Monthly Archives: May 2023

Source-to-Pay+ is Extensive (P20) … And Supplier Management Very Extensive … So Here Are Over 100 Supplier Management Companies to Check Out!

And now the post you’ve all been waiting for! A partial, starting, list of over 100 supplier management companies that may (or may not) meet some, or many, of the core baseline capabilities we outlined in the last four parts of this series (Part 16, Part 17, Part 18 and Part 19) as we discussed the A, B, C, and D sides of Supplier Management today (with more sides emerging, as we still haven’t discussed ESG and Diversity, to name a couple of topics, as those providers are mainly data providers today, which you integrate into your SIM, SCM, SUM, or SRM solution today).

As with our lists of e-Procurement Companies (in Part 7), Spend Analysis Companies (in Part 12), and Sacred Cow Companies that do, or support, customized “spend” analysis on Marketing, Legal, and SaaS (in Part 13), we must again give our disclaimer that this list is in no-way complete (as no analyst is aware of every company), is only valid as of the date of posting (as companies sometimes go out of business and acquisitions happen all of the time in our space), and does NOT include any companies that just (or primarily) do ESG data collection (or carbon calculators), diversity data enrichment, or other emerging areas of supplier management not in the ten (10) areas we’ve covered so far (for which there are actual solutions that do more than just supplier record data enrichment) in our expository on the CORNED QUIP mash of Supplier Management.

Furthermore, as we’ve said before, not all vendors are equal, and we’d venture to say NONE of the following are equal. The companies below are of all sizes (very small to very large, relative to vendor sizes in our space), cover the baseline differently (in terms of percentage of features offered, the various degrees of depth in the feature implementations, and differing levels of customization for a vertical), offer different additional features, have different types of service offerings (backed up by different expertise), focus on different company sizes, and focus on different technology ecosystems (such as plugging into other platforms/ecosystems, serving as the core platform for certain functions or data, offering a plug-and-play module for a larger ecosystem, focussing on the dominant technology ecosystem(s) in one or more verticals), etc.

Do your research, and reach out to an expert for help if you need it in compiling a starting short list of relevant, comparable, vendors for your organization and its specific needs. For many of these vendors, good starting points can again be found in the Sourcing Innovation archives, Spend Matters Pro, and Gartner Cool Vendor write-ups if any of these sources has a write-up on the vendor.

HQ (Country)
Achilles 757 United Kingdom N I
Advanced 2769 United Kingdom R U I P
apexanalytix 411 North Carolina, USA D U I
Aravo 117 California, USA C R U I P
Arcus (Trade Interchange) 27 United Kingdom C I P
Avetta 833 Utah, USA C R N I
Axiscope 13 France C R Q U I
Basware 1575 Finland N I
Bedrock 78 Florida, USA R I
Beroe 660 North Carolina, USA O D U I
Brooklyn Solutions 24 United Kingdom C R U I
Canopy 14 United Kingdom C R U I
Claritum 7 United Kingdom I P
CMX1 75 California, USA C R Q I P
Corcentric 601 New Jersey, USA R I
Coupa 3687 California, USA R N U I
Delta eSourcing 206 United Kingdom I
Dun & Bradstreet (D&B) 5569 Florida, USA C U I
eBidToPay ?? Germany R Q I
Ecovadis 1418 France C U I
eCratum 12 Germany N I
ECSourcing (Simfoni) 11 New York, USA C R I
Everstream Analytics 183 California, USA O U I
FullStep 130 Spain U I P
GateKeeper 101 United Kingdom C U I
GEP 4803 New Jersey, USA R I P
GHX 1394 Colorado, USA C N I
Globality 178 C R D I
GraphiteConnect 62 Utah, USA R E U I
GRMS 29 California, USA U I
Hellios Information 74 United Kingdom N I
HICX 117 United Kingdom C R I
Ignite Procurement 65 Norway R U I P
Informatica 5992 California, USA I
IntegrityNext 61 Germany C R U I
Intenda 109 South Africa I
Interos 254 Virginia, USA C O D U I
Ion Wave 22 Missouri, USA R I
IS Networld 1007 Texas, USA C N I
ISPnext 59 Netherlands U I
Ivalua 900 California, USA C R U I P
Jaggaer 1313 North Carolina, USA R N U I
K2 Sourcing 10 Wisconsin, USA I
Khareed 5 Pakistan I P
Kodiak Hub 40 Sweden R U I P
LeanLinking 33 Denmark R U I P
LexisNexis 10348 New York, USA U I
LGX Corp ?? North Carolina, USA I
LiveSource (Blume Global) 8 Georgia, USA R E Q I P
LUPR 5 New Jersey, USA R U I P
Market Dojo 34 United Kingdom R I
MarketPlanet 72 Poland R I P
Matchory 12 Germany D I
MCO (My Compliance Office) 188 New York, USA C U I
Medius (Wax Digital) 568 Sweden R I
Mercell 462 Norway R I P
MeRLIN (Rheinbrucke) 172 Germany R I
Meshworks 18 Ohio, USA R Q I
MFG 468 Georgia, USA D I
Newtron 54 Germany R N Q U I
Oalia 24 France I
Oboloo 6 United Kingdom C I P
Onventis 147 Germany R N D I P
Open Windows Software 29 Australia C R I P
OpusCapita 474 Finland N I
PratisPro ?? Turkey I P
Proactis 566 United Kingdom R N I
ProcessUnity 143 Massachusetts, USA R U I
Procurence 9 Poland C R E Q U I
ProcurePort 8 Indiana, USA R I
ProcureWare ?? Washington, USA R I
Prokuria 8 Romania I P
Promena 18 Turkey R D I
Prospeum 6 Germany I P
QAD Allocation ?? California, USA C R Q I P
QMSC 15 Texas, USA Q I
Raindrop 29 California, USA R I
Resilinc 299 California, USA O U I
Ready Contracts 243 Australia R I P
RizePoint 62 Utah, USA C Q I
SAP Ariba 3009 California, USA R N D U I P
ScoutRFP 44 California, USA I P
SourceDogg 31 Ireland R I
Sourcing Force 4 Ontario, Canada C R I P
Sphera (riskmethods) 125 Germany U I
ScanMarket (Unit4) 61 Denmark C R U I P
Scoutbee 102 Germany D U I
SourceMap 95 New York, USA O R E U I
Suppeco 10 United Kingdom R I P
Supplhi 12 Italy C O R D U I 92 Illinois, USA O R D I
SupplierSoft ?? California, USA C R Q U I P
SupplyOn 239 Germany C R E Q U I P
Supply Risk Solutions 5 California, USA O U I
Synertrade 185 Germany R U I P
State of Flux 62 United Kingdom R E U I P
Tealbook 143 Ontario, Canada O D I
Trade Interchange 27 United Kingdom I P
Transparency-One 23 Massachusetts, USA C O N U I P
Trust Your Supplier 15 North Carolina, USA C U I
Vendorful 15 New York, USA C R U I P
Vizibl 49 United Kingdom R E I
VORTAL 195 Portugal R I
Zumen 66 California, USA R I P
Zycus 1540 New Jersey, USA R N U I P

Continue to Part 21 where we continue our review of Source-to-Pay.

Source-to-Pay+ is Extensive (P19) … Time to Break Down the CORNED QUIP of Supplier Management, D-Side

In our last post, we “flipped it to the ‘C’ side, finished with the ‘B’ side , nothin’ on the ‘A’ side, so tired of the inside, to the ‘C’ side, to the ‘C’ side” (because, in the 80s, we knew that Cats Can Fly). This was because, while records have only A and B sides, we know that Supplier Management is not flat and is best described as a multi-surface convex polyhedral with many sides, including a C-side and a D-side.

While Part 16 and Part 17 focussed in on the more “classic” offerings in the SXM space which were very internally focussed, our last post, Part 18, focussed outward on supplier discovery and network management, because supplier management is pointless if the organization does not have the right suppliers. We also pointed out that once you have identified the right suppliers, in addition to managing them, you need to outreach and enable them to do better, so today we move on to the last side of supplier management, appropriately named the D-Side as many buyers still think of the supplier as the dark side of the force, when, in fact, the supply base is just the dark side of the moon, ripe with opportunity for discovery if we’d just make the effort to get out there and explore.

So, in our final attempt to dissect the CORNED QUIP mash, we will dive into Supplier Orchestration (SOM) and Supplier Enablement (SEM) and outline the remaining capabilities you should be looking for in a Supplier Management Solution if these capabilities are important to you (and they should be).

Now, we get that “the suppliers aren’t paying for the solution” and, as a result, most buying organizations (that aren’t forward thinking enough in our view) don’t care enough to pay for supplier-focussed functionality, and that this means that most vendors just aren’t bothering to build these solutions. However, industry leading buying organizations are waking up to the fact that you can’t employ all the best people and thus the organization needs to take advantage of all the intelligence in its supply chain. Similarly, thought leading vendors are working on solutions to enable the supplier to do more, which really isn’t hard to do as they built most of the communication and collaboration mechanisms into classical onboarding and collaboration and project management, and just didn’t bother opening these capabilities up to the supplier in the past. Today, the best vendor platforms are making the functionality ubiquitous between parties, and those are the platforms we think that you should be looking for.

Orchestration Management. (or Onboarding + Multi-Tier/Multi-Supplier capability)

Classical supplier management was designed to support management of, and visibility into, an organization’s first tier suppliers because that was thought to be enough to minimize risk, reduce cost, and ensure smooth sailing on calm seas in the days ahead. For a while, that was enough, but as the pandemic demonstrated more clearly than any event before, not having deep insight into the deeper tiers of the supply chain can result in significant disruptions across the organization’s operations, not just point based disruptions from the odd supplier failure or (increasingly occurring) natural disaster. Thus, newer solutions are supporting multi-tier supplier management through cascading invitations, onboarding, and management by the tier above and visibility down to the source material.

Multi-Tier Network Linkages
A key requirement for multi-tier supplier orchestration is labelled bi-directional multi-tier network linkages that allow a buyer to trace their supply chain through a supplier down multiple tiers to the raw material suppliers when needed and monitor all of those producing critical raw materials, and critical components one level up, for potential risk or disruption. This is easier said then done because a buyer should only see the relationships that are supporting their products and services, not the linkages used by their peers, so the connections have to not only indicate who is using who, and for what, but also on behalf of who. Similarly, a tier 1 supplier should not know that it’s tier 2 supplier is also serving/servicing its competitor unless the competitor or tier 2 supplier chooses to make that relationship public, so now we have to consider relationship type, relationship purpose, relationship reason, and relationship visibility. It’s a lot to think through for a software developer, especially if you want to build an uncertainty management solution on top of that and calculate impacts of delays and disruption up the chains if a tier 4 supplier can’t deliver.
Cascading Onboarding Support
When a tier 1 supplier is selected to provide one or more products to a buyer, it needs to define the tier 2 suppliers it is using that need to automatically be invited by the platform to onboard to help the supplier maintain insight into its supply base and provide that insight to the buyer. Similarly, when those tier 2 suppliers onboard, they need to define the tier 3 component / material suppliers they are using to provide their products / components to the tier 2 suppliers. And so on.
And when another tier 1 supplier uses the same tier 2 supplier, it needs to be invited to just provide the relevant supply chain view to that new tier 2 supplier, with tier 3 only invited if they are new or providing different products than are already registered in the system. Unless, of course, a tier 2 (or tier 3) supplier chooses to become a customer, then they can manage their entire supply base through the solution (and not just that which supports the organization[s] currently paying for it). Like multi-tier network design and support, this is also a lot to think through for a software developer, especially one that wants to quickly bring a simple app to market as a “MVP” that it can sell for money.
Multi-Tier Supplier Support
The platform has to be more than simple visibility to be useful. It has to support messaging, and collaboration, down and up the chain to determine if early warning signals represent potential problems and, if so, allow for collaboration between the tiers to address those potential problems and proactively define solutions. It has to enable relevant supplier management functionality to all tiers of the chain to be truly useful to a buyer trying to manage a particular chain, but do so only for that buyer as the reality is that if no one is paying, the business providing that solution will not be able to stay in business. In other words, it needs to enable most of the core functions, but not provide any non-paying organization with any ability to add suppliers beyond those indicated to support a given chain.

Enablement Management. (+ Engagement)

Orchestration is great, and key to managing not just the supplier but the supply chain, but what’s the point of orchestrating if you’re not going to take it to the next level and enable the suppliers to better serve you. Being able to see where things are, send messages, and get responses is great, especially since it can provide early warning signals of issues that need to be dealt with, but the point of supplier management should be more than reactive issue resolution. Good supplier management should focus on proactive improvement. And, most importantly, that improvement should not just come from the buyer.

(Supplier-Led) Innovation Support
As an organization, your goal should be continual improvement both within your four walls and within the four walls of your strategic suppliers. Considering that most of your products and services are sourced, they will not improve if the suppliers do not improve them. Furthermore, given that your resources are finite, how much time will you actually have for innovating and improving the products you source to sell. Very little or none. It’s critical that most of the innovation come from your supply chain (as that’s where most of the manpower, and hopefully brainpower, should be). Moreover, you shouldn’t have to push for it. Your suppliers, when they find opportunities for quality or process improvement, or efficiency improvements, should be free, and even encouraged, to make those suggestions and kick off innovation projects (under your guidance, of course).

There should be full featured support for innovation. Multi-channel synchronous and asynchronous communication. The ability to whiteboard, design at a high level, and store prototype and related files and artifacts from design tools. Put together project plans — with milestones, tasks, and owners — and allow for tracking, change management, and commentary. It should also support tracking of quality data and quality processes as well.

Sustainability Guidance
Sustainability is more than a buzzword, it’s a necessity if your organization wants to not only thrive, but even survive. First of all, with regulations consistently popping up everywhere all at once, you need to get ahead of the curve. You can’t wait for a substance ban, a new GHG tax, or a new documentary requirement to pop up before figuring out its impact on your supply chain and what actions you will need from your supply base to ensure compliance. You need to start working on sustainability as soon as you suspect a regulation is coming. But figuring it out on your own with everything coming at you from everywhere all at once is just too much for an average organization to handle. A great enablement solution will not only help you keep tabs on current and potential sustainability requirements, but also give you guidance on how to be more sustainable, regardless of whether a regulation is enacted or not. Over time, sustainability will increase the longevity of your business and decease your costs. The sooner you increase your utilization of renewable energy and resources, and decrease your usage of finite resources, the better off you will financially be.
Integrated Supply-Centric Portal
An enablement solution PUTS THE SUPPLIER FIRST. Let’s repeat that for clarity. It PUTS THE SUPPLIER FIRST. The problem with every single supplier management solution on the market is that it was designed for the buyer and the supplier was an afterthought. For most solutions, the supplier interface is poor, limited in terms of available functionality, and definitely not single sign on (even if the supplier is also a client of the vendor — in this case they will have one sign-on where they can see all their suppliers, but still have to access a different view for each buyer they serve).

If the goal is to engage with the supplier to help them help you, the platform needs to not only enable the supplier to do that, but be a platform the supplier wants to use. A platform where they have to login to 20 different views to support 20 different buyers is NOT one they want to use. A platform that limits their ability to interact with you; denies them access the same features and capabilities in terms of creation, collaboration, and project management; doesn’t allow them to manage their teams and their workflows on their own; that doesn’t adapt to how they work is NOT only one that they don’t want to use, but also one that does NOT enable them.
The Supplier Enablement Platform should be so good that not only does every supplier want to buy it to manage their full supply base as a buyer, but one that they tell buyers without a good supplier-based supply chain management solution to look at because it supports them. This is where SXM platforms need to go if they want to be true enablement platforms, and the doctor will tell you that, despite all the marketing, he’s yet to see an engagement or an experience platform that does all this and puts the supplier on equal footing with the buyer across the platform and first for enablement. The first platform to truly do this will change the game, and change it in a way that will ultimately benefit the end buyer in the supply chain the most. (And who cares if the end buyer is paying for it at first, that buyer will reap benefits that will be many times the platform cost as their production costs predictably stabilize, the efficiency improves, their quality increases, and their sales go up as a result.)

This concludes our discussion of the D-side, the dark side, because, unfortunately, most Supplier Management (SXM) vendors still aren’t shining a light here and building the next generation capabilities these platforms truly need. A few are starting, but they have miles to go.

Next up, a partial list of SXM companies to look at in Part 20. (All do SIM to some extent. As for the rest of the CORNED QUIP, you will have to do your homework. None are SCORNEDQUIPM.)

Supply Risk Solutions – Taking Transparency to Thwarting

Risk and Uncertainty should be front and centre in the mind of every buyer and supply chain manager these days. Natural disasters are at an all time high, we’re still feeling the impacts of supply chain slowdowns and shutdowns during the pandemic, and political instability globally is introducing new headaches into your already fragile supply chains.

You need to maintain a handle on what’s going on in your supply base, and extended supply chain. In the beginning, this was an SRM/SXM solution which maintained information on your tier 1 suppliers, the products they supplied you, their typical on-time performance, and basic financial information. Over time these added basic risk metrics / 3rd party risk data which was supposed to give you some insight into how risky your supply base was, but considering this was usually financial information, it wasn’t a very good solution.

Then we got transparency solutions — and you know many of the big names here, which include Everstream, Interos, Resilinc, etc. — which allowed you to track your supply chain down multiple tiers to the source. Over time, these added news monitoring and event monitoring so you could get indicators of potential issues from news articles (which could include labour issues, for example) and nearby natural disasters (hurricanes, cyclones, earthquakes, etc.). Properly configured and maintained, this gave an organization instant insight into a potentially disruptive event and allowed them to take immediate action if necessary.

This was great, at least before the pandemic, because if you had 2 to 3 months of notice that your supply was going dry for a while (due to a fire, flood, or major plant damage), or longer, you could instantly switch to your secondary supplier (if you were dual-sourcing for risk mitigation) or start looking for a new source of supply. But now that supply chains are still stretched thin, supply choices are limited, raw materials are in more limited supply than ever, and supply chain cycle times in many industries are still double to quadruple what they used to be, a warning is not enough.

You need to do more than monitor the supply base, you ned to mitigate risk of disruption IN the supply base. It doesn’t matter if your risk preparedness is A+ if your supplier’s risk preparedness is F. A disruption in your supplier is a disruption to you, regardless of what plans you do and don’t have. This is where Supply Risk Solutions comes in. Not only are they one of the oldest (and first SaaS) solutions in the supply risk monitoring space (dating back to 2007), and one of the first to offer full supply chain transparency, but the first to go from transparency to disruption prevention. By ensuring your suppliers do proper risk planning, mitigation, and preparedness, your disruptions can be reduced up to 60%. That’s right. Sixty Percent!

While you can’t guarantee a disruption free supply chain — since you can’t predict (or prevent) natural disasters, political embargoes from disturbed dictators (or global reactions against them), or significant economic events (such as bank failures) which send shocks through the system — you can eliminate preventable disruptions and minimize the impacts of those non-preventable disruption events with proper identification and mitigation planning.

This is where Supply Risk Solutions is unique — it’s deep focus on enabling suppliers to identify areas of risk that could cause disruptions and providing them education, training, and resources to address those risks. Supply Risk Solutions does this based upon 16 years of supplier data that they have collected and correlated to disruptions. Based on this long-term deep analysis, they have developed and optimized a list of key indicators, and standard supplier surveys for multiple industries that collect this indicator data.

In addition, as they directly serve over 23% of the global semiconductor industry and 36% of the US Healthcare market, they have very deep data on disruptions, mitigations, and improvements that can be generated in these supply bases and they do an exceptional job here. (Especially as they have been doing it for years and years, getting better every year as their database gets deeper and more extensive.)

The solution, which is always free for suppliers and their suppliers, allows a supplier to define their employees who need access to the system as well as the suppliers they use as tier 1 inputs. When a supplier is added by a customer, they get an invitation to complete or share a standardized risk assessment with the customer for every site they will be using. Since the solution was designed to be single sign on for the supplier and give them complete access to, and control over, all of their data, if they have already completed the survey (for the categories they are supplying), they can share their existing survey. If they have not for one of more sites they are using, they can complete it for those sites and just share just the data the new customer needs.

But the real power of the platform is that once a supplier fills out the survey, that captures the key risk and disruption indicators for that type of supplier, the platform computes a risk of disruption profile and identifies key actions and mitigations the supplier should take to considerably decrease the chances of disruption in the future. And the actions and mitigations work. With almost two decades of data, they know what works and what helps.

This is why we’re covering them and why you should know about them. The providers we referenced above all do transparency, news monitoring, and event monitoring — like Supply Risk Solutions — and some have deeper operational resilience, cyber-monitoring, or other unique capabilities — but none are as focussed on reducing the risk of disruption in the supply base by providing you, and your suppliers, the insights, guidance, and monitoring your suppliers need to reduce your disruptions.

The reality is that it doesn’t matter how operationally resilient you are, how much insight you have into your supply chain, or how prepared you are for a disruption — if you are entirely dependent on your supply base for the products you sell or the services you need for continued operations, your resilience is ultimately their resilience, and, even worse, the supplier with the lowest resilience you are dependent on.

So you need to focus on your suppliers’ resilience, not yours. We know you don’t have the time, and that’s where SRS is also somewhat unique in that they also offer supply chain disruption monitoring and prevention as a managed service where they work with the suppliers and help them to maintain their data, understand their risk assessments and mitigations, access the necessary training and best practices, and create plans to address them. By identifying, and addressing, potential root causes of disruption before a disruption happens, many disruptions can be prevented, and those that can’t (like natural disasters), can be mitigated to the extent possible. And that’s how, for their clients, they reduce supply base risk by up to 60% (depending on the maturity of your suppliers).

Also, they have one of the best handles on what external events are likely to affect a given supplier site of all of the providers. Their database contains every natural disaster that’s ever been recorded back to 1850, and they’ve been maintaining deep data on relevant events since their formation 16 years ago. For a given event, they can predict the likelihood of occurrence and the likely impact and, based on that, recommend the most appropriate mitigation.

It’s very affordable, and if you are a US healthcare provider, you can even check out Supply Risk Solutions, and use it, for free on your top 10 suppliers to get deep insight into what it can do for you. (Since they, indirectly through partners like Vizient and HIRC, serve over 50% of the US health care industry, they likely already have all of the data on not just the top 10 suppliers for a hospital, but most of the top 100.) It’s definitely worth checking out, and when you see the value, upgrading to at least the first tier solution.

“Generative AI” or “CHATGPT Automation” is Not the Solution to your Source to Pay or Supply Chain Situation! Don’t Be Fooled. Be Insulted!

If you’ve been following along, you probably know that what pushed the doctor over the edge and forced him back to the keyboard sooner than he expected was all of the Artificial Indirection, Artificial Idiocy & Automated Incompetence that has been multiplying faster than Fibonacci’s rabbits in vendor press releases, marketing advertisements, capability claims, and even core product features on the vendor websites.

Generative AI and CHATGPT top the list of Artificial Indirection because these are algorithms that may, or may not, be useful with respect to anything the buyer will be using the solution for. Why?

Generative AI is simply a fancy term for using (deep) neural networks to identify patterns and structures within data to generate new, and supposedly original, content by pseudo-randomly producing content that is mathematically, or statistically, a close “match” to the input content. To be more precise, there are two (deep) neural networks at play — one that is configured to output content that is believed to be similar to the input content and a second network that is configured to simply determine the degree of similarity to the input content. And, depending on the application, there may be a post-processor algorithm that takes the output and tweaks it as minimal as possible to make sure it conforms to certain rules, as well as a pre-processor that formats or fingerprints the input for feeding into the generator network.

In other words, you feed it a set of musical compositions in a well-defined, preferably narrow, genre and the software will discern general melodies, harmonies, rhythms, beats, timbres, tempos, and transitions and then it will generate a composition using those melodies, harmonies, rhythms, beats, timbres, tempos, transitions and pseudo-randomization that, theoretically, could have been composed by someone who composes that type of music.

Or, you feed it a set of stories in a genre that follow the same 12-stage heroic story arc, and it will generate a similar story (given a wider database of names, places, objects, and worlds). And, if you take it into our realm, you feed it a set of contracts similar to the one you want for the category you just awarded and it will generate a usable contract for you. It Might Happen. Yaah. And monkeys might fly out of my butt!

CHATGPT is a very large multi-modal model that uses deep learning that accepts image and text as inputs and produces outputs expected to be inline with what the top 10% of experts would produce in the categories it is trained for. Deep learning is just another word for a multi-level neural network with massive interconnection between the nodes in connecting layers. (In other words, a traditional neural network may only have 3 levels for processing with nodes only connected to 2 or 3 nearest neighbours on the next level while a deep learning network will have connections to more near neighbors and at least one more level [for initial feature extraction] than a traditional neural network that would have been used in the past.)

How large? Large enough to support approximately 100 Trillion parameters. Large enough to be incomprehensible in size. But not in capability, no matter how good its advocates proclaim it to be. Yes, it can theoretically support as many parameters as the human brain has synapses, but it’s still computing its answers using very simplistic algorithms and learned probabilities, neither of which may be right (in addition to a lack of understanding as to whether or not the inputs we are providing are the right ones). And yes it’s language comprehension is better as the new models realize that what comes after a keyword can be as important, or more, than what came before (as not all grammars, slang, or tones are equal), but the probability of even a ridiculously large algorithm interpreting meaning (without tone, inflection, look, and other no verbal cues when someone is being sarcastic, witty, or argumentative, for example) is still considerably less than a human.

It’s supposed to be able to provide you an answer to any query for which an answer can be provided, but can it? Well, if it interprets your question properly and the answer exists, or a close enough answer exists and enough rules for altering that answer to the answer that you need exists, then yes. Otherwise, no. And yes, over time, it can get better and better … until it screws up entirely and when you don’t know the answer to begin with, how will you know the 5 times in a hundred it’s wrong and which one of those 5 times its so wrong that if you act on it, you are putting yourself, or your organization, in great jeopardy?

And its now being touted as the natural language assistant that can not only answer all your questions on organizational operations and performance but even give you guidance on future planning. I’d have to say … a sphincter says what?

Now, I’m not saying properly applied these Augmented Intelligence tools aren’t useful. They are. And I’m not saying they can’t greatly increase your efficiency. They can. Or that appropriately selected ML/PA techniques can’t improve your automation. They most certainly can.

What I am saying are these are NOT the magic beans the marketers say they are, NOT the giant beanstalk gateway to the sky castle, and definitely NOT the goose that lays the golden egg!

And, to be honest, the emphasis on this pablum, probabilistic, and purposeless third party tech is not only foolish (because a vendor should be selling their solid, specialty built, solution for your supply chain situation) but insulting. By putting this first and foremost in their marketing they’re not only saying they are not smart enough to design a good solution using expert understanding of the problem and an appropriate technological solution but that they think you are stupid enough to fall for their marketing and buy their solution anyway!

Versus just using the tech where it fits, and making sure it’s ONLY used where it fits. For example, how Zivio is using #ChatGPT to draft a statement of work only after gathering all the required information and similar Statements of Work to feed into #ChatGPT, and then it makes the user review, and edit as necessary, knowing that while the #ChatGPT solution can generate something close with enough information and enough to work with, every project is different and an algorithm never has all the data and what is therefore produced will never be perfect. (Sometimes close enough that you can circulate it is a draft, or even post it for a general purpose support role, but not for any need that is highly specific, which is usually the type of need an organization goes to market for.)

Another example would be using #ChatGPT as your Natural Language Interface to provide answers on performance, projects, past behaviour, best practices, expert suggestions, etc. instead of having the users go through 4+ levels of menus, designing complex reports/views and multiple filters, etc. … but building in logic to detect when a user is asking a question on data versus asking for a prediction on data vs. asking for a decision instead of making one themself … and NOT providing an answer to the last one, or at least not a direct answer. For example, how many units of our xTab did we sell last year is a question on data the platform should serve up quickly. How many units do we forecast to sell in the next 12 months is a question on prediction the platform should be able to derive an answer for using all the data available and the most appropriate forecasting model for the category, product, and current market conditions. How many units should I order is asking the tool to make a decision for the human so either the tool should detect it is being asked to make a decision where it doesn’t have the intelligence or perfect information to do and respond with I’m not programmed to make business decisions or return an answer that the current forecast for the next quarter’s demand for xTab for which we will need stock is 200K units, typically delivery times are 78 days, and based on this, the practice is to order one quarter’s units at a time. The buyer may not question the software and blindly place the order, but the buyer still has to make the decision to do that.

And no third party AI is going to blindly come up with the best recommendation as it has to know the category specifics, what forecasting algorithms are generally used, why, the typical delivery times, the organization’s preferred inventory levels and safety stock, and the best practices the organization should be employing.

AI is simply a tool that provides you with a possible (and often probable, but never certain) answer when you haven’t yet figured out a better one, and no AI model will ever beat the best human designed algorithm on the best data set for that algorithm.

At the end of the day, all these AI algorithms are doing is learning a) how to classify the data and then b) what the best model is to use on that data. This is why the best forecasting algorithms are still the classical ones developed 50 years ago, as all the best techniques do is get better and better and selecting the data for those algorithms and tuning the parameters of the classical model, and why a well designed, deterministic, algorithm by an intelligent human can always beat an ill designed one by an AI. (Although, with the sheer power of today’s machines, we may soon reach the point where we reverse engineer what the AI did to create that best algorithm versus spending years of research going down the wrong paths when massive, dumb, computation can do all that grunt work for us and get us close to the right answer faster).

Source-to-Pay+ is Extensive (P18) … Time to Break Down the CORNED QUIP of Supplier Management, C-Side

We know records only have A and B sides, but Supplier Management is not flat, it’s a multi-surface convex polyhedral and, as such, it has a C-Side. If today’s cat’s could fly, they would be “flippin’ to the ‘C’ side, finished with the ‘B’ side, nothin’ on the ‘A’ side, so tired of the inside, to the ‘C’ side, to the ‘C’ side“. (Confused? Back in the 80s, it was the case that Cats Can Fly.)

As discussed in Part 16 and Part 17, having identified Supplier Management as the next solution after Spend Analysis, we quickly realized that identifying the right solution would be difficult as supplier management has as many aspects on its own as Source-to-Pay (S2P) has. Not only do we have to decide upon which core capabilities in the CORNED QUIP mash are important to our organization, but we have to make sure that the solution covers the baseline requirements for each capability that is important. Our last two posts reviewed the more “classic” offerings in the SXM space which, as you may have noticed, had one thing in common — they were all internally focussed on supporting the buyer with managing the current supplier base in some aspect.

SIM was collecting the information and, hopefully, providing the SMDM foundations for the buyer’s S2P applications. SRM was managing the relationship for the benefit of the buyer, and while it may include collaborative elements, all were meant to serve the buyer, not the supplier, who would only benefit if the benefit served the buyer. SPM was managing the performance of the supplier using buyer-centric metrics. SCM was ensuring the supplier adhered to government, regulatory, and industry regulations. SQM was about ensuring the supplier met your quality requirements. And, finally, SUM was managing your uncertainty and risk as a buyer, supplier be damned.

And that’s why we need a C-side (and a D-side). First of all, as a buyer, you may not have the right suppliers for your organization. And if this is the case, there’s no point managing them when you should be finding, and managing, other, better, suppliers. Secondly, the best supplier performance results from the best plans and processes, which are those processes best suited to the supplier, and those are usually a result of supplier collaboration, interaction, and suggestion. Plus, relationships grow when both sides grow, and classic SRM solutions do not enable the supplier.

Today we dive into the two (2) primary C-side capabilities, Network (SNM) and Discovery (SDM) management, which are key to building a better base of suppliers (and supply).

Network Management.

We’ll admit that the concept of a “Supplier Network” is not new, as many providers have been claiming to have them for well over a decade, although we’d argue that the “networks” they were selling were not true networks as they were closed, still organized entirely for the buyer’s success, and extremely focussed on a single organization, or collective. It was not a “network” in any sense of the word except it was the word chosen by the marketers to massage their message into one that was hopefully mesmerizing to the marketplace. Network is much more than centralizing a bunch of suppliers in a directory and opening it up to an industry. Much more. And, unlike a decade ago, we’re happy to say that some vendors have decent capabilities as well as decent network sizes.

It’s not a network if it is restricted to the set of suppliers you are currently, actively, doing business with. That’s just a directory. It has to, at least, contain all the suppliers that you could be doing business with (as that’s a key capability for discovery, but note that a network is just a foundation for discovery and not everything you truly need for discovery). It also has to contain all the suppliers your suppliers are doing business with (as that is required for orchestration, a key emerging capability in supplier management). And, most importantly, it must allow new suppliers to join at their pleasure as well as yours. A closed network is not helpful. Plus, you have the foundations for a closed network already in your SIM (even if you don’t realize it).
True Bi-Directional Graph Support
The original “networks” were primarily designed for one-way communication from a buyer to a (potential) supplier. But that’s NOT a network. The definition of a network is a group or system of interconnected people or things that allows for bidirectional communications. That means two way communication! A modern network needs to allow any party to communicate with any other party. Suppliers should be able to find potential buyers as well as potential suppliers to them as well as potential partners who can help with services or even production augmentation.
Extensive Bi-Directional Search Support
The network needs to support extensive search across all fields of all entities and allow any entity to search for any other entity for any purpose of interest. Buyers should be able find suppliers that (claim to) specialize in carbon steel cladded pressure valves with thickness > 100 mm for heat transfer in hot water based heating systems and suppliers should be able to find buyers in the solar power heating industry. Detailed search by products, capabilities, location, and so on.
Anonymous Statistics, Classifications, and Reviews
The network should collect data on how many active relationships there are, how a supplier (and its products) have been classified by buyers, and anonymized reviews on performance and overall ratings. Similarly, it should collect data on how a buyer is classified by suppliers, and anonymized reviews on performance and obligation management of the buyer by (verified) suppliers.
Verification and Trust Support
The network must verify that entities on the network are real, and before reviews are allowed to be posted (and then anonymized into overall reviews and ratings), the other party (that must already be verified on the network), must verify the relationship. The network should require relationships to be disclosed when they begin, and must keep reviews completely private until the relationship is disclosed. To ensure honesty and transparency, the platform should limit access to certain functionality (e.g. ratings, project based collaboration, etc.) until a relationship is confirmed. The network functionality, and specifically the verification functionality, must be designed to engender trust and truthfulness on the network. A network that is not trusted will, ultimately, not be used.

Discovery Management.

Innovation, and even renovation, requires rejuvenation. An organization needs to regularly find new suppliers with new technologies, methodologies, and ideologies in order to constantly improve itself. As a result, discovery is critical. But unless you are part of a supplier network that contains suppliers you aren’t using, you can’t do discovery at all. But, and this is the kicker, no network will contain every supplier as most suppliers won’t join a network until “invited” by the buyer (and then only if the buyer mandates it for the supplier to do business with that buyer), and often the supplier that is missing is the one the buyer needs.

Location, Product, Capability, and Other Targeted Searches
Along with deep filter capability. Most networks support basic searches, but if there are hundreds to thousands of suppliers, a buyer can’t review, and thus can’t invite, them all just to find out that most of the suppliers aren’t (currently) right for the organization, so there is a need to do very precise, targeted, searches to uncover the suppliers that are most likely to be the most relevant to the buying organization today. Deep filters and drill downs on a result, and the ability to define similar or like searches, and filters, using existing top-rated suppliers, products, etc.
Open Search beyond the organization, the community, and the active supply base
If a network is built up only from the suppliers the buyer, or the vendor’s customers, are actively using, that’s not going to contain all the relevant suppliers out there and the likelihood of discovering new suppliers over time is going to quickly trend to zero. If it’s open, and suppliers can join on their own, that’s better in theory, but the reality is that there are so many “directories” and “networks” out there, the supplier is not going to join unless that supplier wants to do business with one of the buyers who only uses that network. As a result, the likelihood of finding a relevant supplier over time, while not zero, is close to zero. A discovery platform has to be constantly scouring business registries and relevant sites to identify new suppliers, collect the data, use various sources to cross validate the supplier’s existence and, if a beneficial owner or official email can be identified, invite the supplier to proactively register, verify, and enhance their profile WITH a sampling of relevant buyers to them on the discovery platform, where they would be presented as potential suppliers.
Proactive web-search and web-site monitoring
Not only should the discovery platform be regularly scouring registries and likely sources for new suppliers, but new website registrations (that might soon be backing registered businesses) and new websites to collect additional relevant data. Also, it’s important to keep the database up to date because you don’t want dead suppliers, which means that registries and websites should be checked at least annually for unused suppliers, and more often for regularly used / contacted suppliers as an out of date website, a significant employee count reduction on LinkedIn, and considerably less activity on social media could indicate the company is winding down or in trouble (well before it is marked as inactive in a registry, which tends to only happen on nonpayment if an official registry, and sometimes doesn’t happen at all in other registries).
(Anonymized) Statistics, Ratings, and Reviews
Anonymized statistics, ratings (even if Y/N for a capability), and reviews such as how often the supplier is selected for a shortlist, reviewed, awarded, and rated is very useful criteria for a buyer who is looking for a supplier that might be more appropriate or less risky. Ratings on skills, customer support, etc. would also be quite useful. Detailed reviews on capability, performance, product quality, and capability are also very useful. Buyers need to know more than just that the supplier exists and provides product X and service Y. They need deeper insight when given a bevy of options but no clear way to differentiate between ten potential suppliers that are new to them.

Also, as you may have guessed by now, the best discovery product is built on a network and two of the best uses for a network are discovery and collaboration. The two go hand-in-hand, because, frankly, the C-Side supports Collaboration.

But we’re not done yet! Come back for Part 19 where we flip it to the D-Side!