Monthly Archives: December 2024

One Supply Chain Misconception That Should Be Cleared Up Now

This originally posted May 14 (2024).  It’s being reposted because this definitely needs to be cleared up before the new year (due to the constant proliferation of AI, which is, when all is said and done, just another technology).

Not that long ago, Inbound Logistics ran a similarly titled article that quoted a large number of CXOs that made some really good observations on common misconceptions that included, and are not necessarily limited to (and you should check out the article in full as a number of the respondents made some very good points on the observations):

The misconceptions included statements that supply chains should:

  • reduce cost and/or track the most important metric of cost savings
  • accept negotiations as a zero-sum game
  • model supply chains as linear (progression from raw materials to finished goods)
  • … and made up of planning, buying, transportation, and warehousing silos
  • … and each step is independent of the one that proceeds and follows
  • accept they will continue to be male dominated
  • become more resilient by shifting production out of countries to friendly countries
  • expect major delays in transportation
  • … even though traditional networks are the best, even for last-mile delivery
  • accept truck driver shortage as a systemic issue
  • accept the blame when anything in them goes wrong
  • only involve supply chain experts
  • run on complex / resource intensive processes
  • … and only be optimal in big companies
  • … which can be optimized one aspect at a time
  • press pause on innovation or redesign or growth in a down market
  • be unique to a company and pose unique challenges only to that company
  • not be sustainable as that is still cost-prohibitive
  • see disruption as an aberration
  • return to (the new) normal
  • use technology to fix everything
  • digitalize as people will become less important with increasing automation and AI in the supply chain

And these are all very good points, as these are all common misconceptions that the doctor hears too much (and if you go through enough of the Sourcing Innovation archives, it should become clear as to why), but not the biggest, although the last one gets pretty close.

 

THE BIGGEST SUPPLY CHAIN MISCONCEPTION

We Can Use Technology to Do That!

the doctor DOES NOT care what “THAT” is, you cannot use technology to do “THAT” 100% of the time in a completely automated way. Never, ever, ever. This is regardless of what the technology is. No technology is perfect and every technology invented to date is governed by a set of parameters that define a state it can operate effectively in. When that state is invalidated, because one or more assumptions or requirements cannot be met, it fails. And a HUMAN has to take over.

Even though really advanced EDI/XML/e-Doc/PDF invoice processing can automate processing of the more-or-less 85% of invoices that come in complete and error free, and automate the completion and correction of the next 10% to 13%, the last 2% to 5% will have to be human corrected (and sometimes even human negotiated) with the supplier. And this is technology we’ve been working on for over three decades! So you can just imagine the typical automation rates you can expect from newer technology that hasn’t had as much development. Especially when you consider the next biggest misconception.

Enterprises have a Data Problem. And they will until they accept they need to do E-MDM, and it will cost them!

This originally published on April (29) 2024.  It is being reposted because MDM is becoming more essential by the day, especially since AI doesn’t work without good, clean, data.

insideBIGDATA recently published an article on The Impact of Data Analytics Integration Mismatch on Business Technology Advancements which did a rather good job on highlighting all of the problems with bad integrations (which happen every day [and just result in you contributing to the half a TRILLION dollars that will be wasted on SaaS Spend this year and the one TRILLION that will be wasted on IT Services]), and an okay job of advising you how to prevent them. But the problem is much larger than the article lets on, and we need to discuss that.

But first, let’s summarize the major impacts outlined in the article (which you should click to and read before continuing on in this article):

  • Higher Operational Expenses
  • Poor Business Outcomes
  • Delayed Decision Making
  • Competitive Disadvantages
  • Missed Business Opportunities

And then add the following critical impacts (which is not a complete list by any stretch of the imagination) when your supplier, product, and supply chain data isn’t up to snuff:

  • Fines for failing to comply with filings and appropriate trade restrictions
  • Product seizures when products violate certain regulations (like ROHS, WEEE, etc.)
  • Lost Funds and Liabilities when incomplete/compromised data results in payments to the wrong/fraudulent entities
  • Massive disruption risks when you don’t get notifications of major supply chain incidents when the right locations and suppliers are not being monitored (multiple tiers down in your supply chain)
  • Massive lawsuits when data isn’t properly encrypted and secured and personal data gets compromised in a cyberattack

You need good data. You need secure data. You need actionable data. And you won’t have any of that without the right integration.

The article says to ensure good integration you should:

  • mitigate low-quality data before integration (since cleansing and enrichment might not even be possible)
  • adopt uniformity and standardized data formats and structures across systems
  • phase out outdated technology

which is all fine and dandy, but misses the core of the problem:

Data is bad (often very, very bad), because the organizations don’t have an enterprise data management strategy. That’s the first step. Furthermore this E-MDM strategy needs to define:

  1. the master schema with all of the core data objects (records) that need to be shared organizational wide
  2. the common data format (for ids, names, keys, etc.) (that every system will need to map to)
  3. the master data encoding standard

With a properly defined schema, there is less of a need to adopt uniformity across data formats and structures across the enterprise systems (which will not always be possible if an organization needs to maintain outdated technology either because a former manager entered into a 10 year agreement just to be rid of the problem or it would be too expensive to migrate to another system at the present time) or to phase out outdated technology (which, if it’s the ERP or AP, will likely not be possible) since the organization just needs to ensure that all data exchanges are in the common data format and use the master data encoding standard.

Moreover, once you have the E-MDM strategy, it’s easy to flush out the HR-MDM, Supplier/SupplyChain-MDM, and Finance-MDM strategies and get them right.

As THE PROPHET has said, data will be your best friend in procurement and supply chain in 2024 if you give it a chance.

Or, you can cover your eyes and ears and sing the same old tune that you’ve been singing since your organization acquired its first computer and built it’s first “database”:

Well …
I have a little data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

Oh, data, data, data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

It has nonstandard fields
The records short and lank
When I try to read it
The blocks all come back blank

I have a little data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

My data is so ancient
Drive sectors start to rot
I try to read my data
The effort comes to naught

Oh, data, data, data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

You Don’t Need Gen-AI to Revolutionize Procurement and Supply Chain Management — Classic Analytics, Optimization, and Machine Learning that You Have Been Ignoring for Two Decades Will Do Just Fine!

This originally posted on March 22 (2024).  It is being reposted because we need solutions, Gartner (who co-created the hype cycle) published a study which found that Gen-AI/technology implementations fail  85% of time, and its because we have abandoned the foundations — which work wonders in the hands of properly applied Human Intelligence (HI!).  Gen-AI, like all technologies, has its place, and it’s not wherever the Vendor of the Week pushes it, but where it belongs.  Please remember that.

Open Gen-AI technology may be about as reliable as a career politician managing your Nigerian bank account, but somehow it’s won the PR war (since there is longer any requirement to speak the truth or state actual facts in sales and marketing in most “first” world countries [where they believe Alternative Math is a real thing … and that’s why they can’t balance their budgets, FYI]) as every Big X, Mid-Sized Consultancy, and the majority of software vendors are pushing Open Gen-AI as the greatest revolution in technology since the abacus. the doctor shouldn’t be surprised, given that most of the turkeys on their rafters can’t even do basic math* (but yet profess to deeply understand this technology) and thus believe the hype (and downplay the serious risks, which we summarized in this article, where we didn’t even mention the quality of the results when you unexpectedly get a result that doesn’t exhibit any of the six major issues).

The Power of Real Spend Analysis

If you have a real Spend Analysis tool, like Spendata (The Spend Analysis Power Tool), simple data exploration will find you a 10% or more savings opportunity in just a few days (well, maybe a few weeks, but that’s still just a matter of days). It’s one of only two technologies that has been demonstrated, when properly deployed and used, to identify returns of 10% or more, year after year after year, since the mid 2000s (when the technology wasn’t nearly as good as it is today), and it can be used by any Procurement or Finance Analyst that has a basic understanding of their data.

When you have a tool that will let you analyze data around any dimension of interest — supplier, category, product — restrict it to any subset of interest — timeframe, geographic location, off-contract spend — and roll-up, compare against, and drill down by variance — the opportunities you will find will be considerable. Even in the best sourced top spend categories, you’ll usually find 2% to 3%, in the mid-spend likely 5% or more, in the tail, likely 15% or more … and that’s before you identify unexpected opportunities by division (who aren’t adhering to the new contracts), geography (where a new local supplier can slash transportation costs), product line (where subtle shifts in pricing — and yes, real spend analysis can also handle sales and pricing data — lead to unexpected sales increases and greater savings when you bump your orders to the next discount level), and even in warranty costs (when you identify that a certain supplier location is continually delivering low quality goods compared to its peers).

And that’s just the Procurement spend … it can also handle the supply chain spend, logistics spend, warranty spend, utility and HR spend — and while you can’t control the HR spend, you can get a handle on your average cost by position by location and possibly restructure your hubs during expansion time to where resources are lower cost! Savings, savings, savings … you’ll find them ’round the clock … savings, savings, savings … analytics rocks!

The Power of Strategic Sourcing Decision Optimization

Decision optimization has been around in the Procurement space for almost 25 years, but it still has less than 10% penetration! This is utterly abysmal. It’s not only the only other technology that has been generating returns of 10% or more, in good times and bad, for any leading organization that consistently uses it, but the only technology that the doctor has seen that has consistently generated 20% to 30% savings opportunities on large multi-national complex categories that just can’t be solved with RFQ and a spreadsheet, no matter how hard you try. (But if you want to pay them, an expert consultant will still claim they can with the old college try if you pay their top analyst’s salary for a few months … and at, say, 5K a day, there goes three times any savings they identify.)

Examples where the doctor has repeatedly seen stellar results include:

  • national service provider contract optimization across national, regional, and local providers where rates, expected utilization, and all-in costs for remote resources are considered; With just an RFX solution, the usual solution is to go to all the relevant Big X and Mid-Sized Bodyshops and get their rate cards by role by location by base rate (with expenses picked up by the org) and all-in rate; calc. the expected local overhead rate by location; then, for each Big X / Mid-Size- role – location, determine if the Big X all-in rate or the Big X base rate plus their overhead is cheaper and select that as the final bid for analysis; then mark the lowest bid for each role-location and determine the three top providers; then distribute the award between the three “top” providers in the lowest cost fashion; and, in big companies using a lot of contract labour, leave millions on the table because 1) sometimes the cheapest 3 will actually be the providers with the middle of the road bids across the board and 2) for some areas/roles, regional, and definitely local, providers will often be cheaper — but since the complexity is beyond manageable, this isn’t done, even though the doctor has seen multiple real-world events generate 30% to 40% savings since optimization can handle hundreds of suppliers and tens of thousands of bids and find the perfect mix (even while limiting the number of global providers and the number of providers who can service a location)
  • global mailer / catalog production —
    paper won’t go away, and when you have to balance inks, papers, printing, distribution, and mailing — it’s not always local or one country in a region that minimizes costs, it’s a very complex sourcing AND logistics distribution that optimizes costs … and the real-world model gets dizzying fast unless you use optimization, which will find 10% or more savings beyond your current best efforts
  • build-to-order assembly — don’t just leave that to the contract manufacturer, when you can simultaneously analyze the entire BoM and supply chain, which can easily dwarf the above two models if you have 50 or more items, as savings will just appear when you do so

… but yet, because it’s “math”, it doesn’t get used, even though you don’t have to do the math — the platform does!

Curve Fitting Trend Analysis

Dozens (and dozens) of “AI” models have been developed over the past few years to provide you with “predictive” forecasts, insights, and analytics, but guess what? Not a SINGLE model has outdone classical curve-fitting trend analysis — and NOT a single model ever will. (This is because all these fancy-smancy black box solutions do is attempt to identify the record/transaction “fingerprint” that contains the most relevant data and then attempt to identify the “curve” or “line” to fit it too all at once, which means the upper bound is a classical model that uses the right data and fits to the right curve from the beginning, without wasting an entire plant’s worth of energy powering entire data centers as the algorithm repeatedly guesses random fingerprints and models until one seems to work well.)

And the reality is that these standard techniques (which have been refined since the 60s and 70s), which now run blindingly fast on large data sets thanks to today’s computing, can achieve 95% to 98% accuracy in some domains, with no misfires. A 95% accurate forecast on inventory, sales, etc. is pretty damn good and minimizes the buffer stock, and lead time, you need. Detailed, fine tuned, correlation analysis can accurately predict the impact of sales and industry events. And so on.

Going one step further, there exists a host of clustering techniques that can identify emergent trends in outlier behaviour as well as pockets of customers or demand. And so on. But chances are you aren’t using any of these techniques.

So given that most of you haven’t adopted any of this technology that has proven to be reliable, effective, and extremely valuable, why on earth would you want to adopt an unproven technology that hallucinates daily, might tell of your sensitive employees with hate speech, and even leak your data? It makes ZERO sense!

While we admit that someday semi-private LLMs will be an appropriate solution for certain areas of your business where large amount of textual analysis is required on a regular basis, even these are still iffy today and can’t always be trusted. And the doctor doesn’t care how slick that chatbot is because if you have to spend days learning how to expertly craft a prompt just to get a single result, you might as well just learn to code and use a classic open source Neural Net library — you’ll get better, more reliable, results faster.

Keep an eye on the tech if you like, but nothing stops you from using the tech that works. Let your peers be the test pilots. You really don’t want to be in the cockpit when it crashes.

* And if you don’t understand why a deep understand of university level mathematics, preferably at the graduate level, is important, then you shouldn’t be touching the turkey who touches the Gen-AI solution with a 10-foot pole!

The Supply Chain of Supply Chain Talent is Not Only Broken … It’s Running On Empty!

This originally posted on February 16 (2024).  It is being reposted in case you missed it due to its importance as the talent problem is only getting worse (and “AI” is not going to make it better).

A recent article in Forbes noted that The Supply Chain of Supply Chain Talent Is Broken, which it is, and has been for well over a decade. The problems started back with the global first world truck driver shortages back in the early 2000s, but the real problems were much deeper and hidden from view due to the fact supply chains were otherwise running smoothly and no one was looking behind the curtain or shining a light into the dark recesses of the supply chain.

Why? Because of the rampant digitization of procurement, logistics, and supply chain over the past twenty years, a time when globalization reached its peak, conflict was at a minimum, inflation was in the rear-view mirror, and natural disasters were still manageable, supply chains just worked. Predictable processes, routes, costs, and flows allowed simple systems to manage the supply chains almost automatically. Supply Chains didn’t need traditional supply chain talent to run; they needed buyers, logistics managers, inventory operations, and compliance personnel who could use systems — IT geeks ruled the day!

At the same time, seasoned supply chain professionals — negotiators, logistics professionals, and inventory/warehouse managers — were retiring in droves, and no one was replacing them. More importantly, no one was replacing them because there was no perceived need. These were the individuals who where doing supply chains in the 80s and 90s, before modern systems managed everything, when there were still lots of regulations to deal with (as the EU was still forming), when you didn’t always have container ships available (or easy container transportation to all locales), and when you would have to know, by rote, who to call when a truck wasn’t at the factory or the dock for a pick-up. When you had to do everything by phone and fax, because email was a luxury; when you had to deal with dozens of import/export regulations (and know how to create the reports by hand), and how to manage logistics scheduling on paper, especially when availability of certain carriers or personnel would change by the day. When you had to truly know how supply chain operations worked end to end, and not just push buttons on a virtual screen.

But then they retired, and no one replaced them. Even worse, no one was recruited to replace them. The organizations saw no need, since the systems did everything, the EU and harmonized regulations across regions made trade easy, and the big global carriers managed logistics for them. As long as they had negotiators, system operators, outsourced carriers, and outsourced consultants to do the rest, who cared? They certainly didn’t.

Furthermore, because there was no need in the organizations, people who studied Operations Research and might have went into Supply Chain went elsewhere, and as demand shallowed, so did students, but more importantly, so did apprenticeships. Now, with disruptions on the rise, globalization retreating, inflation resurging, supply chains breaking due to slowdowns, (port) shutdowns, and double canal slowdowns/closures (Panama and Suez), and current systems not designed for the world today, there’s no one who can handle the current situation. And that’s why supply chains are broken, talent chains are broken, and most importantly, why they are empty.

All of this happened behind the scenes because no one was watching, no one was thinking about the future, and no one was doing a risk assessment or managing the risks that were destined to come. All despite the fact that natural disasters were on the rise, political tension was on the rise, and we were being warned that a pandemic was the top global risk for over a decade.

Now we are at a point where software alone won’t fix this, consultancies who don’t have talent either (despite telling you to go to China for two decades) won’t fix this, and hope won’t fix this. The only thing that will fix this is the re-introduction of supply chain apprenticeship programs, as noted by the Forbes article, along with the return of retirees with actual knowledge to mentor the new recruits, which is missed by the article. Most organizations, or consultancies, these days barely have enough talent to manage their own operations yet alone train a batch of new recruits on the side, especially if they didn’t live through the rise in global trade in the 80s and 90s. The retirees did, and they have the knowledge the consultancies, and modern systems, don’t. Along with new recruits, it is their (temporary) return that is needed to fix the supply chains.

Sourcing Success in these Turbulent Times Require Long Term Planning and Cost Concessions

This originally posted on January 2 (2024).  This is being reposted, in case you missed it, due to the rising criticality of Long Term Planning!

In a McKinsey article a few months back on How medium-size enterprises can better manage sources, McKinsey said that small and medium-size enterprises often struggle to find Procurement cost savings. Yet there are ways to do it while still pursing growth and providing a superior customer experience. The article, which concluded with an action plan for procurement cost savings, recommended:

  • establishing CoE teams
  • improving forecasting
  • expanding (the) use of digital procurement tools
  • gaining greater market intelligence
  • establishing a culture of — and process for — continuous cost improvement
  • incorporating supplier-driven product improvements

which, of course, are all great suggestions, and mostly address four of the five reasons that McKinsey give that prevent companies from reining in spending, which included

  • a lack of spending transparency (which would have to be corrected to improve forecasting)
  • talent gaps (which can be minimized with the right tools, market intelligence, and CoE teams)
  • underused digital tools and automation (which is directly addressed by using more of them)
  • exclusion of procurement and supply chain in business decision (which would hopefully be a byproduct of a corporate culture for continuous cost improvement that only happens when procurement and supply chain is not involved higher up)

but the fifth is largely unaddressed — the myopic focus on the short term which McKinsey claims could be addressed by putting more effort into planning and forecasting. But that doesn’t solve the problem.

Better forecasting will allow for longer contracts to be signed for higher volumes, which can lead to long term strategic supplier relationships, and better planning can allow this to happen, but this does not completely address the need for long term planning.

Supply Chains today are not the supply chains of the last ten to twenty years.

  • rare earths are even rarer
  • many critical raw materials are in increasingly limited or short supply
  • transportation can be unpredictable in availability and cost; even though most of the world declared COVID over in mid-2022, China still had mandatory lockdowns, ocean carriers scrapped many of their ships for insurance (and in some cases, post-panamax ships that had never made a single voyage), airlines furloughed too many pilots who found other jobs or just flat out retired, and the long-haul trucking in North America (the UK, and many first-world countries) has been on a steady decline for over a deacde
  • ESG/GHG/Carbon Requirements are escalating around the globe and you need to be in compliance (both in terms of reporting 1/2/3 and ensuring you don’t exceed any caps)
  • human/labour rights are escalating and you have to be able to trace compliance down to the source in some jurisdictions; you need suppliers who insist on the same visibility that you do
  • diversity is important not just to meet arbitrary requirements for government programs or arbitrary internal goals, but to ensure you have the right insight and expertise to solve all types of problems that might arise

And you can’t effectively address any of these problems unless you think long term AND accept that some of the solutions will cost more up front.

  • In mid November, the trading price for Neodymium (a rare-earth that is critical for the creation of strong permanent magnets, which makes it possible to miniaturize many electronic devices, including the [smart]phone you might be reading this on) was over $87,000 USD/mt. In comparison, hot roll steel was around $850 USD/mt. In other words, Neodymium was 100 times more expensive than steel. And while you can still buy steel for about the same price you could 10 years ago (it was around $900 USD/mt), Neodynmium is almost $20,000 more (as it was around $69,000 USD/mt in November 2013). It’s not the only rare earth to increase about 26% in 10 years, with further increases on the horizon. You need to have a strategy to minimize your need (which could include product redesigns that use more sustainable alternatives or recycling strategies that use recovered materials from older phone models). And when it comes to recycled materials, due to a historical lack of recycling efforts, or research into technologies to make recycling efficient and cost effective, recycled materials are almost always more expensive at first. Always. But as adoption increases, plants, technologies, and processes get more efficient, and the cost goes down (while, at the same time, raw material prices for materials in limited supply continue to go up). In other words, if you want to mitigate the ever-increasing costs for rare earths and other materials that are in limited supply, you have to incorporate the use of recycled materials, and maybe even invest in your own plants (and recycle your own phones you buy back because it’s cheaper just to buy them back and extract the rare earths yourself than buy the recycled rare earths from someone else).
  • Global trade is costly and unpredictable. Supply assurance is finally dictating near-sourcing and home-sourcing (which SI has been advocating for almost fifteen years, as inevitable disaster was the logical conclusion of outsourcing everything to China as eventually a pandemic, global spat, natural disaster, or other event would send shockwaves through the world when it severely disrupted the trade routes [because even though the chances of a pandemic, natural disaster on the scale of Krakatoa or the Valdivia earthquake, or another catastrophic event is minimal in any given year, over the course of a century, it becomes very likely]), and that is going to require re-investing in those Mexican factories (that worked just fine, by the way) you shut down twenty years ago, training appropriately skilled workers in low cost North American (or Eastern Europe) locales, and paying a bit more per unit (and even transportation until the carriers rebuild those routes). But in the long term, as global transportation costs continue to rise, and the local-ish resources get much more efficient (using the best technology we have to offer), your costs, and transportation risks, will go down while your competitor costs continue to go up.
  • if you don’t insist, and ensure, up front that your suppliers can report the data you need, how will you get it; chances are those suppliers need help and modern systems, which temporarily increase their operational costs as they install, integrate, and learn the systems; not more than a few cents here and there per unit, but a noticeable blip on the overall costs none-the-less
  • if you want suppliers that monitor their supply chain and insist on no slave/forced/child labour, appropriately treated and well paid labour, and, better yet, a community focus throughout the supply chain (so that the humans who mine the materials, harvest the food stuffs, weave the silk, or otherwise do the foundational work have a reasonable quality of life, health, and safety), you’re going to have to put the effort in to find them and the extra money to support them in their humanitarian efforts; since most of these workers in remote low-cost locales are paid pennies on your dollar, it’s another blip on the total cost to ensure they are paid every penny they deserve, but it’s still a blip; but you can’t afford not to do it if your jurisdiction has laws making you responsible for slave labour that later gets discovered in your supply chain
  • and while diversity shouldn’t cost more, since it’s the same number of employees, the reality is that the supply base embracing it could be a minority, and if these minority suppliers suddenly become in demand, market dynamics may kick in and they may charge a premium that your competitor will pay; but, as new challenges continue to arise, you will need the diversity to solve them; so, another blip in the cost you need to absorb

In other words, you need the long term focus to guarantee success, and you need to understand that, up front, it may cost a bit more. However, done right, your costs will decrease over time while your competitors’ costs skyrocket. So if you truly want success, in any high dollar, strategic, or emerging category, plan for the long term. And you will truly succeed.