Yes, I promised you a story full of intrigue, filled with bad Jedi and happy Sith only 20 hours ago. And here it comes (I’m watching Star Wars episode 2 at the moment). You see, there is a setting where we can watch the unfolding of what some laughingly call ‘Artificial Intelligence’ (it would be if it was designed by the CIA, but the American Administration is now in shutdown). To get there there are three parts.
In part 1 we look at the ‘disinformation’ and here we see the parts that do not match. You see, Dab Mashed potatoes with unions were discontinued in both Coles and Woolworths. The IGA still has it as I was able to verify in person (I had to travel to Summer Hill for that). So this is part 1.
Now we get to the slightly better stuff. You see, some might think that combining DML with Predictive Analytics (some think it is AI) is a solution. You merely set this in a massive database and voila (a theatrical of ‘here it is’) and that was that. This is merely my version of what I think it is happening.
You merely set the model on all the articles you have and you take settings of ‘minimum order size’ ‘estimated margin per item’ and a few other things and there you have a matrix showing the items that just don’t make the cut for your ‘predicted margin of profit’ model and they are ‘discontinued’. And it goes on for nearly all retail models, and it might be a consideration that this is a speculated idea of why PM Albanese invited Lulu into the mix against Coles, Woolworths, IGA and Aldi. I have no data on this, but I reckon it might be a reason that it stops the DML/Predictive Analytics madness. You see, there is a setting that it is folly to get any customer 100% happy (it really is), so these giants are heading for a mere 90% and they throw out the least margin articles out of their consideration, but there is a flaw, thrown out 10 articles is a start, but that leaves one less at 90% and 9 less at 1%, as such you have a base of 81%, so now we are off to the races. And as there is no substitute for added pressures, Lulu gets invited to Australia (in case the others went the way of the dodo, I meant Coles and Woolworths). There is no supporting evidence, so this is (highly) speculative. But there is another setting. You see, this solution requires programming skills and that is where ‘Accenture plans to boot staff it can’t train to use AI, 12,000 already culled’ comes in. This solution will require hundreds, if not thousands of people being reskilled and places like Accenture cannot do that, unless they trim the staff they have in several places. And 12,000 were ‘culled’ because it hinders their bottom line. To support this I give the following thoughts ‘What time was taken to assess a person whether he/she could be re-skilled?’ Who had the knowledge to assess this and what time frame was developed here? If this goes through it will mean a lot of engineers will be required in a short term setting.
And I merely used the Deb potato mash as an example, but what happens when it this pattern is released on pharmacy or other items? So whilst we might think that Accenture is dabbling in greed, the plain setting is that this is the direction that commerce is driving itself into.
And this setting is about to be set on unverified data. Consider that Gemini AI had it wrong on Coles and Woolworths (see image), so what else did they get wrong and when that data is unverified how will the Predictive Analytics work with any level of accuracy? Mere simple questions at the top of my mind. And that was the setting of that ‘so called’ AI.
Now, the setting is that parts of this are speculation, but does this make it wrong? It might be unverified, but the setting of the 12,000 culled into joblessness is recorded all over the media, and it is for the reason of ‘reskilling’ but what makes it impossible to reskill a person? As I see it, it is merely time and that is as I see it, time Accenture seemingly doesn’t have. And the setting of DML and Predictive Analytics? I see that as a limit towards viable data and that is the setting that plenty are ignoring. Some will ‘embrace’ the customer telling them that their data is awesome, but that is the second folly in this. Most of them are merely at the tally stage and their systems tend to come from legacy data, implying it is filled with holes and holes of non-data.
So think of this what you want, but the larger setting is about limiting YOUR ability to choose because it affects THEIR profit margins. Come to think of it, when was the last time you saw Sarsaparilla on the shelves of your supermarket? I remember a few years back there was Black knight licorice, where did that go? So think of all the things you liked and it is no longer there, why is that? Some are unviable as they cater to hundred of thousands of customers and they need to ‘adjust’ their stock accordingly. But what was denied to you? And the setting of adding predictive analytics to their profit mix is only making that worse for you. So what about part 3? Well that is where you the consumer comes in, it is what defines you, not what ‘their’ unverified data says you are.
So have a think about what you are about to lose and have a great day and enjoy your next coffee, if only to force you to their brand of Nescafe.
Lawrence van Rijn - Law Lord to be 