Like most, you probably get very excited seeing slick dashboards that visibly present your procurement activities, process metrics, and alerts. One of the key value propositions for a transactional procurement system is the data that can be used for reporting, strategic sourcing, and real-time insights that give companies a competitive and/or cost advantage.  The dashboards certainly make the data look good and there is power in having a finger on the pulse of your procurement operations.  But, how good is the underlying data that is the basis for your reporting, analysis, and real-time dashboards?  Is it clean? Normalized? Enriched?

For most companies, spend analysis begins quarterly with a data preparation process that is done based on historical data.  Typically the data needs to be cleansed, normalized, and enriched.  Often this is done by a 3rd party service. By the time the data is prepared and reported it becomes outdated, and at the very least a backward looking analysis.  Of course we can learn from history, but in the meantime, haven’t we had a quarter of “insights” from our real-time reporting?

Marketplaces are an opportunity for all systems in your landscape to work from, not only approved and contracted suppliers, but also pre-cleansed data.  For instance, the data in the marketplace can be mapped to product categories and to suppliers.  When a user purchases products and services from the marketplace the categories and suppliers are identified correctly and carried forward to the transaction data that is used for reporting.  As a practical example, I worked with an amusement park company that bought flowers.  When the flowers were purchased for the theme park, it was a direct material.  When the flowers were purchased for headquarters to make the parking lot pretty, they were indirect.  The marketplace in this case can correctly identify the category based on the context.  The user searches on the context (eg: flowers for the parking lot) and the system presents the appropriate data. 

Marketplaces also have the benefit of guided buying.  In guided buying, the data has attributes that identify the specific product or service with a procurement objective – diversity spend, green spend, on-contract spend, etc.  The benefit of having the enriched data before the transaction is that employees can make their product decisions based on procurement objectives. Employees in this case have an influence on the objective.  Is your current practice to tell employees after a quarter that the company didn’t meet diversity spend goals and they should do better next time?  Or, do you let employees know as they are making purchases how they will impact the metrics? 

The Marketplace moves the data cleansing, normalization, and enrichment pre transaction.  Now, the real-time analytics (ie: Artificial Intelligence) is based on the purified and enriched data.  Category managers will have confidence that the real-time statistics are accurate based on the cleansed and enriched data going into the process.  Employees can be a better participant in driving procurement goals. 

  

Catalog Marketplace

Not a catalog, but a marketplace.  The marketplace is a single point for all systems to access cleansed and normalized data with contracted and approved suppliers.  It orchestrates many different parties (business units, central category managers, suppliers, etc) that need to manage content to scale in a central and decentralized (eg: local sources) environment. All product and services content goes through the marketplace validation and approval processes. 

Transactions – familiar on-line buying in eProcurement

  • Usability encourages employee participation to realize procurement objectives – contract compliance, diversity spend, green spend, etc. 
  • Without participation, the company will not have complete transaction data.  The company loses valuable information when employees circumvent the process. 
  • Gives the information context that leads to insight.  Provides the context on top of the marketplace data that leads to future insight for that context. 
  • Portable and convenient – create purchase requests any time and on any device

Analytics

Real-time analytics/AI based on cleansed data – not a quarterly view of historical data

  • Confidence that the data is accurate
  • Capability to enrich the data with other data sources.
  • Insight – adjust on the fly; not backward looking

The above best practice encourages employee participation, builds transactions based on different contexts, and enables business to adjust and realize their strategic objectives. Having accurate and correctly categorized data during the entire lifecycle of the transaction is critical to the real-time insights that can be gleaned from the role-based dashboards and analytics.  How confident are you in your reporting?

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