AI: Applied Indirection

You read that right. AI at most companies is not Artificial Intelligence. It’s not Autonomous Intelligence, Augmented Intelligence, Assisted Intelligence, or even Amplified Intuition. In reality, it is marketers taking Green Day’s AI a little to literally (and treating everyone like an American Idiot*) and repackaging old tech with a new label.

You see, most of what the Marketing Mad Men are trying to sell as AI are just old-school statistical algorithms in a brand-new wrapper. And the only reason these technologies are finally hitting the market and getting good results is the sheer amount of processing power and data we have at our disposal — because dumb algorithms (which is what they are) only work well when you have a lot of processing power, a lot more data, and the power plant to run that processing power 24/7 at 99% capacity across dozens, if not hundreds, of trial parameterizations until you find something that, well, just works.

But it’s not intelligence. It’s advanced curve fitting, regression, k-means clustering, support vector machines, and other statistical inference techniques that existed in SAS in the 1990s. Except now, the curve fitting is nth degree polynomial, advanced trigonometric, geometric, n-dimensional, step-wise, and adaptive. The regression is nonlinear, non-parametric, stepwise, and much more robust … and accurate because you can process millions of data points if you have them. The k-means is not clustering around one or two dimensions, but one or two dozen if necessary in a large multi-dimensional space — and the clusters can be of arbitrary n-dimensional geometric shapes using kernal machines. The support vector machines are not just based on primal, dual, and kernal classification with a bit of gradient descent but enhanced with multi-class support vectors, advanced regression, and transduction (to work with partial valued data). And so on.

And don’t think there’s anything new about “deep neural networks” either. They are just multi-level neural networks which were common-place in the 1990s with more levels and more nodes per level with more advanced statistical classification functions in each node trying to figure out how to extract patterns from unclassified data to classify and structure it, which happen to get better results because they can work on millions of data points, instead of thousands, and do tens of millions of calculations and re-calculations instead of tens of thousands. And that’s the only reason they get better results “out of the box”. There is absolutely nothing better or more advanced about the core technology. Nothing. It’s still as dumb as a door-knob, no matter how whizz-bang the markets make it out to be.

And at the end of the day, the “active” part of the neural network is a fraction of the overall network (which means as much as 90% of the computation is wasted), and if that can be identified and abstracted, you typically end up with a small neural network no bigger than the ones being used twenty years ago, which, even if more than three or four layers, can probably be redesigned as a three-or-four layer network. (See the recent article on the recent MIT Research, for example.) [But if you’ve studied advanced mathematical systems, this is not an unexpected results. Over-dumbification has always led to unnecessary processing and inferior results. Of course, over-smartification also leads to ineffective algorithms because data, typically produced by humans, is not perfect either and we need to account for this as well and detect small perturbations and deal with them. But it’s always better to be thoughtful in our design than to just brute force it.

In other words, many modern marketing madmen in enterprise software have become the new snake-oil salesmen, often selling simple statistical packages for a million dollars or raising tens of millions for yesterday’s tech in a shiny new wrapper. But it’s not intelligent, or even intuitive, by any stretch of the imagination.

That’s not to say that there isn’t technology that can qualify as assisted technology (and maybe even augmented in special cases), just that the majority of what’s being pushed your way isn’t.

So how do you know if you are among the majority being subjected to Applied Indirection or one of the few minority being offered a solution with true Assisted Intelligence capabilities? Stay tuned as we discuss this topic more in depth in the weeks to come …

* It’s much preferable to be a Canadian Idiot. We’re nicer and the “AI” marketers don’t bother us as much.

A Mere Eighty Nine Years Ago Today …

The Tariff Act of 1930, known as the Smoot-Hawley or Hawley-Smoot Tariff, was signed into law and implemented protectionist trade policies that raised tariffs on over 20,000 imported goods to the highest levels since 1828 (when the US relied very heavily on tariffs for public funding purposes).

Why is this act so significant? Most economists agree that this act and the following retaliatory tariffs by America’s trading partners were MAJOR factors that resulted in the reduction of American exports and imports by more than half during the GREAT DEPRESSION.

And let us point out that it wasn’t called the GREAT DEPRESSION as a marketing gimmick. It was called the GREAT DEPRESSION because it was one of the greatest declines of the global economy in all of recorded history! In a mere three years, the worldwide GDP fell by an estimated 15%. That’s FIFTEEN times the decline of GDP during the Great Recession of 2008-2009.

In most countries, this depression lasted until the late 1930’s — a whole decade — and in some countries it lasted all the way until the beginning of World War II! In other words, it was 15 times as bad as the Great Recession (which is a marketing gimmick as this was just a blip when all was said and done) and lasted 15 times as long!

And while it officially stated on Black Tuesday (on October 29, 2009), the Tariff Act of 1930 only served to exacerbate a bad situation, and turned what might have only been a truly great recession into a great depression.

So, my American Readers, tell me what you think is going to happen if you decide to keep your current trade-war happy President in charge for another term (assuming the world survives his first term)? [The worst thing is that his father had to live through the Great Depression and should have not only understood how bad protectionism can backfire but passed that message on as a successful businessman.)

Sourcing Talent Is Rare, Especially Since They Also Have to Manage Risk

Yesterday we told you that Sourcing, like the many facets of Supply Management, is not as easy as it seems as the skills required to go from RFI to award are numerous and compose up a laundry list that is rare to find even in most sourcing teams, yet alone individuals, including:

  • (Cost) Analysis / Market Analysis
  • Logistics
  • Needs Identification
  • Negotiation
  • Project Management
  • Resource Management
  • Supplier Identification
  • Trend Identification
  • … and …
  • Risk Management

The last of which we left off of yesterday’s list because this is a list in itself. You see, in today’s Sourcing landscape, turbulence is not just what you experience in an airplane on your way to a site visit – it’s what you experience trying to manage your supply chains on a daily basis. Just like fluid flows can become highly irregular with the slightest perturbation, so can the flow of goods in today’s ultra-outsourced ulta-global supply chains.

Turbulence is a hidden risk in every supply chain, and one most organizations are never prepared for because, when a risk assessment is done, it is always focussed on easy-to-identify technological, economic, market, financial, organization, environmental and social risks — not random events that can temporarily interrupt your supply chain and cause temporary disruptions with serious financial or brand consequences. Temporary disruptions which, if regular in nature, can put your organization in real jeopardy and temporary disruptions, which, by their very nature cannot be planned for or even identified in an up-front risk assessment.

For example, when buying product components from China, an experienced risk team is going to identify:

  • Supplier Risk
    Are they financially stable? Will they adequately protect your IP? etc.
  • Factory Risk
    Is the quality acceptable? Are there workplace or safety hazards that could shut it down?
  • Port Risk
    Will the product be safe? Is there any danger of strike or overcapacity? On both sides …
  • Export and Import Risk
    Are all regulations adhered to? RoHS? WEEE? Has all the paperwork been completed and submitted on time?
  • Technology Risk
    Is the real-time product tracking and distribution system reliable? Backed Up? Integrated properly with all parties?
  • Environmental
    Is the product being made or stored in areas subject to regular natural disasters such as hurricanes, typhoons, earthquakes, etc.?
  • Social Responsibility
    Is the product conflict / slave labour free? Are all employees of all partners treated equitably? Is the product, and its production, environmentally friendly or at least environmentally safe? Can the product be safely disposed of?
  • Market
    Will the market still want your product when it is available? Is a competitor going to beat you to the market?
  • Economic
    Will the economy maintain or improve? Or will it worsen, leading to reduced demand across the board? What is the job forecast looking like in target markets – job loss in those areas can weaken consumer demand.

and a few dozen other common risks from the risk identification and management playbook.

But it’s not going to identify one-time random events such as:

  • Unlikely Terrorist Attack by a random civilian who goes postal and, when trying to go postal, thanks to a gas leak, accidentally blows up a building due near the docks and causes the port to become unaccessible for 3 days
  • Delayed Delivery due to Paperwork Mix-Up
    One truck is scheduled for delivery of your product to your distribution warehouse, another for mid-term storage at a competitors warehouse on the other side of the continent. And because the small carrier you’re using doesn’t have real-time inventory tracking, and your product is scheduled for JIT delivery, the mix-up isn’t detected until the expected delivery date when your product is half-way across the country.
  • False Stock-Out due to Inventory Mis-Key
    The clerk enters 8,000 units instead of 80,000 into the system, stores exactly 8,000 in the proper location in the ware-house, and puts the other 72,000 units of your hottest selling product at the back of the warehouse reserved for discontinued inventory.

Each of these events can happen, and each can cause a real, unexpected, and unpredictable turbulent impact to your supply chain. Are you ready for it? Can you sourcing team react and adapt when it does?

Sourcing Talent is Rare

Sourcing, like many facets of Supply Management, is not as easy as it seems. The skills required to identify the products and services required, identify potential suppliers, construct an appropriate RFI, evaluate that RFI, construct an appropriate RFP, evaluate that RFP, identify suppliers for negotiations/RFQ, assess the market, assess the RFQ responses against the market, select one or more finalists, negotiate, define the award, create a contract, and manage the whole process are quite numerous. Especially since that’s just the basic process. A determination of demand, of current market conditions, of expected cost, etc. will require spend analysis, (should-cost) modelling, and (statistical) trend projection. If multiple bids are competitive, and an auction is out of the question, then (strategic sourcing) decision optimization, and the mathematical modelling it entails, is also required. Plus, if the buy is strategic, then multiple stakeholders will be involved and cross-functional team-management skills will also be required. All this, and more, may be required just to get to a contract.

Then comes the actual Procurement. This will involve considerable skills in logistics, inventory, and global trade. When do you place the order? What is the best mode of transportation? Do you cross-dock or not? If the inventory is available too early, do you store it over-seas, before export, or locally, after import. If there are value-add components, do you take them or leave them, as they can considerably increase import or export tariffs? For example, sometimes the difference between shipping a cartridge in a printer and shipping it separately will save a few percentage points off of the total cost. (Check the HTS codes if you don’t agree.)

So, to re-iterate, you need the following skills at a minimum:

  • (Cost) Analysis / Market Analysis
    What are the current market conditions, what is the expected or best cost, etc.
  • Logistics
    What is the best method of transportation and how do you time it to optimize costs and revenues, etc.?
  • Needs Identification
    What do you need, when, and are there alternatives, etc.?
  • Negotiation
    What do you offer? What’s your minimal viable alternative? etc.
  • Project Management
    How do you balance your resources (time, money, talent) to achieve the goal? etc.
  • Resource Management
    What’s the best use of your limited resources? When do you buy and sell? etc.
  • Supplier Identification
    Which suppliers want to supply you? Which suppliers are acceptable to you? etc.
  • Trend Identification / Projection
    Are demands going to increase, decrease, or stay the course? etc.

These skills are not easy to come by and not easy to advance. For example:

  • Analysis
    requires mathematical skills and training
  • Logistics
    requires cost analysis and network modelling skills and training
  • Needs Identification
    requires the ability to elicit details from both analyses and stakeholders
  • Negotiation
    requires training and people skills
  • Project Management
    requires knowledge and training
  • Resource Management
    requires strong analysis skills and an understanding of the inherent value and limitations of each resource
  • Supplier Identification
    requires the ability to assess a supplier across multiple dimensions and know what those dimensions should be
  • Trend Identification
    requires analysis, statistical training, and an instinct for the right questions

Now do you understand why even if you could get approval for the staff you need, finding the right individuals might be hard?