Every Chief Data Officer (CDO) knows that accurate spend visibility, and the subsequent analytics, makes the difference between a “business as usual” and a “best-in-class” procurement organization.
But without the right spending insights, organizations can’t make the smart decisions that lead to continuous improvements and economic advantages. And the obvious question then emerges: “Can we trust any of our existing spend analysis?”
One of the main culprits obfuscating the truth about spending – traditional approaches to data mastering produce less-than-optimal (and traditional) results. The velocity and variety of data is outstripping MDM approaches that are dated, don’t scale, and are highly resource-intensive. Most manufacturers still rely on application integrations to unify data. This may work for some applications, but it is not the solution to every problem. Others aggregate data into lakes and then employ data engineers to write business rules to compensate for data quality and variety. This method falls short as well.
So how can a business – and more specifically obtain a more accurate analysis of their spending? Tamr put together a new guide: CDO Guide to Spend Analytics for Manufacturing to help answer this question
Inside, we outline how “mastering” spend analytics allows you to:
- Make better business decisions by cleaning and mastering your data
- Effectively manage suppliers, spend, and materials
- Quickly act upon latent data by combining Machine Learning and human expertise