Category Archives: Services

Roughly Half a Trillion Dollars Will Be Wasted on SaaS Spend This Year and up to One Trillion Dollars on IT Services. How Much Will You Waste?

Before we continue, yes, that is TRILLION, numerically represented as 1,000,000,000,000, repeated twice in the title and yes we mean US (as in United States of America) dollars!

Gartner projects that IT spend will surpass 5 Trillion this year. When you consider that 30% of IT spend is usually for software, and that one third (or more) of software spend is wasted (for unused licenses, which is why we have a whole category of IT and SaaS specialists that analyze your out-of-control SaaS and software spend and typically find 30% to 40% overspend in a few days), that means that roughly half a trillion dollars will be wasted on software this year.

Even worse, Gartner projects that spending on IT Services will reach 1.5 Trillion. And the waste here could be two thirds! Now, we all know that you need IT services to implement, integrate, and maintain those IT systems you buy. But how much do you need? And how much should you pay? Consider that an intermediate software developer should be making 150K a year (or 75/hour), that says that an intermediate implementation specialist shouldn’t be making any more than that, and not billed at more than 3 times that (or 225/hour). But how much are you being billed for relatively inexperienced implementation consultant, with maybe a few years of overall experience and maybe six months on the system that you are installing? the doctor knows that rates of $300 to $500 are not uncommon for these resources that are oversold and overcharged for.

But this isn’t the worst of it. As per our upcoming article Fraud And Waste Are Not The Same Thing, many implementation “partners” will try to get all they can get and make sure that when you go in for a penny, you go in for a pound and they will push for:

  • frequent change orders during implementation, usually billed at excessively high day rates as they have to “divert resources” or “work overtime”
  • unnecessary customizations or real-time integrations that are an extensive amount of work (and cost) when out-of-the-box or daily flat-file synchs are more than sufficient
  • extensive “process evaluation” or “process transformation” processes that are well beyond what you need to eat up consulting hours
  • extensive “best practice” education when your practices are good enough for now and/or those best practices are already encoded in the system you just bought and paid a pretty penny for and just following the default process gives you the same education

That will often double to triple the cost. But that’s not the worst of it. As per comments the doctor has made on LinkedIn, he regularly hears stories of niche providers losing 200K deals because customers said their quote was too low because all the Big X companies quoted over 1,000K for 100K worth of work. Literally. This is because, as the doctor has noted in previous posts and comments on LinkedIn:

  • they don’t have the talent in advanced tech (and even The Prophet has noted their lack of talent in areas of advanced tech in multiple LinkedIn posts, though he has been much more diplomatic than the doctor in discussing their lack thereof; but he did note in a 2024 advice post that consultancies are going to have a hard time attracting talent this year) — for every area, they’ll have a team leader who’s a superstar, two or three handpicked lieutenants who are above average, and then 20 to 40 benchwarmers who are junior and not worth the rate they are charging)
  • they have an incredible overhead — posh offices to house the partners making more than top lawyers who have a lifestyle to maintain
  • they don’t have the knowledge of, or experience in, modern tools — some of which are ten times more powerful than last generation tools; this, of course, means the Big X benchwarmers are using last generation tools which take ten times the manual labour to extract value from
  • etc.

There’s a reason the doctor said that if you want to get analytics and AI right, DON’T HIRE A F6CKW@D FROM A BIG X! and stands by it! Unless you want to pay 1K an hour, you’re not getting that one superstar resource trying to be the front end to two dozen projects that his three lieutenants are trying to manage, all of which are staffed by junior to intermediate individuals who can barely follow the three to five year old playbook.

There’s a reason that The Prophet predicted in his 9th prediction that SaaS Management Solutions [will] Start to Eat Services Procurement Tech and that many companies will go in house if they have tech expertise. Because he realizes that these consultancies will have a hard time not only hiring, but retaining, tech talent when they have hiring freezes, salary freezes, and reduced engagements as more and more companies can’t afford the ridiculous rates they’ve been charging recently. (Companies may not have had a choice during COVID where it was implement on-line collaboration and B2B tech or perish, but now they do.)

But there are still many companies who will, when they encounter a (perceived) tech need, immediately pick up the phone and call Accenture, CapGemini, Deloitte, McKinsey, etc. and bring them in to help them understand who to bring in for an engagement, instead of widening the net to niche providers who are 3 to 5 times cheaper, and who will deliver results at least as good, if not better.

Now, again, the doctor would like to stress that, despite how much he insists they are usually not the right solution for advanced tech implementation, that Big X are not all bad, and sometimes worth more than the high fees they charge. Most of these companies started off as management/operational/finance/strategy consultants and grew big because they were one of the best, and in certain domains, each of these companies still are. But being good at a few things doesn’t mean they are good at everything, and that’s very important to remember.

And while there will be exceptions to the rule (as every one of these companies has some tech geniuses), the reality is that when you need more bodies than there are talented bodies in an entire industry, you’re not going to get them and, because consultancies are not cool when you want to be a tech superstar (and join a startup that becomes a unicorn), the ratio of superstar to above average to average to below average talent in these organizations is much worse than in multinational tech companies (like Alphabet, Apple, Meta, Microsoft, etc.) where you know the majority of their employees are not the best of the best. (Because if they were the best of the best, there’s no way they’d lay off 10,000 employees at a time every time the market jitters.)

In short, manage that IT services spend carefully, or you’ll be double paying, triple paying, or worse and providing a big chunk of the roughly ONE TRILLION DOLLARS in IT services overspend that the doctor predicts will happen (again) this year. (Unless, of course, you agree with Doctor Evil who says, why make trillions when we could make … billions. Because that’s exactly what happens when you overpay for software and services. Don’t expect the Big X to say anything as they get the majority that overspend, and that’s how they stay so [insanely] profitable.)

Data-Driven Workforce Planning — WTF?

Data is good. And you should make use of it all the time. And while data might help you identify gaps in your work force capability, it can’t help you plan your future workforce. Why? A couple of reasons. First of all, you don’t know what’s coming down the pipe in future Procurement and Supply Chain needs and issues. Secondly, existing skill sets may not be enough to address those future needs and issues (which could require evolved versions of current skill sets or even entirely new skill sets). So while the doctor would agree that the 14% of Procurement Leaders who believe they have adequate talent to meet future needs are idiots that never look at the data, he would also argue that looking at the data alone will not allow one to adequately define their workforce needs.

Planning implies you are building a workforce for the future. Data can only identify gaps in your workforce today. And while you need to fill those gaps to conquer today’s challenges, put out the fires, and get to the point where you can start seriously thinking about the future, analyzing historical data is not going to get you there. You need to look at how new technologies will change production, how new technology will change logistics (not just green vehicles, but better planning technologies, more efficient cross-docking techniques, etc.), how regulations will impact trade, and so on. There’s no data on that yet (other than patent documents, vendor spec sheets, draft legislation, and so on). So how can you analyze data you don’t have?

So, why do we need to talk about this? Well, Info-Tech Research group is flooding the PR and Business News Wires with an article on how data-driven workforce planning is key to future-proofing organizations. And while data-driven workforce planning is key to getting your workforce right today, as we just explained above, it can’t future proof your workforce because you don’t know what skills your future workforce will need.

Yes, there are serious talent shortages in IT and Procurement. Yes, it reinforces the reality that a proactive approach to workforce management is something that most organizations should have been doing a decade ago. Yes data-driven insights are often the fastest way to see where you don’t have enough people or enough people with the right skills to tackle the job. And yes tools that can help you are highly valuable. But don’t confuse solving today’s challenges with people you will hire tomorrow with solving the problem of future workforce planning.

Now, if you hire the right people with the right education and the right skill sets in analytics and the ability to learn on their own, they will be more prepared than those employed by your peers. This may put you in a better place, as they may even have the skills to identify the gaps when the world changes, but there are no guarantees. So find top talent with the education, drive, and ability to learn, continually train them, give them time to look ahead once in a while, and you’ll be better off than those who just hire the cheapest resource they can to put out the latest fire.

SourcingShark Wants to Give You Sourcing Insights That Take a Bite Out of Your Sourced Spending

Sourcing Insights was co-founded in 2017 by a CPO who knew the importance of spend-based insights for Sourcing Success and a technologist who spent over two decades developing P2P analytics and audit software who both saw the need for deeper insights into organizational spend for strategic sourcing, especially in direct material industries (as most of the [leading] spend analysis solutions on the market was focussed on indirect spend or analysis at the category level). Together they built a hybrid company that offers a leading spend analytics solution as well as expert services that can get you started and make sure you get the value out of the solution that you expect.

In other words, while Sourcing Insights appears to be just another spend analysis company, it’s not just another spend analysis company. The reason being is that it supports spend by commodity and/or part based spend analysis of the box, tracks price movement at the part/commodity level out of the box, and the definition of commodity or part-based plans out of the box. But first, let’s cover the basics.

The entry point to SourcingShark is either:

  • a customizable spend overview dashboard that not only summarizes spend by various dimensions (commodity, month, PO, supplier [group], etc.),
  • a commodity dashboard that summarizes the commodity codes / parts in the system, associated contracts, purchase order, (potentially) duplicate invoices, and other spend metrics of interest to the organization,
  • or a merged dashboard that combines all of this information into one dashboard and allows for filtering by commodity or organization (and soon to be organization/division groups)

From the supplier widget[s], you can dive into the vendor summary dashboard which can be configured to display the same information, but just on the vendor, or other vendor-specific information that we’ll discuss a bit later.

Before we dive into some of the more unique (out-of-the-box) capabilities of SourcingShark, we will note that they cover all of the basic out-of-the box reporting requirements that one would expect from a modern spend analysis application (for direct materials). This includes deep, customizeable dashboards for

  • invoice spend (vendor type, vendor, cost center, GL, creator, company [if you have a multi-level organization]),
  • PO spend (vendor, cost center, GL, company, part/commodity category, part/commodity, creator, etc.),
  • Invoice Analysis, and
  • PO Analysis.

However, the more/most unique capabilities revolve around (direct) vendor deep dives, part/commodity analysis (& price movement), and strategy insights.

When it comes to vendor deep dives, they have the following out of the box:

  • Deep Vendor Management where you can track deep (SIM level) vendor details if you want to, map vendors to all of the commodities/parts they supply, associate them with contracts, quickly see spend-based summaries by part/commodity, by GL, or Company (if you are a multi-level organization).
  • Vendor Score Dashboard which allows you to overview vendor performance as the platform can track on-time delivery, quality scores (based on disruptions, PPM, SCARs, etc.), commercial scores (based on supply agreements, cost improvements, financial ratings), and risk scores (if you have access to third party feeds to collect the appropriate data and define your risk model), and provide you with widgets to drill down into all of this data, which can also include metric-based summaries of all system data fields
  • After-The-Fact Vendor Summary which presents a detailed summary of after-the-fact purchases

When it comes to part deep dives, they have the following out of the box:

  • Spend Summary that summarizes the spend by part by vendor, invoice, amount, month, etc.
  • PO Spend Summary that summarizes the spend by part by vendor, invoice, amount, month, etc.
  • Price Movements that shows the price movement for (a category of) related parts over a time frame, with the ability to drill down by vendor, and see the potential savings if all parts were bought at the lowest price
  • PO Price Accuracy Analysis that shows the percentage of vendors, POs, and invoices which were accurate (to the PO or Contract)
  • Part / Commodity Deep Dive where you get just the part related spend and metrics, can define your part/commodity strategy, and track the success to that over time
  • Exportable PO-Based Purchase Price Variance Analysis where, for each part/SKU in the system, you can get the PPV for the time-frame of your choice using actual PO data

As alluded to above, they also support contract metadata management which allows a user to define all of the relevant data for contract, and spend, analysis; associate those contracts with vendors and parts; and define contract summary / analysis dashboards and reports as needed.

And, with their new release this month, they now support Part/SKU Strategies where an organization can capture their current and future sourcing strategies along multiple key dimensions, including:

  • target # of suppliers
  • suppliers under contract (not necessarily the same, you may want a spot-buy supplier just in case)
  • supplier reach (local, regional, national, international, etc.)
  • primary supplier award / supplier split percentage
  • desired volume incentive rebates
  • PPP Trend expectations
  • target savings

as well as track the project status, the communication status (with potential suppliers), the primary type of commodity sourcing strategy (contract renegotiation, multi-round RFX, etc.), and the primary price (commodity) driver, typically associated with a market index of the primary material (or material with the highest variability). It looks pretty basic when you first see it, but it’s incredibly powerful and useful and will likely evolve over time, especially when they add in full Bill of Material Support / (Sub) Assembly Support, slated for their next release (target 2024 Q1).

Finally, the team has the experience and the services to support your spend analysis efforts. They can handle all of your data refreshes, design your custom dashboards, and walk you through proper spend analysis methodologies, or even do the first pass for you, to make sure you achieve your organizational goals and have the knowledge you need to do spend analysis right going forward. Sourcing Insights might not be as old as the grandparent spend analysis vendors of the space, but they are already one of the best platforms out there for direct spend analysis.

Prices too High? Take a Leaf from the Green Cabbage!

Green Cabbage, formerly known as PAAS Advisors (which stood for Product Analysis and Strategy), is an interesting spend analytics offering as it is both a product and a service advisory practice. The platform provides unequalled insights into the indirect technology, contingent workforce, and clinical categories; deep invoice analytics down to the line item; market intelligence theses (MITs) on very specific indirect technology, contingent workforce, or clinical sub (sub) categories that are far deeper and fresher than any peers; and a third party negotiation (support) service (where they will negotiate at the Senior Executive/C-Suite level) to help you get the best contracts possible on key high-value contracts. That’s a lot to digest, but we’ll tackle each point in this write up.

Let’s break down the “practice and platform” part first, starting with their pricing model. Their pricing model is a variation of standard percentage of savings model — it’s a subscription model with a savings target and a guaranteed savings of at least 3X, which is better than just a straight cut of savings for you. If they don’t help you hit the savings target they promise, you will get a discount, or an extension to your subscription, but if you blow way, way, past the target (like many of their clients do), instead of paying more than 3X what you would have otherwise have paid through pre-negotiating a fixed fee for unlimited use of the platform, you pay the pre-negotiated subscription fee.

It’s important to understand their pricing model, as it drives the unique approach they take in their practice, which is designed to deliver savings to the clients that engage them for software and services as fast as possible. Most spend analysis companies start by attempting to load, cleanse, classify, and enrich all of an organization’s spend data before attempting to do any analysis or identify any savings opportunities. This can take weeks or months, which means its weeks or months before the first opportunity is identified. To allow them to start pursuing, and capturing, opportunities in just a few weeks, Green Cabbage starts by loading all of an organization’s contracts, starting with the Indirect Technology Human Capital, and Clinical Supply contracts, because the most immediate opportunities are where contracts are needed ASAP (because the organization allowed them to expire) or in the short term (as they are coming up for renewal), and in those categories where Green Cabbage are experts in finding cost reductions quickly.

From just the contracts, using their deep community intelligence provider benchmarks and market knowledge, they can identify the best opportunities to go after immediately in indirect technology, contingent workforce, and clinical supply categories. They can even negotiate on behalf of the client and often get savings better than their client would on their own due to their deep domain knowledge and years of experience analyzing and negotiating in these categories, usually with senior executives in the supplier organizations.

Once the contracts are loaded, only then will Green Cabbage begin to load and classify all of the organization’s spend data into their One Workspace Spend Analysis platform, which can be provided to them as flat file exports or loaded through an API. The organization can define their own categories and Green Cabbage will map the organizational spend to those categories. Once the spend has been loaded into One Workspace, the organization can build some basic spend reports to do some basic spend analysis on their own, export the clean categorized data to Excel files for local spend analysis, or use the customized workspaces with deep pre-built custom dashboards for Indirect Tech, Human Capital and Clinicals.

The Indirect Tech module is designed to help a buyer identify the current and upcoming projects based upon expired and expiring contracts that need to be renewed to support their organization. The main dashboard shows the buyer the YTD savings, the upcoming renewals by contract, the top suppliers by spend, key category metrics, and the primary actions that can be taken (such as upload a contract or request a MIT). From here, the buyer can click into the suppliers dashboard or straight to an indirect technology supplier dashboard that summarizes key metrics (last year of spend, lifetime spend, estimated spend this year, next key [contract] date, relationship length, agreement gaps, etc.), contracts, and visual timelines. From there, the buyer can click into a contract and see associated details or kick off a project.

In addition to the supplier dashboards, there are also spend analysis, renewal, project, and MIT dashboards. The spend analysis dashboard allows the buyer to create custom reports to slice the data by different dimensions. The renewals dashboard in the Indirect Tech Module summarizes the status of contracts coming up for renewal (queued, in review, out for sourcing, terminating, etc.) as well as the category breakdowns, spend by stage, and timeline summaries. The projects dashboard allows contract renewal projects to be created, assigned, and tracked while providing a summary view of all current projects. It also supports savings tracking by agreement. From a project, the buyer can click into the renewal details and access the current (draft) version of the contract for review, the reviewers, see any notes or documents they uploaded, and the activity log.

Finally, the MIT — Market Intelligence Thesis — dashboard allows the buyer to quickly access the completed MITs, month-over-month and year-over-year savings from projects based on the MITs, and key MIT metrics (in process, completed, estimated savings available, % discount from baseline, etc.). The Green Cabbage Market Intelligence Thesis is much more than just a benchmark, it’s a detailed sub-category analysis on a specific product or service of 1 to 2 pages done in near-real time by expert advisors that augments the benchmark data with deep vendor insights into the SKUs being purchased, market conditions, and negotiation strategy. The MIT is offered at three different levels:

  • lightweight: basic MIT as described above
  • comprehensive: lightweight MIT as well as a detailed analysis of standard/available terms & conditions
  • competitive: competitive MIT as well as a detailed analysis of top 3 competitors across similar SKUs and similar terms and conditions, with appropriate negotiation strategies and expected savings under different conditions

Unlike some providers which simply do this every quarter (Denali, SpendHQ, etc.) and provide this as a reporting service, or others that do fully automated real-time augmented benchmark production based on current data, trends, and standard practices based on the trends and current market conditions, Green Cabbage does a custom, semi-manual, MIT upon request within three (3) business days, and usually within one (1) business day, on every request to make sure the client always has the most up-to-date information appropriate to that client’s situation. They can do this because their platform automates the benchmark computations and their advisors are experts in the indirect technology and human capital categories and are analyzing and negotiating in the categories on a daily basis. As such, their analysts can turn around a custom analysis specific to a client’s situation in an hour or two.

However, as per our intro, Indirect Tech is not the only area they go deep. They also go deep in contingent workforce/staffing agency in their Human Capital module that more-or-less mirrors the Indirect Tech module with a main dashboard and dashboards on contingent workforce suppliers, human capital spend analysis, renewals, projects, and MITs. The main dashboard summarizes savings to date, percentage from baseline, forecasted spend (vs. actual for historical), top agency relationships, expiring contracts, and key metrics. The other dashboards are similar in purpose to Indirect Tech, but customized to Human Capital.

The main difference is in the MITs, where a contract owner / project owner can benchmark as many positions as they want in a sub-category or category for a given provider (should they be looking to renegotiate) or a small set of providers (should they be looking for true market intelligence or looking to negotiate with multiple providers and trying to figure out how to best split demand). The benchmarks are similar, wth all the benchmark data (which shows the low/medium/high averages, the service locations, the expected savings at each level) auto-generated. The only exception is the additional market/negotiation notes at the position level that is manually generated on top of the basic thesis information. Note that there is a limit to the number of positions if you want the guaranteed turnaround time, but if they have a few extra days, they have done detailed benchmarks of over 1,500 positions in the past, and with their deep insights, expertise, and negotiation skills obtained savings percentages typically only seen by providers who offer deep multi-level decision optimization across multiple national and regional contingent workforce providers. (We’re talking 30% range in some cases.)

(When you have deep benchmark data and powerful spend analytics, you can quickly divide contingent workforce needs among the providers best suited to offer those positions at a lower cost, use this data for fact-based volume-based negotiation, and shave off almost as many points as the best optimization engines without any mathematical modelling whatsoever, and not have to worry about if the split between the providers is one you are comfortable with.)

Other key features of the platform include:

  • Clinicals: which is their clinical supplies spend analysis module that is similar to their Human Capital Module (except the SKUs are clinical suppliers and not contingent workforce positions)
  • GC Legal: which maintains a standard set of Terms and Conditions clauses that specify exactly what different Ts and Cs means to the client (and helps the analysts do custom MITs and negotiation projects)
  • SKU Search: that allows the client to search for particular SKUs across their suppliers and contracts
  • Outside Data: that allows them to import additional data to augment their spend from third party products, with out-of-the-box integration options for a number of indirect tech (SalesForce, etc.) and contingent workforce (ServiceNow, etc.) providers
  • Invari: their invoices platform
  • End-to-End Security: all MITs, which are often based on organizational contracts, are done through the platform, where data is fully encrypted both in transit and at rest, and not through e-mail, FTP, or other unsafe data transmission methods employed by some other service/advisory firms

Let’s talk about Invari now. This is an analytics backed invoice management platform that allows an organization to upload, manage, and analyze invoices in real time. While it can support any category and supplier, it is designed to support their technology, human capital, and clinical supply categories and benchmarking in particular. When purchased, they request at least 3 months of invoices for all of your providers, and will accept up to 3 years of history if available in order to get enough invoices to allow them to train a custom model for every single provider so that, when an invoice is uploaded, it can be automatically parsed at least 95% of the time for immediate availability. Because models are customized per supplier per client, their system detects any issues and when the invoice cannot be parsed or key information cannot be found. When this happens, the invoice processing system kicks the invoice out to a manual processor who will fill in the missing information in under 3 hours and then update/retrain the model to prevent the same error from happening again.

In addition to allowing invoices to be immediately available for management and analytics in the future, these detailed models also allow the system to build up invoice profiles by supplier and the system can detect when an expected invoice is missing (because you always get a monthly invoice for a service by a certain date in the month), duplicated (because the spend profile is doubled in a month, etc.), or suspect (because it doesn’t fit the pattern).

The main dashboard provides an overview of key invoice KPIs (pending submission, awaiting approval, total count, unresolved, missing), an overview of missing invoices (so immediate action can be taken), a summary by providers, and a summary of top variances.

The approvals dashboard shows all of the invoices that need to be approved, along with variances from the best “prior” invoice, colour-coded on the green to red spectrum (so you can quickly see if there is a likely price issue even before drilling in to the invoice). On this screen, you can quickly pop-up the six-month history for more details on the variance and trends and pop-up the invoice summary window that summarizes billing arrangements (from the contract), line items, and sub-charges.

Fore more details on costs and variances, you can dive into the invoice analytics dashboard that provides a variance report across suppliers over the past X months (on a green – red spectrum that represents decreases to increases) that also clearly identifies new charges (in yellow) so you can see where regular billings start or change. From here, you can dig into a supplier and see the same breakdown by line item / SKU, and then, in that breakdown, you can drill into a particular line item / SKU and see the same breakdown across the sub-charges. For example, at the top level, you see all your providers. When you drill into Your-BroadBand-Provider, you see High Speed Service, Mesh Network Rental, Taxes and Fees. When you Drill into High Speed Service, you see monthly service fee, modem rental, and fixed IP lease. And, of course, you can also search across contracts for specific SKUs and set up alerts when new variances are detected off of new invoices.

At this time it’s worth pointing out that in Indirect Tech, Green Cabbage does true micro-SKU benchmarking, unpacks all of the different offerings in a SKU offered by a tech provider who might include multiple modules in a SKU or a broadband provider who will pack in rentals with subscription fees, and can tell when a provider changes a SKU description or composition. This allows it to do price benchmarking (or at least price range benchmarking) across individual products and services and provide more finer grain details and guidance than the majority of its peers, even in the specialized SaaS market.

And while Green Cabbage might not be a common name in S2P, or one getting a lot of buzz from the analysts, they are bigger than you think. Serving eight (8) of the top ten (10) private equity firms in the US and four (4) of the top private equity firms in Europe, global consultancies like KPMG and BCG, along with other big name Fortune 1000 clients, they have over 500 Billion of spend under management (which is sizeable when you consider that Coupa, that claims to have the most, only has about 4 Trillion in global business spend data), over 1.25 Billion data points, and over 13,000 benchmarkable suppliers in their categories of expertise. That’s very significant, very powerful, and allows them to identify large cost reduction opportunities and negotiate them for you at contract renewal time. (And if you don’t have the volume on your own for significant savings, they also have a group purchasing offering called Receptio that you can look into. Note that since this blog covers technology, we won’t be covering Receptio in this write-up.)

The main weakness right now is that the API is only for getting data in. They are working on extending it to get data out, but there is no timeline for that yet. This is critical for a number of reasons:

  1. their contract management is limited to file uploads and metadata and it would be very useful if they could push rates, benchmarks, and standard Ts and Cs to a contract management/governance platform to support creation, negotiation, and ongoing management of contracts outside of renewal projects
  2. spend export is limited to Excel / flat file dumps; while their tool is good, it’s not BiC for generic spend analysis, especially outside their core categories, and neither is their categorization knowledge beyond their core categories — depending on the spend, it’s not guaranteed to be accurate beyond level 2 or 3 (of a 4 to 6 level UNSPSC or equivalent hierarchy), so if the organization has some very specific or detailed indirect or direct categories it needs deep categorization for, this will have to be done in an external tool (where you can classify to a lower level, do more detailed analytics, and then push the refined data back) and you need Green Cabbage to be the single source of truth (because it allows you to do invoice management and deep invoice analysis and keep your spend data up to date)
  3. you can mark a category or contract as in Sourcing, but there is no connection to an external sourcing tool

We will note that they have indicated they are working on expanding the API for pushing/pulling data out, and that their first priority is to push appropriate data to a contract management platform to allow for contract creation, negotiation management, and governance (as all the platform supports around contracts is file-based uploads and meta-data). Hopefully they finish this by the end of the year and can start extending the API for export of all data in the first half of next year as an organization needs a single source of spend truth and there are lots of great DiY spend analysis tools (like Spendata) that could connect to the Green Cabbage platform for one-off category analysis where Green Cabbage doesn’t provide detailed benchmarks (or support easy/refined classification).

In other words, if you are in an industry that makes heavy use of indirect technology (SaaS, Cloud, etc.), the contingent workforce, and/or clinical supplies and you want a service-based spend analysis offering that can help you find deep savings based on real-time competitive benchmarks and on-demand category analysis, and even use their manpower to capture those opportunities for you, you really should check out Green Cabbage. There’s really no one like them in their categories of expertise.

Don’t Trust an Analyst Firm to Score UX and Implementation Time!

A post late last month on LinkedIn started off as follows:

If you’ve ever read any research papers or solution maps on procurement tech, you’ve probably figured out a couple of things.

1. It’s confusing and overly complex
2. It doesn’t cover the basic, most obvious-of-the-obvious fundamentals that everyone needs to consider.

These are:

– User interface and user experience (UI/UX)
– Ease and speed of implementation

Why don’t they do this?

Honestly, I don’t know the answer.

The cynic in me says it’s because their biggest paymasters have a horrible UI/UX and require a very complex and lengthy implementation.”

This really bothered me, not because UX and implementation time aren’t super important, they are, and they are among the biggest determinants of adoption (which is critical to success), but because anyone would think an analyst firm should address this.

The reality is that no proper analyst will attempt to score these because they are completely subjective! As a result:

  1. There is no objective, function-based/capability-based scale that could be scored consistently by any knowledgeable analyst on the subject and
  2. What is a great experience to one person, with a certain expectation of tech based upon prior experience and knowledge of their function, can be complete CR@P to another person.

Now, some firms do bury such subjective evaluations on UX and implementation time in their 2*2s where they squish an average of 6 subjective ratings into a dimension, but that is why those maps are complete garbage! (See: Dear Analyst Firms: Please stop mangling maps, inventing award categories, and evaluating what you don’t understand!) So no self-respecting analyst should do it. As an example, one analyst might like solutions with absolute minimalist design, with everything hidden and everything automated against pre-built rules (that may, or may not, be right for your organization and may result in an automated sourcing solution placing a Million dollar order with payment up front for a significant early payment discount to a supplier that subsequently files for bankruptcy and doesn’t deliver your goods) while a second might like full user control through a multi-screen multi-step interface for what could be a one-screen and one-step function and a third might like to see as much capability and information as possible squished into every screen and long for the days of text-based green-screens where you weren’t distracted by graphics and animations and design. Each of these analyst would score the same UX completely different! On a 10 point scale, for a given UX design, three analysts in the same firm could give scores of 1, 5, and 10, averaged to 5 … and how is that useful? It’s not!

(And while analysts can define scales of maturity for the technology the UX is based on, just because a vendor is using the latest technology, that doesn’t mean their UX is any good. New technology can be just as horrendously misused as old technology.)

The same goes for implementation time. An analyst that mainly focuses on simple sourcing/procurement where you should just be able to flick a SaaS switch and go would think that an implementation time of more than a week is abysmal, but an analyst that primarily analyzes CLM and SMDM would call BS on anything less than six weeks and expect three months for an implementation time. This is because, for CLM, you have to find all the contracts, feed them in, run them through AI for automated meta-data extraction, do manual review, and set up new processes while for SMDM you have to integrate half a dozen systems, do data integrations, cleansing, and enrichment through cross-referencing with third party sources, create golden records, do manual spot-check reviews, and push the data back . Implementation time is dependent on the solution, the architecture, what it does, what data it needs, what systems it needs to be integrated with, what support there is for data extraction and loading in those legacy systems, etc. Implementation time needs to be judged against the minimum amount of time to do it effectively, which is also customer dependent. Expecting an analyst to understand all the potential client situations is ridiculous. Expecting them to craft an “average customer situation”, base an implementation time on this, and score a set of random vendors accordingly is even more ridiculous.

The factors ARE absolutely vital, but they need to be judged by the buying organization as part of the review cycle, AFTER they’ve verified that the vendor can offer a solution that will meet

  • their current, most pressing, needs as an organization,
  • their evolving needs as they will need to get other problems under control, and
  • do so with a solution that is technically sound and complete with respect to the two requirements above while also being capable of scaling up and evolving over time (as well as capable of being plugged into an appropriate platform-based ecosystem through a fully Open API).

A good analyst an guide you on ways to judge this and what you might want to consider, but that’s it … you have to be the final judge, not them.

That’s why, when the doctor co-designed Solution Map when he was a Consulting Analyst for Spend Matters, the Solution Map focussed on scoring the technological foundations, which could be judged on an objective scale based on the evolution of underlying technology over the past two-plus decades and/or the evolution of functionality to address a specific problem over the past two-plus decades. It’s up to you whether you like it or not, think the implementation time frames are good or not, believe the vendor is innovative or not, and are satisfied with the vendor size and maturity, not the analyst. Those are business viewpoints that are business dependent. Analysts should score capabilities and foundations, particularly where buyers are ill-equipped to do so (and this also means that analysts scoring technology MUST be trained technologists with a formal, educational, background in technology — computer science, engineering, etc. — and experience in Software Development or Implementation –and yes, the doctor realizes this is not always the case, and that’s probably why most of the analyst maps are squished dimensions across half-a-dozen subjective factors [as they are not capable of properly evaluating what they are claiming to be subject matter experts in; as a comparison, when you have a journalist or historian or accountant rating modern SaaS platforms that’s the equivalent of having a plumber certify your electrical wiring or a landscaper judging the strength of the framing in your new house — sure, they’re trade pros, but do you really want to judge their opinion that the wiring is NOT going to start an electrical fire and burn your house down or the frame is strong enough for the 3,000 pounds of appliances you intend to put on the 2nd floor? the doctor would hope not!).

The cynic might say they don’t want to embarrass their sponsors, but the realist will realize the analysts can’t effectively judge vendors on this and the smart analysts won’t even try (but will instead guide you on the factors you should consider and look for when evaluating potential solutions on the shortlist they can help you build by giving you a list of vendors that provide the right type of solution and are technically sound, vs. three random vendors from a Google search that don’t even offer the same type of solution).