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!

AnyData: Your Mid-Market BoB Analytics Solution for Opportunity Identification, Compliance Tracking, and Associated Project Management

AnyData, which we first covered on Sourcing Innovation back in 2017 (in AnyData: Another Analytics Arriviste from Across the Atlantic), has matured significantly since 2017, especially with its addition of auto-rule generation using AI in 2020 (as chronicled in AnyData, making spend analytics accessible by anyone! [Or, ‘The mid-market analytics quandary’]) over on the Spend Matters Content Hub, Pro/Insider subscription required).

Starting out as a Visual Development Framework / Data Hub, AnyData progressed into a good analytics offering, augmented by a good contract management (governance) offering, augmented by a good supplier management (primarily supplier data hub) offering, and that’s about where it was until 2020 when it significantly improved its analytics offering from a usability perspective and began the journey to take the rest of the platform from good to great.

Over the last two years, it has continued to refine its analytics offering from a quick-start/ease-of-use perspective where it has you up and running and doing real analytics in a guided self-service model in as little 15 minutes, added key field extraction and [better] analytics to its contract management module, included ESG/Sustainability support in its Supplier Management module, and built a brand new Project (Activity) (Savings) Tracking module with default templates for analytics-based savings projects, contract ([re-]negotiation projects), and supplier data gathering/compliance projects. In addition, using their rapid development capability, they can build custom, smart, project forms for any project type an organization wants to track very quickly (typically a few hours, a day at most) for a low fee [in addition to the standard templates you get included in the base subscription].

Since introducing their enhanced analytics offering three years ago with AI-based rule-derivation and easy re-classification, they have enhanced each part of the process to guide an average Procurement Practitioner and fledgeling analyst through each step of the process in a best-practice way that teaches them the basics while allowing them to go wide and deep as soon as they are ready.

For most clients, the AnyData process is this:

  1. Upload the file
  2. Determine if you want to
    • load the data Fresh,
    • Merge the data in, or
    • merge new data in while Replacing existing data for a time-period
  3. Select a Taxonomy (Standard, Industry Best Practice, or Tailored)
  4. Configure the Automation Process as needed
    (fields to analyze, priority, confidence intervals, etc. … or use the defaults)
  5. Review the Business KPI Dashboard and, optionally, drill into the Categorization Data Quality Dashboard
    • Optionally: Define rules for any significant or relevant unclassified spend (note that 100% mapping is not necessary, and not achievable by ANY solution on the market; 90%+ of the spend in a category is enough)
    • Optionally: Override the auto-generated rules, especially if you have a few products or services you treat atypically (for the chosen taxonomy; e.g. printer cartridges in electronics vs. office suppliers)
    • Optionally: Review, drag and drop the taxonometric (sub)categories as desired
    • Optionally: Enhance data/classifications as needed
  6. Review the Significant Opportunity Dashboards
  7. Dive into the Dashboards of Interest,
    which you can modify as needed to update / add analysis in a visual manner as needed
  8. Kick-off one or more analytics/savings project on an opportunity of interest
  9. Repeat from any step in the process as needed

A few points of note:

  • Through the SaaS front-end, file size is limited by browser limits but since they support compressed file uploads (and real-time decompression), that can easily be a 20GB file (uncompressed); if the initial file is too big, they support SFTP
  • AnyData is fast, so under a million rows of data only takes minutes to fully process
  • AnyData has best-practice starting taxonomies for multiple industries and can provide you with one upon setup
  • They tie their industry best-practice taxonomies to the standard taxonomies (like UNSPSC) and can make use of multiple data points for classification and for the industries they know well, their default rule generation will correctly classify 80%+ out of the gate
  • Their visual focus and the ability to drag and drop categories makes taxonomy classification super easy (and fields makes rules classification easy as well)
  • Rules can be on any combination of fields and use multiple types of matching (exact, partial, regex, etc.)
  • The Data Quality dashboard gives you a quick overview of the quality of data you uploaded (and the confidence you can have in the auto-generated rules without reviewing any manually, until you identify a need to do so in a category deep-dive)
  • The opportunity dashboards identify the best opportunities uncovered in the automated out-of-the-box analysis
  • It’s a click to start a savings/analytics project
  • You can jump back to any step at any time and continue on (down a different path) …

It’s tailored for quick start, quick execution, and quick time-to-value for a mid-market staffed by Procurement Professionals who are short on time and short on analytics training as it trains those procurement professionals how to do proper analytics through (semi-)guided workflows as they go.

If you’re a Mid-Market looking for a Best-of-Breed (BoB) analytics solution, AnyData should definitely be on your short list, especially since it’s one of the few offerings that can be obtained at an incredibly affordable price point due to the high DiY nature of the tool (and the focus on self-selection and self-serve SaaS sales). There aren’t many tools where you can get enterprise subscriptions starting at less than 2K/month, and few equal AnyData.

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.)

Kodiak Hub: A Supplier Relationship Management for Sustainability

Kodiak Hub is a relatively new Swedish solution for Supplier Relationship Management. Founded in 2015, it primarily served the Nordics for its first few years but began its expansion into the DACH and UK Regions during COVID (and even serves the NA market, although they don’t plan to tackle the NA market until the coming year).

A visit to its site might lead you to believe it’s a category management platform, billing itself as the starting point in a journey towards smart strategic sourcing, but that’s not quite what it is, or at least not where it’s found its niche and its true capability shines.

It’s true capability shines in sustainability, responsibility, risk assessments, and performance evaluations of suppliers, and their products, where those suppliers are creating (custom) (build-to-order) (manufactured) products where regulations need to be adhered to, carbon/GHG needs to be reported, and the organization needs to ensure they are acquiring a sustainable product (or service) as well as a sustainable supplier.

It’s primary platform is organized into three sections: Insights, Impact, and Intelligence along with a home dashboard that visually shows you the regions of all of your global suppliers and allows you to hover over those regions to see the number of suppliers, the regional economic rating, and the Country safe(SOURCE)TM Rating.

The safe(SOURCE)TM Rating is one of the truly unique capabilities of Kodiak Hub and one of the capabilities that positions it as a strong Sustainable Supplier Relationship Management platform. Using indices and public data sources, it is able to create a regional risk assessment profile that allows an organization to quickly spot geopolitical, environmental, and sustainability risks even before sending out an assessment to a supplier, and to create a generic risk profile when specific information is (not) yet available. When this is combined with local economic indicators (to spot risks of [significant] currency fluctuations, increased bankruptcy, etc.) as well as the ability to pull in credit scores (from credit agencies) (with appropriate data feed subscriptions), it provides an organization relatively deep insight into what expectations it should have for a supplier even before analyzing its policies, practices, and external assessments.

The supplier profiles or scorecards that Kodiak Hub can maintain are quite extensive, allowing an organization to maintain all the compliance, performance, risk, and sustainability data it needs on suppliers, products, and services to power its supplier management, sourcing, and procurement. It supports all standard company profile data, including supplier type and spend totals, detailed (customizable) assessment data, detailed on-site audit data (which will override the existing data as necessary), (third-party) risk/ESG/CSR data/rankings/metrics, externally computed KPIs, and related company, product, and service linkages. It can also store any and all documents of relevance or interest (insurance, certification, specifications, contracts, etc.).

Insight is the entry point to the platform’s supplier, product, and services summary screens that capture, and allow a user to query, all of the data associated with a supplier, product, or service.

Impact allows you to create and dive into (data-driven) supplier assessments, (onsite) supplier audits, KPI-based evaluations, and identified actions (in progress).

Assessments are unlimited and can be on the supplier in general, specific products or services, and even restricted to specific category management or sourcing projects. They can cover quality, health and safety, compliance & governance, human rights, environmental, business, product, information security, and other areas of relevance to the organization and use pre-built (template) questionnaires, customized variants, or custom questionnaires.

Right now, even though they can be assigned a “type”, actions are essentially requests to the suppliers with an integrated messaging trail for asynchronous communication that allows suppliers to ask questions, buyers to provide answers, and action states to be recorded (pending approval, in progress, completed, etc.). Future versions of the platform will contain specific types to ensure necessary information is captured, processes and workflows are followed, interim checks and approvals are in place, and so on.

Intelligence is its integrated analytics platform that allows a procurement professional to analyze suppliers across campaigns, projects, KPIs, assessments, categories, products, capabilities, etc. Relationship managers and buyers can create custom dashboards and reports, and customize the pre-built dashboards as needed.

The UX is very clean, modern, broken into logical segments, and very easy to use. It’s intuitive where to go to get the information you need and how to update new information when it comes in. This reviewer finds it so intuitive that he believes you can jump in and be productive with it without any training whatsoever.

So if you’re looking for a great supplier relationship management platform to manage your sustainability efforts and assess your supplier risks, we recommend you include Kodiak Hub in your shortlist.

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.