Spend analysis

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Spend Cube

Spend analysis is the process of collecting, cleansing, classifying and analyzing expenditure data with the purpose of reducing procurement costs, improving efficiency and monitoring compliance. It can also be leveraged in other areas of business such as inventory management, budgeting and planning, and product development.

There are three core areas of spend analysis - visibility, analysis and process. By leveraging all three, companies can generate answers to the crucial questions affecting their spending, including:

  • What am I really spending?
  • With whom am I spending it?
  • Am I getting what’s been promised for that spend?

Spend analysis is often viewed as part of a larger domain known as spend management which incorporates spend analysis, commodity management and strategic sourcing.

Companies perform spend analysis for several reasons. The core business driver for most organizations is profitability. In addition to improving compliance and reducing cycle times, performing detailed spend analysis helps companies find new areas of savings that previously went untapped, and hold onto past areas of savings that they have already negotiated.

Automated spend analysis software can be a valuable tool for chief procurement officers (CPOs) at large, global, diversified enterprises, and a useful tool for many others.[1] The resulting spend visibility helps CPOs and CFOs gain insight into what their company buys and from whom, and it helps them realize savings promised by past sourcing efforts. The original approach to building spend cubes and the name "spend cube" refers to the three dimensions of the cube - Suppliers, Corporate business units, and Category of item. The contents in the cube are the price and volume of items purchased. John Anderson and Laura Boteler, of A.T. Kearney, Inc., developed the first spend cubes to be used in strategic sourcing.

References[edit]

  1. ^ A. Bartels, T. Pohlmann, H. Lo and C. Lee, Market Overview 2008: Automated Spend Analysis, Forrester Research, 2008