The power of data is indisputable and so is the challenge posed by poor quality data to procurement organizations that are turning increasingly to data for spotting patterns, predicting spend, and improving processes and procurement performances. Good data is the key to spend analysis and one of the cornerstones of good data in the context of spend analysis is structure.
The power of data is indisputable and so is the challenge posed by poor quality data to procurement organizations that are turning increasingly to data for spotting patterns, predicting spend, and improving processes and procurement performances. Good data is the key to spend analysis and one of the cornerstones of good data in the context of spend analysis is structure.
The structure provides the basis for easy spend analysis and hence, choosing the right data structure and depth is the key to any spend taxonomy. Spend taxonomy is the classification of an organization’s spend in a hierarchical order and the hierarchical order could range from three to five levels based on the complexity of their spend. There is, however, no one size fit all spend taxonomy. This leaves organizations building their spend taxonomy with the question of which approach to take. A best practice for organizations building a spend taxonomy would be to align spend data structure to the needs of the product. This would better serve the procurement strategy. Furthermore, as data classification is usually the root cause of inaccurate data stories, a taxonomy, is critical to managing internal agreement on the method used to classify data and imperative to using supply-side data. Achieving the full potential of spend analytics, the information-based decisions that follow, and the savings that organizations can make requires a rock-solid data structure. In short, spend analytics begins with taking the right approach to building a spend taxonomy, which in turn can offer reporting that enables an organization to make strategic budgeting and operating decisions. Click here the original article published by PASA.
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