Category Archives: Decision Optimization

Next Generation Sourcing

As stated in yesterday’s post, for Sourcing to continue to have an impact in a modern Supply Management organization, it needs to be taken to the next level. And I’m not just echoing the statements of The Altimeter Group, AMR, CAPS, Greybeard Advisors, The Mpower Group, Purchasing Practice, or my own persistent ramblings over the years (as I have been pushing for Total Value Management and Next Generation Sourcing strategies since day one). A modern supply management organization truly needs to take their sourcing practices to the next level if they are going to continue to distill value from Sourcing.

When you consider that:

  • Once you institute RFX, the manpower savings from automating bids can only be claimed once.
  • By the time an organization gets to the third auction, there are no more savings to be had as the fat from supplier margins has been squeezed out.
  • Once the allocation has been optimized across the supply base in a way that minimizes unit costs, transportation costs, (interim) storage costs, etc., re-running the optimization won’t lower costs further unless something changes — such as the identification of a new supplier, an alternate material (that is cheaper), or additional demand (that increases the economy of scale).
  • Once contract management and monitoring is put in place and no invoices are paid that are not for delivered, defect-free products, at contracted rates, there is no more on-contract leakage to be stopped.
  • Once controls are put in place to stop off-contract purchases that should be on-contract (through integration of the e-Procurement system with the Contract Management system), there is no more off-contract leakage to be stopped.
  • And once spend analysis has identified all the opportunities, the savings won’t actually materialize until something is done about them. This something cannot be appropriately identified unless the appropriate information is available to the knowledge worker.

As a result, in order for a mature Supply Management organization to continue to extract considerable value from (e-)Sourcing, e-Sourcing needs to be taken to the next level. Whether you call it DDSN2 (Demand-Driven Supply Networks), Next Practices, or Total Value Management, the message is the same. Take your Sourcing to the next level, or risk decreasing returns.

So where does one start? Upgrade or bring in a modern e-Sourcing platform. For some organizations, who are already using a top-tier provider and who have purchased a suite license, this will just mean learning how to take full advantage of the end-to-end integrated functionality and improving processes. For others, using point solutions from top-tier providers, this will mean buying licenses to the whole suite and/or integrating the point solutions with other solutions they already have. For the market majority, this will likely mean either replacing existing first generation systems (from providers who haven’t made any updates to the base functionality in the last five years) or, in laggard cases, skipping first generation e-Sourcing systems entirely and starting off with modern systems that have better, integrated, functionality.

And then, once these systems are in place, processes are updated to capture more data and consider more information in sourcing decisions, in a process that one vendor on the leading edge likes to call High Definition Sourcing.

Since this process is the closest to what Sourcing Innovation believes is necessary for organizations that want to take their sourcing to the next level (and, in the words of CAPS, become value-focussed), this will be the subject of the next series of posts (starting next week). Stay tuned!

Information … Information … Information

Yesterday’s post discussed the lack of realistic starting points for an average organization that wants to merge onto the value focussed path and the need for information. Then the post discussed e-RFX applications and how they are not always the answer as most are not configured for collecting more than a moderate amount of data, and the information required to make the right decision might require a large amount of data to be collected.

For example, consider the information required to make the right decision in a global freight bid where the company has over 5,000 lanes across five continents that are currently being serviced, in part, by almost 500 carriers. Not only will there be a need to collect up to 1,000,000 LTL and TL bids to know what the lowest rates are, but there will be a need to collect data on capabilities (refrigerated, freezer, hazardous martial, etc.), capacities, and serviced lanes. And then, once all of the information has been collected, past performance, guaranteed service levels, (commitments to) sustainability (such as biofuels and hybrid vehicles) will have to be considered in addition to costs and on-time-delivery capabilities. And if multiple carriers are almost equal, long term viability, strategic partnerships, and/or commitment to social responsibility might also need to be considered.

All-in-all, this represents a significant amount of data that needs to be collected, analyzed, and distilled into useful information — data that is not even going to be collected if a firm is still using a first-generation e-Sourcing platform. This is because:

  1. Traditional RFX tools, which are now a commodity (as every provider and their dog has one — trust me), are not built to collect that much information.
  2. Most of the RFX tools that can handle that much information, typically by way of Excel import and export, are not designed with supplier usability in mind. No supplier is going to quote 5,000 lanes at multiple LTL and FTL levels if they only service 3,000 and 2,000 can be broken into 20 cross-regional groups where each lane in the group is priced the same by mile.
  3. Of the few tools that allow for generic pricing and (typically) single-dimensional overrides, most won’t designed with the ability to easily design multiple levels of overrides and the OLAP-like navigation that’s really need to quickly zoom in on the relevant data items (which need to be viewed or altered).
  4. And while most of the better RFX tools allow a user to define as many RFIs, RFPs, and RFQs as the user desires, these generally have to be crammed into rigid workflows that may or may not fit the scenario at hand.
  5. Plus, while most of the tools can push data out into an auction or a SIM tool (that is the foundation for SPM and/or SRM), most don’t allow data to be pulled back in, since the first generation e-Sourcing model was a linear RFX -> Auction -> Decision Optimization -> Award -> Contract Management -> SPM flow.

And then, once you get past all that, you still have to analyze the data to distill the information required to make a good award decision. Because even the best strategic sourcing decision optimization on the market will fail if it’s not provided with the right data AND the right constraints (or, depending on your choice of terminology, rules). The right constraints can only derived by a knowledge individual that has the right information at her disposal.

So how do get the right information? You take your sourcing to the next level. So what does this Next Generation Sourcing look like? Stay Tuned.

VFS Enablers: Competitive Enablers in a New Wrapper

Generally speaking, I’m not hard on CAPS Research because they tend to produce some of the best research and papers in the space, but I had to take a crack at VFS in yesterday’s post because I don’t think we need another acronym. And while it may look like I’m taking another crack at their recent “Value Focused Supply” publication in this post, I’m trying to point out that the next level of strategic supply management in your organization, regardless of what you call it, isn’t that hard to obtain. It’s just the next rung on the ladder, and only one small addition to the capability repertoire will get an organization there.

According to the white paper, the critical enablers of VFS are:

  • executive engagement
    No initiative will succeed over the long term without executive engagement, which is also a critical enabler of classic competitive supply strategies.
  • value chain goal alignment and measurement
    This is a fundamental requirement of any supply strategy designed to enhance an organization’s overall competitive position — and a core requirement for any enhanced competitive supply strategy, such as DDSN and TVM.
  • supply market understanding
    Without supply market understanding, even a simple e-Auction will fail miserably.
  • collaboration approaches
    The best results always materialize from collaboration.
  • supplier relationships
    Without a good supplier relationship, quality, on-time delivery, and emergency orders are at risk.
  • organization and human resources
    The right people will always be required to pull the strategy off.
  • information/analytic capabilities
    This is essentially the only enabler that’s new, sort-of. While information/analytic capabilities are a requirement of competitive sourcing strategies, as good information is necessary to select the right strategy and analyze the bids, classic competitive sourcing did not require decision optimization, modern (POS-based) forecasting techniques, inventory optimization strategies, or (true) spend analysis.

Thus, any organization that has mastered standard competitive sourcing can easily move on to next generation sourcing strategies simply by adding a new tool or two to their toolkit — complete overhauls not required.

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You Cannot Overlook SSDO And Optimize Your Supply Chain

I was taken aback at this recent article in SupplyChainBrain on Supply Chain Optimization in the New Analytics Economy which outlined five analytics-enabled objectives which did not include strategic sourcing decision optimization, which is the next logical step in the sequence. Consider the objectives:

  • Supply Chain Visibility
    Step one is to understand how much the supply chain is costing you.
  • Demand Forecasting and Inventory Optimization
    Step two is to segment the supply chain, forecast demand, and then optimize inventory for each segment.
  • Network Optimization
    Step three is to periodically perform TCO assessments on the different segments of the existing supply chain network to identify the optimal performance configuration.
  • Predictive Asset Maintenance
    Step four is to perform preventative maintenance to minimize downtime and maximize uptime.
  • Spend Analytics
    Step five is to understand how much is being spent on each procurement category and identify those with the most savings opportunities.

The next natural step is:

  • Strategic Sourcing Decision Optimization
    Once the categories with the biggest savings opportunities are identified, it’s time to optimally source them so the overall TCO is minimized and the utilization of the current networks, optimized in step three, is maximized.

How could you possibly stop at step five?

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