Category Archives: Market Intelligence

At least Twenty Two Hundred and Sixty Five Years Ago Today …

The Pharos of Alexandria was constructed. Estimated to be over 100 meters in height, and one of the Seven Wonders of the Ancient World, it was built on the island of Pharos opposite the isthmus on which Alexander the Great founded the city of Alexandria. The lighthouse was commissioned by the Ptolemy I after the death of Alexander, and due to its location, it not only guided ships by day and night but secured safe access to the city of Alexandria.

We bring this up to show the long history of lighthouses, which to this day are important in the prevention of ships hitting the rocks and wrecking off the coast (like the Stephen Whitney did One Hundred and Seventy Years ago today off the southern coast of Ireland (killing 92 of 110 on board). And while the wreck resulted in the construction of the Fastnet Rock lighthouse, an early example of an oil burning lighthouse (replacing the previous wood or coal lighthouses). And while it didn’t have the brightness of the kerosene burning lighthouse that would replace it, it was a great start.

Because the ability to see in the dark is valued, especially at sea. And this is an extremely relevant metaphor to procurement often lost in a sea of data with no ability to see where the rocks are. This is important because without sight, not only will your organization not realize the Procurement Innovation that is to come we have been discussing all week, but it won’t even realize the opportunities available it today.

Stay tuned.

Procurement Innovation Tomorrow

In our last couple of posts, since They Terk Er Jerbs!, we have been discussing Procurement Innovation today and how automation and tactical data processing is actually a good thing for robots and software to take over, since most of it is mind-numbingly dull and hinders our creativity and productivity — and as that is about the only area we can truly best the machine (although they are making a damned good effort to take over there too), we better focus it on it now when we can.

(Even though it’s not likely we’ll see true AI in our lifetime, as processing power and parallel computing continues to improve, the prediction capability of machines will eventually get so high that some people might be tempted to say eh, good enough and let machines take over jobs and make decisions in areas they will be 95% accurate and sufficiently successful, or at least, good enough, on average. (Moreover, by the time they make one mistake so catastrophic that people die in a situation where no human would ever have made that mistake [as they can't see what they are not coded to see], it will be too late as we will be living in the world of E.M. Forster, The Machine Will Stop, and that will be it … and then, in a few dozen millennia, Earth will again be the Planet of the Apes).

But the power that comes from the machine’s ability to number crunch is going to go beyond number crunching, m-way matching, and guided buying with visual guilt. For example, one of the common innovations you are going to see tomorrow is invisible buying. And the invisible touch of the machine once it takes over some of the most boring buying tasks will be such that it will crawl under your skin, you’ll fall for it, it will take control, and if it ever gets taken away, it will take you apart. (And your only recourse will be to play Genesis.)

Just what do we mean by invisible buying? Basically stock room and MRO ordering, the bane of your buying existence, will be a thing of the past.

Who is better able to analyze purchase and inventory data and:

  • Auto-detect regularly needed items
  • Auto-compute typical usage schedules
  • Auto-predict best order quantities
  • Auto-re-order on reaching an auto-computed minimum threshold
  • Auto-adjust inventory levels using RFID, Arduino, & IoT
  • Auto-m-way match between all e-docs and auto-pay

Us? Or the software-driven machines?

That’s right, the software driven machines. Besides, what value is there wasting our time doing regular re-orders off of established contracts. None. Our time is better spent identifying the next contract to get in place to avoid cost, achieve savings, and, hopefully, provide more value to the organization. So the machines will take this over. And that’s fine. Because, at the end of the day, there is too much spend falling into the tail costing us big $$$. In most organizations, tail spend, which can be as much as 30% of the spend, is, on average, 15% to 30% over best market cost. 20% of 30% is 6%. That could be hurting your bottom line more than your top spend that is strategically sourced every three years and typically only has 2% to 3% left to shave off through smarter sourcing. Think about that.

Procurement Innovation Today

As hinted at in yesterday’s post, Procurement Innovation today mainly revolves around automation, but when that automation allows us to focus more time on analysis, strategy, and actual relationships than just pushing paper and matching numbers, that’s a very good thing.

The truth is you don’t even get savings by matching numbers because, in effect, what you are doing is preventing overpayments. Thus, all matching paper does is prevent loss. To save, you have to find a way to reduce costs below current baselines, and, to be really aggressive about the definition, reduce costs below expected baselines through the identification of an appropriate business strategy or process improvement.

Furthermore, if you really want to get analytical, you cannot claim cost avoidance as savings unless that cost avoidance is the result of a strategic or smart decision that allows volume to be reduced through actual need without the process improvement. For example, if you generally order 110 crates of ingredients, 10 spoil in the storage locker before they get sold, and you identify this and alter your order size so you are only ordering 101 crates and losing 1, that is not cost avoidance. This is loss prevention. But, if you realize that your current supplier is packing such that only 95% of the ingredients can be used (because the tomato paste sticks to the containers, the containers are too large and when customs does its random inspections, 5 times the food is wasted) and you switch to a new supplier where 98% of the ingredients can be used, (because the containers are non stick, smaller, or the spices are stronger), that is cost avoidance as you can now reduce the order size by 3% and serve the same need. Similarly, it’s not cost avoidance if you invest in printers that print double sided to reduce paper, as you are still using the same amount of ink (which costs more than blood) and the increased printer cost dwarfs the paper cost. It’s only cost avoidance if you can figure out how to reduce the total printing done by the organization (such as double monitors to prevent print outs, more online materials, etc.).

And automated m-way match is only one area where automation is helping us get more tactical. Another is automated price comparison, feature comparison, contract item identification, and what is emerging as guided buying in many of the catalog-enabled P2P solutions. If there is a contract item, it appears first (and the system can even be configured to prevent a user ordering anything but the contract item if it is in stock). If not, then items from preferred suppliers are shown. If no contract or preferred items, then either the lowest cost items that meet the need or items most ordered by the peer group are displayed. And so on. And the better solutions will even pop-up visual guilt information that shows a requisitioner how much it’s costing the organization if they don’t use a contract, preferred, or low-cost item (in hard dollar savings or missed volume/discount opportunities).

Automation, when properly used, is always a good thing. Of course, proper use is key. Automation never replaces the human element, it only enhances it. And any manager that doesn’t get that should be the first employee of an organization to be let go. Because any manager that can’t see how to use automation to make her people more valuable is not one worth having.

And for the record, I’m not saying that automation won’t displace some people – it will. Some people may not be willing or able to adapt to the new role, and will need to be replaced. And while this is unfortunate, that doesn’t mean that the organization can’t find them a different role in a different department or that they can’t go do something else more suited to them. What I am saying is that automation, properly applied, doesn’t reduce overall headcount. It just makes that overall headcount considerably more productive and value generating. And that should be the focus.

The Procure to Pay User Experience Should NOT be Overlooked!

The history of enterprise software systems is fraught with implementation failures. This is especially true in the ERP and MRP space, which have contributed to some of the biggest supply chain failures in history (including Hershey Foods, Adidas and Foxmeyer). But not all failures are catastrophic. The majority are just the result of (significant) project overruns in terms of time and money or the inability to deliver critical features or functions in the original system specification. And this is more common than one may think. Some estimates put the rate of project overruns in IT as high as 85%. That’s problematic.

Why are there so many failures? The reasons are many. Some are the result of poor change management; others are the result of the selection of inappropriate process automation for the company; and still more are the result of limited or low-quality information. If one goes through the list of possible reasons, we see there is one commonality across the majority of failures: the user experience. Poor change management leaves users confused. Inappropriate process selection frustrates users as it increases time and effort (rather than decreasing it), and low-quality information makes users question why they are migrating to a new system at all. (And when significant system features or functions fail to be implemented at all, that’s the worst user experience.)

That’s why the user experience (UX) is important, and why the doctor has been writing tomes on it this year, starting with a number of multi-part series co-authored with the prophet over on Spend Matters on:

What Makes a Good UX? Part I
What Makes a Good UX? Part II “Smart Systems”
What Makes a Good UX? Part III “Mission Control Dashboards”

The UX One Should Expect from Best-in-Class e-Sourcing, Part I
The UX One Should Expect from Best-in-Class e-Sourcing, Part II

The UIX One Should Expect from Best-In-Class Auctions, Part I
The UIX One Should Expect from Best-In-Class Auctions, Part II

The UX One Should Expect from Best-In-Class Optimization … Part I
The UX One Should Expect from Best-In-Class Optimization … Part II
The UX One Should Expect from Best-In-Class Optimization … Part III
The UX One Should Expect from Best-In-Class Optimization … Part IV

The UX One Should Expect from Best-in-Class Spend Analysis … Part I
The UX One Should Expect from Best-in-Class Spend Analysis … Part II
The UX One Should Expect from Best-in-Class Spend Analysis … Part III
The UX One Should Expect from Best-in-Class Spend Analysis … Part IV
The UX One Should Expect from Best-in-Class Spend Analysis … Part V

… with SRM & CLM on the way …

But that is just the beginning. Now that we have fairly adequately covered the core Sourcing technologies, we need to cover P2P, and that, as we all know, is the domain of the revolutionary. So, starting last week, the doctor teamed up with the revolutionary and, in the months to come, we are going to bring you deep, deep insight into Procure-to-Pay, both from a UX and a FX viewpoint so that at the end of the day you have deep insight into not only what P2P has to do, but how it should do it.

Our first instalment of The Procure-to-Pay User Experience premiered last Thursday over on Spend Matters Pro (membership required), and more will be coming.

Stay tuned!

Why You Have to Find that Fraud in Big Spend Stacks …

We recently published a piece on how it’s hard to find fraud in big spend stacks, and it is an important one. While fraud in most organizations might be relatively small, and might be mostly controllable by the right culture, processes, and systems (but that’s a subject for a future post), it’s still going to be there, and the most common form of fraud you are not going to detect is collusion fraud.

But this can be the most costly. Let’s say Bill and Ted both have invoice approval rights in the services procurement system and can singlehandedly approve services procurements up to 20K. Let’s say Bill’s buddy Bob has a services firm and let’s say Ted’s buddy Tim also has a services firm. Let’s also say that the organization also has a great need for temporary contingent labour to man the warehouse, clean the offices, and guard the assets of the company.

Let’s say that oversight of these services is left up to the approver for verification. Let’s say that Tim routinely sends two services guards when the general policy is to have three guards on duty and that Bob typically sends only two janitors to do the work that would typically be done by four by the old services provider. Who’s to say that Tim doesn’t send two guards but bill for three? And who’s to say that Bob doesn’t send two janitors and bill for four? And if these invoices are sent bi-weekly, they are going to fall well within approval limits.

Moreover, who’s to say that Ted doesn’t know about Tim’s over-billing and Bill doesn’t know about Bob’s over-billing? And who’s to say that Bill and Ted don’t have a deal to approve the over-billings for each other because their wives are getting an “efficiency consulting” fee from Tim and Bob’s companies?

Maybe this doesn’t happen in your company, but it happens more than one thinks, and just because you never detected this, how do you know it’s not happening? Invoices from real suppliers for real services at approved rates can still contain fraudulent over-billings for services not actually delivered, and those proceeds can still be partially kicked back through indirect channels to organizational employees.

But how do you detect this? Very sophisticated AI-based algorithms that detect unusually high approval patterns between two organizational employees, for amounts that should have been reduced with new contracts, that don’t match typical, anonymized, organizational patterns. And then human investigation to find the truth.

So why is this so important? Besides plugging the leaks? Because if you can’t find internal collusion, how will you ever detect potential cases of external collusion? And gather enough corroborating evidence to at least get an investigation going? If industries collude, and jack prices above market prices, the organization will lose considerably more than it will lose to Bill and Ted (from the evil, parallel, universe). And this happens more than you think too, it just doesn’t always get detected and investigated. Fortunately, sometimes it does, and sometimes, even if there is no certainty that fraud happens, regulators, presented with enough evidence still investigate — like they are doing now among the German automakers (which led to a surprise raid on BMW headquarters as recently reported in the New York Times) that are suspected of conspiring to hold down the prices of crucial technology (as initially reported in July). Regardless of the outcome, technology that can identify potential fraud and gather correlating evidence will keep everyone more honest, and that’s a good thing.