Source-to-Pay+ is Extensive (P31) … Time for Invoice-to-Pay

When we started in Part 1, we noted that even though all core sourcing and procurement technologies have been available for twenty (20) years (although it is debatable just how good the initial versions of many of these applications were) … the majority of organizations still do not have what any modern analyst would consider reasonable support for the full, core, source-to-pay process.

However, now that inflation is back with a vengeance, anticipated savings is leaking faster than a bald spigot, and most organizations are in a cash crunch as a result of down sales during the pandemic (and now due to a lack of core inventory to sell), they need to update their procurement tech stack fast.

But, and this is the kicker, they can’t do it all at once. We went into a lot of the details as to why, but, basically:

  • the applications don’t work without data … and don’t work well without LOTS of data … clean, organized, enriched data … (that you don’t have now and won’t have for a while)
  • the applications don’t deliver without user training …
  • you need value out of the gate to justify the purchase … and good luck getting enough value to justify the license cost of an entire suite!
  • your users need to see results for them to adopt … and use … a solution long term

So, you need to figure out where to start. And after three posts, we figured it out — e-Procurement. We then spent a few posts discussing the need for e-Procurement, the benefits, the barriers to e-Procurement (which were not what you think), and providing you with a large list of vendors. But then we had to step back and figure out what came next again because, depending on the particular situation at hand, there were good arguments for contract management, spend analysis, strategic sourcing, and supplier management (but not invoice-to-pay). It took quite a bit of analysis, and the answer was spend analysis because, even if all things seemed equal, or one solution looked more attractive than another, spend analysis could identify the (biggest) opportunities and the solution best suited to the most / biggest opportunities, and so spend analysis always made the most sense to adopt after e-Procurement.

After that, it was difficult. But, if all opportunities are equal, or there is no one to do the thorough spend analysis that can help differentiate the savings opportunities that can be enabled by each S2P module, there still has to be a best choice for what’s next. And that was … Supplier Management. The reason? Just like you needed to get your spend data captured for everything to function (which is what e-Procurement does), no matter what you’re doing, you’re interacting with suppliers, so you need to manage them effectively.

Then it was easier. Even though you technically need to find the products and services before you contract for them, the reality is that you are already buying products and services, you already have contracts, and chances are you can’t find most of those contracts when you need them, don’t know what the obligations and deliverables are for anything that’s not available through the e-Pro catalog, and don’t even know the pricing, permitted price escalations, etc. Furthermore, most organizations without a modern CLM don’t know how many evergreen contracts they have, when they automatically renew if not terminated or renegotiated by that date, when key contracts they need are expiring, and so on. Nor do they understand just how much excess manual effort and time the organization is taking to re-negotiate existing or negotiate new contracts. They are also completely unable to do a proper analysis of existing payment terms, key risk clauses that are required for a new regulation, and so on.

Contract Management may not identify any big opportunities, but without a good, enforceable, contract that can be easily monitored throughout its lifetime, the reality is that the identified savings will likely never materialize. Thus, Contract Management was key to have in place before you started strategically sourcing, as you want to immediately turn the bids into contract terms before the process disconnect from not having a good CLM solution causes bids to be retracted “because they were only good for 15 days” or some other excuse a supplier will come up with to not honour a bid. And then it was time for e-Sourcing, the ora et labora of the savings-focussed part of the Source-to-Pay process, and the ORA in particular: Optimization, RFX, and e-Auctions.

And now that we’ve finally covered all the core upstream modules, and e-Procurement, there’s just one left, the one that comes after e-Procurement and the one we skipped because it’s relative value was limited compared to the other solutions (when you consider that any e-Procurement solution worth its price can accept and store invoices and do some minimalistic processing). This isn’t to say there isn’t value in the solution, as a good I2P solution will greatly increase invoice-processing and payment-related efficiency, reduce the manpower needed for 100% invoice verification, and enable financing and global trade. Furthermore, a great I2P solution will also enable other value-generation capabilities the organization wouldn’t have otherwise. In fact, over time, it will become one of the more valuable solutions since one analysis, sourcing, supplier management, and contract management take the waste out of the process and your organization becomes a Source-to-Pay leader, the key to maintaining S2P value will be efficiency and 100% capture and compliance. That’s why no Source-to-Pay implementation is complete without a modern invoice-to-pay/accounts payable module, and why you must implement it even if the initial estimated ROI is considerably less than the other solutions.

But what should you look for? And why? That’s the subject of our next part where we’ll break down the core in Part 32.

A Critical Sixth Mistake Most Tech Buyers Make — in Source-to-Pay and Beyond!

To infinity and beyond isn’t just the goal of Buzz Lightyear, it’s also an accurate description of how often tech buyers make this critical mistake. And what is this critical mistake?

Not negotiating an easy, full, self-serve, cost-free, 100% DATA OUT clause in the contract — and forcing the supplier to prove it works one third (or one half) of the way into the agreement.

Sure, buyers always ask “can we get our data out if we choose not to renew” and sure suppliers always say “of course you can get a full data dump“, but the supplier rep is always going to say yes after the developers say it’s possible (but that doesn’t mean it’s encoded in the product, and more often than not with older platforms it requires the tech team to do the data dump — which might be more difficult and take a lot longer than they expect because they are using a shared database, have data and files split across multiple databases / servers, or they can only extract data a few files / tables at a time — and it might even come at a huge cost for their time), even if it’s really not. (It’s not just whether or not the development team can extract the data, it’s whether or not they can do so in some sort of standard format that would allow you to at least load it into a standard database or file storage system.)

The most important thing to remember is that even if a solution is the perfect fit for you now, it does not mean it will be the perfect fir for you next year, and by the time renewal comes up, due to changing organizational needs, changing provider directions, or a combination of the two, it may no longer be appropriate at all. Should this happen, you need to be able to migrate to a new solution quickly and easily, and this will require being able to extract all of your data from the current platform, self-serve, in a standard format that you can then push into a new platform as soon as that new platform is identified.

The only way to ensure this is to insist on a clause in the contract along the lines of the following:

The platform will contain a self-serve feature that will allow a buyer administrator to export any and/or all data in _____-format (e.g. XML, flat-file) in accordance with standard _____ (e.g. cXML, SQL) in a format that will allow the data to be immediately loaded into _____ (e.g. SAP, mySQL) application by executing a single load control-file/script. Attachments, if not stored in the database, should be capable of being downloaded in a (multi-)part ZIP file, with names and relative directory paths matching any indexes in the database directory files. If still in development, this capability must be fully implemented before one third [or one half] of the subscription term has expired.

Furthermore, on or before YYYY-MMM-DD, the supplier will walk the buyer administrator through a test of the export process wherein the buyer will self-serve export all of the data and then load it into a test instance of the indicated backup system. Should the test fail, the supplier will be subject to a monthly subscription penalty of X% a month until the functionality is complete and the test succeeds. Should the functionality not be finished by the time two thirds [three quarters] of the subscription term has expired, the supplier will be subject to a monthly subscription penalty of 2X% a month (as the buyer will have to invest in manual effort to recreate critical data in backup systems).

Any supplier that objects to the first part of the clause is likely NOT one that you want to be considering as most modern platforms support full data import and export through APIs and are built on the principles of data sharing. Furthermore, if the platform still doesn’t support export in a standard format, but claims they are working on it, you should expect most of the capability within a year if the platform really is serious about joining the modern data sharing club (and, thus, should not balk too much at the second part of the clause if they truly are serious as it should only take a few months to figure out a good export module for even a large schema).

Depending on how much data you produce, and how much manual effort it would be to manually recreate a copy of the data you can’t extract, X=20% would not be unreasonable in our view.

Finally, note that this requirement not only protects you in the situation where the platform isn’t right for you, but also increases the chance the platform will be right for you, as a platform that supports open data integration can usually be augmented with ease if you need additional functionality in the future, but don’t necessarily need a whole new platform as the current platform still does what it was purchased to do just fine.

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 some 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.

Finally, a second reminder that inclusion on this list DOES NOT imply Sourcing Innovation is recommending 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.