Category Archives: SaaS

What is Spend Orchestration?

Spend Orchestration is all the rage. But what exactly is it?

Well, as we tried to point out in Demystifying the Marketing Madness for you, where we said it meant we don’t do anything different than all the other orchestration providers, but it sure sounds cool!, Spend Orchestration is essentially:

Clueless for the popular kids.

It’s a coming-of-age comedy where you have a slick looking, popular, over-funded new-age SaaS platform from fresh-out-of-college (dropouts) who want to do “good deeds” for the Procurement space by giving your Procurement department a “makeover” that connects all of your applications together so you can “manage your spend” and match stakeholders with the procurement professionals that can meet their needs (as the platforms try to justify their existence).

Upon implementation of the spend orchestration, there will be one fiasco, hardship, and falling out after another as you realize the platform doesn’t do anything if you don’t have core Procurement platforms for sourcing, supplier management, analytics, contract management, procurement, and invoice management/accounts payable … otherwise, it’s just intake to nowhere and orchestrating faster push and pull from your incomplete, outdated ERP/MRP. Also, without good platforms in place, it will just make it easier for the stakeholders to admonish you on a daily basis when your Procurement process doesn’t actually pick up the pace or perform more preferably. And you will be more jealous of your peers that skipped the orchestration platform and went straight for the S2P or P2P platform that actually solves some of your Procurement problems.

Now, eventually you will acquire the missing pieces (or these orchestration platforms will build basic functionality) and you will kiss and make up at a big fat Procurement Wedding like ISM or DPW, where they invite you on an all expenses paid trip to participate in their prestigious Power Procurement panel, but it will be a very rocky road on the way.

Our suggestion is that if a company comes knocking with “spend orchestration“, you tell them thanks and no thanks and save the comedy hijinks for the big screen. If you do need orchestration — which you won’t know for sure until after you’ve consolidated your applications, determined which are not easy to direct connect (due to a lack of [Open] APIs), which don’t allow easy access across the organization, and where orchestration might actually help — you want to get that orchestration from a company that has grown up, not one just starting it’s teenage high-school journey!

Orchestration Won’t Solve a Reckless Runaway SaaS Proliferation Problem!

In a recent LinkedIn Post, THE REVELATOR asked Why you need an Internal and External Metaprise Strategy for optimal Intake and Orchestration capability? and noted that:

  • Most large enterprises use between 10-25 procurement software platforms, with some complex organizations exceeding 25. Just for Procurement!
  • A 2022 study by Forrester Consulting found that large enterprises use an average of 367 software applications and systems.
  • A 2023 report by Zylo found that large organizations deploy an average of 660 Software as a Service (SaaS) applications.

Moreover, the doctor has seen stats:

  • as high as 87 individual SaaS products in a single department in larger orgs
  • exceeding 40 for Marketing or Sales … when you can’t find more than a half dozen apps that actually do something significantly different

All the doctor can say to this is that if the number of platforms you are using numbers is in the three digits, you don’t need orchestration, you need consolidation!

For example, Marketing and Sales is all lead generation/management and customer prediction/funnel/CRM. With no coherent strategy (beyond maybe SalesForce for CRM), every employee or team will purchase their own set of Apps and the organization will have 5 to 10 apps that more or less do the same thing with 90% overlap. And similar situations abound throughout the organization.

So yes, these organizations need a strategy, and that strategy should be to centralize app decision and management in each department to prevent unnecessary app sprawl. After all, each app you orchestrate costs you even more money than the app subscription cost (as the orchestration app will charge you based on the number of integrations, and how many of those it supports out of the box), which ends up ballooning your overspend to integrate apps you shouldn’t be using in the first place.

Which means that the first thing these organizations need is a SaaS App Optimization platform that can crawl their SaaS purchase and usage data, identify what’s used, identify more-or-less duplicate apps, and identify which app should be consolidated upon based on usage. This will not only reduce costs by over 30% once the unnecessary apps can be dropped (at the end of the current license or payment cycle), but increase productivity (as [cross functional] teams work in the same app ecosystem).

Moreover, this is just the tip of the overspend iceberg. Once the first round of consolidation is done, these organizations need to tackle SKU sprawl in their enterprise platforms, and their ERP, Cloud Host, and Back-Office Systems in particular where the common vendor strategy is to offer “bigger discounts” when the client purchases packages that contain modules they don’t need or more seats than they will actually use, which, even with the bigger discount percentage off of list price, are still designed to cost the organization more than they should be spending. To do this, they will need to use a vendor, like Green Cabbage that we recently reviewed, that are experts in enterprise software system purchases and know how to unbundle these consolidations and get you insight into market pricing on a SKU basis for hard-nosed fact-based negotiations.

Only once the organization’s platforms have been consolidated and optimized should the organization embark heavily into orchestration, as this is the only way to ensure they don’t do unnecessary work or pay unnecessary costs.

Put Your Research in the Forefront with Forestreet!

Forestreet is a dichotomy and a juxtaposition in that it is a relatively new entrant to the ProcureTechSphere, as it only launched its platform in late 2022, but a relatively old company as it was founded in 2017 to super power supplier and market research for sourcing and category management professionals.

Like many recent supplier discovery startups (which have been quickly stood up on third party Gen AI, and which could fall just as quickly), as well as category management consultancies, the founders realized almost a decade ago that one of the things that was really holding sourcing professionals back was a lack of market knowledge when they had to source a new category, replace a supplier, or understand the market impact of a regulation or incident and set out to build a platform to make that happen (not knowing how much effort would be required to do it right). This is especially true when the sourcing and category management professionals are being constantly bombarded with marketing spiel and no real product or service insights.

This is the product they have been working on for the past eight years. An advanced technology platform that scours the web, in near real time, and brings back all of the information a human needs to make a good decision on category selection for a market event based on the current supplier landscape, supplier selection for inclusion in a market event, and even basic market entry based upon current market and supplier information.

It works extremely well and enables a human to do the research that used to take them weeks in a couple of hours and make good, market informed, decisions while finding suppliers and insights they never would have otherwise. Moreover, since the foundations were developed pre Gen-AI, the core is built on solid, tried-and-true, hallucination-free, technology that includes traditional AI and machine learning, a deep knowledge graph, and verifier technology (as it does use Gen-AI to identify potentially relevant sites, articles and sources, but then verifies every site, article, and source returned is valid and parses the content using tried-and-true tech for better indexing and cross-correlation [based on the knowledge graph]). The founders, who believe that AI is the most overused and most misused term in technology (and it is), know that the path to success depends on identifying the right advanced technology (or algorithm) for each problem encountered, the right technology may or may not be AI, and it’s ultimately not about the technology but the solution it enables. They know that a sourcing professional needs to have a research superpower and their goal is to give you one, using whatever technology is appropriate. (You shouldn’t care about “AI”. You should care about results!)

Let’s talk about the main part of the application today, and what improvements (currently in development/alpha) are slated for next quarter. (More great things will likely materialize later in the year, but SI only covers what it has seen).

Market Explorer (Today)

Market explorer is designed to give you enough domain expertise in 30 to 120 minutes, depending on how deep you need to go, to identify if there is a market (opportunity), who the main suppliers are, and what the primary issues are that you need to be aware of. To start, all you need to do is either provide a sample company (website) or define a category and a geography. In the first case, if you provide a sample company (website URL), it will identify the potential markets and geographies and allow you to refine your search criteria to industry (s) (roles), locations, and keywords, all of which will have auto-suggestions but all of which can be overridden. In the second case, you just define the category by keywords and, optionally, provide a geography of interest.

Once you confirm your market, it will go off and scour the web and in three to five minutes bring back all of the companies it can find with profiles on each. It will preload at least the first page of each website, and pre-load additional pages as soon as you access the supplier so you can click through the supplier’s site through the Forestreet platform. You can then select each supplier of interest, and then it will alter its market intelligence overview of the market accordingly based on your selection. The tool is designed to allow you to quickly scan through 60 to 80 suppliers in 20 minutes, build a reasonable starting set (for further research), and quickly hone in on the right market and supply base. Once that is done, depending on the complexity, it will take the user 30 minutes to a few hours to identify the right pool of suppliers for an RFP or the right elements for a customized market intelligence report to the C-Suite. (This effort, when you think about the amount of time these tasks take now, is nothing. Your effort has been reduced by weeks to part of a morning or afternoon.)

Currently, the market intelligence overview gives you a market size estimate, top company list, company segmentation by revenue range, geographic distribution, mosaic breakdown by primary offering, feature map, emerging topic list, related news and ESG overview (with correlated ESG articles indexed separately). From the overview, you can click into a feature analysis, explore phrases relative to the market, dive into the news archive or the ESG view, or dive into a profile of each returned supplier.

Forestreet built their own custom ESG model across 25 sub-categories and scores the market (and, if possible, each supplier) across that model, using available data and sentiment (that is often the best generic score you can find). In the ESG view, you see the average positive or negative for each major score, the relevant articles, and can dive into individual factors and sources and company groups.

With regards to the company profiles the system builds for you, it pulls back basic profile data like name, location, contact information, revenue, market bracket, a brief overview, and a momentum score against the market based on market overage. It will also pull legal information and identifiers (incorporation dates, status, key personnel, etc.), a summary of key features and services, associated news and events (that contribute to the larger market archive), the ESG rating and a listing of its primary competitors based on the market data.

In addition, it can output the entire market report, or just selected portions, to a PDF presentation for your management presentation.

And, if after the first pass you want to dive into a subset of the market, alter the criteria, and/or retrieve more information on a subset of suppliers, you can make the necessary alterations to your request, run it again, and in another 15 to 20 minutes you’ll have more refined information. Many professionals get what they need after the second try, and if not, it’s the same 15 to 20 minutes to run it a third time. Even the most complicated market research questions are usually sufficiently answered within 3 tries and 2 hours. Considering that a human doing the research manually would, before the introduction of Forestreet, have to spend weeks to compile everything that the Forestreet platform does in minutes, it is a phenomenal tool that enables superhuman performance and a pure focus on the strategic value-add work a skilled professional should be doing, not the manual Google searching or, even worse, the validation of each Gen-AI output because you know many of the results will be useless and and some, sadly, made up!

Market Intelligence (Tomorrow, well, Q2 actually)

Right now, the market intelligence product is quite good, and actually industry leading in many respects, but they know you need more, they are working on more (and SI has seen the development alpha, beta customers will have access by early Q2, product is expected to launch by late Q2), and what’s coming will be even better. You will be able to do the work of expert consultants on your own in a few hours for most markets. Here’s a brief overview of what’s to come (and it looks great).

  • Deeper Market Data for a Market Landscape including
    • trends and innovations: the next version of the platform will not just identify emerging topics, but overall market trends and innovations with descriptions of each
    • financial predictions: is the market growing, static, or declining in size
    • ESG themes and [emerging] challenges: what is the bulk of the activity and content centered around, why, and what are the challenges; not just the E in ESG, but for example carbon capture in plant emissions, etc.
  • Deeper Market Analysis including:
    • feature distribution: not just feature maps, but distributions and a deeper analysis thereon
    • topic analysis: deeper dive into topics and related features, ESG criteria, etc.
    • market distributions: dive into a region, feature subset, etc. and have detailed data all the way down like you would in a modern spend analysis system that rolls up an n level category from the transaction level to the global spend view and lets a user drill all the way down
  • Broader Vendor Profiles: there’s a lot planned here, but most of this hasn’t hit full alpha, so we’re not going to discuss it in detail (as it’s unclear what will hit the coming beta and how well it will work), and if they get even half of it production ready, trust me in that you will be amazed (and hopefully throw your Gen-AI chatbot in the virtual trashbin where it belongs)

It will be very easy to walk through the analysis step by step in the next version and, of course, output it, or just sections of it, to a Powerpoint for your presentation. You will be able to walkthrough at least (working alpha):

  • Summary Overview
  • ESG
  • Risk and Challenges
  • Cost and Price Drivers
  • Market Size
  • Acquisitions and Mergers
  • New Products and Services
  • Innovations and Opportunities
  • Trends
  • Regulations and Consequences
  • New Suppliers
  • Growth Projections
  • Key Players … and, of course, deep dive into any company, which will have all of the information available in the current release, a deeper capability overview, a SWOT analysis, and hopefully, a few other pleasant surprises by the end of next quarter

If you haven’t heard of Forestreet, well, you have now, and if you don’t have a tool like that in your arsenal and you have tens of millions in strategic spend, you should … and have no reason NOT to check them out. You know that the doctor is an expert in advanced tech and constantly rails against most of the AI BS that has hit the market over the last few years (and ruined the good name of the great AI tech that came before, which was supposed to give you all the innovations chronicled in these two series on The Complete AI in Procurement, Sourcing, and Supplier Management, but just gave you gibberish that told you to eat one rock a day). This should tell you that if he’s finally saying “there’s something there, and it’s pretty damn good” then there is something there, it’s pretty damn good, and you probably shouldn’t be without a tool like this if you’re spending tens (if not hundreds) of millions on strategic spend categories.

Thus, if you don’t have a tool like Forestreet (and the doctor knows you don’t), check them out. While he’s sure there are exceptions it won’t work for, Forestreet have been building their knowledge graph (real AI tech) for 8 years and it’s broad and deep enough that it will work for the majority of companies. Moreover, even if it only gets you 80% to 90% of the way there, and you still have to do a bit of manual digging into key issues or topics or potential suppliers, it’s still saving you weeks of work. That’s what counts as it allows you to focus your Human Intelligence (and potential) on what matters, not the drudgery of getting to that point.

In the Software World, It Is Never Build vs. Buy!

In a LinkedIn post, THE REVELATOR asks “Why is the build versus buy debate a moot exercise?”.

The answer to this question is super simple.

If you are NOT a software* company, it is NEVER build. NEVER, EVER. Especially since “Build” typically means outsourcing to a Big X who are typically specialist implementors, not builders, and will just have to outsource to a Dev Shop and add a high margin to manage that outsourced project for you IF they want to get it right. (Just Google “Accenture Hertz Lawsuit” to see what happens when they get it wrong, so the smart Big X really do add a layer between you and an outsource Dev Shop in South America, Eastern Europe, or India … and trust us when we say that the last option ain’t always great either!) In the end, the project will cost 5X to 10X, take significantly longer than you expect, and rarely deliver entirely what you want.

The debate today should be “assemble vs. buy”, because the most you should do is determine whether its best to go with one provider who provides some functionality across the board for a function, but maybe not as deep as you want in certain areas, or if you want to assemble a slew of best of breed modules that go deep everywhere you want deep. In the latter case, you are deciding whether you are going to select a slew of best of breed modules from a slew of vendors and oversee the integration yourself (one time cost plus incremental costs on the update of each component solution) or go with an “orchestration” solution (and its year over year SaaS fee) vs. just selecting one of the same old Big Suite providers that will handle everything (with a fee to match).

The only thing that remains correct about the “build” vs buy debate is that you need to maintain the “build” mentality, in that you may have to lego-block “build” from a collection of best-of-breed modular solutions. However, the “build” will never be a build from scratch, just a build from components, the same way we used to assemble our own desktop systems.

* and even if you are a software company, if the type of software needed is not the type of software you build, and there is a reasonable SaaS solution, you should go with that;

Myth-busting 2025 2015 Procurement Predictions and Trends! Part 11

Introduction

In our first instalment, we noted that the ambitious started pumping out 2025 prediction and trend articles in late November / early December, wanting to be ahead of the pack, even though there is rarely much value in these articles. First of all, and we say this with 25 years of experience in this space, the more they proclaim things will change … Secondly, the predictions all revolve around the same topics we’ve been talking about for almost two decades. In fact, if you dug up a Procurement predictions article for 2015, there’s a good chance 9 of the top 10 topic areas would be the same. (And see the links in our first article for two “future” series with about 3 dozen trends that are more or less as relevant now as they were then.)

In our last instalment, we continued our review of the 10 core predictions (and variants) that came out of our initial review of 71 “predictions” and “trends” across the first eight articles we found, in an effort to demonstrate that most of these aren’t ground-shattering, new, or, if they actually are, not going to happen because the more they proclaim things will change …

In this instalment, we’re again continuing to work our way up the list from the bottom to the top and ending with “AI”.

AI

“AI” is the only “prediction” or “trend” that would not have appeared ten years ago. (Ten years ago it would have been “analytics”, the favourite precursor technology.) There were 10 predictions across the eight articles, and this was the only category where they were not in synch (because the technology, as well as the usage thereof, is not only still evolving but not well understood). Given the vendor hyper-focus on AI (and especially Gen-AI) over the past few years, it is yet another “prediction” or “trend” that is not new, as we are still in the (over)hype(d) cycle, but one that should be adequately addressed as it’s where we have the biggest gap between expectation (pushed by the vendors and the analyst firms and the consultancies) and reality.

Before we go any further, here were the ten predictions from the articles:

  • Advancements in AI and Automation
  • AI: overhyped or underestimated?
  • AI and The Digital Transformation Revolution will Continue
  • Artificial Intelligence in Procurement
  • Automation and Artificial Intelligence
  • Digital Transformation, Automation, and AI
  • Focus on AI Talent in Procurement and Skill Upgrading
  • From AI adoption to AI adaption
  • Integration of AI and Advanced Analytics
  • We’ll Evolve from AI Adoption to True Integration

They range from continued adoption to adaption to analytics enhancement to seamless integration to true advancement in underlying technology, and with the exception of continued, mostly unbridled, and definitely unresearched, adoption, they are more-or-less all off the mark.

The analyst firms are still overhyping this technology to the max (despite continuing to publish studies that 85%+ of technology projects fail)). At least six (6) in seven (7) vendors are overhyping (Gen-)AI to the max, if not nine (9) in ten (10). The Big 3 (Google, Microsoft, and, of course, “Open”-AI) are promising miracles for all who adopt their technology. It’s being marketed as the ultimate panacea, the magic elixir of your dreams, and the silicon snake oil that actually works (among other things). And when you combine the facts that most people don’t have the mathematical and technological background to understand what a given “AI” technology is and, as Bertrand kindly pointed out, humans are biologically wired to be lazy, most are happy to close their eyes, cover their ears, sing “la la la la la la”, and buy in to the BS promises hook-line-and-sinker. So, whether the technology is right or not (and we’ll give you a hint, it usually isn’t), they’ll buy it. (And then blame the vendor when it fails to deliver, who will blame the consultant for improper implementation and training.)

So how accurate were these predictions? Did any hit the mark? Come back for Part 12!