Category Archives: SaaS

Enterprises have a Data Problem. And they will until they accept they need to do E-MDM, and it will cost them!

This originally published on April (29) 2024.  It is being reposted because MDM is becoming more essential by the day, especially since AI doesn’t work without good, clean, data.

insideBIGDATA recently published an article on The Impact of Data Analytics Integration Mismatch on Business Technology Advancements which did a rather good job on highlighting all of the problems with bad integrations (which happen every day [and just result in you contributing to the half a TRILLION dollars that will be wasted on SaaS Spend this year and the one TRILLION that will be wasted on IT Services]), and an okay job of advising you how to prevent them. But the problem is much larger than the article lets on, and we need to discuss that.

But first, let’s summarize the major impacts outlined in the article (which you should click to and read before continuing on in this article):

  • Higher Operational Expenses
  • Poor Business Outcomes
  • Delayed Decision Making
  • Competitive Disadvantages
  • Missed Business Opportunities

And then add the following critical impacts (which is not a complete list by any stretch of the imagination) when your supplier, product, and supply chain data isn’t up to snuff:

  • Fines for failing to comply with filings and appropriate trade restrictions
  • Product seizures when products violate certain regulations (like ROHS, WEEE, etc.)
  • Lost Funds and Liabilities when incomplete/compromised data results in payments to the wrong/fraudulent entities
  • Massive disruption risks when you don’t get notifications of major supply chain incidents when the right locations and suppliers are not being monitored (multiple tiers down in your supply chain)
  • Massive lawsuits when data isn’t properly encrypted and secured and personal data gets compromised in a cyberattack

You need good data. You need secure data. You need actionable data. And you won’t have any of that without the right integration.

The article says to ensure good integration you should:

  • mitigate low-quality data before integration (since cleansing and enrichment might not even be possible)
  • adopt uniformity and standardized data formats and structures across systems
  • phase out outdated technology

which is all fine and dandy, but misses the core of the problem:

Data is bad (often very, very bad), because the organizations don’t have an enterprise data management strategy. That’s the first step. Furthermore this E-MDM strategy needs to define:

  1. the master schema with all of the core data objects (records) that need to be shared organizational wide
  2. the common data format (for ids, names, keys, etc.) (that every system will need to map to)
  3. the master data encoding standard

With a properly defined schema, there is less of a need to adopt uniformity across data formats and structures across the enterprise systems (which will not always be possible if an organization needs to maintain outdated technology either because a former manager entered into a 10 year agreement just to be rid of the problem or it would be too expensive to migrate to another system at the present time) or to phase out outdated technology (which, if it’s the ERP or AP, will likely not be possible) since the organization just needs to ensure that all data exchanges are in the common data format and use the master data encoding standard.

Moreover, once you have the E-MDM strategy, it’s easy to flush out the HR-MDM, Supplier/SupplyChain-MDM, and Finance-MDM strategies and get them right.

As THE PROPHET has said, data will be your best friend in procurement and supply chain in 2024 if you give it a chance.

Or, you can cover your eyes and ears and sing the same old tune that you’ve been singing since your organization acquired its first computer and built it’s first “database”:

Well …
I have a little data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

Oh, data, data, data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

It has nonstandard fields
The records short and lank
When I try to read it
The blocks all come back blank

I have a little data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

My data is so ancient
Drive sectors start to rot
I try to read my data
The effort comes to naught

Oh, data, data, data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

666+ S2P+ Solutions … But Key Problems Are Still Not Addressed!

You’ve seen the Mega Map and the 666 solution logos on it.

You’ve heard the doctor and THE REVELATOR say repeatedly that another massive purge is coming to our space over the next 18 to 24 months (which will be the greatest since 2009-2011 where hundreds of companies were acquired, merged, or went insolvent), and that it’s already starting (with a few notable insolvencies, at least as far as the doctor is concerned, already occurring).

You’ve heard us say that there isn’t room for this many companies because even if you account for market size and vertical, we still only need so many solutions of the following varieties:

  • Sourcing
  • Supplier Management
  • Spend Analysis
  • Contract Mangement
  • e-Procurement
  • Invoice to Pay (I2P) / Accounts Payable (AP)

And even when you consider the wide variety of needs across all possible size – vertical -region combination, two to three dozen solutions in any category is more than enough to handle all of the complexities when you take even the most varied companies into account, but we now have over a hundred options in some of these categories. Only the strong, sorry, the smart, will survive … and only if they have enough money to do so (and enough control to make smart decisions, i.e. if they are controlled by greedy investors who double and triple prices that force them out of their target market, they will be the next casualty).

But even with all these solutions, core needs are not met. The reason being: in today’s business environment that is seeing a return to protectionism, sanctions, and border closings; a continual rise in natural disasters (thanks to global warming that will once again reign unchecked under administrations coming into power in multiple “first world” countries); and a continual disruption in logistics (due to epidemics, pandemics, reduced capacity, Panamanian droughts, and Houthis in the Red Sea), solutions are needed that go beyond siloed Procurement.

Back in 2022, THE PROPHET first tried to get the message out there with his proclamation that alt-suites would rise. (They still haven’t, but we do need new types of cross-functional applications.) He also made five predictions. They varied in terms of usefulness and vision (in the doctor‘s view, two in particular are desperately needed, although one of these needs to be broader than defined; one is nothing more than just an enhanced dashboard across various S2P applications and needs to be rethought, and two aren’t quite right [but contain ideas that can be built on]).

But THE PROPHET was right in that we need to rethink Procurement Technology in some organizations, who needs to contribute to Procurement, and how Procurement Process fits into overall operational processes. The solutions that worked for the last 20 years aren’t always enough anymore, and it’s not just a question of “intake” (which is not new despite what the providers will have you believe, see our prior posts on the subject) or “orchestration” (which is just a fancy term for SaaS middleware).

Here are three solutions that are needed now more than ever:

1. Design for Supply (DFS)

THE PROPHET was right on the money here. Not only is 80% of the cost locked in during design, but so is 80% of the risk. You not only need cost control, but you need supply assurance. This means that R&D needs to work with Procurement during design to ensure the products can be sourced affordably at low risk, and that Procurement needs to work with Supply Chain / Logistics to make sure the products can be reliably sourced in a timely manner (and the organization won’t have to stock months and months of inventory). Product design and development organizations need integrated DFS solutions that span R&D, Procurement, and Supply Chain.

2. Supply Chain Sourcing (SCS)

In the world of Direct, when organizations need to source for BOMs (Bill of Materials), they need to do it Supply Chain Aware. Under pressure, Procurement will always search for the lowest cost — but what if that is from a supplier in an unstable region; that is not part of the current, optimized, supply network; that can’t offer timely and secure delivery? Sourcing needs to be supply chain aware. And Supply Chain needs to be aware of what Sourcing is looking at so they can do network planning if the current supply network is not sufficient.

In fact, it would be even better if the DFS and SCS solutions were hosted on the same underlying platform.

3. Risk 360

This was the second platform where THE PROPHET was almost right on the money as well with his Assess-to-Monitor alt-suite. Risk is everywhere, both inside and outside the organization, inside and outside your partners’ organizations, inside and outside your suppliers’ organization, and its everywhere your physical, financial, and digital supply chains touch. Supplier risk, supply chain risk, cybersecurity risk, personnel risk, etc. can’t all be separate solutions. They need to be one integrated platform that constantly monitors, assesses, and protects your organization.

There are, and will continue to be, a need for new solution types, in S2P+, but these would be a great start!

It’s Not AI (First,Led,Powered,etc.) or Autonomous. It is Solution with Augmented Intelligence!

By now you know our stance on Gen-AI (and how it should be relegated to the rubbish heap from which it came) because it’s not about “AI”, it’s about outcome. And outcome requires a real, predictable, usable solution that helps Human Intelligence (HI!) make the right decision. Such a solution is one that uses tried and true algorithms that support tried and true processes that provide a human with the insight needed to make the right decision at the time, every time a decision needs to be made.

This requires a solution that walks the human user through the process, step by step, and presents them with the information required to make a decision as to whether to progress to another step, what the next step is, and any conditions that need to be put on that next step. This requires a solution that automatically runs all of the typically relevant analysis, on all of the available data, and presents the insight, along with any typical decisions (as [a] default recommendation[s]) made on any similar situations that can be found in the organizational history.

Automation should only occur in situations the organization has defined as acceptable according to well defined, human reviewed, and verified rules. Not default vendor rules or unverified probabilities or unverified random computations from a random algorithm. A good solution is one that walks a user through the process, often allowing each step to be completed with a single choice or click. It’s not one that makes the choice for the user, which may or may not be the right one, but one that helps the user makes the right choice. It might seem like a subtle difference, but it is a very important one.

Even though an AI-powered autonomous solution might seem to make the right decision over 90% (or 95%) of the time, it doesn’t mean it actually is. If it looks right, it might be a good decision, but it doesn’t mean it’s a good decision for the organization at the time, or the best decision that can be made. Only human review, at the time, can make that decision. A good solution runs all the analysis it can, summarizes the results, and lets a human verify the data for any recommendation made by the system.

To better understand the the subtlety, consider a situation where the organization lets the system automatically re-auction all regularly purchased products and commodities for manufacturing or MRO where the price is typically constant over time using a lowest bidder takes all e-Auction that results in the auto-generation and auto e-Signature of a one year contract. Now, most of the time this is probably going to work okay, but imagine you let it run on full auto-pilot and in the e-Auction queue is your regular RAM contract that expired three days after a major RAM plant factory fire (that happens about once every decade if you trace back through the last forty years), and prices have just skyrocketed about 50%. Prices which would drop back down as soon as the plant comes back online in three months. Locking in a full year contract would result in excessive cost overruns on the items for almost nine months longer than necessary, instead of just three months or so. A human would know to buy the bare minimum on the spot market at overly inflated rates and wait until the market stabilized before running an e-Auction to lock in the next contract. But a system told to just re-auction and re-order at every contract expiration would do this that. It wouldn’t know that the current market rates are just temporary, why, and how to change course. This is just one example where over-automation and AI will lead to failure without Human Intervention.

A good system presents the user with the products/commodities that are typically automatically auctioned, the history of costs, the current market costs, the recommendation for auto-sourcing and term, the expected results, and whether the recommendation is for the auction to auto-award and contract or, when the auction is complete, pause and include a human in the loop to make a final decision. A well designed system minimizes the work and input required by a human, eliminating all the tactical data analysis and e-paperwork, making it easy to make the right strategic decision without a lot of effort. Technology isn’t about trying to replace human intelligence (which it can’t), but about eliminating unnecessary drudgery or computation (“thunking”) that humans are not good at (or don’t have the time for), so that humans can focus on strategic decisions and value add.

That’s why the right answer is always a solution with augmented intelligence. Not autonomous AI solutions.

You Should Never Build Your Own ProcureTech Solution! Ever!

Integrate your own custom suite to suit your processes, maybe, but never build from scratch. (And we should not have to be talking about this again after just publishing on the subject two weeks ago, but too many conversations are indicating that we still need to shout this loud and clear!)

For some reason, this comes up every decade, usually after a hype cycle has peaked, marketers have switched from focussing on solutions to sound bites from a suite of providers who have released products that don’t meet customer needs, the implementation failure rate has edged back up to the 80%+ range, and customers have gotten absolutely positively fed up with the whole situation.

Customers, fed up with the valueless hype, marketing sound bites, high failure rate, and utter lack of solutions from the vendors targeting them on a daily basis, start to think that the right solution is to build their own.

Sourcing Innovation tackled this subject in depth back in 2015 when it wrote a 4-part series on why you should NOT build your own e-Sourcing solution, followed by an explanation of why you should not build your own Contract Management and e-Procurement platform. (links here)

That’s why we are both repeating and elaborating on last Friday’s Rant on why A Company Should Never Build It’s Own Enterprise Software Systems.

Not only do we have the situation where:

  • the company is not an expert in building software products
  • the company is not an expert in best practices across all of its processes
  • by the time a custom solution is developed, it’s out of date
  • it’s not about the product, it’s about the process you should be working toward and, most importantly,
  • it’s about the data that drives the process!

But we have the situation where, as highlighted in THE REVELATOR‘s article:

1. Developing your own is NOT being an early adopter! (Which is what many companies considering build-your-own think they are.)

Early adopter means someone who adopts leading edge technology from a third party, not someone trying to fast track their digitization effort with custom built tech. This is just high risk with little chance of reward for all the reasons mentioned in all of our prior articles.

2. They think Gen-AI will fix their data problem and allow them to develop their own!

If you’re read anything on Gen-AI on this blog you know that’s the last thing it will do. For Gen-AI to have any chance of working at all, it needs a huge amount of good, clean, data. Otherwise, it’s garbage in, hazardous waste out. No technology has ever needed such large amounts of near-perfect data to have even an abysmal chance of working, and the fact that the marketing madness has convince many CPOs that Gen-AI can fix a data problem is downright terrifying!

3. They obviously think that the initial quote will be close to the final cost.

No where are cost overruns more extreme than in custom development by a non-software organization that contracts a Big X with poor specifications that look easy, and that, due to lack of manpower, sends The C-Team (if you are lucky) because it’s just another instance of system X (when it’s not).

To be honest, in this situation, if the costs ends up being only 3X to get something usable (but still not what you wanted), given the high technology failure rates, that would be amazing.

We know it’s hard to find appropriate solutions given all the noise out there, and the overabundance of vendors that all look, sound, and go all in on useless Gen-AI the same, as it just takes one glance at the Mega Map to figure that out, but that doesn’t mean there aren’t vendors out there appropriate for you. Vendors that put solutions, not tech first, that built affordable tech that works (and didn’t take too much money from investors who then insisted on quadrupling the price), and that will work in an ecosystem with out vendors to solve your problems.

You just have to look hard. Real hard. Probably harder than you’ve ever had to look before. (Expect to eliminate 6 out of every vendors you look at for short list consideration and probably go through 20 to find 3.) But trust us, when you find the right vendor, it will be worth it. The solution will work, will configure to your liking, will be extremely usable for the problems your team faces every day, and will be one where the provider will grow with you for the decade to come.

Good things come to those who wait to find the right vendor. (Even if they have to crawl through multiple pig sties to do so.)

Dear Enterprise Software Vendor: Should You Fire Your PR and Marketing?

Note the Sourcing Innovation Editorial Disclaimers and note this is a very opinionated rant!  Your mileage will vary!  (And not about any firm in particular, as a few non-isolated incidents opened up a whole new line of questioning.)

In response to a post by eCornell (which is/was here), THE REVELATOR wrote this comment (which is/was here) which is repeated here in its entirety in case it gets deleted, since anytime we tried to have a serious conversation around sales, marketing, public relations, and/or Gen-AI with Big X firms and/or (mid-sized) consultancies and analyst firms, they have quickly deleted our comments, and sometimes their entire posts rather than enter into a real conversation on the subject (and now we have developed an implicit distrust any corporate account and keep copies of everything):

NOTE: The following post was inspired by a comment by Paul Rogers

Despite feeling like someone walking the hallowed halls of Cornell University wearing a “Yeah, Harvard University” t-shirt, sometimes you have to say things that need to be said – which is the purpose of sharing this article.

Ask ChatGPT the following two questions:

? What is the role of the Public Relations professional?
? What is the role of the Marketing professional?

Do you see any mention of end client or customer success as a priority? Whose best interests are PR and marketing professionals focused on? What does the answer to these questions tell you?

Corporate communication has always been about putting a positive spin on business and the brand. It reminds me of the 1986 Richard Gere movie Power – if not a great movie, it is certainly interesting and engaging. Denzel Washington’s role as public relations expert Arnold Billings is worth the price of admission alone.

Unfortunately, beyond the company they represent, are PR and marketing people doing more harm than good?

Thoughts?

To which the doctor responded (which is/was here)

Well, SI, which has repeatedly told companies in our space to fire their PR firms going back to 2008: Blogger Relations, firmly believes that PR firms are doing more harm than good because

  1. you are NOT selling enterprise software to consumers and
  2. it’s not “image”, it’s “solution”!

As for marketing, corporate marketing can be good if it exists to educate and explain, but when was the last time that happened on a regular basis in our space? Over a decade ago … now it’s all AI-this, orchestrate-that, and whatever the bullcr@p of the day is. It’s all buzz, no honey. All show, no substance. All confusion, no clarity. (It’s bad enough that Trump has brought back the Land of Confusion with his populist politics that have taken by storm the first world over, we don’t need it in our workplace!)

So, right now, I’d say at least 6/7, if not 9/10, marketers are doing more harm than good and should be fired with their PR brethren.

There are over 666 companies in our space, and way too many pandering any type of solution you can think of. While we need at least 3-5 in each industry group – market size – geo region – module focus you can think of for competition, we don’t need 30+. Most are not going to survive, especially when most of these don’t have solid solutions built from years of experience that solve real customer problems (as opposed to just offering some shiny new tech that looks good but doesn’t solve the majority of pain points in real organizations).

This means that companies need to focus less on marketing and selling and more on:

  • market research, especially listening to what the real pain points are of the customers they want to sell to (and they need to focus in on a customer group here, you can’t be everything to everyone in our space and any company that thinks it can is the first company you should walk away from)
  • solution (not product) development — not shiny new tech, tried-and-true tech that works
  • market education, explaining what they do, how they do it, and why it solves real pain points after building a solution that solves the pain points they identified in their research

Which means, especially if money is tight, they should forget the marketers and instead focus on hiring researchers and educators. People are getting tired of the 80%+ tech project failure rates. They’d welcome some real insight and real focus on real solutions. If only the market would wake up and realize this!