Slideshow Transcript

1. Slide 1: “Measuring, Monitoring and Managing the Credit Department” © Presented by: Jim Menard, C.C.E. email: sugarpine@charter.net CMA Business Credit Services
2. Slide 2: You can’t manage what you can’t measure 2
3. Slide 3: If there is one thing that credit executives agree upon, it is that they cannot agree on which measures to use The person with the most authority usually dictates the measures to be reported to management. Even though we report to management, most of us like to track other measures to \"see how we are really doing.\" 3
4. Slide 4: The purpose of this presentation is to serve as a reference guide and provide you a collection of performance measures used. Dynamic credit executives plan and direct the credit, collection, and accounts receivable functions to increase sales and profits. Using valid measures of performance is critical in this process. 4
5. Slide 5: Most of the measures that are currently in use have value. Unfortunately, they also have some flaws. The challenge is to understand the individual measures and use them accordingly. The credit professional will have a clear understanding of the individual measures of performance and implement the appropriate measures to meet the needs of their organization. 5
6. Slide 6: 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. 6
7. Slide 7: 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. 7
8. Slide 8: Using Appropriate Measures of Performance Can Help: Identify areas of expertise Improve policies and procedures Shorten lead time Reduce customer complaints Improve financial performance Focus employee training and support Reduce costs Perform fair individual and group evaluations 8
9. Slide 9: Using Appropriate Measures of Performance Can Help: Identify areas of potential growth Reduce errors or defects Increase customer satisfaction Increase customer retention Improve employee morale Increase productivity Increase cash flow Reduce bad debt 9
10. Slide 10: The following questions will help you determine if the right measure is being used: What does the measure express? What do the results of the measure indicate? Does the measure support the objectives? Is the measure valid? Is there a more valid measure that should be used? Does the use of the measure's results comply with organizational goals and values? Should the measure be used independently or in conjunction with other measures? 10
11. Slide 11: Days Sales Outstanding (DSO) Definition: This figure expresses the average time in days, that receivables are outstanding. It helps determine if a change in receivables is due to a change in sales, or to another factor such as a change in selling terms. An analyst might compare the days' sales outstanding with the company's credit terms as an indication of how efficiently the company manages its receivables. Formula: Ending Total Receivables x Number of Days in Period Analyzed Credit Sales for Period Analyzed 11
12. Slide 12: Sample Data Sales A/R Bal Current 31-60 61-90 90+ Jan $ 3,400 $6,210 $3,350 $1,800 $995 $65 Feb $ 3,600 $6,015 $3,555 $1,600 $800 $60 Mar $ 3,900 $6,325 $3,650 $1,750 $855 $70 $10,900 15 Days Sales Outstanding (DSO) $6,325 x 90 days / $10,900 = 52 days 12
13. Slide 13: Best Possible Days Sales Outstanding or Average Terms Based on Customer Payment Patterns Definition: This figure expresses the best possible level of receivables. This measure should be used together with DSO. The closer the overall DSO is to the Average Terms Based on Customer Payment Patterns (Best Possible DSO), the closer the receivables are to the optimal level. Formula: Current Receivables x Number of Days in Period Analyzed Credit Sales for Period Analyzed 13
14. Slide 14: Sample Data Sales A/R Bal Current 31-60 61-90 90+ Jan $ 3,400 $6,210 $3,350 $1,800 $995 $65 Feb $ 3,600 $6,015 $3,555 $1,600 $800 $60 Mar $ 3,900 $6,325 $3,650 $1,750 $855 $70 $10,900 15 Best Possible Days Sales Outstanding or Average Terms Based on Customer Payment Patterns $3,650 x 90 / $10,900 = 30 days 14
15. Slide 15: Sales Weighted DSO Definition: This figure expresses the average time, in days, that receivables are outstanding. Formula: ((Current Age Category / Credit Sales of Current Period) + (1 to 30 Day Age Category / Credit Sales of Prior Period)+(31 to 60 Day Age Category / Credit Sales of 2nd Prior Period) + (61 to 90 Day Age Category / Credit Sales of 3rd Prior Period) + (91 to 120 Day Age Category / Credit Sales of 4th Prior Period) + (etc.)) x 30 Note: There are several formulas to calculate Sales Weighted DSO. This is a simple expression of those formulas. 15
16. Slide 16: Sample Data Sales A/R Bal Current 31-60 61-90 90+ Jan $ 3,400 $6,210 $3,350 $1,800 $995 $65 Feb $ 3,600 $6,015 $3,555 $1,600 $800 $60 Mar $ 3,900 $6,325 $3,650 $1,750 $855 $70 $10,900 15 Sales Weighted DSO 3650/3900 = (.936) 1750/3600 = (.486) 855/3400 = (.251) 70/3200 = (.022) = 1.695 1.695 x 30 = 50.8 or 51 days 16
17. Slide 17: True DSO Definition: The accurate and actual number of days credit sales are unpaid. Formula: 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. The sum of True DSO for all open invoices = True DSO per total accounts receivable. 17
18. Slide 18: Delinquent DSO or Average Days Delinquent Definition: This figure expresses, in days, the average time from the invoice due date to the paid date, or the average days invoices are past due. Formula: DSO minus Average Terms Based on Customer Payment Patterns (Best Possible DSO) 18
19. Slide 19: DSO = 52 days Best Possible DSO = 30 days 52-30 = 22 Average Days Delinquent Note: a lower number is considered desirable – this measure retains a sales bias and may not give a true picture of performance. 19
20. Slide 20: Collection Effectiveness Index (CEI) This measure shows the effectiveness of collections over a given time period. Formula: 1-{total past due receivables / (outstanding A/R from the prior month + current month’s sales) x100} Website: www:crfonline.org for an example 20
21. Slide 21: Sample Data Sales A/R Bal Current 31-60 61-90 90+ Jan $ 3,400 $6,210 $3,350 $1,800 $995 $65 Feb $ 3,600 $6,015 $3,555 $1,600 $800 $60 Mar $ 3,900 $6,325 $3,650 $1,750 $855 $70 $10,900 15 1 – {1750+855+70 / (6015+3900) x100 } 1- (2675 /9915) x 100 = 1- .2698 x100 = 73.02 % The closer to 100% the better – the result is affected by a rise or fall in sales. 21
22. Slide 22: 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: 1 -Current Months Past Due Age Categories Beginning Receivables of Prior Month 22
23. Slide 23: Sample Data Sales A/R Bal Current 31-60 61-90 90+ Jan $ 3,400 $6,210 $3,350 $1,800 $995 $65 Feb $ 3,600 $6,015 $3,555 $1,600 $800 $60 Mar $ 3,900 $6,325 $3,650 $1,750 $855 $70 $10,900 1-(1750+855+70 / 6015) = 1 - .445 15 Equals 55.5% Prior Month’s Past Due Collected Note: should be used in connection with other measurements since it focuses 23 heavily on past due accounts.
24. Slide 24: Percent Over 61 Days -- or Percent of Any Age Category Definition: This figure expresses the percentage of Total Receivables that is 61 Days or more past due. Formula: Sum of the 61 Days and Older Categories Total Receivables 24
25. Slide 25: Sample Data Sales A/R Bal Current 31-60 61-90 90+ Jan $ 3,400 $6,210 $3,350 $1,800 $995 $65 Feb $ 3,600 $6,015 $3,555 $1,600 $800 $60 Mar $ 3,900 $6,325 $3,650 $1,750 $855 $70 $10,900 15 855+70 / 6325 = 14.6% over 60 days past due. Can be measured for any of the aging buckets… e.g. % over 90 compared to total A/R. 25
26. Slide 26: Bad Debt to Sales Definition: This 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: Bad Debt Net of Recoveries Credit Sales 26
27. Slide 27: Bad Debt for the Period = $ 115 Credit Sales for the Period = $10,900 $115 / $10,900 = 1.055% Department Goals was 1% Over by .055 % (or $6) 27
28. Slide 28: Active Customer Accounts per Credit and Collection Employee (Total Department) 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: Number of Active Customer Accounts Number of Total Department Employees 28
29. Slide 29: Number of Active Accounts = 36,320 Number of Employees = 33 36,320 / 33 = 1101 active accounts per employee Down from 1200 last period equals Lesser workload per employee 29
30. Slide 30: 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. Departmental Operating Costs Number of Department Employees 30
31. Slide 31: 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: Departmental Operating Costs Credit Sales Is your 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. 31
32. Slide 32: 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: Amount Paid to Attorneys and Agencies Collected Amount 32
33. Slide 33: High-Risk Accounts Definition: This measure identifies significant potential bad debt accounts so they can be collected, thereby maximizing profits by minimizing losses. You must set the criteria for your business. Example: these accounts have at least $2,000 over 60 Days and a total due of $5,000 and 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: Number of High-Risk Accounts 33
34. Slide 34: Other Measurements Number of complaints per collector DSO by collector / division >60 by collector / division Bad Debt by collector / division # of calls made by the collector Aging bucket improvement from / to DSO step Back Method 34
35. Slide 35: Other Measurements New Account turn around time Credit Memo ratio Dispute management cycle time Bad Debt as a % of Sales Adjustments as % of Sales Cash Collection forecast accuracy % Collected of the beg A/R 35
36. Slide 36: Other Measurements Kaizen – “continuous improvement” narrow focus on a specific area of a process with a quick turn around time Six Sigma – see Nov/Dec 2005 Business Credit Magazine for details “provides the techniques and tools to improve… any process” 36
37. Slide 37: Results Accordingly: “companies that correctly implement and manage their metrics… can achieve up to 30% reduction in DSO and 25% reduction in transaction costs”. Business Credit Magazine 11/05 37
38. Slide 38: Q&A Your time to ask the questions Remember to sign up for the Western Regional Credit Conference in Las Vegas on October 17-19 Thank you for participating, Jim Menard, CCE 38