Category Archives: SaaS

Have the Analyst Firms Finally Admitted They Don’t Know What They’re Doing?

the doctor recently went on a big rant about the analyst firms and the utter lack of usefulness in the maps they release, the focus they put on what they don’t understand, and the award categories they invent because, even though they have/had some great talent (and should be doing incredible work), what they’ve publicly released has been mostly valueless to the market they’ve been trying to serve (when it wouldn’t be too hard to provide a lot of value based on all the research and work they do). In the doctor‘s view, this is very sad because if they could demonstrate the value they provide, they would be more relevant across the market (and likely get a lot more business from smaller and/or more innovative providers who think that, because of the budgets the big players like Oracle, SAP, and Coupa have, the analysts are always going to recommend those companies anyway).

However, now he’s gone from sad to mad about something he has just heard from a couple of vendors regarding one of the biggest firms, because, if true, it means not only do they not have a clue about what is and is not valuable in tech, but they are unnecessarily creating confusing and obfuscating technology that still may be best in class.

So what have they done now? Well, apparently they are now basing 30% of the score on whether or not the vendor has “AI” in their platform, something which they’ve repeatedly proven they have ZERO ability to score whatsoever! So, either a vendor makes false, grandiose claims (and tries to use Applied Indirection to fool the Analyst Idiot that they have more than Artificial Idiocy in their Application Implementation), or they get scored low even if they have the best technology built on best practices, proven algorithms, and consistent results that give their customers a 5X to 10X ROI.

True AI adds value, but, in the doctor‘s experience,

  • up to 80% of AI claims are Applied Indirection (at best) or Artificial Idiocy (at worst); in fact, some of the “AI” in spend analysis is still the “AI” they used in the early 2000s, and the doctor would rather not spell out that sad, but still true for some vendors, racial slur
  • up to 80% of the rest, or up to 16% of tech that claims AI, is level one Assistive Intelligence; and this is typically just classic RPA (Robotic Process Automation) using human-defined parameter-based rules, and the “AI” is the automatic parameter adjustment based on user overrides … not very intelligent, eh?
  • up to 80% of the rest, or up to 4% of the tech that claims AI, is level 2 Augmented Intelligence, which is the first level of AI where the tech can learn from human feedback and provide better insights and recommendations over time on one or more specific tasks, and the first level of AI that you should even consider as AI
  • up to 80% of the rest, up to 1% of the tech that claims AI, and the highest level modern technology has generally achieved, is level 3, Apperceptive Intelligence, or Cognitive Intelligence, where the systems can not only learn from specific human feedback to recommendations but from general knowledge and intelligence available to it from integrated data sources to mimic the performance of the best human experts over time, even evolving processes, behaviours, and actions within well-defined bounds
  • and then the rest, 0.1% or less, is nearing level 4, Autonomous Intelligence, where the system can learn, evolve, adapt, and maintain itself over time without human intervention … and hopefully execute meaningful, appropriate decisions grounded in best process and fact that considers all of the relevant information available (and not go off of the rails and advise you to commit suicide because you feel bad, Hail Hitler, or sacrifice a trolley full of people and a cross-walk full of pedestrians because there might be a cat in the road — all things AI has already done)

And even where a platform has semblances of real AI, chances are that the AI (the vendor is now forced to include or arbitrarily be relegated to the dustbin because, apparently, it’s not solutions but buzz-acronymns that matter now) is producing worst results than the best traditional algorithm or methodology on expert curated data sets and dimensions. For example, the vast majority of the market believes AI improves forecasting. It doesn’t. The best AI is still inferior to the best techniques developed in the 70s when applied to the right data dimensions. All the “AI”, which is just fancy, souped-up versions of classical machine learning (using algorithms developed in the 80s and 90s for which we didn’t have enough computing power until recently), does is run all of the data through a model that integrates classification with prediction to filter out the most relevant dimensions and the best curve fitting technique as all these algorithms, at the core, are based on 50+ year old statistics! This means that, at the end of the day, their best case performance is something a human genius figured out 50+ years ago.

But to achieve that best case, the developers have to implement the right AI algorithms, tune them properly, allow them to run long enough to correctly fit (but not over-fit) the training data sets, and monitor those algorithms over time … and to do that they need to be an expert in those algorithms, which they probably aren’t. So, in order to “check a box”, and sell you a product, they are ultimately integrating algorithms that will give you an inferior result (while requiring considerably more computing power that runs up your cloud utilization bill), versus sticking to tried-and-true algorithms and processes that their experts tweaked over years and that their experts can explain and verify at any time.

And this is an almost reasonable example of what a technology vendor might do (as the best predictive algorithms are not untested “AI” but based on classical, tried-and-true, statistical or optimization functions). Most of what the doctor has seen is MUCH worse than this. And the fact that some big analyst firms are now forcing vendors with good tech to integrate underdeveloped, unproven, and often untested AI just to get a rating, make a map, or be recommended is downright stupid.

SHAME ON ANY ANALYST FIRM THAT DOES THIS! Buzzwords are not products, and unproven tech is not value. Analysts should be recommending the best solutions, regarding of the tech they are based on. the doctor is simply appalled!

It Doesn’t Matter Where You Start, You End with BoB in Analytics!

In a recent article, we asked in the battle of Suite vs. BoB (Best-of-Breed), which do you choose, and ended up with the answer of neither, but potentially both, because, as indicated in our article we asked in our post on Where’s the Procurement Management Platform, you need a true platform (that enables the creation of a true source-to-pay plus ecosystem for the various workflows and processes that need to be managed).

As a result, we indicated you could start where you wanted, provided:

  • you could conceivably manage it,
  • the vendor offers, and publicly publishes, a complete Open API, and
  • the vendor offers the necessary quick-start services.

(And for even more details on each of these requirements, stay tuned for our upcoming article on how it doesn’t matter where you start, you end with BoB in SXM).

But where do you end up? For some Procurement Practitioners, it depends on:

  • the module,
  • the organization’s biggest need for workflow/process management, and
  • the organization’s biggest savings/cost avoidance/value creation opportunities.

(And again, we’ll have even more details in our upcoming article on how you end with BoB in SXM for more details.)

But for Analytics, like SXM, you will end at BoB for analytics as no suite equals the best in class (BiC) (spend) analytics solutions (even if they are built in BiC technologies for generic analytics like Qlik or Tableau) as the true BoB spend analysis solutions (which are fewer and further between than you would expect) are leagues beyond them.

Moreover, for Analytics, you should start with BiC, even if the suite has a pre-packaged solution that’s pretty good, enough to get going, more than your fledgeling analysts are likely to be able to handle in the first year, and appears to be offering the module cheap as an add on to everything else they are selling you. Why?

Lots and lots of reasons. Here are five to get you started:

  • Top X Opportunities: Suites will only show you your top 10 categories, top 10 suppliers, top unmanaged tail categories, etc. No guarantee that these primitive, canned, analysis will be YOUR biggest opportunities. BoB will come with hundreds of built-in analytics, considerably more customization capability, and the power to find opportunities that pre-built suites and dashboards will never give you.
  • Better Classification: Suites will do a decent classification, usually through their black box AI (trained on billions and trillions), but even if they get to 95%, it won’t be great, it won’t be manageable, and it won’t be customizable to your organization’s need. BoB, when it uses AI, will use it to create rules, that can be corrected and overridden, that you can customize to your specific taxonometric needs for optimized Procurement (and no standard industry classification is worth its weight in protactinium), usually starting with an out-of-the-box taxonomy customized to your industry using the vendor’s experience and community knowledge.
  • Better Analytics: many of these tools have a lot more capability in terms of report construction, dimension derivation, metric support, integrated data science, etc. etc. etc.
  • Better UX: while UX is completely subjective, and as per a (previous/upcoming) rant, is not something an analyst should be scoring and advising you on (as the best UX is the one that works best for you), in general, the probability is very high that you will find these BoB tools more customizeable in workflow and configuration, more logical in workflow, and much easier to use (if this wasn’t the case, no one would buy these tools and the vendors would have closed their [virtual] doors a long time ago)
  • Beyond Analytics: most BoB solutions will have integrated opportunity selection and project/savings tracking, performance/throughput/project metric support, and/or risk-based analytics. The value of analytics is continually overlooked because the “Savings” is identified in the sourcing event, captured in the contract, and realized in Procurement, and no one wants to acknowledge the opportunity would not even have been identified without analytics.

And, finally, why not get used to using a best-in-class tool from the get-go so you don’t have to relearn a new tool when you max out the capabilities of the suite solution and are ready for the next level? Especially when, as you get better and better at analytics and dive deeper and deeper into categories, you can improve the taxonometric mappings, track all the opportunities you identify (and your progress), do what-if analysis when the mood strikes, and get productive in a tool that will do [much, much] more for you in the long run?

So, while you might select a suite SIM module as a foundation for your supplier data store when you need to start centralizing supplier data somewhere for your sourcing projects and procurement buys (which is where your organization has determined it needs to start its S2P journey), when you’re ready for analytics, just go straight to BoB. (And if the C-Suite wants to see reports in the fancy suite, buy the basic reporting package and let them use the basic dashboards. And if the suite supports custom dashboards, then pump the appropriate analytics back in as reporting data. Get good with best-in-class analytics from the go with the best solution you can.)

Suite vs BoB. Which Do You Choose?

Neither!

But you need something. And there is no other option (yet). So are you doomed?

That depends. But first, let’s talk review the Primary Pros and Cons of each.

SUITE
BoB
PRO

  • one vendor relationship to manage
  • modular integration out of the box
  • consistent UX (or it’s not really a suite)
  • pre-implemented with major ERPs
  • the primary module offered by the vendor is truly Best in Class and considerably beyond the average suite capability
  • implementation is typically vendor supported, along with some integration services
  • low (subscription) cost out of the gate, pay as you need
  • today’s BoB comes with full, complete Open APIs to build your own ecosystem
CON

  • likely that only one or two modules are Best-of-Breed (BoB)
  • implementation and integration services are likely third party
  • high cost out of the gate
  • traditionally a closed ecosystem
  • multiple vendor relationships to manage
  • limited integrations out of the box to other modules you will need
  • inconsistent UX across the modules
  • limited to no ERP/MRP support in many modules

In other words, many of the weaknesses of the suites are the strengths of BoB and vice versa. But you want the strengths of both and the weaknesses of neither, even though that doesn’t exist today as no vendor does everything well, nor can they because they would need to be experts in everything. (So unless a vendor hired all the experts, and became a monopoly [and we generally agree monopolies are bad], no vendor could even come close.) Even if a vendor did hire all the experts of today, and build everything out to the best of those experts’ capabilities, they’d soon become an unaffordable mega-suite (and then still not be best in breed in anything because once they built what the experts they hired envisioned, there would be a new generation of experts they still wouldn’t have employed with new, innovative, possibly revolutionary, ideas).

So what do you do? Well, the answer is, as we pointed out in our post that asked where’s the Procurement Management Platform, acquire a platform that is designed to support data-centric end-point integrations for specific processes and organizational needs as this will allow you to select the right module for each task, configure the right procurement workflows, integrate new, even previously unthought of, modules with the Open API, and even support intake and supply chain platform integration.

But, as we noted, there’s no platform. So, unfortunately, you have to assemble your own. But at least today you can. A decade ago there were no options to do this, so either you bought a suite, and lived with it, or you bought best of breed and did extensive work to glue them together in a grit, spit, & a whole lot of duct tape situation (that would take about 69 months).

But today, all of the new best of breed applications are being built from the ground up with complete Open APIs and the newer suites are also offering you APIs to easily get data in and out as well. (Not so much on the workflow configuration / function execution front, but that’s not necessary.) [But please note that an App Store or Marketplace is not an Open API, it’s a closed ecosystem limiting you in what third party add-ons you can select.]

So you can theoretically start with the right instance of a BoB or a Suite as your base and build out the right platform over time, depending on your needs today, and how fast you can digest a new module. If you already have one or more first generation modules, you have the understanding of what these modules do and how to use them and can likely digest new versions of those modules pretty quickly, so you could start with that many modules plus one. If you have no modern S2P modules, then, as we indicated many, many times in our very long Source-to-Pay series, you need to pick a module that represents your most immediate need, start with it, and start to grow your platform from it.

The 39 Steps … err … The 39 Clues … err … The 39 Part Series to Help You Figure Out Where to Start with Source-to-Pay

Figuring out where to start is not easy, and often never where the majority of vendors or consultants say you should start. They’ll have great reasons for their recommendations, which will typically be true, but they will be the subset of reasons that most benefits them (as it will sell their solution), and not necessarily the subset of reasons that most benefits you now. While you will likely need every module there is in the long run, you can often only start with one or two, and you need to focus on what’s the greatest ROI now to prove the investment and help you acquire funds to get more capability later, when you are ready for it. But figuring out how much you can handle, what the greatest needs are, and the necessary starting points aren’t easy, and that’s why SI dove into this topic, with arguments and explanations and module overviews, both broader and deeper than any analyst firm or blogger has done before. Enjoy!

Introductory Posts:
Part 1: Where Do You Start?
Part 2: Where Should You Start?
Part 3: You Start with …
Part 4: e-Procurement, and Here’s Why.

e-Procurement
Part 5: Defining an e-Procurement Baseline
Part 6: There are Barriers to Selecting an e-Procurement Solution (and they are not what you think)
Part 7: Over 70 e-Procurement Companies to Check Out

Interlude 1
Part 8: What Comes Next?

Spend Analysis
Part 9: Time for Spend Analysis
Part 10: What Do You Need for A Spend Analysis Baseline, I
Part 11: What Do You Need for A Spend Analysis Baseline, II
Part 12: Over 40 Spend Analysis Vendors to Check Out

Interlude 2
Part 13: But I Can’t Touch the Sacred Cows!
(including Over 20 SaaS, 10 Legal, and 5 Marketing Spend Management / Analysis Companies to Check Out)
Part 14: Do Not Stop At Spend Analysis!

Supplier Management
Part 15: Supplier Management is a CORNED QUIP Mash
Part 16: Supplier Management A-Side
Part 17: Supplier Management B-Side
Part 18: Supplier Management C-Side
Part 19: Supplier Management D-Side
Part 20: Over 90 Supplier Management Companies to Check Out

Contract Management
Part 21: Time for Contract Management
Part 22: Contract Management is a NAG: Let’s Start with Negotiation
Part 23: Contract Management is a NAG: Let’s Continue with [Contract]Analytics
Part 24: Contract Management is a NAG: Let’s End with [Contract] Governance
Part 25: Over 80 Contract Management Vendors to Check Out

e-Sourcing
Part 26: Time for e-Sourcing
Part 27: Breaking Down the ORA of Sourcing Starting With RFX
Part 28: Breaking Down the ORA of Sourcing Continuing with e-Auctions
Part 29: Breaking Down the ORA of Sourcing Ending with [Strategic Sourcing Decision] Optimization
Part 30: Over 75 e-Sourcing Vendors to Check Out!

Invoice-to-Pay (I2P):
Part 31: Time for Invoice-to-Pay
Part 32: Breaking Down the Invoice-to-Pay Core
Part 33: Over 75 Invoice-to-Pay Companies to Check Out

Orchestration:
Part 34: How Do I Orchestrate Everything?
Part 35: Do I Intake, Manage, or Orchestrate?
Part 36: Over 20 Intake, [Procurement] [Project] Management, and/or Orchestration Companies to Check Out
Part 37: Investigating Intake By Diving In to the Details
Part 38: Prettying Up the Project with Procurement Project Management
Part 39: Deobfuscating the Orchestration and Fitting it All Together

Just What Is a Start-Up?

Do you know? I bet you don’t! And based upon what he’s seeing in the market, even the doctor doesn’t know anymore! (While he knows what a start-up has traditionally been defined as, that doesn’t appear to be the definition anymore, but we’ll get to that.)

Investopedia defines a startup as a company in the first stages of operations.

TechTarget defines a startup as a newly formed business with particular momentum behind it based on perceived demand for its product or service.

Wikipedia defines a startup as a company undertaken by an entrepreneur to seek, develop, and validate a scalable business model … intend[ed] to grow large beyond the solo founder.

Forbes defines startups as a young company founded to develop a unique product or service, bring it to market and make it irresistible and irreplaceable for customers.

StartUps.com quotes Eric Ries and defines a startup as a human institution designed to create a new product or service under conditions of extreme uncertainty.

You get the point. A startup should be:

  • new
  • innovative (seek, develop and validate; unique product or service)
  • market demand focussed
  • growth focussed beyond the founder / founding team
  • awash in uncertainty

This should mean that a company should no longer be considered a startup when:

  • it’s no longer new (after some reasonable amount of time has passed since product launch)
  • the product has been out long enough to be replicated or surpassed by competition (who figured it out on their own without IP theft)
  • the market demand has evolved based upon the product capability
  • it’s grown beyond the founders (and stabilized)
  • the company has been operating with reasonable stability for a while

And while you might debate whether or not

  • a company is still new after 1, 3, or 5 years
  • a company is no longer innovative when it has been equalled or if it’s when the competitors have stabilized
  • the market demand has grown as a result of initial adoption or if a couple of extra years are required for the market capability to mature
  • the company is large enough when the team is double the size of the founding team or if it needs to be triple, quadruple, or based on industry averages
  • you need 2, 3 or 5 years of stability

the doctor is quite certain the majority of you would agree that a company is NOT a startup

  • if it has been in existence and live with its product for over 5 years
  • any semi-unique capabilities have long been equalled by companies that followed (where some of those followers may even have been acquired for their maturity)
  • the market demand has considerably grown and matured (possibly to the point that even related solutions were started, grew, and were acquired into mainstream suite players)
  • the company has surpassed 10-15 employees or quadrupled in size relative to its founding team, whichever is larger
  • if it has well over 5 years of stability

But yet, on the list of companies being considered for the Demo 2023 start-competition at DPW, you have a company that:

  • has been in business for 13 years with a beta product in testing the year it was formed
  • barely had any unique capabilities on launch (just had a much lower price point and easier UX and added some semi-unique capabilities as it went along, along with stronger back-end processing, but since then new startups have come along that equalled it and one was acquired)
  • the market demand has consistently grown and matured since before the company was founded to the point related solutions were acquired and integrated into suites
  • the company is almost 10X it’s first month size (and over 100 employees)
  • while it had years of stagnation from a growth perspective, it never shrank

WTH? This is simply ridiculous. They basically let a company check a box and call itself a startup without any validation whatsoever (presumably because that company knows its only chance of winning a competition or award is to call itself a startup). It’s sad, and it’s not useful. the doctor has already complained about analyst firms (associations, and conferences) inventing meaningless awards, but if you’re not going to have any requirements or quality control, even the awards and competitions that could be meaningful are now meaningless as well.

And the doctor has to rant about this because it’s not just DPW that are including mature small companies in their startup competitions and startup award categories, it’s the majority of the publications, conference, and analyst firms in the space. DPW is just the latest example the doctor has seen over the last few years (and the one that pushed him over the edge).

(There’s a reason that, at least when he was Lead Consulting Analyst at Spend Matters, the doctor argued for strict limits on length of existence, product availability, customer count, and market size in the Future 5. Without guidelines, requirements, and limits, the designation is meaningless.)

So while the doctor might be calling out DPW as allowing one of the most egregious mischaracterizations of “start-up” that he has seen in quite some time, they should not be singled out, and definitely should not be singularly judged, for this. It doesn’t take more than a little research across the other analysts firms, associations, and award-giving conferences and directories for one to discover DPW is not alone in using a very loose definition of start-up (which sometimes barely qualifies in the “small company” category). Some days it seems that the majority of outfits are allowing any company that wants to be a startup to call itself one as long as it is under some arbitrary revenue number or employee count, even if the company should not have been considered a startup for over five years.

This is a problem that plagues enterprise software, and one, as professionals, we need to demand be fixed. Words and classifications have meaning, and the minute an organization that should be verifying that the words and classifications are used correctly stops doing so and allows anything to be anything, those words and classifications no longer have meaning and any evaluations (or awards) based on those words and classification lose all meaning.

As with an illogical insistence on undefined “AI” or maps that mesh 6 different, barely related, subjective factors into a single dimensional score, these categorizations are unhelpful, and may even cause harm when a company is misclassified as a startup. Some organizations are so risk averse that they will not deal with any company that has wrongly been called a start-up, and others will choose that startup assuming it’s in early stages and going to get bigger and bigger over time (and they should contract with the winner before it gets big and its prices go up, assuming it will fill in the missing functionality that they want over time as more employees are added). But how big a company gets is not just a function of (more) time, it’s a function of what it offers, how much of the market can use what it offers, and how much the company can sell it for. Some companies with niche offerings will never reach an arbitrary revenue threshold, and some with ultra efficient operations will never reach an arbitrary employee threshold, which means neither of these metrics (which are not part of the definition of startup) are an acceptable measure.

And it’s time for us independent analysts and consultants to say enough is enough — Procurement may not be the island of misfit toys anymore, but that doesn’t mean it’s still not relegated to the basement with the IT Crowd in many companies. Procurement’s not going to get its due, and the CPO is not going to have a seat at the big table, until we collectively start treating it with the professionalism it deserves.