Procurement, Supply Chain Network Design and M&A: Tips For Getting at the Data
Categories: Analytics, Procurement Commentary, Procurement Strategy & Planning, Supply Chain | Tags: L1, Process and Best Practice
I’ve recently been thinking quite a bit about the intersection of supply chain network design and procurement in an M&A context. The combination of the two areas can dramatically extend the role and scope of procurement in M&A strategy development, due-diligence, and post merger integration. I blame a recent article in Logistics Viewpoint for setting the mind at work on the topic.
One of the fundamental challenges in any type of M&A situation from either a supply chain or procurement vantage point is getting at the data in a timely manner. Of course, there can be complications (e.g., clean room deal environment) that limit the ability of a broader team to access information. But even short of this extreme, the biggest handicap facing operations and purchasing analysis concerning M&A is the ability to get at information quickly. Note, information about a target or recently acquired entity is not just “cost” unit cost data (but more on this in a minute).
Logistics Viewpoint echoes this perspective, especially in the time of M&A strategy development and pre-merger activity. As they observe, “the pre-merger phase is uniquely challenging in that data for potential markets and acquisition/merger targets is often difficult to access. Strategy building and decision making relies heavily on assumptions rooted in available data.”
Assumptions and data don’t always go well together – especially when tens of hundreds of millions of dollars (or billions) are on the line in the area of M&A synergies and risk.
But how can you get at data more effectively? Here are a few tips.
Walk, don’t run, to adopting and using e-discovery type tools to unearth contracts and other documents that could be useful as part of M&A analysis. Seal Software is a specialist in the area of finding and interrogating any type of document that could be construed as a contract within the systems purview of an organization (e.g., on servers, desktops, notebooks, and other devices).
Understand the procurement systems environment as a first step within a target company. If they have eProcurement, e-invoicing, sourcing, spend analysis, contract management, or commodity management systems in place, such tools can be a great starting point for unearthing the types of data necessary to do analysis. But don’t just stop at “they use XYZ” for supplier management – it’s not the vendor (or the tool) but the level of adoption and data within it.
Explore trusted strategic distribution and supplier relationships as quickly as possible and find out data sources available from vendors (e.g., line-level invoice details). This can include camping out with large/strategic industrial distributors, 3PLs, and IT suppliers to get data from them and doing an end-run around the source systems internally (supplier data is almost always cleaner and more detailed).
Run sourcing events in RFI mode (e.g., using sourcing optimization tools) as quickly as possible to get data points back from suppliers in terms of the relative market environment (and the benefits, costs, and risks of going to market together).
Don’t be afraid to create “throw away” analytics environments to look at data in context within the thought of necessarily keeping a new cube or creating permanent dashboards. While Endeca (part of Oracle) is one of our all-time favorite tools for building and navigating data mash-ups, it’s also worth considering others such as Opera (which uses the BIQ toolset) as well as simply building your own environment with Tableau, Qlikview, etc.
- Ideas for Supply Chain Design, Mergers, and Procurement
- Tungsten/OB10 Releases Networked, Invoice-Based Spend Analytics: Impressions and Implications
- M&A Synergy: When Supply Chain Design Meets Procurement and Distribution
- Metadata Explained: What it Means for Spend Analytics, Supply Risk, Supplier Performance, and More
- Oracle: Making Sourcing Better Through Analytics