Category Archives: Market Intelligence

… 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!

Tomorrow is March for Science Day. That IS Important For Everyone.

Why? Besides the obvious that all modern technology is the result of science, you won’t get your next-generation cognitive sourcing platform without more advancement in, guess what, data science.

And, right now, in the US, every year, in addition to having to deal with the introduction, and passing, of more anti-science policies, you also have to deal with the fact that funding for science (education) is diminishing as well and it’s the cornerstone of all progress. What do you think inspires the continual advancement of advanced mathematics and statistics? Scientific need. And where do you think the roots of most of your analytical algorithms come from? Science.

So even though you spend your days slicing data and running reports in the back-office to meet the business goals of savings, reduced inventory turn-around time, reduced, risk, etc. — you’re still using the results of scientific research and progress. Don’t forget that. Or someday Kyle may not be able to flick the internet back on again when it starts to fail. (The sad reality is that because of a lack of science education and knowledge, some people actually believe this is how you fix the internet.)

For more information, see March for Science

You Want to Get Cognitive? Then Get Analytical!

As per our post yesterday, the new “cognitive” buzzword is getting a lot of people interested in modern Sourcing and Procurement technology, and that’s a good thing, except when it isn’t. (How can it now be? Not all providers truly offer cognitive capabilities, not all are equal among those that do, and not all are right for your organization.)

And unless you truly understand what cognitive sourcing can do, when it should be used, what technologies you need to power it, and how to properly apply it, the answer is no cognitive sourcing is right for you.

In yesterday’s post, we noted that there were five (deep) technology requirements that a cognitive sourcing platform had to meet to have any hope of truly being cognitive and zeroed in the optimization requirement to indicate that before you even think about getting cognitive you better acquire, and master, strategic sourcing decision optimization because you can’t really properly apply what you don’t really understand, and the vast majority of organizations don’t really have a clue what this is because they don’t have it.

But optimization is not the only area that the average Procurement organization doesn’t have a good grip on. Spend Analytics is another area. Most organizations that have “spend analytics” solutions really have first generation “spend reporting” solutions that are nothing more than a set of canned reports and a few mildly alterable report templates that are customized to certain categories or segments of the supply bases. That’s not analytics.

Regular readers of Sourcing Innovation know that true analytics is the ability to create your own cubes, derive your own dimensions, define your own (pivotable, filterable) reports, and drill across data elements until you find opportunities that cannot be exposed by a canned report. (See the Spend Analysis archives for over a decade of great insights.)

Next generation cognitive systems find opportunities by doing more than just running a set of canned reports on a monthly basis and looking at trends. They are regularly running running variations of dozens, if not hundreds, of analytics on purchase data against deep should cost models populated by ever changing commodity and market costs feeds and looking for variations and emerging trends that could signify potential opportunities as they emerge.

But to understand what’s an emerging opportunity vs. a blip and what is small enough to allow automated platforms to procure and big enough to justify a deep strategic sourcing event or second look at the market, you need to understand just what analytics can do and how to best apply the insight gained from, and the capabilities provided by, a modern cognitive platform — and that requires hands-on experience.

So get a modern spend analytics solution and get your hands dirty in the data. Then maybe, someday soon, you can think about getting cognitive.

You Want to Get Cognitive? First Get Optimized!

The new “cognitive” buzzword is getting a lot of people interested in modern Sourcing and Procurement technology, and that’s a good thing, except when it isn’t. (How can it now be? Not all providers truly offer cognitive capabilities, not all are equal among those that do, and not all are right for your organization.)

And unless you truly understand what cognitive sourcing can do, when it should be used, what technologies you need to power it, and how to properly apply it, the answer is no cognitive sourcing is right for you.

When it comes to sourcing, a sourcing solution must meet a number of requirements in order for it to be considered cognitive. It must be capable of:

  • supporting advanced cost models
    to allow for an accurate determination of should cost
  • supporting sophisticated automated data collection to populate those models from market indices, statistics bureaus, public (government) data repositories, etc.
  • supporting a large repository of trend analysis algorithms
    to help an organization understand market dynamics
  • support sophisticated analytics
    to help organizations slice, dice, and compare all the insights extracted by the cognitive platform
  • support advanced optimization
    to analyze the cost models and all the supply and logistics options available subject to business constraints

If you look at each of these requirements in comparison to an average Procurement organization with some semi-modern Supply Management technology

  • they have some cost modelling capability in their ERP
  • they have some automated data collection around risk and commodity costs through providers like D&B and Ecovadis and Market Index data providers
  • they have some familiarity with trend analysis in their inventory management systems
  • they have adopted a spend analytics platform, which may be a generation behind, but still gives them some cost insights
  • but they have no decision optimization at all

So if you really want to get cognitive, get optimized. Without a good understanding of what optimization can do, and how to use it, how do you expect to figure out when to apply, and not to apply, cognitive sourcing technology properly.

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.