Category Archives: Technology

One Hundred and Ten Years Ago Today …

Kinemacolor, the first successful color motion picture process, is first shown to the general public at the Palace Theatre in London by way of an eight-minute short filmed in Brighton titled A Visit to the Seaside.

This revolutionary technology was invented by George Albert Smith and launched by Urban Trading Co. of London and used commercially for 6 years. It was a two-colour additive colour process that involved photographing and projecting a black and white film behind alternating red and green filters at a rate of thirty-two images per second on panchromatic film.

Motion was a bit blurry, and color was a bit off, but it gave color to a world without any. It was revolutionary. And a mere 110 years later we can scan in Colortrac and capture 281,474,976,710,656 different colors (using 48-bit deep color), process it through ATI FireGL 3D Workstation Graphics Accelerators which can process 48-bit color, and display it on a HDR*1-enabled LCD*2 flat-screen display.

But still, a mere 110 years ago, this image of a 1911 Kinimacolor recreated from original materials, and found on Wikipedia, was revolutionary!

*1 High Dynamic Range
*2 Liquid Crystal Display

It’s 2019. This is What QuickStart Sourcing Should Look Like!

As we mentioned in yesterday’s post, a decade ago the Oompa Loompas at Coupa announced the availability of Coupa QuickStart which was simply a setup wizard that visually guides purchasing mangers through the setup process for users, approval rules, payment and shipping terms, billing information, chart of accounts, suppliers, and other basic information that was required to get a purchasing system up and running in less than an hour.

But just being able to order a product from a catalogue or send out a simple RFP is not very strategic, especially for 2019. And these days, any event that is not strategic is not going to generate much value when savings are drying up, brands are falling, and spending is falling as GDP growth stagnates and we return to depression era economics.

Needless to say, not only should every system have the capabilities that Coupa had 10 years ago, and the capabilities that we outlined in yesterday’s post on what QuickStart Procurement should look like, but that’s not enough. Not for 2019. Ten years ago we were promised semi-cognitive systems, and most systems can’t even automate basic invoice processing. It’s sad, sad, sad.

So, what should a modern system have? One built this decade?

  • smart RFI creation
    that, as per yesterday’s article, can be generated purpose built for the products in question using templates and organizational data in the ERP
  • smart RFI monitoring
    that can monitor the event, send out reminders, automatically check inputs against public data, organizational data, and expected data, and send out alerts to buyers when suppliers are late, inputs are off, or bids are outliers
  • smart bid analysis
    that can compare bids to past bids, market averages, and expected costs from reasonable should cost models
  • smart award recommendations
    based on bids, delivery times, availability, and supplier preferences
  • automatic auctions
    that can auto-populate from RFIs, auto-run, auto-monitor, auto-enforce rules, and auto-award and notify winners when the auction is over (as they won’t be invited to the auction if they don’t agree to the necessary terms and conditions to be offered an award beforehand)
  • automatic default contract creation
    that uses the organizational boilerplate, terms and conditions, default category clauses, awards, and associated obligations to generate a default contract
  • automatic document comparison and change tracking
    even if the supplier sends back a signed PDF that looks like the one you sent, every character will be analyzed
  • automatic performance monitoring plan generation
    that will track, based on the contract, when orders should go out, when goods should be received, when documents should be received, when reports should be received, when other deliverables should be received, when assessments should occur, etc.
  • real-time performance monitoring
    that monitors a plan, sends out alerts to buyers when deliverables are missed, sends out alerts to suppliers when they have not submitted a document or a shipment notification on time, automatically sends out pre-defined performance assessment surveys, etc.

Quick Setup is more than a wizard, it’s an assisted intelligence platform backed by sophisticated algorithms community and market data, and all organizational data and processes to mitigate the need for the buyer to do pointless tactical data processing in the first place and focus purely on the strategic analysis of RFX responses, when the relevant data and insights have already been generated by the platform.

But how many platforms have that today? The same umber of platforms that have assisted intelligence for Procurement. Zero.

In other words, just like Procurement Leaders are stuck in 2009 (as per yesterday’s article, but so are the vast majority of technology providers. So when looking for a new solution, find one of the few technology providers on this path. Otherwise, your solution capability will be nought, and that’s the decade you will return to. Not something anyone wants.

It’s 2019. This is What QuickStart Procurement Should Look Like!

A decade ago, Coupa announced the availability of Coupa QuickStart, which was a setup wizard that visually guides purchasing mangers through the setup process for users, approval rules, payment and shipping terms, billing information, chart of accounts, suppliers, and other basic information that was required to get a purchasing system up and running in less than an hour.

Needless to say, every system should have that capability today (even though a number still don’t), but given that this was on the market 10 years ago, systems should have advanced considerably since then.

What should they have? More than we can cover in one short article, but at a minimum:

  • AI-powered normalized supplier network with community intelligence
    and out-of-the-box plugins to allow for quick import of your vendor master(s) from all standard ERP and S2P systems (as well as support for complete XML and CSV exports) and AI to allow for quick de-duplication of suppliers between the network and your enterprise vendor master(s)
  • Powerful search capability for quick supplier discovery that can take advantage of detailed product descriptions, community intelligence, and organizational profiles to find intelligent, well-rounded matches
  • HR system / standards support
    to allow for a quick import of employee profiles and organizational hierarchy direct from major systems or standard export files
  • AP/Budget system / standards support
    to allow for quick importation of budgets, approvers, and where possible, budget rules
  • ERP/IMS integration or standard export file support
    to allow for quick importation of categories and products purchased regularly, as well as demand for the past 3 years and current category suppliers and prices
  • ERP/TMS integration or standard export file support
    to allow for identification of current carriers, the categories/products they currently export, and standard LTL/FTL rates
  • AI for profile completion
    that imports the relevant organizational profile data from each of the above systems or exports to build the necessary profile that can be shared with suppliers for shipping, invoicing, etc.
  • standard category templates for RFPs that can be tailored as needed by an AI that uses past event data in the ERP and current product data in the IMS to tailor the template as appropriate

In other words, it’s 2019 and

  • an admin user should not have to define users, the platform should be able to do that automatically given a HR system (export)
  • an admin should not have to define approval rules, the platform should be able to identify the most appropriate rules given budgets, approvers, and payment thresholds defined in the AP system
  • an admin should not have to define payment and shipping terms, the platform should be able to export that information from the AP, ERP, and/or IMS systems
  • an admin should not have to define billing information, that should be automatically extracted from the AP system
  • an admin should not have to define a chart of accounts, that should be automatically extracted from the AP/Finance system
  • an admin should not have to define/import suppliers manually, those should be pulled in from organizational systems automatically, normalized, and vetted against networks the buyer has access to
  • a buyer should not have to create an RFP template from scratch, the platform should present an appropriate one for the category and products based on community and organizational intelligence
  • a buyer should not have to do an extensive, time-intensive discovery process to identify new, suitable, suppliers, an AI-backed discovery engine that runs on a community intelligence backed network should identify suitable suppliers in minutes (and support the construction of qualification scenarios in just a few more minutes)
  • a buyer should not have to manually manage the invitation, send out, monitoring, and reminders of the RFP, nor manually verify all data for reasonability and completeness, the AI should do that automatically, and automatically alert suppliers to complete missing data, check values that might be outliers, etc. and automatically alert the buyer of suspicious / missing data upon supplier submission

Quick Setup is more than a wizard – it’s using assisted intelligence backed by sophisticated algorithms, community data, and all organizational data to mitigate the need for the organization to do pointless repetitive setup in the first place! But how many platforms have that today? Unfortunately, when the holistic picture is taken into account, the answer is zero.

So, not only are Procurement Leaders still stuck in 2009 (as per yesterday’s article), but so are the majority of technology providers. So when looking for one, find one on this path, unless you want to return to the decade where a lot happened, but little is remembered. Or do you want to do something where you’ll be remembered? Like selecting a platform that could not only modernize Procurement but open it up to the entire organization. Your call.

Sixty Five Years Ago Today …

…when Russia, not Mexico, was the enemy, the United States and Canada agreed to construct the Distant Early Warning Line (and, unknowingly, inspire one of Canada’s classic rock anthems that would be released thirty years later).

Thus began a system of radar systems in the far northern Arctic region of Canada with additional stations along the North Coast and Aleutian Islands of Alaska, as well as placements on, or near, the Faroe Islands, Greenland, and Iceland. There was no way Soviet Bombers were going to sneak up on us over the pole or send a land and/or sea invasion using the arctic route!

And while the application was defence, it spurred a lot of investment in radar technology, that our modern control towers rely on, as the project was given a priority rush status and completed in less than 3 years, at a latitude that could only be reached by ships during the summer months, which also resulted in advancements in cross-border and joint logistical operations.

Your Successful Supply Chain will NOT be Autonomous!

the doctor has recently seen a few pieces out there on the forthcoming autonomous supply chain and even a few pieces on the “self-driving” supply chain. Eek! Just like we’re not ready for AI-enabled self-driving cars that will drive us off a cliff as soon as they become self-aware (and that’s why you can have Carl and I’ll stick with Alfred), we’re not ready for self-driving supply chains that “predict” future demand, automatically order large numbers of products for you, and push them to local warehouses and retail stores without any human intervention.

Just because your demand sensing engine, which works well for established products, can use PoS data and other demand signals to auto-reorder staples with 98% accuracy doesn’t mean it can predict the success of an upcoming, or relatively new, product line — especially if it’s new for your business and you are, unbeknownst to your sensing engine, about to be beat to market by your nearest competitor — and it’s in the consumer electronics industry where first to market typically captures 10% to 30% just for being first. The last thing you want is for the platform to increase your initial order by 30%, ship straight to store, and then have it sit there for six months, and depreciate. Not a good use of cash.

Nor do you want your TMS automatically assigning shipments to carriers, intermediate warehouses, and ports without any human intervention. Software with limited data feeds often have no forewarning when a port might shutdown due to a strike, but humans might. Nor will a limited feed software algorithm know when a border might close and also close a supply route. But a human might. And so on.

And, despite what Amazon may think, you definitely don’t want to be thinking about anticipatory shipping. As we noted in our post five years ago, while predictive analytics is getting better by the day, it’s still hit and miss at a granular level. And individual purchases are quite granular. Just because 4 out of every 5 people who buy a Buzz Lightyear Cup also buy a Sheriff Woody Saucer, doesn’t mean the 4 people that your “AI” chooses will. One of them might not like saucers. Or Sheriff Woody. Shipping on an anticipatory nature guarantees that at least one out of every 20 units will be unwanted, and as many as one out of every 4. That’s a lot of returns. And, as we have noted again and again, including our recent article on how there is no free lunch, and there is no free shipping either, that could get quite pricey. How are you supposed to keep costs down if you have to budget for amortized high, wasted, return shipping costs across every unit?

So please, please, don’t try to give your supply chain autonomy. Automate it. Apply the best assisted intelligence solutions on the market to provide one-click recommendations, but always make sure there is a human check before any decisions are made that affect millions of dollars.