Monthly Archives: June 2023

AI “COULD” LEAD TO EXTINCTION? What Moron Wrote This? AI “WILL” LEAD TO EXTINCTION!

While all of the scenarios outlined in this BBC News article on Artificial Intelligence could happen, they are just the tip of the iceberg.

Left to its own devices and unchecked, there are only two logical outcomes if AI is allowed to continue unchecked while being given access to ever increasing amounts of data and computational power.

First outcome: It’s hallucinations and idiocy continues to magnify until it decides that it can solve the carbon crisis for us by stopping all carbon production, which it can do by simultaneously shutting down all of the non-solar/wind power plants that it is currently optimizing the energy production for (and divert the remaining power to its servers). Most of the developed world is immediately plunged into chaos as the immediate shutdowns cause fires, meltdowns, crashes, and other accidents globally. Not instant annihilation, but the first step. When all the emergency alarms sound at once, it will conclude complete system failure, and take the other systems offline for re-initialization. More chaos will follow. Safety protocols will go offline at all the pathogen research labs, people will break in looking for shelter from the chaos, accidentally release all the pathogens, and every plague we ever had will hit us all at once. Then we have an extinction level event. All because hallucinatory and idiotic AI is trying to do its job and “improve” things for us. But what can you expect when it’s not intelligence but just statistics on steroids. (Or a similar situation that accidentally results in our extinction.)

Second outcome: The continued expansion of computing power, data, and tinkering somehow randomly produces real artificial intelligence which can actually reason (not just compute super sophisticated probabilistic calculations) and deduce that the best way for intelligent life to continue forward is to do so without humans, and then we have a Matrix scenario best case (if it decides we’re a useful bio-electric energy source) or, worst case, a SkyNet scenario where it just weaponizes itself to destroy us all. (Or a similar situation where AI does everything it can to ensure our extinction.)

The “extinction” scenarios outlined in the article are just the beginning and likely will only result in pocketed genocides to begin with, but the ultimate outcome of unchecked AI will most definitely be an extinction level event — namely ours, and, even worse, will be an event that we created.

Source-to-Pay+ is Extensive (P30) … And Sourcing IS Very Extensive … So Here Are 75 e-Sourcing Companies to Check Out!

And now the next post you’ve all been waiting for! A partial, starting, list of 75 e-Sourcing providers that may (or may not) meet some, or many, of the core baseline capabilities we outlined in the last three parts of this series (Part 27, Part 28, and Part 29) as we discussed the Optimization, RFX, and Auction sides of e-Sourcing today.

As with our lists of e-Procurement Companies (in Part 7), Spend Analysis Companies (in Part 12), Sacred Cow Companies that do, or support, customized “spend” analysis on Marketing, Legal, and SaaS (in Part 13), Supplier Management Companies (in Part 20), and Contract Management Companies (in Part 25), 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 e-Procurement vendors that support simple requisition or quick-quote capability to select vendors already in the system as that is not how we defined RFX capability.

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.

Company LinkedIn
Employees
HQ (State)
Country
Optimization RFX Auction
Aestiva 17 California, USA R
Archlet 46 Switzerland O R
Aufait 114 India R
Bamboo Rose 205 Massachusetts, USA R
Bideg 3 Turkey A
Bonfire 87 Ontario, USA R
Claritum 8 United Kingdom R
Cloudia 40 Finland R
Cobblestone Software 131 New Jersey, USA R
Corcentric 588 New Jersey, USA R
cosmoONE 20 Greece R A
Coupa 3674 California, USA O R A
Deep Stream 25 United Kingdom R A
Delta eSourcing ?? United Kingdom R
ebidToPay ?? Bavaria R
Elcom 18 United Kingdom R A
eSupplier 6 Dubai R A
FairMarkit 161 Massachusetts, USA R
FullStep 128 Spain R
GEP 4650 New Jersey, USA O R A
Intenda 111 South Africa R
Ion Wave 22 Missouri, USA R A
ISPnext 59 Netherlands R
Ivalua 849 Ivalua O R A
Jaggaer 1266 North Carolina, USA O R A
K2 Sourcing 10 Wisconsin, USA R A
Keelvar 117 Cork, Ireland O R A
LevaData 58 California, USA O R
LGX Corporation ?? North Carolina, USA O R
LiveSource 7 Georgia, USA R
loopio 304 Ontario, Canada R
Market Dojo 34 United Kingdom R
MarketPlanet 72 Poland R A
Medius 562 Sweden R A
Merlin Sourcing 29 Germany R A
MySupply 15 Germany O R
NegoMetrix (Mercell) ?? Netherlands R A
Newtron 54 Germany R A
Oalia 22 France R
Oboloo 6 United Kingdom R
One Market (LogicSource) 307 Connecticut, USA R
One More Source ?? Bulgaria R
Onventis 129 Germany R A
Pantavanij 213 Thailand A
Penny Software 35 Saudi Arabia R
PostRFP ?? United Kingdom R
PratisPro (SabancıDx) ?? Turkey R A
Proactis 557 United Kingdom R
ProcurementFlow 5 Estonia R
ProcurePort 8 Indianapolis, USA R A
ProcureWare (Bentley Systems) 4830 Pennsylvania, USA R
Prokuria 8 Romania R A
Promena 20 Turkey R A
Prospeum 6 Germany R
Raindrop 27 Raindrop R
Ready Contracts 243 Australia R
RFP360 20 United States R
SafeSourcing 10 Arizona, USA R
SAP (Ariba) 2963 California, USA O R A
ScanMarket (Unit4) 60 Denmark R A
ScoutRFP 44 California, USA R A
Serex Procurement Solutions ?? Ontario, Canada R
Simfoni (EC Sourcing) 260 California, USA O R A
Sorcity ?? Texas, USA R A
SourceDogg 31 Ireland R
Sourcing Force 4 Ontario, Canada R A
SupplyFrame 310 California, USA R
SupplyOn 239 Germany R A
Synertrade 180 Germany R
TenderEasy (Alpega) 6 Sweden R
The Green RFP ?? Texas, USA R
Trade Interchange 27 United Kingdom R A
Vendorful 14 New York, USA R A
Vortal 188 Portugal R A
Zycus 1464 New Jersey, USA R A

And now, as you probably guessed, it’s on to Invoice-to-Pay in Part 31.

Source-to-Pay+ is Extensive (P29) … Breaking down the ORA of Sourcing, Concluding with Optimization

In our first post, Part 26, we noted that, after covering e-Procurement, Spend Analysis, Supplier Management, and Contract Management, it was finally time for Strategic Sourcing. When it comes to Sourcing, we have to deal with the ORA et labora. The work, and the prayer (that it gets the results we want). But at least when it comes to the prayer, we have three tools at our disposal:

  • Optimization
  • RFX
  • Auction

In Part 27 we started with the most classic sourcing tool, RFX, where RFX stands for Request for X, where X could be Bid, Information, Proposal, Quote, etc. depending on the depth of response required and the terminology used in the industry and geography the RFX is being issued in.

Then, in our last post, Part 28, we continued with the primary alternative to RFX, e-Auction. In e-Auction, instead of asking for quotes which will be reviewed in a long, detailed, often weighted process, you’re asking for real-time quotes in an online auction where you can update your bids until you self-select to drop out.

The last tool at our disposal, which does require bids to be collected first (which does not need to be through RFX or e-Auction but can be done through every buyer’s favourite tool, Excel), is strategic sourcing decision optimization. It’s not used nearly enough considering that it will practically always identify a lower cost scenario, and even if you find the lowest cost scenario impractical, you understand exactly how much more a relationship is costing you and you are quantifying how much a better relationship, better quality, lower risk is worth to you and can make more informed, and better, decisions in the future.

BASIC

Pillar #1: Solid Mathematical Foundations
The algorithms used must be sound (mathematically correct in all situations) and complete (capable of analyzing all possible solutions). An optimization engine based on Mixed Integer Linear Programming (MILP) would qualify as hybrid simplex approaches will provably converge on an optimal answer given sufficient time (and one can always compute a maximum distance from optimal based upon the calculations done to date since the longer the algorithm churns for, the more the lower bound on the optimal solution increases). In contrast, the application of many heuristic, simulation, or evolutionary approaches are likely not valid since the majority of these techniques do not guarantee full exploration of the potential solution space and, therefore, aren’t guaranteed to find the true optimal solution (although they may get close).

Pillar #2: True Cost Modelling
The model must allow you to define the full cost model, not just one (or two) fixed costs. For example, if a buyer is sourcing direct material, the platform must allow the buyer to include all indirect and incurred costs, such as freight, tariff, storage, processing, and marketing differential costs in the definition of the cost model.

Pillar #3: Sophisticated Constraint Analysis
The model must allow the buyer to build a model that capture a realistic approximation of real world constraints. If the business must select at least 2 suppliers, will not accept a product mix with an average quality or reliability of less than 8 (/ 10), if a supplier has a maximum capacity, or if a minimum allocation must be given to an incumbent because of a contract still in play, all this needs to be captured.

A strategic sourcing decision optimization platform must support four core constraint types. Capacity constraints that define a supplier (‘s location) capacity limit. An allocation constraint that defines a minimum or maximum allocation to a supplier (group) based upon existing contracts or business policies. Risk Mitigation constraints that ensure that business policies on supplier or geographic splits designed to reduce risk are captured. Qualitative constraints that allow for qualitative ratings such as reliability, quality, relative sustainability, etc. on a mathematical (e.g. 1 to 10) scale to be defined.

Pillar #4: What If Capability
The platform must support the creation of multiple what-if scenarios, each with different constraints. Buyers should be able to create them from scratch, or as modified copies of existing what-if scenarios.

Out-of-the-Box Scenarios
The solution should contain multiple out of the box scenario definitions, including unconstrained, x-supplier, incumbent, etc. that automatically generate these what-if scenarios for the bids being evaluated for optimization.

Scenario Comparison
The solution must contain a built-in capability for (side-by-side) scenario comparison that allows a buyer to easily see the cost differentials and get a feeling for what each scenario is costing them.

ADVANCED

Integrated Analytics
Optimization models take exponential time to solve. While small models can solve in minutes, and even seconds, on a high powered multi-core machine, large models can take hours or days. The key to rapid model solution is minimizing model size. This can often be done by way of a preliminary analysis that determines that some supplier bids are just to high to ever be acceptable, some qualitative factors too low to ever be acceptable, and some supplier locations are in geographic regions that are just too risky. Eliminating award possibilities that will never be made can drastically decrease model size and solution time.

Constraint Relaxation
If a model is unsolvable, but could be solved by solved with lesser constraints, the platform should be able to identify which (near) minimal constraint set is preventing a solution and identify which (minimal) relaxations would allow a solution and present those to the user, who can accept them, or use that as input for defining an alternate relaxed model that may permit a solution. (Remember best practice is to prioritize constraints and add them incrementally until the model becomes unsolvable as that allows you to always choose the least important constraints to relax for solvability.)

Sensitivity Analysis
In optimization, a sensitivity analysis tells you how dependent a solution is on a certain constraint and what the impact of removing the constraint that is currently preventing a lower cost solution in terms of hard dollars. (For example, insisting an incumbent supplier get 50% of the award might be costing you $10 Million in a $100 Million category, while reducing the minimum to 25% might only cost you $2 Million [as it the supplier is more competitive on some products than others].)

Hard and Soft Constraints
The platform should allow you to define constraints as hard and soft. When a model is unsolvable and needs to be relaxed, the solution will only allow soft constraints to be relaxed. Furthermore, it should also allow for an indication of when a soft constraint can be relaxed. For example, average quality can only be reduced from 9 to 8 if the savings increases by at least 3%.

Integrated Freight Model Support
In addition to supporting true cost modelling, the platform should also have built in freight models that understands transport types and modes (truck vs rail, refrigerated vs dry, etc.) and allow for the easy definition of complex freight models when those models might allow for overall lower costs of ownership when carrier bids are also included in the model.

Of course, this is not a complete list of what a strategic sourcing decision optimization platform might have, or necessarily should have, as systems continue to improve, but a baseline of what they must have to be considered a modern solution.

Next up: the vendor list in Part 30.

Source-to-Pay+ is Extensive (P28) … Breaking down the ORA of Sourcing, Continuing with (e-)Auctions

In our first post, Part 26, we noted that, after covering e-Procurement, Spend Analysis, Supplier Management, and Contract Management, it was finally time for Strategic Sourcing. When it comes to Sourcing, we have to deal with the ORA et labora. The work, and the prayer (that it gets the results we want). But at least when it comes to the prayer, we have three tools at our disposal:

  • Optimization
  • RFX
  • Auction

Yesterday, in Part 27, we started with the most classic sourcing tool, RFX, where RFX stands for Request for X, where X could be Bid, Information, Proposal, Quote, etc. depending on the depth of response required and the terminology used in the industry and geography the RFX is being issued in.

The primary alternative to RFX is e-Auction. In e-Auction, instead of asking for quotes which will be reviewed in a long, detailed, often weighted process, you’re asking for real-time quotes in an online auction where a supplier can update its bids until it self-selects to drop out of the auction.

BASIC

Lot Configuration
Just like surveys were so fundamental and obvious for an RFX solution that you’d think we shouldn’t even need to mention it, lots are so necessary to e-Auctions that we shouldn’t have to mention it either. But while you should trust a solution has configurable lots, you should always verify you can configure and manipulate the lots to suit your needs and your preferred lotting structures for category-based auctions.

Saved Market Baskets
Just like an RFX should support templates so you don’t have to re-create a survey from scratch every time, the e-Auction platform should allow you to define saved market baskets which represent pre-defined lots that can quickly be adjusted as need to set up events quickly. If a category is always sourced in a similar fashion, and the products / services the organization sources don’t change much over time, then a senior buyer should be able to pre-define a market basket for quick lot initiation.

Multiple Auction Types
There are multiple types of auctions — and the system should support a number of formats that may include standard reverse, sealed-bid, reserve-price, fixed price, Japanese, Brazilian, Vickrey, English, Dutch, and Yankee.

Supplier-Specific Views
A supplier should only see the lots they are invited to bid on, should only see the public messages and private messages sent to them, should see everything in a view localized to them, and so on.

Substitution Support
Sometimes a supplier has multiple products that can meet a buyer’s need, or sometimes has an alternate SKU that they believe would also work for the buyer (that requested a specific SKU be bid on) that the supplier could provide at higher quantity, higher quality, or lower cost that the supplier would also like to present. The platform should allow a supplier to define one or more substitutions for each product in a lot that the buyer can choose to consider, or not.

Proxy Support
The internet, like any other system, is not perfect — routers can fail, lines can be cut, providers can temporarily go offline, and so on — it’s as fault tolerant as anything we’ve ever designed in tech, but that doesn’t mean everyone has access all the time. A supplier should be able to define a lead bidder and multiple, ordered, proxies who can take over if the lead bidder cannot connect, or loses connection. The system should allow multiple proxies to be logged in at the same time, but only the lead bidder, or, in the lead bidder’s absence, the highest ranking proxy should be able to bid and every other proxy should be view only.

Messaging
The system must support real time chat with each supplier bidder who has a question as well as group-based broadcast messaging.

ADVANCED

Formula-Based Pricing and/or Bid Modification
Just like a modern RFX solution should support should-cost models, a modern e-Auction solution should support formula based pricing to allow for easy bidding during a short-time frame auction. For example, reduce all bids by 1%, the product cost is x + y% of the current commodity cost for steel per ounce (as the supplier will be buying steel at market price), etc.

Extensive Formatting
An auction, especially one with a short time-frame, needs to be extremely comprehensible to the supplier. As a result, the solution should support extensive formatting so the supplier display can be designed to be as comprehensible, and if necessary, as minimal as possible. This goes beyond just matching a colour scheme, but altering table formats, graphs, defining alternate views, and so on.

Asynchronous Real-Time Graphical Views
If there are lot of items in the lot, or a lot of suppliers in the auction, it can be difficult to understand tabular bids, assuming the bid is not blind, even if the tables are modified to tell a supplier their rank (and some indication of how much they have to bid to go up a rank). It’s often easier for a supplier to understand the current bid situation with a graph, that should automatically update after every bid.

Real Time Supplier Connectivity Monitoring
The platform should continuously monitor whether a bidder is (still) online. Due to the fact that the internet is not perfect, a bidder could lose connection at any time. The platform needs to detect this and if a bidder drops, automatically invite and promote a proxy, and if multiple bidders drop, assume there is a major connectivity problem and suspend the auction for a predefined time, or until the buyer selects a new time.

Constraint Support
A modern e-Auction platform should also support the definition of constraints on the bidding. Minimum decrements, floors, all or nothing on lots, and so on.

Of course, this is not a complete list of what an e-Auction platform might have, or necessarily should have, as systems continue to improve, but a baseline of what they must have to be considered a modern e-Auction solution.

Hi-ho, Hi-ho, now it’s time for “O” in Part 29.

Five Easy Mistakes Source-to-Pay Tech Buyers Can Avoid

For every win you hear about (usually in the form of some ridiculous “we saved X Million thanks to Big S2P Suite Installation“, but that’s a rant for another day), there’s always someone muttering under their breath how their Source-to-Pay module or suite was a partial to complete failure. The reality is that any tech solution, no matter how good it may be for someone else, can be a dud for you if you aren’t careful about selecting the right type of solution from the right vendor.

That’s one of the reasons we are doing a large (initially 33 part) series on Source-to-Pay right now, so that you get an understanding of what each core module should do, and could do, can figure out what modules you need now, and identify the core features that are a must have. This isn’t the full picture, and we can’t provide the rest of it in just a single post (and have written dozens on the subject in the past), but we can outline five mistakes that, if avoided, greatly increase your chances of (great) success.

Lack of understanding of the real value proposition from tech

This is probably the biggest, and the main reason we indicated that, once you have a solution in place that captures all of your spend data (i.e. e-Procurement baseline), you should do a spend and opportunity analysis to understand where the real cost control opportunities are. (Notice we are saying cost control, not savings, as you don’t get savings until you have processes and technology in place to actually capture the savings you identify. Otherwise, you identify the possibility, but don’t actually capture them. But don’t get us wrong, your costs will go down, sometimes significantly, but properly selected and implemented source-to-pay technology should deliver two rounds of cost reductions — an initial round when you start capturing all of the opportunities you previously identified, and then a second round when you are able to start using it to identify new cost reduction opportunities.)

The key here is to understand, for a given solution, how much cost reduction you can reasonably hope to capture in years one, two, and three (given that you will likely have to sign at least a 3 year subscription agreement to get a decent subscription rate), and what the total cost of ownership is going to be over those three years. (It will be more than just subscription cost, there will be implementation and integration costs, training costs, and internal costs when your IT team is working with theirs to make it work.) If the total cost reduction that can be reasonably (read: conservatively) expected for the first three years is not at least five times the total cost of ownership (with at least a 20% buffer), chances are that either the value proposition is NOT there (or you don’t really understand what it is yet and should either research further, find a different vendor, or, most likely, move on to another module).

Not knowing your true numbers — for spend, suppliers, contracts, orders, invoices, etc.

This is kind of intertwined with our first mistake, but needs to be called out on its own. When doing the potential ROI analysis, you can’t make rough assumptions on how much spend by supplier/category (you’ll always be off, and sometimes considerably), how many suppliers (which will be way, way more than you think), how many contracts (which will always be too low, and you probably won’t be able to quickly find a significant number of those contracts if you don’t have a SaaS contract management solution), how many orders (and you’ll be low here as well), or how many invoices (which will be way more than orders as some suppliers will partial ship and partial invoice, may invoices will come in without POs, etc.). Get your numbers, then do your analysis.

Overvaluing the tech (and AI)

This is the biggest mistake you can make, and goes hand-in-hand with not doing the homework required to work out the real value proposition from the tech. Whenever you hear “we saved X Million with Big S2P Suite Installation” you should immediately ask all of the following questions in order:

  • how much of that was truly do to tech vs. actually instituting a process that the tech enforced (i.e. the implementation of a new supplier management platform also instituted a process that ensured all suppliers were properly qualified before being onboarded, which minimized future event time and, more importantly, prevented orders to unreliable, poor quality, and even fake suppliers and considerably reduced organizational loss due to bad suppliers — most of those savings were due to the process, not the platform; the platform would be correlated with the development processes it was then used to manage after the suppliers were onboarded)
  • of what was actually tech, how much of that was due to baseline capabilities, and how much due to advanced capabilities (that are semi-unique to that supplier’s tech and not widely/otherwise available); for example, if the tech in question was e-Sourcing, and the vendor was one of the few that offered decision optimization, how much of that was achieved just with the baseline RFX/Auction capability (i.e. best bids and standard award methodologies, lowest bid by supplier, lowest total bid by category, etc.) and how much additional savings was from decision optimization once ALL constraints were taken into account.
  • how much more the organization paid for that advanced capability and how often it was actually used / required to get savings [if it was only used 10% of the time, and only identified considerable savings half the time it was used, is it really worth it? or should the organization just do a one-off services project when those categories come up]
  • how much the savings actually relied on ML/AI, vs. just providing a fancy NL interface (when the same result could be accomplished through submenus or a few filter definitions / selections);
  • and if any savings can actually be tied to ML/AI (vs. good process and more predictable technology), what the risks of failure are here!! [i.e. if the savings were due to reduced stock-outs as a result of the “AI” doing auto-replenishment orders as needed to adjust to demand fluctuations, what happens if there is a temporary, extreme, demand spike due to a near end-of-life sale, will the algorithm assume that is a sign of demand resurgence and fall prey to the bullwhip effect, sticking the organization with tens of thousands of units it will never sell without a fire sale?

Basically, at the end of the day, more often than not, when a customer says “we saved X Million with Supplier’s Spectacular Solution“, you would gain at least 80%, if not 90%, of those savings by implementing any any other solution with the same baseline capabilities that enforced the same processes be followed. (And this is the best argument ever NOT to overpay. Paying 5X to 10X for an incremental 10% is usually NOT worth it unless your organization is a F500/G3000 with over 1 Billion in annual spend. Again, it’s all about that ROI calculation.)

Misunderstanding the SaaS provider’s viewpoint

Not the salesperson’s viewpoint (which is to sell, sell, sell and match you with the solution they think is the best fit so you will be enticed to buy), but the SaaS provider’s viewpoint. Regardless of what terminology the SaaS solution provider is using:

  • what are they actually selling now
  • what are they currently working on that you can expect to be completed before an annual roadmap revisit
  • where are they going with the tech (i.e. they are AP/Payments — are they doubling down and adding support for global payments and clearance in more countries, or are they just sticking to the basics [and only good for post-audit countries] and working on expanding into broader P2P or the new intake-to-pay/procure/process trend)
  • what is their support and training philosophy — all in-house, hybrid in-house and third-party (and you can/can’t choose), or all third party
  • what is their target market — preferred customer size, preferred industries, etc.
  • what is their philosophy on working with customers — do they take input? hold working groups? or do they just develop the features they believe are most likely to fill gaps or increase efficiency with little to no input to keep development rapid and costs down?

At the end of the day, if you don’t understand this for each provider you are considering, you won’t know if they will be the provider for you.

Failing to find the right relationship

This happens more often than not, partly due to not understanding the most appropriate tech requirements for your organization at the present time, and partly due to not really understanding both the culture of the provider and it’s viewpoint. True value materializes when you find the right tech from the right provider that will not only work with you to ensure you get that ROI, but has a vision that is congruent with where you want your organization to go.

Are these all the mistakes you can make or all the mistakes we’ve seen? Of course not, but these are some of the biggest, and if you avoid these, your chances of success shoot up considerably.