Category Archives: Technology

Seventy Years Ago Today …

John Bardeen, Walter Brattain, and William Shockley invent the point-contact transistor (when they first observed the effects) and pretty much paved the way for the modern electronics revolution as the transistor is the fundamental building block of modern electronics technology.

As defined by Wikipedia, a transistor is a semiconductor device (with at least three terminals) used to amplify or switch electronic signals and electrical power. A voltage or current applied to one pair of terminals controls the current through another pair of terminals. When they are combined in integrated circuits, as they normally are today, they can create logic gates, and that’s the fundamental building block of modern computers. (The other primary components of an integrated circuit are diodes, resistors, and capacitors.)

Without transistors, we’d still be computing using vacuum tubes using machines that take up entire rooms and only using computers for mathematical calculations. The inventors were truly deserving of their nobel prize.

Procurement Innovation The Day After Tomorrow

This week has been all about Procurement Innovation and how maybe it’s a good thing that They Terk Er Jerbs! as the only jobs that are perfectly suited for software and robotic automatons are those that we really don’t want to do. Let them match line items. Let them scan barcodes. Let them push e-paper all the live long day. No one writes folk songs about the paper drivin’ man, so they can have the damn e-paper.

But they won’t stop at automatic e-paper or transaction mapping or even invisible buying. They will go deeper. They will go broader. They will take all that can be taken with computation alone. Wherever true intelligence is not needed, they will emerge. So where else will they emerge?

Software and the machines will be everywhere, in every job, and they will be there all the time. 24 / 7 / 365. They won’t be able to do everything, but they will be everywhere. In a presentation last week, the doctor covered a dozen different areas we’ll see them today, tomorrow, the day after tomorrow, and the day after that … just in Procurement alone. And these weren’t all the examples. We won’t cover them all in this blog (and if you want to know them all, keep your eyes out for an upcoming talk), but we will cover one today.

Specifically, once invisible buying is out of the way, one area they will considerably invade the average Procurement organization is through tail spend minimization. Not only will invisible buys take a chunk out of organizational tail spend, but all of that calculation will also identify

  • other buys that fit the MRO / regular re-order pattern that should be put under contract / rate card and left to invisible buys
  • buys that are becoming significant and should be analyzed for strategic sourcing

Not everything will fit in these 3 categories, but a big chunk will … and then further enhancements will take more and more out of tail spend until it becomes a vanishingly small part of organizational spend compared to what it is today. So watch for the future, it’s coming faster than you think.

They Terk Er Jerbs! Good for them.

Because, if they were intelligent, if they weren’t already insane, they would be! One definition of insanity is doing the same thing over and over and expecting different results. But an even better one is wanting to do the same mind-numbing task over and over and over again until anyone with a modicum of intelligence would go insane.

Like screwing the same rivet 10,000 times a day. Walking up and down the same 20 aisles looking for sold out products day after day. Or performing well-defined calculations millions and millions and millions of times. This last task is something good accounts payable and procurement folk have to do over their career without AI if they want to realize the savings they should.

I say let the machines do that. And then find ways to do more intelligent actions with the results that the machines can’t do. That’s Procurement Innovation. And if you were on the ball and set up your Google Alert and noticed that the doctor was in L.A. yesterday giving a talk on Procurement, and, more specifically, Procurement Innovation. Procurement Innovation that is going to arise when you let the machines do the tactical drudge work and focus on the more strategic aspects of product acquisition. And give yourself time to get innovative … and creative … instead of just pushing virtual buttons all day. (In some P2P systems, it takes 15 clicks to actually get a product delivered when it should take 0. And how many products do you need? It’s amazing you aren’t insane! Someone should calculate the mental strength and willpower of a Procurement professional. That would be an interesting study.)

One needs to remember that AI is not I, but it is A. It is artificial, and it is extremely well suited to running lots of advanced calculations against expert defined models, well-defined variables, and big data sets to identify opportunities, outliers, and options for pursuit even the smartest of us couldn’t see because our mental calculation powers stop in the ones per second while a typical laptop’s calculation capacity is in the millions per second. Even if the best algorithms we have are, relatively speaking, dumb, the machine will outperform us in evaluating data against models and desired outcomes and identifying the best directions to pursue (which is different than being able to evaluate the perceived best options and actually pick the best ones).

And because of this, it is extremely well suited to checking invoices against POs, goods receipts, and contracts — which is one key to making sure the savings that are negotiated are actually captured. The best I2P systems today with advanced OCR can reach invoice processing accuracy (IPA) levels of 98% with no human intervention, including automatic return to supplier if issues are identified, and the proper configuration of rules can enable up to 100% of these automatically processed, corrected, and confirmed invoices to be automatically queued for payment (and paid). Considering that the average invoice “error” rate in an organization is 10% to 15% and that this typically results in overpayments of 1.5% or more, automatically processing 98% of invoices and eliminating 98% of the errors is huge.

And it’s a key component of two of the innovations — true automation and overspend prevention — that the doctor highlighted in his talk that can be addressed today, and tomorrow, and change your work, and even your life. (When you work smarter, you will get smarter.)

They Terk Er Jerbs!


Now that the age of the robots are here (and this can’t be denied as the robots are in Walmart now [Source: Reuters]), will you be the next to join Darryl Weathers’ crew in screaming that they took your job?

Or will you welcome their entry into the workforce and their willingness to do the work you don’t want to do and take the opportunity to (learn to) do something better and more interesting and, frankly, more intelligent.

Face it. You don’t want to check inventory. It’s boring. You don’t want to apply the same rivet all day on the production line. It’s boring. And you certainly don’t want to harvest [as evidenced by the fact that most farms can't find enough domestic workers during harvest season to do the same boring task minute after minute, hour after hour, and day after day during harvest season].

But you’re sometimes willing to actually stock shelves — organizing a display can be mildly creative, and you would probably rather help someone find a product and have some form of personal interaction than scan shelves for products people may or may not want. You’re probably also more willing to do quality testing on the outputs of the production line than construction, at least that’s verification of quality and a bit of creative destruction, and you’d probably be even more willing to review design aspects and even assist in prototype development if the company gave you a bit of training. Etc.

Robots will take jobs, but the jobs these artificially intelligent machines take are not always the interesting jobs, and there are jobs they can’t take. They are not truly intelligent, and as a result they can’t truly anticipate what we will want, they can’t create new works of art without guidance, and they can’t always read our mood and feelings, especially if we are not being forthcoming about it. Yes they can predict based on trends and be right a lot, but this means they can also be spectacularly wrong. And when it comes to quality, they can’t test for anything they haven’t been programmed to test for. So if a product had a major usability design flaw, as long as it passed the material stress tests, the robot would never know.

There may come a day when they are almost as good at us at design, creative, and social jobs, but that’s still a ways off. For now, we can at least be content in the fact that while they take some jobs, they can’t take all aspects of those jobs and we can create new job definitions that expand upon what they can’t do. We will have to keep learning, and truly work smarter, but screaming They Terk Er Jerbs won’t get us anywhere (as it hasn’t since the dawn of the industrial revolution). So, for now we can take solace in the fact that we can create a two-tier society: us, and them, and relegate them to the lower tier, as long as we don’t grant them citizenship! (Even pretending to is too much!)

And use them, and advanced software, to do our jobs better! Even in Procurement. How? Stay tuned.

None of Us is as Dumb as All of Us! Unless, Of Course, You Include AI!

the doctor sees a lot of unsolicited pitches hit his inbox each and every day. Since SI does not cover press releases (since he just does not give a damn about your meaningless marketing sound-bites which do little to nothing to advanced education and technology) he ignores most of them. But this week he saw one of the most ridiculous headlines ever:

Can AI Harness the World’s 2 Billion Social Media Influencers?

Ignoring the fact that that the headline is factually incorrect (there are 2 Billion Users, NOT Influencers), this is one of the dumbest questions ever posed and anyone who understood anything about the state of AI today would not even want to ask it!

Generally, if you are going to train AI, you want to train AI on expertise. And where’s the last space you’d expect to find expertise? That’s right! Social Media.

But that’s just the tip of the why-you-should-not-do-this iceberg! If you include everyone, you not only include everyone of above average intelligence, but everyone of below average intelligence by very definition. So while you will have a few geniuses, you will also have morons, imbeciles, and possibly even idiots (as per the original Binet IQ scale). Do you really want them training your AI?

Moreover, what do people share on Social Media? Their most brilliant ideas? Well developed arguments? Philosophical contributions? Wisdom? Profound insights? Or pictures. Comments on politics. Viewpoints on pop culture. Their thoughts of the moment. Complaints. Rants. Digs. Manifestos. Insults. Self Praise. And so on. And most of it in blurbs, not sentences, and definitely not paragraphs. And in addition to the onslaught of bad grammar, the rate of spelling errors is atrocious.

Is this what you want to train an AI on? Really? You really want an AI that is going to make decisions like an angry dumb, self-obsessed, neurotic, troll with self-esteem issues making your decisions? And that’s likely a best-case scenario.

the doctor doesn’t know about you, but if he’s going to trust an AI, he wants that AI trained by experts for specific tasks, with performance analyzed and tweaked by other experts, since, as we know, there is no such thing as artificial intelligence, since no algorithm is intelligent, no matter how advanced, and what we really have are advanced automated reasoning algorithms. But if those algorithms were trained by the impaired, those algorithms are the last algorithms he would ever want to use. And those algorithms should NOT be on your list either.