Pricing errors leak profit

Pricing errors leak profits and they could be dramatically reduced with some effort.  Companies that have straightforward list prices are much easier to manage then when companies negotiate complex contracts.  Pricing errors are common place when companies negotiate regularly because there are so many exceptions to prices and conditions that sales people agree to which must first be put into a contract and second either executed by sales reps taking orders or automated into a system.  This exception process leads to a lot of errors.

Our customers cut across many different industries and these issues are prolific whether you are in metals, high tech, insurance, or other business to business situations.  One of our customers in the metals industry performed an extensive Six Sigma study prior to engaging us.  The study found their sales process and inter-communication caused thousands of problems a year.  The quantifiable errors cost them $1.4M a year and the upside was most likely $5M – $7M a year.

In Six Sigma, it is critical to have a well defined business case that outlines the purpose of the project as well as a goal statement that addresses the business case.  For the customer, the business case was obvious:

  • $750 million in sales, 60 thousand invoices, 3 thousand discrepancies.
  • No system in place to verify accuracy of contract and pricing for orders.
  • Loss of revenue, customer confidence, control of pricing in marketplace.

And the resulting goal statement was defined as:

  • Improve competitive pricing and invoice system for quarterly savings of $350K.

The customer’s first priority was reducing pricing errors in accordance with the business case and goal statement.  Today’s market requires more extensive information on invoices than in prior years including the price and how the final price is derived.  Their price components were base price, alloy surcharges, scrap surcharges, freight, freight equalization, and fuel surcharges.  Each one of these components were either contract values or tied to a monthly index average.  The steps for calculating and looking up values produced significant errors as shown in Table 1.

Total Invoices Price Errors Input Errors Retro Price Late Price Sheet Incorrect Price Sheet
Plant 1 561 225 5 21 93 217
Plant 2 39 31 2 0 0 6
Plant 3 489 220 2 31 103 133
Plant 4 411 248 8 4 45 106
Plant 5 221 29 27 4 6 155
Total 1721 753 44 60 247 617
% of Reasons 43.80% 2.60% 3.50% 14.40% 35.90%
% of Invoices 4.20% 1.80% 0.10% 0.10% 0.60% 1.50%
Avg cost/yr to correct $348,503.00 $152,483.00 $8,910.00 $12,150.00 $50,018.00 $124,943.00

Table 1

This table looks at invoice discrepancies only when payments received did not match the invoiced amount.  The number of invoice discrepancies were 4.2% of the total 60,000 invoices per year.  Errors were broken down into five categories including:

  • Price Errors, which were mis-calculations or incorrect lookups of price components.
  • Input Errors, which occured when transposing prices from spreadsheet calculations to the invoicing system.
  • Retro Errors, which were caught after the fact and changed.
  • Late Price Sheet, which occured when sales people failed to get price changes in on time before invoices were set out.
  • Incorrect Price Sheets, which were spreadsheets maintained by sales people that had errors or were interpreted incorrectly.

We worked with them to eliminate all of these errors by using a centralized pricing structure and automatically generating price sheets.  Sales people used the tool which had a similar interface as a spreadsheet which they were familiar with and prices were automatically stored in the central system.  So, when invoicing needed prices, they were always up to date and interpretation disappeared.

It was interesting to note in the study that more often than not, customers notified them when they thought they were over-billed, but customer reported under-billing was almost non-existent as shown in Table 2.

January February
Location Over Under Over Under
Plant 1 $39,867.13 $0.00 $6,965.65 -$232.35
Plant 2 $20,895.40 -$2,171.66 $5,842.22 $0.00
Plant 3 $29,933.82 $0.00 $3,282.29 $0.00
Plant 4 $13,555.53 $0.00 $8,392.71 $0.00
Plant 5 $1,700.74 $0.00 $87.73 $0.00
Monthly Total $108,124.28 -$2,171.66 $24,803.08 -$232.35
Running Total $108,124.28 -$2,171.66 $132,927.36 -$2,404.14
Annualized Rate $1,297,491.36 -$26,059.92 $797,564.16 -$14,424.84

Table 2

Statistically, the over and under billing errors should have been similar.  In the customer’s case, only one customer actually called back when he was under-billed.

As mentioned previously, with the new system the prices were correct the first time.  When we piloted the system, they checked 5 customer’s prices for a month period and found over $77,000 in under-billing that would have previously gone unnoticed.

The Six Sigma study also took an in depth look at why errors occurred.  The source of errors fell into the six bins shown in Illustration 2.  The main source of errors was the loose price sheet document, which they called a CPF.  This document was managed by sales people, but with little structure.  Sales is a creative process so sales people needed flexibility in managing customers, but the loose form significantly contributed to errors.

Market Environment CPF Document Pricing System Errors CPF Interpretation Time of Order vs Time of Shipping
1. No time for detailed price agreement with customer 1. No requirement for documenting agreement with customer 1. Same person not always available to price 1. Long learning curve for interpreting CPFs 1. Lack of need for documented agreement with customer for specific delivered price
2. Customer’s system is not compatable with CPF 2. No time for detailed price agreement 2. Input error prone 2. Complexity of CPF, agreement, non-standard info sources 2. No comparison of pricing to customer PO
3. Information not received in a timely fashion 3. CPF constructed several days after agreement 3. Illegible, handwritten info 3. Inconsistent interpretation of CPF and add-ons 3. Price is optional part of order entry
4. Amendments not received 4. Pricing using wrong sheet 4. Calculation errors 4. Same person not always available 4. Price at order entry not transferred to pricing
5. CPF not updated 5. Information not received in a timely fashion 5. Transposition errors 5. Didn’t capture info correctly from CPF 5. No checks on previous billing history
6. Information not available on time 6. Amendments not received 6. Employees time constrained 6. Missed charging for extras
7. No verification process with customer 7. CPF not updated 7. Documents hard to read 7. Misread the CPF
8. Format of CPF not compatible with pricing needs 8. Information not available on time 8. Working from the wrong sheet, line, or column
9. Information not available on time 9. No controls to ensure correct info is being used 9. No controls on using wrong infor from CPF
10. Price protected orders/shipments hard to ID
11. No controls on what ammendments are used for pricing
12. No controls on effective dates

We were able to address the majority of the error sources discussed above without interfering with the creativity of the sales people.  By centralizing pricing, standardizing calculation methods, and tables, we brought structure to the process but allowed sales people to customize price sheets according to individual needs.

Metals pricing is particularly complicated and if you’re going to tackle your own pricing errors, you don’t necessarily need to do a Six Sigma study before you start.  It certainly helps to unearth the estimated savings, but you probably already have a gut feel for where the leaks are coming from.  The first thing to do is get a handle on all the contracts floating around and the special conditions.  You can segment these, put them in spreadsheets and start from there.  Once you have the the special conditions isolated, you can put together a framework for exceptions that captures the majority of the conditions.  Then, you can offer those exceptions as the only exceptions you’ll allow from sales reps.  Giving reps some freedom within a process gives them some negotiating latitude that you can put into a system to cut down on errors.  It’s not simple, but it can be done and will help increase profit.

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