Category Archives: Best Practices

Why A True Supply Management Professional Still Will Not Be Replaced by Technology

Algorithms still don’t sense, still can’t read the majority of non-verbal cues (as even the best mood detection algorithms can barely differentiate between “happy”, “indifferent”, and “sad” … even when the people it is analyzing have big smiles, flat lips, and big frowns), take calculated risks that go outside the programmed parameters, or form common bonds. They don’t feel, and they are not intelligent. And while their predictive capabilities are now getting scary in some respects, they are not infallible, and as we discussed in our last post, when they fail, they fail in a big, big way.

As first noted in our original post five years on Why a True Supply Management Professional will Never be Replaced by Technology, not only do algorithms not feel, but they are als incapable of accurately predicting how a person will respond to a suggestion that has any emotional impact whatsoever. Especially in today’s individualistic society where the message is what is interpreted by the recipient and only someone with a shared understanding will be able to comprehend what that is and react accordingly. As a result, an algorithm cannot negotiate (unless it is negotiating with another algorithm — but that’s not the best of ideas. When two algorithms negotiate, they develop their own undecipherable shorthand [as evidenced in multiple studies and real world occurrences, which includes two creepy Facebook bots talking to each other in a secret language], and we won’t be able to figure out what they did or why. (Was it to optimize the best win-win situation or was it to advance the plans for building SkyNet. We don’t know.)]

Secondly, as pointed out in our previous posts, successful negotiation depends on more than a first party transmitting a message to a second party that the second party can accept, but understanding all of the possible messages which might be accepted, their likelihood, and which are the most preferable to each organization and selecting the best one for the situation at hand. And while an algorithm can compute which options are likely given certain assumptions, and which of these options are the least distance from optimal according to some metric, it cannot determine what assumptions to make. Only a person who can feel, and feel what the other party is feeling, can be the judge of what good assumptions are. And, secondly, algorithms cannot sense. They don’t feel, and they don’t have instinct —- because that requires real intelligence!

Thirdly, as described above, they can’t accurately read non-verbal cues. Even if someone is stating that they may be agreeable to an offer, the reality might be that they may have no intention of ever accepting the offer, and are only indicating the contrary either because it’s the culturally polite thing to do or they want to stall for more time while they figure out their position. It’s often the case that such a person is not as good at masking their demeanor as they are at masking their words. It might be the case that their non-verbal cues give more away than they would like, but only a trained negotiator with years of experience and instinct could be an accurate judge of this.

But, even more importantly, they still typically can’t detect patterns in unrelated data, as it’s typically the case they can only process specified data in a specified set of ways. And a fixed data pool never tells the whole story. A fixed algorithm might not know that a fire today will impact resource availability in six months, that your main competitor is likely to go out of business due to a massive loss in a patent infringement lawsuit, or that a new technology is going to make the current technology obsolete in 18 months, with prices and demand starting to plummet in six months. As a result, in each of these instances, the algorithm would buy (today) (at a much) higher (price) than it needs to.

In short, the proper application of good, assistive intelligence, technology will make you two, ten, and maybe even one hundred times more productive (depending on the metric), but it cannot replace you. No matter what a vendor may claim. So don’t be scared of new technology for your supply chain —- embrace it. But don’t trust it blindly. Verify. Then you’ll have the best of both worlds — efficiency, with reliability — provided not by the system, but by your intelligent brain.

… And Keep Your Big Platforms. Big Brains Will Still Win in the End!

Five years ago, about the time when the big data hype first reached insane hype levels, SI published a post that it was sick of all the big data hype and how it is not the answer to all our problems because, not only is this a load of baloney, the reality is that there’s no such thing as big data in business. As we said then, relative to our ability to process it, data has always been big. And, in business, big has always been meaningless. Furthermore, in business, we’ve always been able to process as much data as we need to in reasonable amounts of time if* we make good algorithm and technology decisions

Plus, the fact that all of the hype around big data is often centered around the fact that we will be able to replace science with math and processes with AI programs is even more ridiculous. There is no such thing as artificial intelligence. And even though we’ve finally taken automated reasoning to the point that we have assisted intelligence, there’s a big difference between recommendations from a leading expert system (which not only can’t know when it is wrong but how much it can be wrong the few times it is wrong) and an average, experienced, professional in the domain (who can know how likely they are right, and if they are not likely to be right, how far off they are likely to be).

But even worse than the big data hype is the big platform hype … how mega platforms backed with cognitive abilities can do it all! They can do a lot, but they can’t do it all. And any delusions we might have that they can are only going to get us into trouble. Because as soon as we start trusting them blindly, we’re going to turn two blind eyes and that’s when the 2% failure rate is going to kick in, and materialize in the absolute worst way possible.

In Procurement, it’s going to miss the fact that a new organizational vendor is a very high risk and make a 2 year sole-source award for a small, but critical, custom made component in your (engine/control system) assembly when, in fact, it should be excluding the vendor which just had its credit score downgraded from a B+ to a D-. It’s not going to predict that in all probability, the vendor is not going to be able to secure enough loans to stay afloat (until it fulfills your orders and other customer orders and grows its business after losing a major contract that accounted for one third of its production) and will shut down and stop delivering product in 3 months when no one’s watching. Your production line will go down for 2 weeks while you find a backup supplier to quickly bring a production line up, make a minimal order, and air-freight it to you. If it’s a big automotive production line that goes down for 2 weeks, that’s easily 10M down the drain, and that 1M you saved is wiped out ten times over in a second.

But that’s not the worst thing that can happen from us turning two blind eyes. In this situation, the company temporarily loses some money, and as long as it has enough inventory to keep most of its customers happy, and it can keep its failure quiet, no one notices. Now, if its a medical diagnostics vendor and a (visually-based) diagnostic expert system (designed to help with the identification of all skin conditions) used by a remote doctor fails and mistakes melonoma for a relatively benign lesion, it’s a whole different story. When you consider that skin cancer is one of the five fastest spreading cancers, by the time the patient goes back in and insists something wrong, it could be too late — the spreading could be too far and the patient will be doomed (since melonoma, while only 1% of skin cancer, is not only one of the fastest spreading skins cancers but also has the highest fatality rate and causes the majority of skin cancer deaths each year).

Big Platforms give Big Confidence, but it’s false confidence. I’ll take a real human expert any day. Yes, she’ll make a mistake sometimes. But she also knows when she’s not sure and you should get a second opinion. That’s not always something a system can tell you. It’s above a threshold, below a threshold, or on the line (and no decision is made or classification is given). But that’s not always the right way to look at a situation.

* And, FYI, hiring college drop-outs whose college experience consists of cutting and pasting HTML and javascript code and fiddling with it until it works is not a good technology decision. There’s a big difference between being able to code a web-page and develop a highly scalable, reliable, and efficient enterprise computing system. BIG DIFFERENCE!

Are You Ready to Get Analytical But Don’t Know How? Read On!

Now that you’ve read our last three posts and understand that you need to get more analytical if you want to get cognitive, hopefully you’re ready to dive deeper but just don’t know how to do that.

The four part answer is almost as easy as it was for optimization, just a bit more nuanced. What’s the nuance? Figuring out if your provider offers a modern spend analytics platform or is still a generation (or two) behind (when you are still behind yourself) is the nuance. So how do you determine if a vendor at least passes the sniff test? We’ll get to that, but first, let’s talk about where you start.

At a high-level, the four-part answer is almost the same as optimization. Just the vendor names change.

1) If you are using a sourcing or analytics platform from a modern provider with modern (next generation) analytics capability, use it (and acquire the module if necessary).

Who are the vendors? While we can’t say this list is thoroughly exhaustive, if you look at Spend Matters Deep Solution map, you see that the following providers make the map: AnyData, (SAP) Ariba, (Opera) BIQ, GEP, iValua, Jaggaer, Sievo, Simfoni, SpendHQ, Synertrade, and Zycus. Not all are equal, and this list is likely not exhaustive, but depending on your organizational needs, a sub-set of these providers is likely your starting point. (What Sub-Set? Depending on whether you are data, function, process, technology, configurability, or services oriented, the sub-set will vary. And practitioners who want to know which vendors match which subset can contact Spend Matters.) And if you are a do-it-yourself type, you could probably start with a platform like Spendata.

2) If you are not using a modern analytics platform or a modern sourcing platform with analytics, get a modern analytics platform or a modern sourcing platform with analytics, your choice.

Again, you can start with the dozen of providers above, which you can quickly narrow down depending on whether you prefer best of breed or sourcing suite and whether you favour technical orientations or service orientations. If the list is still too large, find the subset that bests fits your organizational size, industry, category focus, geography, and culture and focus in on those.

3) If you are using another sourcing or analytics (reporting) platform that is not meeting your needs, and can replace it, do so.

As with the optimization providers, a few of these providers have a considerable portion of their customer base that consist of customers that switched from another provider with a solution that didn’t meet their needs and, thus, have a lot of experience with change management, fear squashing, migrating your data over, and getting you up and running on the right processes quickly. Simply craft the right RFI and you will quickly zero in to the handful of providers that will likely be the best fit for your situation.

4) If you are using another sourcing platform or reporting platform that is otherwise meeting your needs, or can’t be replaced at the present time, or both, augment it with a pure-play deep-dive best of breed modern analytics solution.

So if you are in the situation that you just bought a best of breed Source-to-Contract or Source-to-Pay solution and can’t replace it, or you have a first generation BI tool that produces reports the executives love but doesn’t meet your needs, augment it with a point-based best of breed solution. From the above list,
AnyData, (Opera) BIQ, Sievo, Simfoni, SpendHQ, and Spendata fit that bill.

But what about the “sniff test”?

How do you differentiate a last generation solution from a current generation solution? Three tests. Have them, in front of you, in a live demo:

  • Build a Cube with Derived Dimensions and a new Report on the Cube on the Spot
    if they can’t do so (in 15 minutes), they are a last generation platform that can only work on pre-defined and pre-built OLAP cubes
  • Run a categorization exercise on at least 3 months of your transaction history / invoice data and at least 100,000 transactions
    if they can’t either use their AI, or powerful (collaborative) filtering and priority based rule definition, and get to the 95% mark in an hour, it’s not for you … (and, trust me, you don’t need AI to get to the 95% mark if the rule definition capability is appropriately defined)
  • Map the cube to a new taxonomy, create new derived dimensions, and create a set of filters that will allow comparison reports to be run between the cubes
    let’s face it, there is no one size fits all taxonomy for analysis, and this is the kicker test to see if the platform can support any taxonomy that is needed, run any analysis you want, and allow you to run comparison reports both as checksums and as differentials to figure out where the opportunities are hidden

All this should take less than a morning or afternoon. But it means the provider deserves to be on your short list.

Are You Ready To Get Optimized But Don’t Know How? Read On!

Now that you’ve read our last two posts and understand that you need to get optimized (and analytical) if you want to get cognitive, hopefully you’re ready to get optimized but you just don’t know how.

The four-part answer is pretty easy.

1) If you are using a sourcing platform from a modern provider that offers optimization, acquire the module and start using it.

If you’re already using (SAP) Ariba, Coupa [Trade Extensions], EC Sourcing [with bidmode Inside], Jaggaer (Indirect/Direct/Advantage), Keelvar, or SynerTrade, acquire the sourcing module, turn it on, and start using it. We know that not all platforms are equal (as made clear by the Optimizer Persona in the Spend Matters Solution Maps), but all are more than enough when you are just beginning your sourcing journey. Plus, the majority of these providers are all actively developing their optimization solutions and should stay ahead of your optimization needs.

2) If you are not using a sourcing platform, get one that has decision optimization.

We gave you six names, and these six names can all help you. While we have our preferences, the right solution is utterly dependent on your organization size, industry, dominant categories, geography, and culture and which provider matches your profile the best. There’s only six names, and a relatively short RFI should allow you to quickly zero in on the 2 or 3 that are most likely the best for you.

3) If you are using another sourcing platform and it is not meeting your needs and can replace it, replace it with an optimization-backed sourcing platform.

A few of these providers have a large customer base that consist of those that have switched from another provider with a solution that didn’t meet their needs and, thus, have a lot of experiencing with change management, fear squashing, migrating your data over, and getting you up and running on the right processes quickly. Simply craft the right RFI and you will quickly zero in to the 2 or 3 providers that will likely be the best fit in this situation.

4) If you are using another sourcing platform and it is meeting your needs, can’t be replaced at the present time, or both, augment it with an optimization-backed sourcing solution just for those events where optimization is a must-have.

You just bought Source-to-Contract or Source-to-Pay Solution X a year ago and you know that Finance / Operations / etc. will not approve a new solution for at least a few years because they still believe systems should last five to ten years. In that case, you get a pin-point solution that you use to augment your current solution as a bolt-on. Two of the providers in particular that we mentioned — EC Sourcing with bidmode Inside and Keelvar — are small, mid-market focussed, pin-point best of breed optimization-backed RFX solutions that start in the six figure range (or five figures on an event basis) that can be used to augment a traditional Sourcing platform at a low cost and deliver a high value.

And, no matter what Don’t Say It’s Not That Easy. It is. Yes it’s work to create the technology RFX, reach out to the vendors, make the short-list, do the negotiations, select a (new) vendor, create a transition plan, create an integration plan, and get it done. But making the decision to get a platform that will save your organization an average of 10%+ year-over-year and taking action to do it is easy. And there’s no situation there isn’t an answer for. So, just do it. You won’t regret it.

M&A Has Been Mad. Platforms Will Disappear. But There Will Be More Than One. But Who?

We’ve been writing a lot about M&A lately, including, but not limited to, our pieces on:

because M&A is still going strong. (And, as per our recent post on The Hidden Value of SI Association, SI is acutely aware of this because this is how it loses its customers. SI works with these companies, helps them become known and successful [through a focus not on buzz but actual education, process improvement, and appropriate roadmaps], they get noticed by cash-rich firms, who then buy them, and in many cases, strip out the management teams and/or consultants.)

We’ve also noted that not only will some platforms have to disappear (to make the mergers successful) but that (in our recent piece on One Vendor Won’t Rule Them All … And One Ring Won’t Bind Them), due to the wide range of needs that organizations need and the different process that are used around the globe in organizations headquartered in different regions and run by different cultures.

But that being said, now that Sourcing and Procurement technology is starting to become more mainstream — and the majority of organizations are looking for analytics, procurement automation, and supplier program management — those organizations that are looking for their first platform (as well as the early adopters of first generation platforms that are now almost a decade behind) are trying to figure out who they should look at and, more importantly, what product lines they should look at (now that some organizations have as many as three different product lines for Procurement under one organizational roof).

This is hard to predict, especially since the Fortune 500 is in more flux than it’s ever been. It used to be if you were on the list, you were on the list for years (if not decades) and changes were subtle. Now a company can make it one year and as a result of one major disruption or media fiasco, be in bankruptcy the next year (and disappear from the list). And while most of the companies in our space are not on the Fortune 500, these companies are now being bought by the big enterprise software giants, including SAP (with a market cap over 100B), that are.

And the instability in enterprise software companies amplifies they smaller they are, and when the biggest stand-alone public company in our space has a valuation of a mere 2.5B and the largest private company in our space would likely get a valuation in the same range, you can see where we are when the average large company has revenues that you have to round up to 100M and the average BoB vendor rounds to the 10M range.

But the platforms provided by some companies, due to the immense value they offer, will survive, even if under a different name, as part of a different platform, under a different company, held by a different holding co, whose name may change three times over the next decade. And who will they be?

Simply put, they will be those platforms that are the hardest to replicate and offer the deepest capabilities that are key to value identification, like optimization, advanced predictive and prescriptive analytics, cognitive process automation, semantic risk identification and monitoring etc — whether the platform is a standalone best of breed platform in a financially stable 10M company or part of a suite of a larger 100M company or just one module in a suite in stable of suites in a 1B enterprise. So don’t try to guess which vendor will survive, instead focus on what platform will survive — and chances are you will be setting your organization up for success.