We Know You Should Have A Lot Of Global Trade Data …

As per our last post, if you want to design and run a relatively smooth running supply chain, you need a lot of data. As per our post, at a minimum:

  • product compositions
  • supplier locations
  • route details
  • alternate products, suppliers, and routes
  • sanctions
  • denied parties
  • tariffs, export and import
  • taxes and recoverables
  • carbon/GHG
  • commodity market and product cost data
  • currency conversions and trends
  • natural disaster risks
  • man-made disaster data
  • consumer and market sentiment data

Which leaves you with two major problems.

  1. where do you get it?
  2. how do you manage it?

There are two choices on where to get it:

  1. data consolidators and brokers
  2. government / public sector sources

As much as possible, you want to rely on option b), because, in this AI-HYPE filled world, data is now the most valuable commodity, the data brokers know it, and even when they are getting it from a government / public source (for free) and then processing it for your consumption, they are charging a premium for it. A subscription to even a fraction of the above data could cost you more than the annual SaaS subscriptions you are feeding it into (not counting your AI token costs which are going to continue to increase without bound if you are unnecessarily relying on AI for tasks you do not, and should not, be using Gen-AI LLMs for).

So you want to use the cheap/free government and public sources as much as possible. While this sounds easy enough, every single source will be in a different format, with different access requirements, different update frequencies, and different levels of completeness. We’re talking about everything from Excel files to real-time json requests, with multiple types of authorizations, access protocols, and transport protocols.

This bring us to the second issue — how do you manage it?

You basically need a DIY data orchestration platform. And the reality is, the majority of today’s orchestration providers, despite their grand claims, don’t really do that! Out-of-the-box, you can only integrate solutions they have already integrated with, and only import any data they have previously mapped. Plus, they are limited in intake to what they have designed for. Most of them aren’t even as powerful as last generation data mapping frameworks that allowed a data analyst to integrate all of the data from various sources into one common, central, database. (Now, it typically involved creating yet another data warehouse / lake / lakehouse.)

What you need is a next-gen supply chain orchestration platform that was built from the ground up to allow you to plug, play, and orchestrate data sources as well as workflows and applications using pre-defined mappings, Web 3.0 Markup, standard terminology, and statistical AI (with known confidence) that will auto-map as much as possible, minimize what can’t be auto-mapped, and generate additional data objects and tables for storage where your systems aren’t already handling that type of data.

A next generation system that also incorporates auto-mapping, auto-schema-extension, and auto-data-orchestration alongside workflow construction and third party system integration using APIs, MCP, and other integration technologies along with all of the common authorization protocols. A fully dynamic data platform that can serve as the core of a next generation SCP platform. One that is a level beyond the majority of platforms calling them orchestration platforms today,

And, finally, one that understands how to organize, federate, and classify data for true analysis.

But that’s another post!

How Much Global Trade Data Should You Have?

As per our recent series on supply chain stability, and the need for visibility and audits, you need a lot of supply chain data. On your products, suppliers, and routes. As well as their products, suppliers, and routes. Down to the source.

But is that all you need — just suppliers, products, and routes down to the source?

Well, as per our previous series, you also need detailed data on alternate locations and other product offerings from your suppliers, alternate suppliers and their alternate product offerings, alternate routes, and alternate carriers that service them.

But that’s not enough.

Product existence is not availability, and availability is not obtainability. You also need to know if the countries, parties, or connected parties (owners) are sanctioned and if they use restricted or banned substances in their products or operations. If so, you can’t do business with them … and spending hours, days, weeks or months evaluating them just to figure that out when you try to order the first shipment.

But even if there are no sanctions or official roadblocks, it still might not be possible to acquire the goods you want from certain suppliers due to export and import tariffs. That means you need to know any export tariffs and import tariffs that will be applied, in the export country, import country, and any intermediate countries (that may not have [usable] FTZs).

Also, since some goods and services will be acquired, change hands, or used in the source countries, you also have to be aware of all the country, state, and municipal taxes that you will need to pay, as well as any taxes you can potentially reclaim.

This means we’re up to:

  • product compositions
  • supplier locations
  • route details
  • alternate products, suppliers, and routes
  • sanctions
  • denied parties
  • tariffs, export and import
  • taxes and recoverables

Is that all?

Well, in some countries you have to be cognizant of carbon/GHG production, so you need to be able to track how much carbon is produced in the production of each unit and be able to report that when needed, as well as control that if the country the good is being produced in, or sold in, has a carbon quota or carbon tax.

And it sounds like we’re nearing completion, but not really.

We left out cost data. If you have to find alternate products or suppliers, you really want to understand your costs. And not just market costs, should costs. Which means you should be tracking, when possible, raw commodity costs, component and part costs that allow you to estimate production costs on top of input costs, and currency exchanges, that allow you to build reasonable should cost models.

And while this might be enough to make perfect sourcing plans, we all know plans rarely turn into reality. So having the data to build the perfect hypothetical supply chain is a great start, but only in theory. In practicality, you need to know how realistic the supply chain is.

This means you need relevant supply line related data as well. Transport times, and risk of spoilage and theft are critical. As is natural disaster risk data related to storms (hurricanes, tsunamis, [fire] tornados), the possibility of floods, wildfires, blizzards; and earthquakes (or volcanic eruptions) in areas where they are common. You need to track this data to judge the potential reliability of supply chains.

Now we’ve added:

  • carbon/GHG
  • commodity market and product cost data
  • currency conversions and trends
  • natural disaster risks

While you think this may be everything, we’re sad to say that while it’s close, it’s not.

It’s not just natural disasters that matter, it’s man-made disasters. Mines collapsing, factories burning down, and unexpected supplier and carrier bankruptcies can also bring down your supply chains. So you need real-time event data.

Furthermore, while it won’t bring down supply chains, it can greatly vary demand and being aware of consumer sentiment, including mass displeasure and (potential) boycotts. If you’re selling consumables or creating high-priced electronics with a limited shelf-life, you don’t want to overproduce. And if there are indications of a demand surge, you want to be prepared so you don’t have costly stock-outs that could result in unhappy customers.

That’s quite a lot of data. And that’s a minimum.

When Was The Last Time You Did A Full Audit Of Your Supply Chain!

When a single event puts over 25T of global trade in jeopardy, or about 20% of Global GDP, you know you need a full end-to-end understanding of your critical supply chain.

The event I’m talking about is the 2026 US-Iran War that saw the Strait of Hormuz closed.

1. Global trade in goods and services is about 35% in US Dollars.
2. 80% to 90% of all traded goods move by ship through canals, straits, seas, and oceans.
3. About 8% of maritime trade by volume passes through the Strait of Hormuz.

Do the math, and it’s easy to see that the blockage / closure of the Strait puts over 25T of global trade in jeopardy, because wars in the Middle East tend to drag out for years!

The world was not ready for this. (They thought the US would never risk a war with Iran because of that … especially when the US could have continued last year’s strategy of just bombing uranium enrichment sites once per year as they neared completion and prevented Iran from ever reaching nuclear potential that way.)

Most company’s supply chains were even less ready — especially since some sectors saw way more than 20% impact, especially when it’s (one of) the largest trade route(s) for certain products like LNG (20%+/-), (crude) oil/petroleum (25%+/-), fertilizers (33%+/-), and sulfurs (50%+/-). Multi-national businesses without alternate sources or routes at their immediate disposal were put in instant financial jeopardy (and risk of bankruptcy)

As a result, you need more than supply chain visibility, you need full end-to-end supply chain awareness for all critical product lines, and that requires a full audit. You need to know where everything is coming from, what routes it’s taking to get to you, what alternatives exist (and to what extent — can you replace all, part or none), and what financial impact its disappearance would entail.

Even if you can get it at a reasonable price, supply chain insurance isn’t going to be enough anymore. As with any insurance, there will be exclusions for war, terrorism, etc. unless you pay astronomical prices, conflict zones will be excluded, and when a disaster wipes out an area and affects many clients at once, payouts won’t be quick and you can expect a massive amount of paperwork and effort will be required to get one (as the insurer won’t have enough cash on hand and will have to delay and delay until they can liquidate assets, which is difficult to do in crashing markets that result from economic disasters).

When something happens, you need to be able to react, reroute, and reorder quick. That will require not only deep visibility, but pre-defined mitigation plans when key regions, routes, or resources are impacted. The only way you will know this is if you do a full audit and associate each product to (sub-tier) suppliers, locations, countries/zones, and routes. That way, when a critical event (is likely to) happen(s), you can immediately identify the affected parties, locations, routes and associated products, and determine what you need to do in order to ensure continued supply. It might be switching plants, distribution routes and methods, or even suppliers.

If you haven’t done a supply chain audit in a few years, or ever, you should do one ASAP. You don’t want to be caught off guard when the next major disruption happens!

Why it’s just easier to do your job in the Age of AI

Every year articles make the rounds on how to do nothing at work or look busy to either slack off or keep your annoying cow-orkers away so you don’t end up having to do their work too. Now, a few in 2006 really annoyed me and I decided to point out how stupid they all were by selecting one in particular and pointing out just how stupid it was because it was harder and more work to follow the advice then to just do your job for your 35 hours a week you had to work.

But I’m not here to tackle another inane article about how to slack off or avoid responsibility, because hopefully by now you’re not dumb enough not to fall for it, especially since smart managers (and workforce monitoring solutions) aren’t either.

I’m here to tell you why it’s just easier to do your job in the age of AI than to try to use AI to do it for you.

1. You’ll have to tell the AI what you want at least 3 times. Maybe 10. Or More.

Gen-AI LLMs should be called Artificial Idiocy. There’s nothing intelligent about them. They don’t understand anything. It’s all a Grand Illusion. Automated puppet-theatre … and we’re the suckers born every minute for using it.

As a result, they produce a lot of good sounding text that sounds close to what you need, but upon further review, always misses one or more key points of your request … until you repeat it and rephrase it ten times ten different ways and your strive to perfection slowly reduces to anything acceptable whatsoever.

2. You’ll still have to edit the final outputs and execute the work in the tools it can’t drive because they don’t have the APIs for the LLM to execute.

So, after spending hours trying to get it to output the perfect report and process, you have to go edit, finish, and execute that process. Spending as much time as if you just skipped the AI in the first place.

3. You have to deal with the consequences of the errors you miss.

If you’re using a modern Procurement system which is AI-first and allows external AI to drive it, a request to “restock the supply room at the lowest cost” can result in ten times the amount of printer ink, paper, pens, and cleaning solvent you go through in a year because it hit a volume break at the production plant and skipped the intermediate supplier, ignoring the fact that you have to rent a warehouse for the truckloads of cleaning solvent you just ordered for your office building (even though you only use one floor — it assumed you wanted enough for the twenty story office building).

You’ve spent too much, have no room for the inventory, and have to explain to your boss why ordering years worth of office supplies was a good idea.

4. You have to explain the AI bill that was five fold what you planned.

While also explaining that it was your idea, not the AI’s, to screw everything up.

It’s always easier, and less risky, to use your Human Intelligence, and not the AI, to get your job done.

So, You Didn’t Succession Plan — What Do You Do Now?

Back when SI first started talking about talent in year one, we noted that the most important thing you need to do is succession plan — because even if you do everything right, acquire and keep the right talent, and thrive … it will all come to an end when the talent gets lured away, retires, or dies (and it does happen).

You see, if you succession planned, you would have done a number of things that, frankly, you should have started 20 years ago (if you were in business then), or the year you started (if you weren’t).

1. Captured their knowledge from day one

You would have acquired a KMS (Knowledge Management System) and started capturing their knowledge from day one. Even if it’s not directly tied to the systems they use, you’d at least be capturing key knowledge that your junior people don’t have.

2. Captured key artifacts from day one

Furthermore, as time went on, you’d acquire systems for all of their major tasks and ensure that all of the key steps were done online in those systems. No bypasses allowed. Sure, how they made the decisions would be in their head, at least to the extent it’s not captured in the KMS, but all the steps, and artifacts would be there for whomever comes next.

3. Identified at least one internal successor for each critical resource and have that individual mentored by the critical resource ASAP

So that, even if the potential successor isn’t ready for a senior role when the critical resource is no longer available, at least you’ll have retained some of the knowledge, some of the artifacts, and some of the capability. And if you can find a suitable replacement externally quickly, that person will be much more effective as they’ll have a capable right hand resource, artifacts, and knowledge.

But you didn’t do any of this. So what do you do?

Well, first take Wouk’s advice and get it out of your system:

When in danger or in doubt,
Run in circles, scream and shout

Second, identify and acquire a suitable successor as soon as possible, even though it could be costly. You need someone suitable who’s ready, not half ready.

Third, you need to acquire the expertise and systems to jump start the replacement.

  1. Get a KMS ASAP. Don’t make the same mistake again.
  2. Acquire systems that will be used to automate key functions, as well as capture, store, and index all the key artifacts for quick look up that are needed to execute them — no disconnected email, documents on various cloud drives and untracked laptops, or other haphazard solutions.
  3. Hire expert consultants who are former practitioners to help populate that KMS with key knowledge and execution systems with templates and as much process knowledge as those systems can hold.

You’ll still have a rough time sailing choppy seas … but you might not sink if you start on the right track now. No guarantees, but it’s likely your only chance. The Age of AI Hype has proven dumb systems and inexperienced kids can’t do the jobs of senior talent, and since you forced so much of that talent into early retirement with your AI BS, you’re in trouble if you can’t retain a few grey hairs and start training the next generations to take over now.