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Can you tell what’s wrong with this picture?

Bloomberg predicts Gen-AI will be a 1.3 Trillion market by 2032.

MarketResearch predicts the Procurement Software Market will be worth 17.6 Billion in 2032.

Give up? The answer is simple. ????????????????????????????????????????!

Every single business needs to procure. Every single procurement department in every single business is being crushed under the weight of compliance requirements, risk assessments, logistics delays, supply chain interruptions, auditability requirements, DEI requirements, quality requirements, budget constraints, etc.

???????????????????? ???????????????????????? ???????????????????????????????? ???????????????????? ???????????????????????? ???????????????????????????????????????????? ????????????????????????????????.

In comparison, ???????????? ???? ???????????????????????? ???????????????????????????????? ???????????????????? ????????????-????????!

Companies have survived just fine without it for thousands of years. There’s yet to be a single use case that provides value and does so reliably. (Maybe a few for specialty tailored LLMs, but not Open-AI Gen-AI.)

Seriously think about this!

Surviving the coronavirus crisis for physical small businesses: Take a lesson from creators! (Part 2)

As we made clear in Part 1, two general categories of business have been hit hard by the coronavirus shutdown: services and non-essential products. Your business is likely already online to some degree — but now’s the time to go all in on e-commerce, or at least all in on social media, and reach your customers via virtual means in the electronic showroom. For physical shops that sell goods, we addressed in detail ways that you can boost sales by going online in Part 1.

But that leaves services, which is a much tougher category as some businesses, regrettably, won’t survive, and others will only scrape by with massive layoffs in the interim, and then only if they can still partially operate. However, this doesn’t mean that the owners or disenfranchised workers can’t either find alternate means of employment/self-employment or set themselves up to bounce back in the future. (We’ll address what the disenfranchised can do in Part 3.)

The services category of business includes, among other categories:

  • Restaurants (which in some jurisdictions are permitted to stay open just for take-out service)
  • Non-essential healthcare (cosmetic procedures, nutritionists, etc.)
  • Personal services (child care, barbershops and hair salons, gyms, tattoo parlors, etc.)
  • Bars and coffee shops
  • Entertainment venues & galleries
  • Recreational facilities

And while everything looks bleak, some of these business still have hope (as do some of the staff displaced if they take a different view on their abilities and career).

What hope? What can they do? For the answers, read the doctor‘s full article over on Spend Matters to find out!

20 Analytics Predictions from the “Experts” for 2020 Part II

In our last post we started reviewing 20 analytics predictions being peddled by the major analytics futurists and analytics sites. Why? Because while overly optimistic futurist authors rarely get it right, their predictions do point out two things. What should be done — and isn’t getting done — and where the space needs to go.

And even though 19 of these anti-predictions won’t (fully) come to pass this year, we started reviewing them one by one to give you a reality and indicate what is likely coming sooner than later, and what is still a pipe dream. Most of the predictions we reviewed yesterday were those that fell into the “aren’t happening” or “aren’t really happening at all” (because they are more of the same old, same old) buckets, but today we get to some that will start to materialize and the one, yes one, that is 100% true — and that you need to be fully aware of.

So settle in and let’s finish this.

AI becomes more mainstream

Well, acceptance of AI will continue to become more mainstream, but considering that most “AI” providers are actually providers of “Artificial Indirection” and have no AI at all, not even at the level of “Assisted Intelligence”. Most providers of “AI” are just providers of RPA (robotic process automation) at-best, and a configurable rules-engine at worst.


A few vendors are offering multi-hybrid analytics solutions, and a few more will, but there will be nothing new. It will be one solution for integrated in-platform analytics, another for do-it-yourself analytics, and possibly an in-house developed third for database management and cube construction. But there’s going to be no significant changes here — most practitioners are going to use what their vendors give them.

Analytics will become usable by business analysts

Well, this one is half true. With recent advances in user interfaces and usability, it will become more usable … but … only to the better half of the business analysts … and … only with training. And this is where this particular prediction fails. Training has been high on the priority list for a decade, and it’s also been high on the “cut when budgets need trimming” list for a decade as well. There will be little to no training as per the norm, so only the most dedicated will self-learn and use it.

Data governance takes centre stage

This prediction is likely to come sooner than you might think, but not in 2020. Until there is a big cost associated with the lack of data governance, like training, it’s going to remain high on the priority list but not going to get centre stage. This will only change when lack of governance risks a huge fine or a large organization loses a major court case with a large judgement that was the result of lack of governance (which resulted in data exposure) which could have happened to any governance.

AI ethics standards will emerge

We all wish this will happen, but as with data governance, until a large organization loses a discriminatory court case as a result of an AI decision, and the court holds the organization responsible for that AI decision, no one is going to put any real effort, beyond lip service, into AI ethics. At least from a vendor perspective. A few lawyers hungry to make a name for themselves might, but that’s about it.

Analytics will hit the C-Suite

Re-set the woody woodpecker laugh track. If the average business analyst is not going to get much more involved with analytics, then you can bet the average C-Suite executive is not going to get much more involved either. They might get better reports and dashboards, but that’s it.

Intelligent assistants that connect the dots will become more pervasive

This is another half-truth. “Intelligent assistants” that allow a user to interact with the application in natural language, and especially English, will continue to infiltrate S2P platforms, but as to connecting-the-dots … not likely. That will require true embedded machine learning technology, and that’s still far away for the average provider.

Open source is going down the drain thanks to cloud platforms

This is yet another half-truth. While it is true that as more and more providers lock into a cloud platform (such as Azure, Microsoft, and Google) they will lock into whatever analytics are provided in the platform, this is not going to stop open source efforts — although uptake may trickle off for a while.

Effective implementation will continue to be a challenge

This is mostly true. Effective implementation will continue to be a challenge for the majority of organizations, and only a few best-of-breed providers will see the challenge of effective implementations decrease. As data continues to proliferate, especially considering the average quality of data, analytics will continue to get more challenging on the whole.

And now, finally, the one prediction the doctor found that is 100% accurate.

Companies will continue failing analytics & AI transformations

This is absolutely true. Considering that analytics requires good data and AI requires lots of good data, good algorithms, and experts to guide the algorithms, and most companies have poor data, poorer algorithms, and a dearth of experts … and often rely on vendors who peddle applied indirection, the doctor expects a big uptick in failures until the space educates themselves on what AI truly is, what the levels are, what is actually out there, and who is actually offering it.

For details on what the levels are, and what is coming, keep your eyes on SI and SM, and if your organization has been smart enough to subscribe, check out the doctor‘s pieces over on Spend Matters Pro on AI in Supplier Discovery, Sourcing, Optimization, Procurement, and Supplier Management.

AI in Procurement: [Spend Matters Pro subscription required]
Today Part I,
Today Part II
Tomorrow Part I,
Tomorrow Part II,
Tomorrow Part III
The Day After

AI in Sourcing: [Spend Matters Pro subscription required]
Tomorrow Part I,
Tomorrow Part II
The Day After

AI in Sourcing Optimization: [Spend Matters Pro subscription required]
The Day After Part I,
The Day After Part II

AI in Supplier Discovery: [Spend Matters Pro subscription required]
The Day After

AI in Supplier Management: [Spend Matters Pro subscription required]
Today Part I,
Today Part II
Tomorrow Part I,
Tomorrow Part II
The Day After

How Do You Know If That SaaS is Priced Right?

As per our recent post on What is that Platform Worth?, SaaS is good, but only if you get an RoI from the subscription license fee. So how do you know if that SaaS platform is priced right for you?

Six years ago we ran a post on Good SaaS vs. Bad SaaS where we focused on some of the key non-functional characteristics that should be examined in your SaaS purchase process. Six years have past, and they still haven’t really changed. In summary,

Good SaaS is Bad SaaS is
focussed on value sold on cost
has RoI models and plans to achieve them talks about process improvements and associated cost reductions
is designed to support business cases is focused on manpower reduction
has offerings and prices applicable to different customer sizes has a one-size-fits-all offering and pricing scheme
competitively priced for what you need priced out of the ballpark

Breaking it down, a good SaaS vendor comes in with a proposal that

  • competitively prices the solution based upon a value model that
  • demonstrates a realistic realizable ROI based upon an
  • appropriate implementation plan that not only addresses
  • process and workflow improvements that will result not only in manpower reduction and cost reductions but
  • increased throughput and improvements that will increase the overall value Procurement contributes to the organization.
  • And the vendor will be able to help you summarize all of this in a business case customized for your organization.

    It’s about your needs, not their optimal sales process / price-point.

Purchasing Blues (Repost)

It’s the first day of summer, so:

Click Here to sing along!

Well, it’s time to raise a fuss
and it’s time to raise a holler
About diminishing returns
from the corporate dollar
I just heard from my boss
who governs me
If I don’t save the cash
he’s gonna fire me

Sometimes I wonder
What I’m gonna do
If there ain’t no cure
For the purchasing blues

The buyer he told me to
go beat on the supplier
That his margins must be high
with ours under the wire
So I talked to the supplier
he said that costs were elevated
He was losing all his money
at the rates we had created

Sometimes I wonder
What I’m gonna do
If there ain’t no cure
For the purchasing blues

So I found a consultant
told her ’bout my problems
She discovered that
the supplier was just stalling
Material costs were falling
and the exchange rate was fair
I had wasted all my time
just pulling out my hair

Next time I have a problem
I’ll find me a solution
I’ll find a sourcing expert
and get my retribution

No more will I wonder
What I’m a-gonna do
I’ll find me a cure
For the purchasing blues