Monthly Archives: January 2019

Supply Market Intelligence … Harder than it Looks … But Possible with Modern Systems, Part II

See Part I for the story to date. Suffice to say that when the following are objectively analyzed, one can expect good market insights:

  • financial statements, particularly those from public companies (as false statements are a criminal offence for the CFO and CEO in some countries)
  • customer interviews, good or bad, as it’s a third party product/service view
  • performance reporting, as any hard metric is objective
  • internal stakeholder interviews, where the bias is minimized through targeted questions
  • price index data, that can be used to roll-your-own forecasts
  • public consumption data from government contracts, as they are great benchmarks

… provided one has the right platforms!

What are those platforms? Well, consider that the following sources are (primarily) numeric:

  • price index data
  • performance metrics
  • public price contracts

And the following sources are primarily (subjective) textual:

  • customer interviews
  • stakeholder interviews

And the following, final source is mixed:

  • financial statements

And that makes it pretty clear you need a platform that has the following if you want to process the price data:

  • A Great Open API
    as the price index data will be on multiple exchanges — which use different APIs, security protocols, currencies, and even data encoding formats and you will need to be able to easily retrieve and integrate all of it
  • Multi-Level Formula Based Cost Models
    to accurately capture and represent all of the commodity, component, product, and service costs that you need to track for cost estimation and analysis, bill of materials, sourcing, etc.
  • Powerful Analytics (Integration)
    you need to be able to store, analyze over time, and use multiple, multi-variate, statistical algorithms to detect trends and project them over time, as well as alter the assumptions, parameters, and model inflection points (due to predicted inflection events)

… and a platform that supports the following if you want to process the textual data:

  • advanced semantic processing
    that can extract key topics and opinions and classify them to process or technology, functional area, etc. (as well as identify incongruities)
  • advanced textual analytics
    the platform needs to be able to assign general descriptions numeric weights against important factors (perceived risk, customer service level, etc.) to determine if the general view is improving, weakening, or staying static
  • advanced sentiment analysis
    that can extract not only general opinions about a supplier, process, etc. but specific opinions about process, technology, etc. components — for example, the stakeholder might be soured on the relationship with a supplier because they have p!ss-p00r customer service but agree they make the highest quality parts (and would be usable if they ever bothered to answer the d@mn phone); just an overall negative sentiment of 0.6 is not that meaningful

… and to process financial statements, the platform needs to merge the advanced textual analytics to populate a standard financial model template, adding in any additional revenue or expense, asset or liability, etc. lines that are missing from the standard model so the books balance and can be analyzed.

So where do you find these capabilities today?

Well, as previously indicated, you will find:

  • advanced cost models in direct sourcing platforms that support full multi-level bill of materials
  • advanced forecasting in modern analytics platforms that support machine learning
  • advanced sourcing support given predictive costs in platforms that support strategic sourcing decision optimization
  • advanced document analysis in industry leading contract management solutions (which can be adapted to parse and analyze and break apart and score any document type given a template and samples)

In other words, modern Analytics, Optimization, and Contract Analytics solutions. And this is just another reason SI has been preaching advanced optimization and analytics since day 1.

Supply Market Intelligence … Harder than it Looks … But Possible with Modern Systems, Part I

Last year, about this time, we wrote a piece on Supply Market Intelligence and how it was Harder Than it Looks because there are a number of sources that might yield intelligence, including:

  • Suppliers,
  • Internal Sources, such as
    • internal stakeholders
    • performance reports
    • SRM programs
  • External Sources, such as
    • news feeds and alerts
    • price index forecasts
    • blogs and social media
    • peer companies
    • research services
    • advisory programs

… but not all are equal. And not all are fully accurate. For example:

  • Supplier company websites only show you what the supplier wants you to see, which is typically not the full picture, and maybe not even a true part of it
  • Internal Sources, such as
    • internal stakeholder interviews capture bias as well as expertise
    • performance reporting can only report on hard metrics the organization had the foresight to capture
    • SRM programs — and the insights yielded — vary by company and supplier
  • External Sources, such as
    • news feeds only cover the stories that interest the journalists
    • price index forecasts use in-house algorithms that are not disclosed that may not be accurate
    • blogs and social media cover the stories that can be sussed out by the bloggers and analysts

But some of them contain valuable data that when appropriately, and objectively analyzed, can yield good insights, as per our follow up post:

  • financial statements, particularly those from public companies (as false statements are a criminal offence for the CFO and CEO in some countries)
  • customer interviews, good or bad, as it’s a third party product/service view
  • performance reporting, as any hard metric is objective
  • internal stakeholder interviews, where the bias is minimized through targeted questions
  • price index data, that can be used to roll-your-own forecasts
  • public consumption data from government contracts, as they are great benchmarks

… and so on. But it can be pretty hard to make sense of all this … unless you have the right platform with the right capabilities. Now, it might not be a single platform from a single vendor and instead be a base Sourcing / Procurement platform augmented with multiple best of breed modules and API services from multiple vendors, and that’s fine. The point is that it’s possible to make sense of this with modern technology. What technology? How? That’s the subject of our next post.

Fifty Years Ago Today …

Soviet spacecraft Soyuz 4 and Soyuz 5 perform the first-ever docking of manned spacecraft in orbit and the first-ever transfer of crew from one space vehicle to another (which was also the only time such a transfer was accomplished with a space walk).

This was a historic event in space exploration as it is one of the capabilities necessary to have a(n International) Space Station and we’re not going to reach the age of extra-planetary supply management (Part II and Part III) unless we can build space stations and efficiently dock spacecraft with them on inter-planetary supply runs.

The Key to Successful Supply Management? No MoBAs, no PiMPs, no Paper Pushers, and no over-reliance on dumb bots.

It seems the list gets longer every year as those looking for a quick-fix try to take shortcuts to solving their problem that involve pushing those problems to third parties who are even less competent to solve them.

A few years ago we said the key for a successful supply management center of excellence was no M(o)BAs and no P(i)MPs!. This is because successful supply management relies on supply management expertise and experience, not on meaningless business models and knowledge-free project management frameworks. (Remember that SI still firmly believes that individuals that only have MBAs are just Master of Business Annihilation!)

This is because not only is it the case that you can’t manage what you can’t understand, but all you can do if you try is make it worse! Supply Managers are overworked and under-resourced, and any misstep has a ripple effect throughout the supply chain — one that can go from a minor delay to a major catastrophe. Management knowledge and project management skills are good things, but whereas supply chain is concerned, only if this knowledge and skill is added to a fundamental understanding of the supply management process that needs to be performed.

However, as we indicated last year in our post that The Key to Successful Supply Management? No MoBAs, no PiMPs, and no Paper Pushers!, simply eliminating the unknowledgeable MoBAs and PiMPs is not enough anymore. Paper pushers have to go to. There’s no time for tactical people who only receive, process, and send e-paper in a modern fast moving supply chain when the majority of this work can be automated by modern bots.

Today’s professionals need to be able to identify, implement, and make use of modern assisted and augmented intelligence solutions that can help them identify what needs to be analyzed, what needs to be addressed, what needs to be done, and the best ways to potentially go about it. The individuals who can do this are not PO paper pushers or AP invoice processors. They are knowledgeable and capable sourcing, procurement, and supply management experts who know their domain, and the tools, first and the business and project management second.

And they can’t be hampered by dumb bots. Dumb bots do poor invoice matching and create a lot of false positives to be unnecessarily checked. Dumb bots simply flag differentials between current and market price with no understanding of what the cause for the difference is and whether or not savings could actually be realized if a sourcing event was conducted. Dumb bots automate auction and RFX stages on a schedule, but don’t ensure that stages are complete or requirements are met. Dumb bots can extract potential terms, costs, etc. but make no sense of them and not even classify them properly. And so on.

Smart bots are needed, but dumb bots create more tactical work than they take away. So make sure they go with the paper pushers when you show them the door.

Single Multi-Tier Risk Mitigation Strategies Don’t Mitigate Risk

Last year we penned a post on how single tier risk mitigation strategies don’t mitigate risk and that they may, in fact, increase risk. As we indicated in our previous post, the following standard single-tier risk mitigation strategies have the potential to increase risk:

    • Dual Sourcing
      without careful planning, both suppliers could use the same Tier 2 source
    • Alternate Design
      can simply reduce / eliminate the need for one rare raw material in favour of another material that ends up being more rare
  • Financial Risk Monitoring
    for shakey suppliers isn’t enough to catch production shortcuts that a supplier might be taking to cut costs that increase your risk when the product is used or sold
  • Replacement Product Lines
    can share parts and suppliers that actually increase risk from a disruption

We indicated that if you wanted to truly mitigate risk, you have to go multi-tier and work with your supplier to identify the most likely risks in their, and your, supply chain and how to mitigate them.

And this is a great start, but simply using the least risky supplier at each tier doesn’t help you if a random natural or man-made disaster takes out a supplier for a few months (or permanently). There needs to be a dual sourcing strategy, and a well planned one. Using two suppliers in the same region or that use the same raw material source is not dual sourcing. Alternate design that is specific to a small supply base that could be wiped out with a single disaster or single market event is not sound alternate design. Financial risk monitoring using third parties that don’t have deep insight into certain markets, regions, or mining operations is not enough — by the time an issue is detected, it could be too late. And of course, trading one product line with known risks for another with unknown risks is pretty much the opposite of risk mitigation.

That’s why you not only need multi-tier risk mitigation in a single supply chain, but multiple supply chains with multi-tier risk for any critical products or product lines. As per our recent post on how the risk disconnect is still big, Sourcing and Procurement need to place a much bigger focus on risk to ensure negotiated scenarios are actual scenarios to realize the savings and value the organization expects.