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portada Financial Award and Revenue Mining: An Accounting Guide to Analyzing Financial Awards and Revenue Mining Data using the ABC Methodology(tm)
Type
Physical Book
Language
Inglés
Pages
42
Format
Paperback
Dimensions
22.9 x 15.2 x 0.3 cm
Weight
0.09 kg.
ISBN13
9781670361226

Financial Award and Revenue Mining: An Accounting Guide to Analyzing Financial Awards and Revenue Mining Data using the ABC Methodology(tm)

James Lester Cpa (Author) · Independently Published · Paperback

Financial Award and Revenue Mining: An Accounting Guide to Analyzing Financial Awards and Revenue Mining Data using the ABC Methodology(tm) - Lester Cpa, James

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  • Condition: New
Origin: U.S.A. (Import costs included in the price)
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You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.

Synopsis "Financial Award and Revenue Mining: An Accounting Guide to Analyzing Financial Awards and Revenue Mining Data using the ABC Methodology(tm)"

This guide is designed to teach the reader on how to develop a revenue financial data mining tool using a spreadsheet and a simple methodology I've developed that can identify revenue opportunities, provide higher quality revenue reporting, potential to increase revenue recognized, and help explain revenue fluctuations for the reader's organization. First, this guide develops the reader's understanding about how to conceptualize financial orders and revenue. Next, this guide teaches the reader how to develop a financial data mining tool using only a spreadsheet and the ABC methodology. Then the reader is provided simple examples within this guide to practice using the financial data mining tool the reader created to better understand and explain revenue fluctuations and identify revenue opportunities. Finally, at the end of this guide the reader is able to bring additional insight and value to the reader's organization by developing processes, potentially generating increased revenues, and creating reports that are proactive, accurate, repeatable, and verifiable in analyzing orders, backlog, revenue, and revenue forecasting variances.

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