Category Archives: rants

Tomorrow is March for Science Day. That IS Important For Everyone.

Why? Besides the obvious that all modern technology is the result of science, you won’t get your next-generation cognitive sourcing platform without more advancement in, guess what, data science.

And, right now, in the US, every year, in addition to having to deal with the introduction, and passing, of more anti-science policies, you also have to deal with the fact that funding for science (education) is diminishing as well and it’s the cornerstone of all progress. What do you think inspires the continual advancement of advanced mathematics and statistics? Scientific need. And where do you think the roots of most of your analytical algorithms come from? Science.

So even though you spend your days slicing data and running reports in the back-office to meet the business goals of savings, reduced inventory turn-around time, reduced, risk, etc. — you’re still using the results of scientific research and progress. Don’t forget that. Or someday Kyle may not be able to flick the internet back on again when it starts to fail. (The sad reality is that because of a lack of science education and knowledge, some people actually believe this is how you fix the internet.)

For more information, see March for Science

We’re In the Midst of Conference Season … What Have We Learned So Far?

There are two conference seasons in enterprise software, Spring and Fall, and enterprise sourcing and procurement falls into this squarely.

Every year, it seems to get crazier and crazier, but what have we learned?

The Bigger You Want to Appear, the Bigger Your Conference Needs to Be

Back in the day, if you were big, you satisfied yourself with a low-key user workshop … so low-key that it might not have even made your website. These days, you do big 3-day affairs, splashed across the relevant parts of the web, and keynote it with the biggest names you can get, whether or not they have anything to do with Sourcing.

The Bigger You Want to Appear, the More Events You Appear At

It used to be that you went to an event or two and splashed your banner, but now you go to every major event — ISM, Procurement Leaders, ProcureCon, SIG, etc — and all their instantiations. You’re on a constant roadshow, because the gospel needs to be spread far and wide.

The More Attention You Want, The More You Focus on Indefinites

Instead of focussing on functions, or process improvements, or knowledge, there is a big focus on value, customer success, or organizational recognition.

In other words, many of the big vendors, who have been pumped up by big PE coffers or IPOs, have apparently used their reserves to lure away the big enterprise CMOs under the assumption that the broader enterprise success strategies will work in Sourcing and Procurement. Their tactics are certainly getting them noticed, but these people are used to selling to IT, Operations, Marketing, Accounting, etc. — everyone but Procurement.

They haven’t yet figured out that Procurement is different.

First of all, Procurement are tough negotiators — they’re not going to pay a penny more than they think the software, and the services (be it implementation, process improvement, or other best practice education) that comes is worth. So unnecessarily boosting overhead by spending money on trade shows that don’t deliver value (because they don’t enable any learning opportunity) or on keynotes that don’t advance the knowledge of the attendees (because they don’t know anything about Procurement) or on drastically overpriced venues doesn’t help their case.

Secondly, Procurement want more than one-way conversations. They want interactions. They want input into the next release and the overall roadmap. And they want to learn as they do it. But these days, many user conferences have done away with the user feedback sessions, even though it’s the perfect place to do it.

It wasn’t long ago the marketers in this space got that. Let’s hope they reclaim their top spots after the new mega cos realize that the enterprise marketers they brought in are missing these fundamentals. Because for our space to advance, everyone has to be smart on all sides.

How Many Billions Are Lost Each Year to Dumb Sourcing?

Today I saw an article entitled E-Sourcing is Dead, Long Live Intelligent Sourcing Systems and all I could say is what parallel world did this article materialize from? Given that we’ve had Strategic Sourcing Decision Optimization with multi-line item support, freight brackets, and carrier support for 17 years, advanced analytics algorithms with smart trend projection and outlier analysis for just as long, and easy access to pretty much all market and public sector buy data in e-friendly countries for over a decade, this should be the case. But it’s not.

We’re not even in a position to say half of mid-size or larger organizations even have anything resembling a modern e-Sourcing solution, and only a small fraction of those have embedded optimization capability, and only a small fraction of their customers actually use it. In reality, e-Sourcing is barely alive and just coming into it’s own. After all, the oompa-loompa empire is only valued at about Two point Five Billion … and in software terms, that’s pretty puny when you consider the market valuations of companies like SAP (approx 107B) and Oracle (approx 220B) … either of these companies could easily buy out the oompa-loompas and put them back in the chocolate factory on a whim! (Which would be a shame since they make great coders.)

But regular readers will know this to be the case, as it’s been SI’s core lament for a decade now — and the market still doesn’t look poised to change. Even though, as SI has stated over and over (and over) again, the average year-over-year savings from the proper application of optimization backed sourcing is 10% across the board. That means if you’re sourcing 105M, that’s 10.5M in savings that could be yours, as soon as you can attack all 100M of spend. If it takes an average of 3 years to get through all spend, that’s 3.5M a year for easy taking. But you’re probably sourcing closer to 1.05 Billion, which means you’re overspending by an average of 105 million, or 35 Million each year. That’s a lot of money, but obviously not enough to take notice.

So obviously we need bigger numbers. How much money is lost in the economy overall each year due to the lack of application of advanced, optimization backed, sourcing? While it’s pretty hard to get a firm grasp on OPEX in the US, and how much of that is addressable by optimization-backed sourcing (as payroll can’t be optimized, only outsourced services, and taxes are taxes), the US Census keeps good data on CAPEX, and in 2015, CAPEX was 1.65 Trillion! Ten Percent of that is 165 Billion. If, and this is an overly aggressive estimate, 10% of that was optimized, that still leaves 149 Billion on the table in the US alone. The US is about one forth of the global market, and assuming CAPEX / OPEX ratios are about equal, this says, globally, that’s about 600 Billion from CAPEX alone left on the table each year because companies aren’t optimizing spend. SIX HUNDRED BILLION. And that’s a lower, lower bound estimate. Is that number big enough for you???

Don’t Get Sucked in By Impressive Words!

It’s conference season, and that means marketing overload for many vendors. And there’s a few words the doctor is hearing a bit too much and he’s NOT impressed! So what are these words?

Digitization

Digital. Digital Procurement. Digitized. Digitized Procurement. Digitization. Ugh. They’ve been using variations of the same word for almost 20 years — and despite claims to the contrary, the meaning hasn’t really changed. You’re analog, or you’re digital. There’s no degrees to digital.

Look at the dictionary definition for crying out loud! Of, relating to, or using data in the form of numerical digits. What’s new, or even enticing, about this? ABSOLUTELY NOTHING!

Internet of Things

The internet has ALWAYS been an internet of things. Computers are not people. They are computers. The only difference today is that we are sticking computers in more things to collect and transmit sensor data automatically rather than reading it, and entering it into the computer. It’s not the big whoop most companies are making it out to be as most companies haven’t developed much that uses that near real-time in a truly useful way.

Cognitive

It’s not artificially intelligent. It’s cognitive. And the bull crap has reached a whole new level. Let’s look at the definition.

Of or relating to the mental process of perception, memory, judgment, and reasoning.

Yes computers can perceive through sensors, store data in memory, use algorithms to assign, or judge, and use very advanced automated algorithms to reason, but we’re overlooking one key word here. Mental. Computers don’t have a mind, and they are not intelligent. The implication here is that which is cognitive is intelligent, and they are not intelligent.

We haven’t even reached true AI yet in any field and we are supposed to believe that a little Sourcing or Procurement vendor has reached the next, cognitive level of AI development? While a best in class vendor may have a few algorithms that are almost cognitive for a few, select, situations, considering the billions going into AI research and the limited progress most specialist vendors are making, you know we’re not ready to be throwing this term around.

And, an honorable mention (because, while not common in our space yet, it’s coming):

Postmodern

the doctor‘s been seeing this word a lot on social media in marketing and commentary, and, unfortunately, it seems like it’s starting to creep into our space. For those of us that actually went to a real University and have a sound (classical) education, we know that Postmodernism is a rather broad intellectual movement across the arts and fields with applied arts (like architecture and archaeology) based on a philosophy that takes us from the literary-influenced philosophy of modernism to a post-modern way of thinking that developed in the middle of the last century and reached wide acceptance in the 1980s, when it was a Land of Confusion.

This was the time of the MRPs (and not the ERPs). Do we really want to be associating our new and innovative solutions with that era?

So please, please, please don’t get sucked in by the the impressive words. Instead look for impressive, time-saving, value-adding functions (and forget the feature lists). (But that’s another rant.)

Keep Your Self Driving Car. I’ll Still Choose Good Ol’ Alfred Every Day of the Week!

As the doctor pointed out back in 2014, calling #badwolf on self-driving cars is well-founded. Just last month we had more accidents involving self-driving cars (from Tesla and GM) where a Tesla “ploughed into the rear” of a fire engine in Culver City and where a GM car collided with a motorcycle in San Francisco.

And when you get injured, as in the case of the motorcycle driver, who do you sue? If the car is self-driving, then there’s no driver, just source code. Source code isn’t an entity, so all you’re left with is suing GM, as the cyclist whose motorbike was hit with the GM car is doing (as per this article in Engadget and this article in Popular Science). But is it the company? When technically it’s the software — written by who knows how many employees who used who knows what from open source to speed up development, which was again contributed to by who knows how many authors?

But you can’t sue software, it’s not an entity, at least not a legal one, and that can’t happen at least until we grant it intelligence … and the right to own assets. So, it’s GM, but are they liable under the law? And, if not, how can the individual in the vehicle, not driving, be held liable?

And what happens if the “AI” becomes artificially intelligent and decides to “improve its own code” or the code gets co-mingled with the company’s “sentiment analysis” technology and all of a sudden gains a strong “dislike” for the self driving cars of the competition and, using it’s limited action-reaction processing algorithms, determines the best course of action is to “crash into the competition cars”. What then? We’re driving cars with a “kill” switch we have no control over!

And we’ll never know if there is one! With 99M+ lines of code in an average self-driving car OS, how would you ever find the kill switch until it triggered? And if it triggered en-masse, all of a sudden we have Maximum Overdrive on a global scale! Are you ready for that? the doctor is not!