Spend Taxonomy: Data and Analysis

Spend Analysis Best Practices:

1. Audit your existing spend data and data management capabilities.

2. Gather data from inside and outside your organization to increase visibility.

3. Adopt a common classification schema throughout the enterprise. 

  • UNSPSC,

  • NAICS 

  • SIC 

  • Customized Codes 

4. Use category expertise to augment the process and confirm that data and the classifications can be validated. 

5. Develop and then establish repeatable data cleansing and classification capabilities through the use of software or services. 

6. Classify spend at a granular level. 

7. Use business intelligence to improve core spend data. 

8. Use advanced reporting and decision support tools. 

These best practices should be expanded throughout the business and the frequency should increase over time.   

Spend Data Classification Levels:

Level 1

Annual aggregation of high-value services or commodities which are the most obvious opportunities for aggregation.

Your organization will want to completely examine it’s spend. Although a high-level summary can provide a road-map, it is important to conduct a deep dive using all the data that is available. 

Level 2 

Supplier data in relationship to categories.  This enables your procurement organization to focus on leverage opportunities and identify ‘low-hanging fruit’. 

Use of the Pareto principle or the 80/20 rule will shorten this process and to give your organization more transparency by identifying the suppliers that are responsible for the majority of the spend. 

Level 3 

Data at the item or service level of classification system and a consolidated view of the spend. 

This provides additional visibility into purchases and exports actionable analyses.  It gives you a detailed view of spending by company, division, site and buyer. 

Challenges:

This analysis requires access to ALL of your organization’s spend data – both inside and outside the procurement organization. 

It also requires deep expertise into categories and suppliers and will eventually require a sophisticated analytical tool. 

2019-01-03T01:11:34+00:00

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