receivables Credit Sales Ending Total Receivables Ending Current Receivables CEI % Dec 740 Jan % Feb % Mar % Apr % May % Jun % Jul % Aug % Sep % Oct % Nov % Dec % Appropriate Uses 1. To evaluate individuals, subgroups and the overall group relative to the effectiveness of collection efforts. 2. CEI is appropriate evaluations over time, such as monthly, quarterly, and annually. 3. To measure and compare decentralized operating companies. 4. Benchmarking your organization with the Best in Class to identify areas and methods for improvement Inappropriate Uses 1. Being used solely to interpret individual employee performance. 2. Describing the condition of past due receivables. 10

13 Performance Measures Days Sales Outstanding (DSO) Definition: outstanding. This figure expresses the average time (aggregate), in days that receivables are Formula: Ending Total Receivables x Number of Days in Period Analyzed Credit Sales for Period Analyzed Advantages 1. DSO gives the aggregate average days that invoices are outstanding. 2. At a specific point-in-time, this measure indicates how long it takes to convert receivables to cash, i.e. measures the liquidity of receivables, expressed in days, is measured. 3. It is a quick and simple calculation. 4. DSO is easy to understand. 5. It can be used to evaluate individuals, subgroups and overall groups. 6. It is easy to understand. Disadvantages 1. DSO does not accurately reflect collection effectiveness because of the impact of Credit Sales and differing terms of sale. As Credit Sales which are not controlled by credit and collection personnel fluctuate up and down, due to such factors as extended terms of sale and seasonal sales, DSO is affected, thereby causing the number of days to be an inaccurate measurement of collection performance. 2. DSO does not accurately reflect the number of days that receivables are outstanding. 3. DSO is insensitive to differing terms of sale or dating. 4. This measure covers up the behavior of delinquent accounts when other accounts are discounting their bills. An Explanation of Sample Data The following data and graph show a general downward trend in the days invoices are outstanding or unpaid. It indicates that invoices were paid closer to payment terms in March than any other month. It also indicates that January was the worst month for payments received relative to credit sales. If the year represented by the data is representative of past years, it warns the accounts receivable department that they need to prepare for a possible poor collection month in January. 11

14 Month Credit Sales Ending Total Receivables DSO Days in Period Dec 740 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Appropriate Uses 1. The DSO calculation is widely utilized by the accounting profession as an acceptable overall measure of accounts receivable in relation to sales. 2. To interpret trends in receivables turnover. 3. Benchmarking your organization with the Best in Class to identify areas and methods for improvement Inappropriate Uses 1. Evaluating collection effectiveness of credit, collection, and accounts receivable personnel and departments. 2. As a pure collection indicator. 3. Being used solely to interpret individual employee performance. 4. Describing the condition of past due receivables. 12

15 Performance Measures Best Possible DSO (BPDSO) Definition: This figure expresses the best possible level of receivables. It calculates DSO making an assumption that delinquency is non existent. Typically Best Possible DSO equates closely to your organizations selling terms. If terms vary it expresses to the optimal level of DSO. Formula: Advantages Current Receivables x Number of Days in Period Analyzed Credit Sales for Period Analyzed 1. This calculation softens the effect of sales on DSO to express the best possible level of receivables. The closer the overall DSO is to the Average Terms Based on Customer Payment Patterns (Best Possible DSO), the closer the receivable is to the optimal level. 2. Over time, this measure indicates how long it takes to convert receivables to cash. 3. It is a quick and simple calculation. 4. Over time the liquidity of receivables, expressed in days, is measured. 5. It can be used to evaluate individuals, subgroups and overall groups. Disadvantages 1. As a stand alone measure this measure has little value. To be meaningful it should be used in conjunction with DSO to ascertain Average Days Delinquent, which will be discussed in the next section. 2. Even though this measure is better than DSO, it still uses Credit Sales and Terms of Sale in the current Age category of the aging. Therefore it is flawed for the same reasons as DSO. 3. DSO does not accurately reflect collection effectiveness because of the impact of Credit Sales and differing terms of sale. As Credit Sales which are not controlled by credit and collection personnel fluctuate up and down due to such factors as extended terms of sale and seasonal sales, DSO is affected, thereby causing the number of days to be an inaccurate measurement of collection performance. 4. DSO does not accurately reflect the number of days that receivables are outstanding. 5. DSO is insensitive to differing terms of sale or dating. 6. This measure covers up the behavior of delinquent accounts when other accounts are discounting their bills. 13

16 An Explanation of Sample Data Like Standard DSO, the following data and graph show a general downward trend in the days invoices are outstanding or unpaid. The main difference between the graph of Standard DSO and this one is that days are lower. The general pattern is the same in both graphs. If the year represented by the data is representative of past years, it warns the accounts receivable department that they need to prepare for a possible poor collection month in January. Ending Current Credit Days in Month Receivables Sales Period BPDS O Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Appropriate Uses 1. The DSO calculation is widely utilized by the accounting profession as an acceptable overall measure of accounts receivable in relation to credit sales. 2. To interpret trends in receivables turnover. 3. To highlight trend differences and potential "terms of sale" issues. 4. Benchmarking your organization with the Best in Class to identify areas and methods for improvement Inappropriate Uses 1. Evaluating collection effectiveness of credit, collection, and accounts receivable personnel and departments. 2. As a performance indicator at a single point in time. 3. As a pure collection indicator. 4. Being used solely to interpret individual employee performance. 14

17 Performance Measures Average Days Delinquent (ADD) Definition: This measure reflects the difference between DSO and Best Possible DSO. It tends to mute but not eliminate the effect that sales has on the calculation, because credit sales are still a key variable in the calculation of the two key components, DSO and BPDSO. Formula: Advantages Days Sales Outstanding - Best Possible Days Sales Outstanding 1. Removes some of the sales bias from standard DSO calculation. 2. It can be used to evaluate individuals, subgroups and overall groups. 3. It is a quick and simple calculation. Disadvantages 1. The disadvantage with this measure is that two biased measures are used in its formula, DSO and Average Terms Based on Customer Payment Patterns (Best Possible DSO). 2. Delinquent DSO does not accurately reflect collection effectiveness because of the impact of Credit Sales and differing terms of sale. As Credit Sales - which are not controlled by credit and collection personnel - fluctuate up and down due to such factors as extended terms of sale and seasonal sales, DSO is affected, thereby causing the number of days to be an inaccurate measurement of collection performance. 3. It does not accurately reflect the number of days that receivables are outstanding. 4. Delinquent DSO is insensitive to differing terms of sale or dating. 5. This measure covers up the behavior of delinquent accounts when other accounts are discounting their bills. An Explanation of Sample Data and a Graphical Representation The data and graph on the facing page indicates that January was the worst month of the year for past due invoices. All invoices were paid in an average of 19 days past the invoice due date in that month. Overall, for the whole year, invoices are paid 11 days past the due date. This is an average and the invoices that were paid in a few days offset those that are paid weeks late. In the ideal situation delinquent DSO would be zero, indicating that all invoices were being paid in the average number of days equal to the terms of sale. 15

18 Month Ending Current Receivables Ending Total Receivables Credit Sales Days in Period DSO Best DSO Avg Days Delinquent Dec 740 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Appropriate Uses 1. The DSO calculation is widely utilized by the accounting profession as an acceptable overall measure of accounts receivable in relationship to credit sales 2. To interpret trends in receivables turnover 3. To highlight trend differences and potential "terms of sale" issues. Inappropriate Uses 1. Evaluating collection effectiveness of credit, collection, and accounts receivable personnel and departments. 2. As a performance indicator at a single point in time. 3. As a pure collection indicator. 4. Being used solely to interpret individual employee performance. 16

19 Performance Measures Sales Weighted DSO Definition: outstanding. This figure expresses the (aggregate) average time, in days that receivables are Formula: ((Current Age Category of Period Analyzed / Credit Sales of Period Analyzed) + (30 day Age Category of Period Analyzed / Credit Sales of Prior Period Analyzed) +(60 day Age Category of Period Analyzed / Credit Sales of 2ND Prior Period Analyzed)) x 30 Advantages Note: There are several formulas to calculate Sales Weighted DSO. This is a simple expression of those formulas. Other formulas or expressions yield the same results. 1. Weighing age-categories by using balance fractions helps smooth out the bias of credit sales and terms of sale used in the DSO and Average Terms Based on Customer Payment Patterns (Best Possible DSO) calculation. 2. It can be used to evaluate individuals, subgroups and overall groups. Disadvantages 1. Balance Fractions must be estimated on invoices over 90 days old. 2. The older the invoice, the less accurate the estimate. 3. The cost in time and systems programming to link every unpaid invoice with its associated time period's credit sales can be prohibitive. 4. Balance Fractions may themselves introduce bias. 5. It is a complicated calculation. 6. It is difficult to understand. 7. It is insensitive to differing terms of sale or dating. 8. This measure covers up the behavior of delinquent accounts when other accounts are discounting their bills. An Explanation of Sample Data The data and graph on the following page indicate sales weighted DSO is trending up. This indicates that management needs to take some action to prevent the trend from continuing. However, if the organization's terms of sale are Net 30 days, there is no real need for alarm. If the organization's terms are Net 7 days, there is a real need for quick corrective action. 17

20 Month Credit Sales Current Receivables Day Receivables Day Receivables 90+ Day Receivables Total Receivables Nov. 14,651,201 7,672,356 3,024, , ,525 12,327,157 Dec. 14,881,064 7,846,547 3,819, ,076 1,161,612 13,663,598 Sales Weighted DSO Jan. 18,826,072 5,001,949 1,793, ,505 1,299,317 9,092, Feb. 15,246,735 4,924,392 2,370, ,918 1,377,022 9,312, Mar 14,865,794 4,957,243 2,358, ,262 1,414,142 9,670, Apr. 17,628,429 4,410,228 1,736, ,082 1,204,725 7,890, May 14,267,621 4,637,478 1,749, ,721 1,236,106 8,167, Jun 16,243,473 4,513,924 1,847, ,239 1,242,971 8,161, Jul. 14,217,137 4,791,621 2,101, ,229 1,258,666 8,602, Aug. 17,529,386 4,968,789 1,824, ,756 1,214,940 8,849, Sep. 15,852,218 5,200,684 3,294,401 1,268,324 1,216,039 10,979, Oct. 16,574,746 5,221,589 2,406, , ,588 9,052, Nov. 14,651,201 7,672,356 3,024, , ,525 12,327, Dec. 14,881,064 7,846,547 3,819, ,076 1,161,612 13,663, Appropriate Uses 1. The Sales Weighted DSO calculation is widely utilized by the accounting profession as an acceptable overall measure of accounts receivable in relationship to credit sales 2. To interpret trends in receivables turnover 3. To highlight trend differences and potential "terms of sale" issues. Inappropriate Uses 1. Evaluating collection effectiveness of credit, collection, and accounts receivable personnel and departments. 2. As a performance indicator at a single point in time. 3. As a pure collection indicator. 4. Being used solely to interpret individual employee performance. 18

21 Performance Measures DSO - Countback Method Definition: The Countback Method for calculating DSO recognizes that sales as a key variable in the calculation of DSO can distort the integrity of the calculation, particularly if sales volumes tend to experience major fluctuations from month to month. The Countback Method of calculating DSO assigns a greater emphasis to sales for the current period in lieu of prior period sales. The assumption is that most of your A/R open balance is contributed to by current month sales rather than sales from prior periods. Formula: The calculation of this measure requires four steps. Step 1 - Ending Current Receivables for the period Credit Sales for the period = Ending Total Receivables for the prior period Step 2 - Ending Total Receivables for the prior period / Credit Sales for the prior period = Percent of Credit Sales for the prior period Step 3 - Percent of Credit Sales for the prior period x Days in Prior period = Days to Add Step 4 - Days to Add + Days in Current Period = Countback DSO Advantages 1. Mutes the sales bias that is frequently encountered in DSO when sales are not steady from period to period (such as month to month). 2. As it is likely that DSO will continue as the standard for A/R performance, because this is the measure taught in U.S. business schools and accepted by the investment community, the Countback Method compliments DSO as a credit and collection performance metric. 3. By substituting current receivables for total receivables in Steps 1 and 2 you can use the Countback Method to also calculate Best Possible DSO and Average Days Delinquent. Disadvantages 1. If sales remain consistently steady from month to month the value of the Countback Method over DSO is limited. 2. It is not likely that the Countback Method is going to be considered, by neither senior financial management nor investors in the business, as a replacement to DSO. An Explanation of Sample Data: Table 1 following represents an application of the four steps required to determine DSO via the Countback Method. The variables required to complete this calculation include ending total receivables for the current month, current and prior month sales and the number of days in the 19

22 current and prior month. We should note that the equation can be adjusted for shorter terms. The formula allows for a seamless substitution of any desired time frame. For terms such as net 10 days, the 28, 30 and 31 day monthly time periods can be reduced to a 10 day period. Table 2 reflects the application of the Countback Method to determining Best Possible DSO. In this formula we follow the same steps as before, however in place of ending total receivables, we substitute ending current receivables for the current month. Table 3 shows the calculation for the Average Days Delinquent Countback Method. This is arrived at by subtracting the Countback Best Possible Days Sales Outstanding from Countback Days Sales Outstanding. Table 1 DSO - Countback Method Step 1 Ending Current Receivables (Month) - Credit Sales (Month) = Prior Period Receivables $710,000 $680,000 $30,000 Step 2 Prior Period Receivables / Prior Month Sales = % of Prior Month Sales $30,000 $560, % Step 3 % of Prior Month Sales x Days Prior Month = Days to Add 5.4% Step 4 Days to Add + Days Current Month = Countback DSO Table 2 Step 1 Best Possible DSO - Countback Method Ending Current Receivables (Month) - Current Credit Sales (Month) = Prior Period Receivables 682,000 $680,000 $2,000 Step 2 Prior Period Receivables / Prior Month Sales = % of Prior Month Sales $2,000 $560,000.36% Step 3 % of Prior Month Sales x Days Prior Month = Days to Add.36% Step 4 Days to Add + Days Current Month = Countback BPDSO Table 3 Average Days Delinquent - Countback Method Countback DSO - Countback BPDSO = ADD Countback Method Days Days = 1.5 Days 20

23 Performance Measures True DSO Definition: The accurate and actual number of days credit sales are unpaid. Formula: The calculation of this measure requires two steps. Step 1 - Number of days from invoice date to reporting date x (invoice amount/net credit sales for the month in which the sale occurred) = True DSO per invoice Step 2 - The sum of True DSO for all open invoices = True DSO per total accounts receivable Advantages 1. It gives credit and collections departments a means of reporting receivables information to management that is accurate and exact, rather than based on averages. 2. True DSO is unbiased by sales. It tracks each invoice to the month of the sale. 3. Once the information is accumulated, with some modifications, it can be used for other comparisons. 4. It can be used to evaluate individuals, subgroups and overall groups. 5. This measure provides and a way to easily calculate Days Beyond Terms of Sale to determine actual slowness of payments. 6. It is easy to understand. Disadvantages 1. For companies with many invoices the process of calculating the number of days from the invoice date on every individual invoice could be very time-consuming and expensive to complete. 2. Tying every invoice back to net sales for the month in which the invoice originated could also be very difficult, time-consuming, and expensive. 3. Maintaining the net sales by month with credit memos being issued months later could again be very difficult, time-consuming, and expensive. 4. It is relatively new and not well known. An Explanation of Sample Data and a Graphical Representation The following table shows all the necessary elements that are needed to calculate True DSO. It tracks the monthly net credit sales, invoice date, days from invoice date, invoice amount, percent of sales weighted fraction, and true DSO. It indicates that the sample customer is paying at 79 days, which is 49 days beyond 30 terms. The 79-day figure is very revealing because by looking simply at the invoice date, one could conclude that the customer is paying 35 days beyond terms, a difference of 14 days. 21

24 Open Invoices from a Sample Customer Individua l Actual % of Sales TRUE Customer Invoic Days From Invoice Weighted DSO Month Credit e Date Invoice Date Amount Fraction (Invoice) Jan. Sales 8, Oct Feb. 8, Oct 61 2, Mar. 8, Nov Apr. 9, Nov May 9, Nov 49 1, Jun. 9, Nov Jul. 9, Nov 43 2, Aug. 9, Nov 42 2, Sep. 9, Nov 38 2, Oct. 9, Nov 38-2, Nov. 9, Nov 35 2, Dec. 10, Nov 31 3, Sample Customer's True DSO Assume the Reporting Date (Today s Date) is 31-Dec Appropriate Uses 1. To determine the number of days sales are outstanding. 2. As an indicator of cash flow. 3. In forecasting accounts receivable balances. 4. In describing the condition of past due receivables. Inappropriate Uses 1. Being used solely to interpret individual employee performance. 22

25 Performance Measures Days Average Collection Rate Definition: This figure expresses, in days, the average time from the invoice date to the date paid. Formula: Total Flow of Funds Total Funds Applied Advantages 1. This type of analysis is more accurate than DSO and Average Days Delinquent to evaluate individual and group performance if one waits until all invoices are paid to do the calculation. 2. It is unbiased by sales. 3. It can be used to evaluate individuals, subgroups and overall groups. 4. It is a quick and simple calculation. 5. It is easy to understand. Disadvantages 1. One disadvantage is that invoices are weighted by amount. When something is assessed a weight, it has the potential to introduce bias. 2. Another disadvantage relates to invoices that have not been paid. If an invoice has not been paid, it will not have "Days Outstanding" and cannot be included in the calculation. By excluding unpaid invoice from the calculation, the Days Average Collection will be artificially high. (If the current date is used for "paid date" so days outstanding can be calculated, the Days Average Collection Rate will be artificially low.) 3. This measure is not effective for evaluating recent performance. Few want to wait three or more months to find out their performance. 4. It is relatively new and not well known. 5. It is insensitive to differing terms of sale or dating. 6. This measure covers up the behavior of delinquent accounts when other accounts are discounting their bills. An Explanation of Sample Data 23

26 The following data indicates the sample invoices are paid in an average of 42 days. Invoice Date Invoice Number Days Outstanding Funds Applied Flow of Funds 27-Oct , Oct , , Nov , Nov , Nov , , Nov , Nov , , Nov , , Nov , , Nov , , Nov , , Nov , , Total $23, $999, Days Average Collection Rate Assume the reporting date (today's date) is December 31st and payment terms are Net 30 Days. Appropriate Uses 1. To compare the amount if time invoices are generally paid to the terms of the sale. Inappropriate Uses 1. Being used solely to interpret individual employee performance. 2. Evaluating collection effectiveness of credit, collection, and accounts receivable personnel and departments. 24

27 Performance Measures Payment Pattern Analysis Definition: This measure compares the patterns that a customer develops or follows when paying their invoices. Formula: THE FORMULA FOR THIS MEASURE IS SO LONG AND COMPLEX, THERE IS NOT ENOUGH ALLOCATED SPACE IN THIS BOOK TO EXPRESS IT. Advantages 1. It is unbiased by sales. 2. It can be used to evaluate individuals, subgroups and overall groups. 3. It is sensitive to differing terms of sale or dating when an individual customer is analyzed. Disadvantages 1. It is very difficult and time-consuming to calculate. 2. It is difficult to understand. 3. It is relatively new and not well known. An Explanation of Sample Data and a Graphical Representation Note: Payment pattern analysis is so complex that there is not enough allocated space in this book to provide sample data and a graphical representation. However, the basic process and eliminates of this measure are explained below. For more information on Payment Pattern Analysis, please see the articles on the subject in the October and November of 1991 issues of Business Credit Magazine. In order to perform a payment pattern analysis you need to know by month the following: 1. Total Receivables 2. Flexible Budget Receivables 3. Proportional Flexible Budget Receivables 4. Static Budget Receivables You then calculate the Collection Experience Variance from the total receivables and the flexible budget receivables. From the flexible budget receivables and proportional flexible budget receivables you calculate the Sales Pattern Variance. Then from the proportional flexible budget receivables and the static budget receivables you calculate the Sales Quality Variance. From the 25

28 flexible budget receivables and static budget receivables you get the Sales Effect Variance. Finally, from total receivables and static budget receivables you get Total Variance. Complete this process per month going back six months each month to calculate the variances for each individual customer and each month you will know the pattern for the past six months that individual customer paid in. Complete this process for all your customers each month for several months and then you can determine if your customer s payment patterns are changing. You will also be able to determine how well you did in the past. Appropriate Uses 1. To determine individual customer payment patterns. 2. Identifying accounts that need focus and work to receive payment closer to terms. Inappropriate Uses 1. Being used solely to interpret individual employee performance. 2. Describing the condition of past due receivables. 26

29 Performance Measures Prior Month's Past Due Collected Definition: This percentage expresses the amount that has been collected in the current month of the prior month's past due amount. Formula: Advantages Current Months Past Due Age Categories Beginning Receivables of Prior Month 1. It can be used to evaluate individuals, subgroups and overall groups. 2. It is a quick and simple calculation. 3. It is easy to understand. 4. It is sensitive to differing terms of sale or dating. (If you include all invoices that are not yet due in the current age category regardless of days outstanding.) Disadvantages 1-1. Because the formula uses Beginning Receivables, which includes Credit Sales in the current age category for the prior month, the percentage is not a completely accurate measurement. 2. It measures only a single element of receivables prior months past due invoices. An Explanation of Sample Data and a Graphical Representation The following data and graph demonstrate a fluctuating percent of prior month's past due collected. It also demonstrates the overall average is fairly flat, indicating this organization is not really improving in the collection of past due amounts. 27

30 Month Current Receivables Day Receivables Day Receivables 90+ Day Receivables Beginning Receivables Past Due Collected Dec. 3,628,310 2,382, ,387 1,307,263 8,033,628 Jan. 5,001,949 1,793, ,505 1,299,317 9,092,723 49% Feb. 4,924,392 2,370, ,918 1,377,022 9,312,807 52% Mar 4,957,243 2,358, ,262 1,414,142 9,670,760 49% Apr. 4,410,228 1,736, ,082 1,204,725 7,890,660 64% May 4,637,478 1,749, ,721 1,236,106 8,167,672 55% Jun 4,513,924 1,847, ,239 1,242,971 8,161,502 55% Jul. 4,791,621 2,101, ,229 1,258,666 8,602,225 53% Aug. 4,968,789 1,824, ,756 1,214,940 8,849,332 55% Sep. 5,200,684 3,294,401 1,268,324 1,216,039 10,979,448 35% Oct. 5,221,589 2,406, , ,588 9,052,797 65% Nov. 7,672,356 3,024, , ,525 12,327,157 49% Dec. 7,846,547 3,819, ,076 1,161,612 13,663,598 53% Prior Month's Past Due Collected Jul. Nov. Appropriate Uses 1. In describing the condition of past due receivables. 2. Evaluating the effectiveness of collecting accounts over 60 days past due. Inappropriate Uses 1. Being used solely to interpret individual employee performance. 28

31 Performance Measures Percent Over 60 Days or Percent of Any Age Category Definition: This figure expresses the percentage of Total Receivables that is 60 Days or more past due. Formula: Total Amount in the Over 60-Days Age Category and all Age Categories beyond 60-Days Total Receivables Advantages 1. It is an indicator of delinquency levels. 2. It provides focus on and alerts management to unusual increases in receivables requiring timely action. 3. Over time it measures the relative health of receivables. 4. It can be used to evaluate individuals, subgroups and overall groups. 5. It is a quick and simple calculation. 6. It is easy to understand. Disadvantages 1. The impact of Credit Sales from the prior month that are in the current Age category distorts this measure. As Credit Sales fluctuate up and down so does Percent Over 60 Days (or the Percent of any Age category or Combination of Age-categories). An Explanation of Sample Data and a Graphical Representation The data and graph on the facing page demonstrate a general downward trend in the percentage of accounts over 60 days past due. This trend indicates the organization is improving in the collection of accounts over 60 days past due. This trend by itself looks good. However, by itself it can be misleading. If this organization is focusing on collecting older accounts and sales are increasing, the amount in the current age-category will increase and over empathize the decrease in the percent of account over 60 days. 29

32 Month Current Receivables Day Receivables Day Receivables 90+ Day Receivables Total Receivables Jan. 5,001,949 1,793, ,505 1,299,317 9,092,723 25% Feb. 4,924,392 2,370, ,918 1,377,022 9,312,807 22% Mar 4,957,243 2,358, ,262 1,414,142 9,670,760 24% Apr. 4,410,228 1,736, ,082 1,204,725 7,890,660 22% May 4,637,478 1,749, ,721 1,236,106 8,167,672 22% Jun 4,513,924 1,847, ,239 1,242,971 8,161,502 22% Jul. 4,791,621 2,101, ,229 1,258,666 8,602,225 20% Aug. 4,968,789 1,824, ,756 1,214,940 8,849,332 23% Sep. 5,200,684 3,294,401 1,268,324 1,216,039 10,979,448 23% Oct. 5,221,589 2,406, , ,588 9,052,797 16% Nov. 7,672,356 3,024, , ,525 12,327,157 13% Dec. 7,846,547 3,819, ,076 1,161,612 13,663,598 15% Percent Over 60 Days Percent Over 60 Days Past Due Jul. Nov. Appropriate Uses 1. Compare with previous periods and averages to determine significant change. Inappropriate Uses 1. Evaluating collection effectiveness of credit, collection, and accounts receivable personnel and departments. 2. As a performance indicator at a single point in time. 3. As a pure collection indicator. 4. Being used solely to interpret individual employee performance. 30

33 Performance Measures Days Deductions Outstanding - DDO Definition: DDO looks at deductions in the same manner that DSO looks at open receivables. It quantifies deduction dollars in days and illustrates, on average, how long deductions are open. Formula: Advantages Dollars of Total Month End Open Deductions x Number of Days in the period Dollars of Deductions created for the period 1. DDO gives the aggregate average days that invoices are outstanding. 2. At a specific point-in-time, this measure indicates how long it takes to resolve open deduction issues 3. It is a quick and simple calculation. 4. DDO is easy to understand. 5. It can be used to evaluate individuals, subgroups and overall groups. 6. It is easy to understand. Disadvantages 1. None identified at this time! An Explanation of Sample Data: This example shows by quarter deductions outstanding at the end of the quarter and deductions created during the corresponding period. With this information in hand it is possible to determine DDO. This data can be calculated on a weekly, monthly, or quarterly basis and formatted to establish a trend analysis of performance in the management of deduction resolution. The following chart and corresponding graph reflects a trend analysis 31

34 Time Period Total Quarter End Deductions in Dollars Dollars of Deductions Created for the Period Days Deductions Outstanding First Quarter 2007 $2,553,425 $9,275, Days Second Quarter 2007 $3,185,575 $7,989, Days Third Quarter 2007 $2,105,125 $7,345, Days Fourth Quarter 2007 $1,768,985 $6,876, Days Days Deductions Outstanding First Second Third Fourth Quarter Quarter Quarter Quarter

35 Performance Measures Bad Debt to Sales Definition: This percentage expresses the percentage of credit sales that were written off to bad debt. A lower percentage signifies that effective credit policies and procedures are employed. Formula: Advantages Bad Debt Net of Recoveries Credit Sales 1. It measures overall accounts receivable performance. In some ways this measure is the ultimate measure. If Bad Debt to Credit Sales is consistently below or at the organizations planned level and within the industry's range, the accounts receivable policies and procedures are effective. 2. It can be used to evaluate individuals, subgroups and overall groups. 3. It is a quick and simple calculation. 4. It is easy to understand. Disadvantages 1. None identified at this time! An Explanation of Sample Data and a Graphical Representation The following data and graph indicate this company had four months with no write-offs to bad debt. It also shows that in three months January, May and December the company had relatively heavy losses to bad debt. This demonstrates the necessity to use this measure in longterm analysis. The short-term can provide extreme bias, such as in the months of February, April, July and November, where the company collected more from prior bad debts than it wrote off to current bad debts. 33

36 Month Credit Sales Bad Debt Bad Debt to Sales Jan. 1,882,607 2, % Feb. 1,524, % Mar. 1,486, % Apr. 1,762, % May 1,426,762 2, % Jun. 1,624, % Jul. 1,421, % Aug. 1,752, % Sep. 1,585, % Oct. 1,657, % Nov. 1,465, % Dec. 1,488,106 1, % Totals 19,078,382 5, % Bad Debt to Sales 0.15% 0.10% 0.05% 0.00% -0.05% Jan. Mar. May Jul. Sep. Nov. Appropriate Uses 1. In comparing the amount of credit sales actually lost to bad debt as compared to the annual plan and reserve for bad debts. 2. Benchmarking your organization with the Best in Class to identify areas and methods for improvement Inappropriate Uses 1. Evaluating current months bad debts relative to current month's credit sales. This is a long-term measure and can be misleading in short-term analysis. 2. Being used solely to interpret individual employee performance. 3. In describing the condition of past due receivables not written off to bad debt. 4. Holding the credit or accounts receivables department accountable for bad debt losses on sales that were approved by a sales employee and not by the credit department. 34

37 Performance Measures Bad Debt Recoveries as a Percent of Bad Debt Loss Definition: This measure looks at the percent of monies collected after they were written off to bad debt. These monies could be dollars collected by recovery teams within your organization, third party collection agencies, or the distribution of proceeds from bankruptcy settlements. Formula: Bad Debt Recovery Write-offs to Bad Debt Advantages: 1. This measure can reflect the effectiveness of your internal collection effort or that of your collection agency. 2. It can serve as a gauge reflecting whether your write-off policy may be too strict or liberal. 3. It can be a contributing factor in ascertaining your organizations reserves for bad debt. 4. The measure is easy to calculate. 5. The measure is easy to understand. Disadvantages: 1. None identified at this time. An Explanation of Sample Data: The following table reflects a month to month summary of write-offs and recoveries. It calculates on a monthly basis the percent of recovery to that of loss. More importantly it is set up to calculate year to date losses and recoveries and reflect that percentage on a continuing basis. 35

38 Bad Debt Recovery as a Percent of Bad Debt Loss Month January February March April May June July August September October November December Total Annual Write-off to Bad Debt Bad Debt Recoveries Recoveries to Bad Debt $ 1,250,315 $ 43,565 3% $ 676,545 $ 187,657 28% $ 51,300 $ 3,675 7% $ 989,750 $ 13,415 1% $ 871,476 $ 137,545 16% $ 1,678,565 $ 211,678 13% $ 44,755 $ 76, % $ 523,775 $ 58,745 11% $ 1,387,455 $ 357,895 26% $ 98,365 $ 121, % $ 812,569 $ 77,569 10% $ 1,125,750 $ 98,235 9% $ 9,510,620 $ 1,387,758 15% 36

39 Performance Measures Actual Loss to Budgeted Loss Definition: Compares an actual loss over a specified period of time to that which was budgeted for that specific time period. Losses can be subdivided into categories such as loss from invoices (commonly referred to a Credit Loss), loss from bankruptcy, loss related to fraud, loss resulting from customer deductions and loss from customer skips. Losses may also be measured as gross or net of recoveries. One can further drill down to root causes by calculating these categories by portfolio type. Budgeted loss should be determined based on historical trends and/or industry averages. Formula: Advantages: Actual Loss for the Period Budgeted Loss 1. Reflects efficiencies related to risk assessment, account management and collections. 2. When measured against deductions it can quickly identify deficiencies within processes. The same is true when measured against other categories such as the initial risk assessment in application decisioning as well as ongoing account management. 3. If budgeted loss is based on industry standards the measure can identify how competitive you are in relation to others within your industry. If actual loss is below 100% it could indicate that you are too restrictive in credit granting thus inhibiting your ability to make sales. If actual loss exceeds 100% it could indicate that you are too liberal in assuming risk and you are needlessly costing the business profitability. 4. It is a quick and simple calculation. 5. It is easy to understand. Disadvantages: 1. None identified at this time. An Explanation of Sample Data The tables on the following page provide a snapshot of actual loses to those that were budgeted. Overall actual losses exceed budget by nine percent. When subdivided by category, in this case it becomes obvious that a problem exists in the deduction management area. Bankruptcy losses are actually below budget, however losses in the deduction area exceeds budget. This is a signal to management that there is a deficiency within those areas that lend to the creation of deductions or in the area of deduction resolution. Further investigation should take place to identify remedy the root cause of the problem. 37

40 Actual Loss to Budgeted Loss Unpaid Invoices Actual Loss for Quarter Budgeted Loss for Quarter % of Actual to Budgeted First Quarter $ 1,125,480 $ 1,000, % Second Quarter $ 755,951 $ 1,000,000 76% Third Quarter $ 621,551 $ 1,000,000 62% Fourth Quarter $ 1,871,455 $ 1,000, % Annual $ 4,374,437 $ 4,000, % Actual Loss to Budgeted Loss Deductions Actual Loss for Quarter Budgeted Loss for Quarter % of Actual to Budgeted First Quarter $ 621,455 $ 450, % Second Quarter $ 313,545 $ 450,000 70% Third Quarter $ 476,515 $ 450, % Fourth Quarter $ 648,555 $ 450, % Annual $ 2,060,070 $ 1,800, % Actual Loss to Budgeted Loss Bankruptcy Actual Loss for Quarter Budgeted Loss for Quarter % of Actual to Budgeted First Quarter $ 76,561 $ 300,000 26% Second Quarter $ 323,508 $ 300, % Third Quarter $ 81,425 $ 300,000 27% Fourth Quarter $ 215,431 $ 300,000 72% Annual $ 696,925 $ 1,200,000 58% 38

41 Performance Measures New Account Decisioning Definition: Examines proficiency in decisioning new account applications. Areas to examine in measuring performance include average cycle time and percent of approvals and declines to total applications decisioned. An inordinately high level of approvals or declines may indicate that risk assessment might be too liberal or restrictive and you may be inhibiting sales or inversely negatively impacting profitability or cash flows. Note: Only properly completed credit applications should be included. Formulas: Average Cycle Time: Sum of the Days to Decision Individual Applications Total Applications Decisioned Percent of Applications Approved: Total Applications Approved Total Applications Decisioned Advantages: Percent of Applications Declined: Total Applications Declined Total Applications Decisioned 1. Examines efficiencies in the decisioning of new account applications lending to improvement in cycle time. 2. Provides an insight into the percent of new account applications approved versus the number declined pointing to a need for a potential adjustment in risk assessment policy. 3. Focusing on cycle time increases customer and sales associate satisfaction as well as increasing credit sales. Disadvantages: 1. An emphasis on cycle time could impact the quality of decision making. Prudent decision making procedures may be abandoned in the interest of time. Strong process controls will minimize this risk. 2. Establishing goals related to percentage of approval or decline rates could have an adverse effect on revenues or profitability. 39

42 An Explanation of Sample Data The following tables look at cycle time for new account applications as well as approval and decline rates for new account applications. In the first example cycle time is being monitored on an ongoing basis. This can be done ongoing as reflected or can be set up monthly, quarterly or annually. The second table reflects approval and decline rates by month. It too can be set up to track quarterly or on an ongoing basis. This information can be compared to predetermined goals in an effort to promote efficiencies and productivity in the new account application cycle time. Application Decisioning Cycle Time Applications Decisioned Days to Decision ABC Supply 3 Bill's Plumbing 2.5 Ajax Electrical 1.25 Acme Supply 4 EZ Builders Mart 2 Ron's Masonry Supply 3.5 Average Days to Decision 2.71 New Account Application Approval and Decline Rates Received Approved Declined Approval Rate Declined Rate January % 17% February % 15% March % 10% April % 9% May % 4% June % 21% July % 12% August % 8% September % 9% October % 17% November % 16% December % 14% Total Year % 12% 40

43 Performance Measures Collection Productivity Definition: Collection Productivity is a measure of the efficiency with which a company's sales are collected, given the resources, human and technological, to perform the task. Formula: You will need two years of data to complete. This is a multi-step calculation and while the steps are outlined below, it would be more convenient to utilize a spreadsheet as designed on the next page. Step 1 - Divide your total sales by number of collection employee for year one and year two = Sales per collection employee Step 2 - Sales per collection employee (year one) / Sales per collection employee (year two) = % change in sales per collection employee Step 3 - Average capital investment in technology for collections / total cost of labor = % of investment in technology to labor cost Step 4 - Divide your ending receivable balance by number of collection employee for year one and year two = A/R balance per collection employee Step 5 - A/R balance per collection employee (year one) / A/R balance per collection employee (year two) = % change in A/R balance per collection employee Step 6 - % change in sales per collection employee - % of investment in technology to labor cost x % of investment in technology to total labor cost Advantages: 1. Collection productivity is the first measure to gauge how productive the effort is, given the resources available to perform the collection function. 2. A simple measure that can be applied to evaluate the relationship between the work inputs and the results output of the collection process. 3. Can be applied consistently across all industries and organizations. Disadvantages: 1. Developed in 2002, it is relatively new and not well known. An Explanation of Sample Data: Examining the factors of the formula in a table, more clearly demonstrates how to the calculation works. Illustration 1 represents the tabled calculations that you can apply to develop your own collection productivity worksheet. Simply adjusting years and changing the data in cells B2, B3, B4, D2, D3 & D4 will produce your results. 41

44 In Example 1, we have expressed an illustration of productivity growth comparing the change in collection productivity for 2007 from 2006 of 9.86%. The increase is due to two of the three input and output factors changing favorably: an increase in sales and a decrease in the number of people collecting the sales. Although the ending A/R increased, its influence was not enough to produce a decline (negative result) in the growth of collection productivity. If, however, the number of collectors would have remained the same in year two, (5 collectors) and everything else remained constant, this example would have produced a negative result or a decline in productivity for 2002 of -7.11%. Illustration 1 A B D 1 Collection Productivity Worksheet Year End 2006 Year End Sales $ 798,555,123 $ 698,555,123 3 Average # of Collection Employees in year Year End A/R $ 125,000,000 $ 125,000,000 5 Sales per employee =B2 / B3 =D2 / D3 6 A/R per employee =B4 / B3 =D4 / D3 7 % Change in sales per employee - =(D5 - B5) / B5 8 % Change in A/R per employee - =(D6 - B6) / B6 9 Average capital investment in technology for the collection function as a % of labor Growth or Decline in Collection Productivity - =D7- (D9*D8) Example 1 Collection Productivity Worksheet Year End 2006 Year End 2007 Sales $ 798,555,123 $ 802,456,134 Average # of Collection Employees in year 5 4 Year End A/R $ 125,000,000 $ 163,000,000 Sales per employee $ 159,711,025 $ 200,614,034 A/R per employee $ 25,000,000 $ 40,750,000 % Change in sales per employee 25.6% % Change in A/R per employee 63% Average capital investment in technology for the collection function as a % of labor Growth or Decline in Collection Productivity 9.86% Appropriate Uses: 1. Allows management to determine the productivity of the collection function. If more or less sales are generated from one year to the next, this formula will assist in staffing needs 2. The result is the expression of growth or decline in productivity of the collection function. 25% 42

45 Operational Measures Active Customer Accounts per Credit and Collection Employee Definition: This figure represents the total number of active accounts per department employee. Generally, the higher the number of accounts per employee, the more efficient the use of technology and people. (This is a departmental measure.) Formula: Advantages Number of Active Customer Accounts Number of Total Department Employees 1. Informs management of the number of customer accounts that are supported by the total department staff. 2. When benchmarked with similar companies that have similar customer types, this indicates to management the number of accounts that could or should be supported by the total department staff. 3. It is a quick and simple calculation. 4. It is easy to understand. Disadvantages 1. None identified at this time! An Explanation of Sample Data and a Graphical Representation The data on the following page indicates this organization feels it can maintain between 2,000 and 2,500 customers per employee. A new employee was added to the staff in September that reduced the average number of accounts per employee. Another employee was added in December with the same effect. Because a higher number of accounts per employee implies the more efficient use of technology and people, an alternative to increased staffing would be to purchase more productive technology. This approach would raise the number of accounts that could be supported by each employee. 43

46 Month Active Accounts Department Employees Jan. 20, ,038 Feb. 19, ,913 Mar. 20, ,027 Apr. 20, ,088 May 20, ,011 Jun. 21, ,184 Jul. 22, ,255 Aug. 22, ,284 Sep. 25, ,337 Oct. 26, ,443 Nov. 27, ,466 Dec. 29, ,422 Accounts Per Employee Active Customer Accounts per Employee 2,500 2,000 1,500 1, Mar. May Nov. Appropriate Uses 1. Determining the appropriate time to hire new employees to support the customer base. 2. Benchmarking your organization with the Best in Class to identify areas and methods for improvement. Inappropriate Uses 1. Comparing your company's staffing level and receivable portfolios with companies that have different classes of customers than your company. 2. Being used solely to interpret individual employee performance. 44

47 Operational Measures Active Customer Accounts per Credit Representative or Collector Definition: This figure represents the total number of active accounts for an individual credit representative or collector. Generally the higher the number of accounts per employee, the more efficient the use of technology and people. (This is an individual measure.) Formula: Advantages Number of Active Customer Accounts Number of Total Credit Representatives or Collectors 1. Provides a way to equitably distribute the same class of customer accounts among employees. 2. Informs management of the number of customer accounts that are supported by the average credit representative or collector. 3. When benchmarked with similar companies that have similar customer types, this indicates to management the number of accounts that could or should be supported by an individual credit representative or collector. 4. It is a quick and simple calculation. 5. It is easy to understand. Disadvantages 1. It ignores different classes of customers. Large customers with complex paper processing procedures may take much more time to collect from than less complex organizations. Workload should be distributed accordingly. An Explanation of Sample Data and a Graphical Representation The data on the following page indicates this organization feels each credit representative or collector can maintain approximately 4,500 customers. A new employee was added to the staff in September, which reduced the average number of accounts per credit representative or collector. Another employee was added in December with the same effect. Because a higher number of accounts per employee implies the more efficient use of technology and people, an alternative to increased staffing would be to purchase more productive technology. This approach would raise the number of accounts that could be supported per credit representative or collector. 45

48 Month Active Accounts Credit Reps. or Collectors Jan. 20, ,076 Feb. 19, ,826 Mar. 20, ,055 Apr. 20, ,176 May 20, ,021 Jun. 21, ,368 Jul. 22, ,510 Aug. 22, ,569 Sep. 25, ,285 Oct. 26, ,479 Nov. 27, ,522 Dec. 29, ,153 Accounts Per Rep. or Collector Active Accounts per Credit Rep. or Collector 4,600 4,400 4,200 4,000 3,800 3,600 3,400 Jan. Mar. May Jul. Sep. Nov. Appropriate Uses 1. Internal workload distribution when viewed in class of trade context. 2. Benchmarking your organization with the Best in Class to identify areas and methods for improvement. Inappropriate Uses 1. Comparing individual receivable portfolios with different classes of customers. 2. Being used solely to interpret individual employee performance. 46

49 Operational Measures Operating Cost per Employee Definition: This figure represents the total dollars spent per employee. The lower the cost, the more effective use of technology and people. Note: Operating Cost per Employee is listed here in the Credit and Collections section, but is just as valuable and applicable under Accounts Receivable. The formula is the same for each department. Formula: Advantages Departmental Operating Costs Number of Department Employees 1. Informs management of the average cost per employee to maintain the department. Knowing the cost per employee to maintain the department is critical. All credit and accounts receivable organizations could reach every goal of their company, division and department if their staffs were large enough. The challenge for management is to not just be effective but also to be efficient. 2. It is easy to understand. Disadvantages 1. This measure does not take into consideration the difference in the cost of technology and the cost of people. Technology can be expensive, yet at the same time it can significantly raise the productivity of employees. At times it is difficult to decide whether to invest in people or technology. 2. Determining departmental operating costs may be difficult. An Explanation of Sample Data and a Graphical Representation The following data indicates it cost $394,718 for an average of 10 employees over the year reported. Monthly costs per employee were as low as $2, and as high as $3, with an overall cost per employee of $3, per month. Is this good? This question is relative. It is very good if the department worked a credit sales portfolio of $3 billion for the year. However, if their portfolio was only $3 million, their cost per employee was extremely high. 47

50 Month Department Expenses Department Employees Cost Per Employee Jan. 30, $3, Feb. 29, $2, Mar. 30, $3, Apr. 30, $3, May 30, $3, Jun. 31, $3, Jul. 31, $3, Aug. 32, $3, Sep. 34, $3, Oct. 36, $3, Nov. 37, $3, Dec. 39, $3, Average $32, $3, Operating Cost per Employee $3, $3, $3, $2, $2, Jan. Mar. May Jul. Sep. Nov. Appropriate Uses 1. Determining the most cost-efficient level to maintain a department. 2. Benchmarking your organization with the Best in Class to identify areas and methods for improvement. Inappropriate Uses 1. Comparing your company's department with companies that have different departmental functions than your company. 2. Being used solely to interpret individual employee performance. 48

51 Operational Measures Cost per Sales Dollar Definition: This calculation relates dollars spent in the credit and collection effort to credit sales generated, or how much it cost the company to process each dollar in credit sales. A higher percentage signifies that a more effective operation is employed. Formula: Advantages Departmental Operating Costs Credit Sales 1. Informs management of the average cost per credit sales dollar. This is another of the few ultimate measures of performance. It is very revealing because it puts the true cost of credit, collections and accounts receivable maintenance in perspective. 2. It is easy to understand. Disadvantages 1. This measure does not take into consideration the difference in the cost of technology and the cost of people. Technology can be expensive, yet at the same time it can significantly raise the productivity of employees. At times it is difficult to decide whether to invest in people or technology. 2. Determining departmental operating costs may be difficult. An Explanation of Sample Data and a Graphical Representation The following data and graphical representation indicate it cost this department a low of one and-a-half cents for every dollar in credit sales. It also indicates the department had a high cost per credit sales dollar of a little over two and-a-half cents. Another thing the data indicates is an upward trend in the cost. This trend is something management should investigate, understand and monitor for corrective action if necessary. Is this cost per credit sales dollar good? This question is relative. It could be answered by benchmarking with other organizations or measuring itself against its own past performance. 49

52 Month Department Expenses Credit Sales Cost Per Sales Dollar Jan. 30,380 1,882,607 $0.016 Feb. 29,128 1,524,673 $0.019 Mar. 30,274 1,486,579 $0.020 Apr. 30,882 1,762,842 $0.018 May 30,106 1,426,762 $0.021 Jun. 31,840 1,624,347 $0.020 Jul. 31,524 1,421,713 $0.022 Aug. 32,872 1,752,938 $0.019 Sep. 34,587 1,585,221 $0.022 Oct. 36,927 1,657,474 $0.022 Nov. 37,130 1,465,120 $0.025 Dec. 39,068 1,488,106 $0.026 Average $32,893 $1,589,865 $0.021 Cost per Sales Dollar $0.030 $0.025 $0.020 $0.015 $0.010 $0.005 $0.000 Jan. Mar. May Jul. Sep. Nov. Appropriate Uses 1. To determine the most cost-efficient level to maintain a department. 2. Benchmarking your organization with the Best in Class to identify areas and methods for improvement. Inappropriate Uses 1. Comparing your companies department with companies that have different departmental functions than your company. 2. Being used solely to interpret individual employee performance. 50

53 Operational Measures Cost of Collections Definition: This percentage represents the cost of collecting the collectable amount of Bad Debt. The lower the percentage, the more effective the attorney(s) or agency(s) employed. Formula: Advantages Amount Paid to Attorney's and Agencies Collected Amount 1. It provides a way to compare the results of various collection companies and techniques. 2. It is a quick and simple calculation. 3. It is easy to understand. Disadvantages 1. The comparison or percentage is skewed by the placement or collection of large accounts. 2. Does not consider accounts that were written off to bad debt where no collection effort was made. 3. Agencies who "cream" large accounts and make no effort on small balances could receive a higher efficiency indicator during short time periods. 4. It is relatively new and not well known. An Explanation of Sample Data and a Graphical Representation The data and graph on the following page indicate it cost this company an average of 18% to collect $321,718. The cost of 18% is excellent by most standards. As in most collection situations, there were some high costs and low ones. The high was 80% and the low 10%. Had this company known how much it would cost to collect the October bad debt, it might not have pursued the debt. However, a 20% return is better than nothing. Accounts receivable organizations should always be looking for the most cost-effective way to collect bad debts. 51

54 Month Amount Paid to Attorneys & Agencies Collected Amount Jan. 4,557 30,380 15% Feb. 4,369 9,128 48% Mar. 4,541 32,274 14% Apr. 4,632 40,882 11% May 4,516 18,106 25% Jun. 4,776 21,840 22% Jul. 4,729 17,524 27% Aug. 4,931 42,872 12% Sep. 5,188 14,587 36% Oct. 5,539 6,927 80% Nov. 5,570 27,130 21% Dec. 5,860 60,068 10% Average 59, ,718 18% Cost of Collections Cost of Collections 80% 70% 60% 50% 40% 30% 20% 10% 0% Jan. Mar. May Jul. Sep. Nov. Appropriate Uses 1. Evaluating and selecting the best long-term technique or company to collect bad debts. 2. Determining the department's long-term success in effectively selecting collection companies or technique. (This determination should evaluate both the current year and several past years.) Inappropriate Uses 1. Determining short-term collection efficiency, i.e. monthly, quarterly and possibly annually. 52

55 Operational Measures High-Funds Accounts Definition: This measure identifies accounts where significant funds could be collected in a relative short time. By identifying accounts that have at least $2,000 over 60 Days and a total due of $5,000 (or whatever amounts are relative to your business) or more that are not paying according to terms because of improper billing or processing problems. The closer to zero the more effective the collection effort, the better the working relationship with the customer and the more credit, collections, and accounts receivable policies and procedures are being followed. Formula: Advantages Number of High-Funds Generating Accounts 1. Identifies accounts where a little effort could be converted into large cash receipts. 2. Prioritizes employee workload. 3. It is unbiased by sales. 4. It is a quick and simple calculation. 5. It is easy to understand. Disadvantages 1. Can take the focus off of smaller accounts that may, without proper attention, develop into large collection problems. 2. It is relatively new and not well known. An Explanation of Sample Data and a Graphical Representation The following data indicates high-funds accounts were at 25 in January, and climbed to a high of 31 in April. However, in May, there was the beginning of a downward trend that took the highfunds accounts to the annual low of 11 accounts. As a result of the effort to reduce the highfunds accounts, the company generated a large amount of cash flow. 53

56 High Funds Month Accounts Jan. 25 Feb. 27 Mar. 34 Apr. 42 May 39 Jun. 32 Jul. 28 Aug. 31 Sep. 24 Oct. 19 Nov. 15 Dec. 11 High Funds Accounts 0 Nov. Appropriate Uses 1. Prioritizing monthly workload. 2. Forecasting potential cash flows. Inappropriate Uses 1. Being used solely to interpret individual employee performance. 54

57 Operational Measures High-Risk Accounts Definition: This measure identifies significant potential bad debt accounts so they can be collected, thereby maximizing profits by minimizing losses. These accounts have at least $2,000 over 60 Days and a total due of $5,000 (or whatever amounts are relative to your business) where the customer is not paying because of its lack of ability to pay or some unknown reason for not paying according to terms. The closer to zero the more effective the collection effort, the better the working relationship with the customer and the more credit, collections, and accounts receivable policies and procedures are being followed. Formula: Advantages Number of High-Risk Accounts 1. Identifies potentially significant bad debt losses so they may be resolved and collected thereby reducing bad debt losses. 2. It is unbiased by sales. 3. It is a quick and simple calculation. 4. It is easy to understand. Disadvantages 1. It is relatively new and not well known. An Explanation of Sample Data and a Graphical Representation The data on the facing page indicates high-risk accounts were at two in January, and climbed to a high of four in April. However, by December they were at only one high-risk account. As a result of the effort to reduce the high-risk accounts, the company with a large amount of potential bad debt loses. 55

58 High Risk Month Accounts Jan. 2 Feb. 2 Mar. 3 Apr. 4 May 3 Jun. 3 Jul. 2 Aug. 3 Sep. 2 Oct. 1 Nov. 1 Dec. 1 High Risk Accounts Nov. Appropriate Uses 1. Prioritizing monthly workload. 2. Forecasting potential bad debt losses. Inappropriate Uses 1. Being used solely to interpret individual employee performance. 56

59 Operational Measures Check Turnover per Cash Applicator Definition: This figure indicates the number of checks processed per person responsible for actually applying checks. A higher turnover rate implies that an efficient system is employed. Note: This measure could include automated remittance processing. (Whether automated processing is included or not is a matter of choice, or in benchmarking comparability, sense consistency is the key.) Once the parameters are set, they should not change in like comparisons. Formula: Advantages Number of Checks Processed Number of Cash Applicators 1. The average number of checks processed per cash applicator can be derived. 2. It is easy to understand. Disadvantages 1. Some checks pay for one invoice and some pay for hundreds or thousands. The number of checks processed is not as good a measure as the number of transactions processed. An Explanation of Sample Data and a Graphical Representation The following data indicates the average cash applicator processed approximately 2,500 to 4,000 checks between January and September. It also indicates the number of checks processed went up in October through December. It is interesting to note that the number of cash applicators went down at the same time, resulting in a significant increase in check turnover per applicator. How could this be accomplished? Perhaps an autocash system was implemented that replaced one of the applicators. 57

60 Month Checks Processed Cash Applicators Jan. 12, ,269 Feb. 10, ,427 Mar. 9, ,247 Apr. 9, ,275 May 8, ,689 Jun. 9, ,134 Jul. 8, ,750 Aug. 9, ,243 Sep. 9, ,292 Oct. 10, ,139 Nov. 11, ,515 Dec. 12, ,034 Average 10, ,834 Check Turnover Per Applicator Check Turnover per Cash Applicator Nov. Appropriate Uses 1. To evaluate the efficiency of the department's cash posting system and personnel. 2. Benchmarking your organization with the Best in Class to identify areas and methods for improvement. Inappropriate Uses 1. Evaluating the performance of an individual cash applicator or automated system. 2. Being used solely to interpret individual employee performance. 58

61 Operational Measures Transaction Turnover per Cash Applicator Definition: This figure indicates the number of transactions processed per cash applicator. A transaction includes all invoices, credits, deductions and payments. A higher turnover rate implies that a more efficient system is employed. Note: This measure could include automated remittance processing. Whether automated processing is included or not is a matter of choice. When benchmarking, comparability and consistency are key. Once the parameters are set, they should not change in like comparisons. Formula: Advantages Number of Transactions Processed Number of Cash Applicators 1. By knowing the number of transactions a cash applicator can process, management can evaluate and forecast staffing levels, compare cash applicators with each other, and determine the efficiency of automated remittance processing. 2. Cash applicators can identify the type of transactions that are difficult and timeconsuming to process. Management can evaluate the difficult and time-consuming processes and develop, test, educate, and implement more productive methods. 3. It is easy to understand. Disadvantages 1. None identified at this time! An Explanation of Sample Data and a Graphical Representation The following data indicates the average cash applicator processed approximately 29,000 to 34,500 transactions between January and September. It also indicates the number of transactions processed went up in October through December. It is interesting to note the number of cash applicators went down at the same time, resulting in a significant increase in transaction turnover per applicator. How could this be accomplished? Perhaps an autocash system was implemented that replaced one of the applicators. 59

62 Month Transactions Processed Cash Applicators Jan. 30, ,127 Feb. 29, ,709 Mar. 30, ,091 Apr. 30, ,294 May 30, ,035 Jun. 31, ,613 Jul. 31, ,508 Aug. 32, ,957 Sep. 34, ,529 Oct. 36, ,464 Nov. 37, ,565 Dec. 39, ,534 Average 32, ,536 Transaction Turnover Per Cash Applicator Transaction Turnover per Cash Applicator Nov. Appropriate Uses 1. Evaluating the performance of an individual cash applicator or automated system. 2. Comparing productivity levels of cash applicators or automated remittance processing. 3. Benchmarking your organization with the Best in Class to identify areas and methods for improvement. Inappropriate Uses 1. Being used solely to interpret individual employee performance. 60

63 Operational Measures Transaction Turnover per Accounts Receivable Employee Definition: This figure indicates the number of transactions processed per individual employee. All employees involved in accounts receivable are included because their combined duties are directed in some fashion to processing transactions of all types. This includes secretaries, administrators, supervisors and managers. A transaction includes all invoices, credits, deductions and payments. A higher turnover rate implies that a more efficient system is employed. Note: This measure could include automated remittance processing. Whether automated processing is included or not is a matter of choice, or in benchmarking comparability, consistency is the key. Once the parameters are set, they should not change in like comparisons. Formula: Advantages Number of Transactions Processed Number of Accounts Receivable Employees 1. It informs management of the average number of transactions per employee. This can help management to evaluate and forecast staffing levels. 2. This measure also assists management in evaluating systems that assist in processing transactions. 3. It is easy to understand. Disadvantages 1. None identified at this time! An Explanation of Sample Data and a Graphical Representation The following data indicates that for every accounts receivable employee the department processes approximately 2,900 to 3,400 transactions between January and September. It also indicates an upward trend in employee efficiency. This upward trend may or may not reflect well on the department because the number of employees went up at the same time as the transactions processed. It is not clear if the efficiencies in transaction turnover per accounts receivable employee are a result of gained efficiencies or an increase of staffing. 61

64 Month Transactions Processed Department Employees Jan. 30, ,038 Feb. 29, ,913 Mar. 30, ,027 Apr. 30, ,088 May 30, ,011 Jun. 31, ,184 Jul. 31, ,152 Aug. 32, ,287 Sep. 34, ,144 Oct. 36, ,357 Nov. 37, ,375 Dec. 39, ,256 Average 32, ,153 Transaction Turnover Acct. Rec. Employee Transaction Turnover per Accounts Receivable Employee 3,400 3,300 3,200 3,100 3,000 2,900 2,800 2,700 2,600 Nov. Appropriate Uses 1. Benchmarking your organization with the Best in Class to identify areas and methods for improvement. Inappropriate Uses 1. Being used solely to interpret individual employee performance. 62

65 Operational Measures Deduction Turnover per Cash Applicator and A/R Deduction Specialist Definition: This figure indicates the total number of deductions processed by cash application and deduction specialists. The higher the turnover, the greater the efficiency per employee. (However, the lower the number of deductions, the more efficient the organization's billing process.) Formula: Advantages Deductions Processed Cash Applicators & Deductions Specialist 1. By knowing the average number of deductions a cash applicator or accounts receivable deduction specialist can process, management can evaluate and forecast staffing levels and determine the efficiency of automated deduction processing. 2. Cash applicators and accounts receivable deduction specialists can identify the type of transactions that are difficult and time-consuming to process. Management can evaluate the difficult and time consuming processes and develop, test, educate, and implement more productive methods. 3. It is easy to understand. Disadvantages 1. None identified at this time! An Explanation of Sample Data and a Graphical Representation The data on the following page demonstrates that every cash applicator and accounts receivable deduction specialist averaged around 1,000 deductions per month from January through September. It also demonstrates an upward trend in employee efficiency from October through December. This upward trend reflects very well on the department because the number of employees processing deductions went down at the same time deductions processed went up. Perhaps this increase in efficiency was due to bringing an automated system on line to process the deductions. However, one must remember the lower the number of deductions, the more efficient the organization's processes. It is possible the company spent money designing and implementing a system for processing deductions when it could have spent the same amount to improve its billing process and reducing the need to process such a large number of deductions. 63

66 Month Deductions Processed Cash Applicators & Deductions Specialists Jan. 3, ,010 Feb. 2, Mar. 3, ,025 Apr. 3, ,027 May 3, ,002 Jun. 3, ,047 Jul. 3, ,041 Aug. 3, ,091 Sep. 3, ,162 Oct. 3, ,814 Nov. 3, ,855 Dec. 3, ,984 Average 3, ,253 Deduction Turnover per Cash App. & Ded. Specialist Deduction Turnover per Cash Applicator & Deduction Specialist 2,000 1,500 1, Jan. Mar. May Jul. Sep. Nov. Appropriate Uses 1. Evaluating the performance of cash applicators, accounts receivable deductions specialists and automated system. 2. Comparing productivity levels of employees or automated processing. 3. Benchmarking your organization with the Best in Class to identify areas and methods for improvement. Inappropriate Uses 1. Determining if the number of deductions received from customers is at an acceptable level. 2. Being used solely to interpret individual employee performance. 64

67 Operational Measures Operating Cost per Transaction Definition: This figure indicates the cost of an individual transaction. The lower cost per transaction implies a more efficient use of technology and people. Formula: Advantages Departmental Operating Costs Number of Transactions Processed 1. Informs management of the average cost per transaction processed by the department. Knowing the cost per transaction is very helpful. 2. Management can isolate the cost of each type of transaction and develop ways to process the transactions at lower costs. 3. It is easy to understand. Disadvantages 1. This measure does not take into consideration the difference in the cost of technology and the cost of people. Technology can be expensive, but at the same time it can significantly raise the productivity of employees. At times it is difficult to decide whether to invest in people or technology. 2. Determining departmental operating costs may be difficult. An Explanation of Sample Data and a Graphical Representation The following data indicates it cost on the average $.31 to process an average 107,738 monthly transactions. Monthly costs per transactions were as low as $.28 and as high as $.34. Is this cost per transaction good? The question is relative. One way to determine proper cost per transactions is to benchmark with companies that are good models. 65

68 Month Department Expenses Transactions Processed Jan. 30,380 95,723 $0.32 Feb. 29,128 96,429 $0.30 Mar. 30,274 98,432 $0.31 Apr. 30,882 99,867 $0.31 May 30,106 97,987 $0.31 Jun. 31, ,532 $0.30 Jul. 31, ,546 $0.29 Aug. 32, ,751 $0.28 Sep. 34, ,744 $0.28 Oct. 36, ,035 $0.30 Nov. 37, ,573 $0.34 Dec. 39, ,238 $0.34 Average $32, $0.31 Cost Per Transaction Cost per Transaction $0.35 $0.30 $0.25 $0.20 $0.15 $0.10 $0.05 $0.00 Jan. Mar. May Jul. Sep. Nov. Appropriate Uses 1. Determining the most cost-efficient method to process transactions. 2. Benchmarking your organization with the Best in Class to identify areas and methods for improvement. Inappropriate Uses 1. Being used solely to interpret individual employee performance. 66

69 Operational Measures Collections Cost per Customer Definition: This measure reflects the average cost expended to collect from your active accounts. It is an operational measure that when compared to performance metrics like DSO and CEI can give management an idea of the impact expenditures in this area might have on past due dollars. If for example increased spending on the collection effort nets profitability that exceeds the higher collection costs, as a result of a reduction in DSO, then it signals to management that the increased expenses are warranted. Formula: Collection Department Budget + Outside Third Party Collection Cost s Number of Active Customers Advantages: 1. Helps management ascertain the optimal level of collection expense per active account. 2. Can demonstrate the level of efficiency in collections when expense is benchmarked against others within your industry if your performance metrics (DSO, CEI, ADD) are at or near industry median values. 3. In an internal comparative analysis situation this metric can act as a performance metric over time. If for example DSO and CEI show a steady decline over a period of time and collection cost per customer remains stable then it is showing greater efficiency in the management of past due balances. 4. Easy to calculate. 5. Easy to understand. Disadvantages: 1. Not much value as a stand alone measure. Must be compared to other measures to be meaningful. 67

70 An Explanation of Sample Data: Despite the fact that Budgeted Collection Expense remains constant the following chart reflects variations in Outside Collection Cost and Number of Active Customers. An active customer is defined as one that has a balance open on their account at month end. Outside Collection Cost reflects monies actually expended during the respective month. The bottom line of the chart is set up to reflect changes on an ongoing basis as they occur. Departmental Budget Outside Collection Cost # Active Customers Cost Per Customer January $ 280,000 $ 7, $ February $ 280,000 $ 11, $ March $ 280,000 $ 3, $ April $ 280,000 $ 10, $ May $ 280,000 $ 4, $ June $ 280,000 $ 11, $ July $ 280,000 $ 14, $ August $ 280,000 $ 2, $ September $ 280,000 $ 3, $ October $ 280,000 $ 4, $ November $ 280,000 $ 9, $ December $ 280,000 $ 7, $ Total Annual $ 3,360,000 $ 91,205 38,791 $ Appropriate Uses: 1. This metric identifies the unit cost of collections. It incorporates monies budgeted for the internal collection function and actual expenditures for outside collection services, including agencies and legal fees, being spent. 2. This measure is best used to evaluate performance when it is compared with the CEI and DSO metrics. It should direct you to the optimal level of spending on the collection effort to attain the desired level of receivable performance. 68

71 Operational Measures Credit Authorization Rates Definition: Identifies the percentage of new accounts opened compared to the total number of new account requests. Formula: Number of new accounts approved during a specified period of time Number of new accounts submitted for approval over a specified period of time Advantages: 1. Signals to the receivable manager whether risk assessment may be too lenient or restrictive. 2. Reflective of the quality of customers the organization may be target marketing. 3. When benchmarked against others in your industry can indicate the level of market share you may be gaining or losing based on the level of risk you are willing to take. Disadvantages: 1. May be difficult to ascertain whether high or low approval rates are resulting from the quality of accounts submitted or misaligned risk assessment policy. An Explanation of Sample Data: This example reflects the number of new accounts submitted for approval for each calendar quarter and divides those into the number of new accounts actually approved. This provides you with the credit authorization rate by quarter. The aggregate of the four quarters is reflected as a fiscal year total. Time Period New Accounts Submitted New Accounts Approved Credit Authorization Rate First Quarter % Second Quarter % Third Quarter % Fourth Quarter % Fiscal Year % 69

72 Operational Measures Credit Line Utilization Definition: Reflects as a percent the actual utilization of the aggregate lines of credit extended by the organization. Formula: Total Outstanding Receivables Aggregate of Credit Lines Extended to All Customers Advantages: 1. Provides the organization a snapshot of its customer s utilization of available credit lines. 2. As credit line utilization is reaching maximum availability it can prompt the receivable manager to identify areas of the portfolio where increases in available lines are prudent. 3. This particular measure can be applied to individual accounts, groups of accounts or the entire receivable portfolio. 4. Allows the receivable manager the opportunity to identify for the benefit of sales and marketing areas for potential sales growth. Disadvantages: 1. None identified at this time. An Explanation of Sample Data: This example shows an aggregate of all customer credit lines and it reflects total outstanding receivables at the end of each quarter. Receivable balances could also be reflected by month or any other time period for that matter. By dividing Aggregate Credit Lines into Total Outstanding Receivables the organization can get a snapshot view of credit line utilization and take appropriate actions to increase utilization, increase lines if utilization is reaching maximum availability, etc. Time Period Aggregate Credit Lines Total Outstanding Percent of Utilization First Quarter 2007 $157,335,257 $97,889,895 62% Second Quarter 2007 $163,450,555 $126,228,950 77% Third Quarter 2007 $171,645,675 $137,565,888 80% Fourth Quarter 2007 $176,898,545 $143,258,963 81% 70

73 APPENDIX ITEMS USED IN MEASURES OF PERFORMANCE ANALYSIS Active Customer Accounts The customers listed on the aged trial balance. Actual Loss Adjustments Age Category Amount Paid Bad Debt Balance Fraction The dollar amount expensed to the business unit. Deductions, journal entries, and over or under payments. A date-range section of the aged trial balance. Payments and adjustments to an individual invoice. 1. Bankruptcies 2. Out-of-court settlements a. Assignment for the benefit of creditors b. Extension agreement 3. Bulk transfers 4. Third party collections a. Collection agencies b. Attorneys 5. Uncollectible invoices 6. Accounts aged over one year 7. Recoveries on prior bad debts 8. Fraud Losses 9. Customer skips Age category / Credit sales for a present or prior period. Beginning Receivables Total receivables from prior month. Budgeted Loss Cash Applicator Checks Processed Collected Amount The dollar amount planned or expected to be expensed to the business unit. A person responsible for actually applying check transactions to customers accounts or invoices. Total number of checks received and applied to customers' accounts. Funds received from attorneys and collection agencies as payments on bad debt. Collection Department Budget Total Salary & Benefits for the FTE s that work in the collections department. Collector A person responsible for collecting on customer accounts. 71

74 Credit Representative A person responsible for credit approval, collections and review on customer accounts. Credit Sales Sales on open accounts or Total sales less cash sales. (A high ratio of cash sales to credit sales [5% or more of cash sales] artificially lowers measures and distorts comparability.) Current Months Past Due Total receivables - Current amount. Current Receivables All invoices not yet due. Includes outstanding customer invoices, credits, deductions and unapplied cash. Excludes bad debt. Department A group of individuals working in the same function. Days in Current Period The number of calendar days (28 to 31 for a month) in the current period. Days in Prior Period The number of calendar days (28 to 31 for a month) in the prior period. Days Outstanding Days to Add Number of days from invoice date to full payment date. Note: Include adjustments Percent of Credit Sales for period x Days in Prior Period. Deduction Specialists Company employees who process, distribute or handle adjustments made by customers. Deduction Any cash expense subtracted by a customer from an invoice. Ending Current Receivables All invoices not yet due at the end of the period. Includes outstanding customer invoices, credits, deductions and unapplied cash. Excludes bad debt. Ending Total Receivables Total amount in all age categories at the end of the period. Includes outstanding customer invoices, credits, deductions and unapplied cash. Excludes bad debt. Flow of Funds Funds Applied Days Outstanding x Funds Applied. Payments and adjustments applied to invoices. High-Funds Account Accounts where significant funds could be collected in a relative short time. Accounts that have at least $2,000 over 60 Days and a total due of $5,000 (or whatever amounts are relative to your business) or more that are not paying according to terms because of improper billing or processing problems. 72

75 High-Risk Account Accounts where significant funds could be collected in a relative short time. Accounts that have at least $2,000 over 60 Days and a total due of $5,000 (or whatever amounts are relative to your business) or more where the customer is not paying because of its lack of ability to pay or some unknown reason for not paying according to terms. Invoice Amount Total dollar amount of invoice. Number of Active Customers The sum of all customers listed on the aged trial balance. Operating Cost All direct and indirect costs assessed to the department or function. Include all managerial, accounting, and clerical personnel, systems costs, postage, depreciation, occupancy, etc. Exclude non-recurring costs, such as temporary help, consultants, one time system development costs, etc. Allocate costs when a person or system performs tasks for more than one business or function. Percent of Credit Sales This is determined by dividing ending total receivables by credit sales for the period under consideration in the formula. Total Applications Approved The number of credit application that have been approved. Total Applications Decisioned The number of credit application that have been approved or declined. Note: Only properly completed credit applications should be counted. Total Applications Declined The number of credit application that have been declined. Sum of the Days to Decision Individual Applications The sum of the number of days to approve or decline individual credit applications from the day the application was received. Total Receivables Total amount in all age categories at the end of the period. Includes outstanding customer invoices, credits, deductions and unapplied cash. Excludes bad debt. Note: All items should be aged based on their creation date. General credits should not be applied to oldest age category. Transactions Invoices, credits, adjustments, deductions, over payments, cash and all items included in the accounts receivable. 73

76 GLOSSARY Active Customer Accounts: The customers listed on the aged trial balance. Adjustments: Deductions, journal entries, over payments, and under payments. Age Category: A date-range section of the aged trial balance. Amount Paid: Payments and adjustments to an individual invoice. Bad Debt: Any expensed loss such as; bankruptcies, out-of-court settlements, bulk transfers, fraud losses, third party collections, uncollectible invoices. Balance Fraction (BF): Age category / Credit sales for a present or prior period. Beginning Receivable: Total receivable at beginning of the fiscal year. Includes outstanding customer invoices, credits, deductions and unapplied cash. Excludes bad debt and credit balance accounts. Cash Applicator: A person responsible for actually applying check transactions to customer's accounts or invoices. Checks Processed: Total number of checks received and applied to customers' accounts. Collected Amount: Funds received from attorneys and collection agencies as payments on bad debt. Collector: A person responsible for collecting on customer accounts. Credit and Collection Employee: All employees involved in the credit and collection function, including secretaries, administrators, supervisors, and managers. Credit Representative: A person responsible for credit approval, collections and review on customer accounts. Credit Sales: Sales on open account or Total sales less cash sales. (A high ratio of cash sales to credit sales [5% or more of cash sales] artificially lowers measures and distorts comparability.) Current Months Past Due: Total receivables - Current amount. Current Receivables: All invoices not yet due. Includes outstanding customer invoices, credits, deductions and unapplied cash. Excludes bad debt. Customer Skip: A customer that cannot be located. Days Outstanding: Number of days from invoice date to full payment date 74

77 Deduction: Any cash expense subtracted by a customer from an invoice. Deduction Specialists: made by customers. Company employees who process, distribute or handle adjustments Ending Current Receivables: All invoices not yet due at the end of the period. Includes outstanding customer invoices, credits, deductions and unapplied cash. Excludes bad debt. Ending Total Receivables: Total amount in all age categories at the end of the period. Includes outstanding customer invoices, credits, deductions and unapplied cash. Excludes bad debt. Flow of Funds: Funds or cash received from payments on accounts receivable. Funds Applied: Payments and adjustments applied to invoices. High-Funds Account: Accounts where significant funds could be collected in a relative short time. Accounts that have at least $2,000 over 60 Days and a total due of $5,000 (or whatever amounts are relative to your business) or more that are not paying according to terms because of improper billing or processing problems. High-Risk Account: Invoice Amount: Operating Cost: Accounts where significant funds could be collected in a relative short time. Accounts that have at least $2,000 over 60 Days and a total due of $5,000 (or whatever amounts are relative to your business) or more where the customer is not paying because of their lack of ability to pay or some unknown reason for not paying according to terms. Total dollar amount of invoice. All direct and indirect costs assessed to the department or function. Include all managerial, accounting, and clerical personnel, systems costs, postage, depreciation, occupancy, etc. Exclude non-recurring costs, such as temporary help, consultants, one time system development costs, etc. Allocate costs when a person or system performs tasks for more than one business or function. Total Receivables: Total amount in all age categories at the end of the period. Includes outstanding customer invoices, credits, deductions and unapplied cash. Excludes bad debt. Note: All items should be aged based on their creation date. Transaction: Invoices, credits, adjustments, deductions, over payments, cash, and all items included in the accounts receivable. 75

78 R E S O U R C E S Visit the Credit Research Foundation website for additional resources Copyright 2007 by the Credit Research Foundation. All rights in this paper are reserved. No part of the publication may be reproduced in any manner whatsoever without written permission. Printed in the United States of America Credit Research Foundation 8840 Columbia 100 Parkway Columbia MD U.S. $