Daily Archives: October 5, 2017

Sourcing the Day After Tomorrow Part XI

In this series we are doing a deep dive into the sourcing process today, and, in particular discussing what is involved, what is typically done (manually), and whether or not it should be that way. We have already completed our initial discussion of the initial project request review phase, the follow up needs assessment, the strategy selection phase, and the communication phase. Now we are in the analysis step. At first glance, it looks like this is more strategic and human-driven than prime for tactical automation, but we have been fooled before (and won’t get fooled again).

We are discussing the analysis step, which has the following sub-steps that have to be completed every time (and not just sometimes):

  • Market Pricing Data
  • Historical and Projected Spend
  • Cross-Category Materials Spend
  • TCO / TLC (Total Cost of Ownership, Total Lifecycle Costs)

Let’s start with market pricing data. While humans need to review and verify the data for accuracy and completeness, they don’t need to manually collect it. Consumer pricing can easily be collected from crawlers and punch-outs, many BPOs/GPOs have APIs and data feeds or at least easily parsed CSV files, and pricing from government contracts can usually be downloaded from government sites and automatically parsed. As a result, most of the market pricing data collection effort is easily automated.

When it comes to historical and projected spend, this can be easily be pulled from a good spend analysis system once all the data has been cleansed, categorized and enriched. A few rules get the relevant spend, the related spend, and the application of a few algorithms can easily automate the calculation of projected spend under standard assumptions.

When it comes to cross-category materials spend, if the organization’s ERP contains bill of materials (and approximate usage of a raw material in the production of a product or service), and if the spend analysis system is configured to support this level of detail, then the cross-category materials spend can be pulled out of the spend analysis system in an automated fashion and matched to the current and projected spend. All a human needs to do is review and verify the data.

Finally, in the TCO/TLC phase, most of the relevant costs factors can be automatically identified by a modern spend analysis system that can match invoices to goods and services and identify the associated costs as well as through a contract analytics systems that can analyze past contracts and pull out the “hidden” costs that the supplier passes on to the buyer (in margins or lump-sum fees). Plus, semantic analysis of product descriptions can allow other direct and indirect costs to be identified, and all of these factors can be compiled to create a should-cost model, with certain costs (such as transportation, import/export fees, taxes, etc.) automatically pulled from market data and other costs estimated using prior costs and estimated costs on related categories. A human has to do the final analysis and sanity check, but so much of the tactical drudge work of analysis can be automated these days that it’s almost cognitive.

In other words, the more we explore the sourcing process, the more we find out how truly tactical the majority of it is. But we’re not done, so in our next four parts we will explore the last two phases of negotiation and contract.