Category Archives: Sourcing Innovation

For Proper Direct Sourcing, Different Organizational Thinking is Required

In our last post we noted that standard sourcing solutions don’t work for direct and referred you to our seven part series with Bob Ferrari of Supply Chain Matters at these links:

And we noted the reason was that direct sourcing doesn’t work isolated from supply chain. Fortunately, direct sourcing and supply chain planning can work together, but only if we

Think Different

This is the only way we are going to realize business and operational planning alignment from source to supply. Right now, it takes too much time across the various strategic, tactical, and operational decision making processes in the gathering, assimilation or transcribing of the most up to date line-of business, functional or operational focused data and information into spreadsheets and antiquated tools to support forecasting, sourcing, supply chain, and logistics systems.

This is primarily due to the fact that not only are each of these processes for different timeframes but they are typically conducted using different business processes. Long term strategic planning is typically conducted using IBP methodologies, mid-term tactical planning is typically conducted using S&OP methodologies, and short-term planning is typically conducted using exception planning, materials replenishment planning, logistics re-routing, etc.

Each plan requires information on the connecting layers in order to make a decision. IBP requires knowledge of what S&OP can do and the best historical results from S&OP to come up with the plans most fit for execution. S&OP requires knowledge of the overriding IBP goals as well as the operational systems used for day to day procurement, inventory replenishment and management, logistics and trade management, and production. Since most of these systems don’t talk, it’s a lot of manual data collection, processing, and pushing up and down the levels and the chain.

These processes need to be connected in integrated planning loops that span:

  • Plan, Source and Procure
  • Plan and Analyze
  • Plan and Produce
  • Execute and Fulfill

Moreover, these planning process frameworks need to be enabled by more effective data management, data harmonization, and analytics that enables these loops to constantly be executed and re-executed as needed to ensure each level of planning and each step of the process has the data it needs to suggest the right answer for the human to make the right decision.

Finally, this will only happen if organizational employees think different and adopt new processes, frameworks, data models, and strategies to integrated planning from source to supply. For some insights in to how this might happen, see part three of our joint series on how today’s Organizational Thinking is Wrong.

Standard Sourcing Solutions Don’t Work For Direct

the doctor recently teamed up with the Supply Chain Master Bob Ferrari over on Supply Chain Matters to bring you an initial seven part series on why Standard Sourcing Technology Solutions Don’t Work for Direct, which you can find at these links:

If you read Parts I and Part II in detail, which you most definitely should because we’re only going to summarize a few highlights here, we detail some of the big reasons they don’t work, besides the fact that most were designed for indirect and can’t even do the basics of direct sourcing. The reasons we put forward included:

  • Direct Material Sourcing is Hard
    • substitution (like satisfaction) is not guaranteed
    • substitution is always conditional when available
    • demand is not easily aggregated
    • delivery time guarantees are often significantly more important
  • Sourcing Platforms Don’t Do Direct Well (as most were designed for indirect)
  • Most Sourcing Platforms Don’t Support Bill of Materials
  • Most Sourcing Platforms Don’t Support Optimization

Then we dove into why direct solutions don’t work either:

  • It’s Not Just Landed Cost, It’s Total Cost of Acquisition
  • It’s Not Just Cost, It’s Supply Assurance
  • It’s Not Just Supply Network Assurance, It’s Timing

That’s just the baseline sourcing side of the equation. We still haven’t talked about the supply assurance side:

  • They Aren’t Designed for Multi-Stage NPD/NPI Sourcing and Quality Assessments
  • They Aren’t Designed to Capture Network Performance and Carrier Risk
  • They Aren’t Designed to Capture and Assess External Risks

That last point is key. If you’re not considering the geopolitics of where you are sourcing from and where you are sourcing to, and how those might change in the near future, you could be in for quite a shock, as many of you in the USA found out this year. If you had been paying attention to the election, noted how much a certain Tech Bro donated to a certain campaign, and compared that number to past campaign contributions, you would have known the election, which appeared neck and neck, was being bought and paid for, which party was going to win, and who was going to be President.

If you did your research, analyze everything he said publicly in the decades leading up to his first campaign for political office, look at what he actually did in his first term, and read Project 2025, you would have known something was coming on the trade front, especially where certain countries were concerned. And you would have known that what was coming was not going to be good for your business if you were sourcing from China.

But it’s not just the “to” destination you have to worry about, especially if the only thing increasing is cost. It’s also the “from” destination, which could be cut off entirely by a new regime that imposes sanctions or embargoes, or could undergo a rapid economic decline due to bad government decisions, external third party sanctions and embargoes, or global shifts in trade. A great discussion of this can be found in Koray Köse’s recent LinkedIn post on on Poland’s Economy: Reslient Amid Political Storms and how it faces a test under it’s new President — and how, should it fail that test, supply chain leaders need to be prepared. It’s the perfect example of why supply chain considerations need to be pulled back to sourcing, because there’s no way an average sourcing professional today would consider any of this when evaluating suppliers for a direct sourcing project.

Features ARE NOT Applications; But Applications Require Features!

THE PROPHET recently asked What Procurement Tech Product Categories Were Really Just Features All Along? Which is a great question, except he cheated.

He cheated with the first 5!

  • Supplier performance management
  • Supplier quality management
  • Supplier information management / supplier master data management
  • Supplier diversity
  • Supplier risk management (not supply chain risk!)

We’ve known for years it should be one Supplier 360 solution! (Even though no one offers that when you consider all of the elements that should be there. Heck, none of them even offer the 10 basic CORNED QUIP requirements … in fact, good luck finding a solution that offers 5 of those requirements among the 100+ supplier management solutions).

He you cheated again with the next 3!

  • Should cost / cost modeling (for procurement, not design engineers)
  • RFX and reverse auctions (when not bundled with broader capabilities or services)
  • Sourcing optimization

We’ve also known for yours it should be cost-model and optimization backed sourcing (auction, RFX, hybrid, single source negotiation, etc.) … otherwise, it’s an incomplete solution. But only a fraction of the 80+ sourcing platforms offer true optimization (less than 10) and fewer still do extensive cost modelling. (Note that we are focussed on modelling, not cost estimation — that requires data, and that can, and probably should, be a third party data feed.)

And he was wrong on the last front.

Real Spend Analytics should be standalone. Wrapping restricts it! The modules you use should provide all the specific views you need, but the reason that spend analysis quickly becomes shelfware in most organizations today is the same reason it became shelfware 20 years ago … once you exhaust the limits of the interface its wrapped in, it becomes useless. Go back to the series Eric and I wrote 18 years ago (which you can since Sourcing Innovation didn’t delete everything more than a decade old when it had to change servers in 2024, unlike Spend Matters when it did its site upgrade in 2023).

But Very, Very right in that features are not applications!

And very, very right in that too many start-ups are launching today as features (which will only survive if acquired and rolled up into existing applications and platforms), and not solutions. While apps dominate the consumer world, in business there is not always an app for that, and, frankly, there shouldn’t be. This focus on point-based apps is ridiculous. It’s not features, it’s functions. It’s not apps, it’s platforms. It’s not orchestration (and definitely not spend orchestration), it’s ecosystems!

Recent stats, such as those published by Spendesk put the average number of apps a business uses at 371, with an average of 253 for SMBs and 473 for enterprise firms. WHAT. THE. F6CK? This is insane. How many departments does an average organization have? Less than 10. How many key functional areas? Less than 12. Often less than 10! How many core tasks in each function? Usually less than 6. That says, in the worst case, an enterprise might have 72 distinct critical tasks which might need their own application (but probably not). This says that SMBs have at least 3 times the app they should have, mid-size organizations at least 5 times, and enterprises at least 7 times. That is insane! No wonder there are so many carbon copy SaaS optimizers (as we covered in our piece on sacred cows), because if you have that many SaaS apps, you have features, not applications. And you need to replace sets of these with functional applications that solve your core problems.

(And if you want to know how to prevent app sprawl, before buying yet-another-app, ask yourself “is this supporting a function that should be done on its own, or just a task that should be part of an existing function” … if the latter, it’s a feature, not an application, and if the application it should be part of does not have an upgrade/module that supports the task, then you have the wrong application and it’s time to replace it, not pointlessly extend the ecosystem!)

Follow the Money to Find Future Opportunity — Which Will NOT Be Fully Found With Autonomous Sourcing!

Spend Matters has thrown caution to the wind and followed Gartner’s lead jumping onto the AI Hype Bus (with no steering and no brakes) that is still heading straight for the cliff and are wheeling out webinars on AI faster than a prairie fire with a tailwind. (Needless to say Sourcing Innovation does not think this is a good thing. There are valid uses for AI and automated processing, but fully handing over financial decisions is like wheeling in the Trojan Horse and leaving it unguarded in the server room with unrestricted access to your bank integration.)

Recently, The Maverick advertised yet another Spend Matters webinar on Autonomous and AI Sourcing where he said we should “follow the money”. Which we should, but there are a few things we need to clarify first.

1. No Money Changes Hands In Sourcing

It changes hands in Procurement … and it’s because most companies don’t follow the money after the contract is signed that 30 to 40 cents of negotiated savings never materialize in many companies, which The Maverick should remember from his AMR and Hackett days, as it was laid clear in Mickey North Rizza‘s famous 2009 “Reaching Sourcing Excellence” series, which we know is in his archives.

2. “Speed” is NOT a strategic edge if you don’t get it right!

If you don’t go out with the right strategy, don’t know the current market price, don’t know the reason for the current market price, and don’t have the knowledge to project if the trend is going to continue, stabilize or reverse, going to market is not a good decision … and it’s an even worse decision to automate the sourcing project and secure an award as fast as possible if you don’t know if it’s the best you could have done or the worst you could have done.

3. “Pecunia non olet”, but yet these vendors are asking you to treat it like it does!

They want you to automate spend analysis, sourcing, contracts, purchases, and everything else that involves money by turning over everything to their Agentric AI because, apparently, money stinks and you don’t want to touch it. (But they are quite happy to not only spend yours for you but takes as much of it as they can for their services.)

But here’s what they don’t tell you.

  • AI is NOT Intelligent.
    The level of intelligence in their “AI” is equivalent to the level of intelligence in a carpenter’s hammer. The level of effectiveness is entirely dependent on how skilled the person “training” the system and how skilled the person “using” the system is, just like the effectiveness of a hammer is dependent on how well the carpenter was trained and how experienced he is in it’s use.
  • AI Does Not Know What it Does Not Know.
    If the data is incomplete, the recommendation is very likely incorrect.
  • AI Cannot Do Better than the Best A Human Has Ever Done in Decision Making.
    So, if none of the situations it was trained on led to great results, neither will what it recommends for you.

You need to remember how Gen-AI does its work (or should we say does not work). It is large document search and summarization and chain of compute. Now, the more advanced players are trying to embed knowledge graphs into this, but these are not perfect either. With good training examples, and a very similar situation, the probability it will work well is very good, but it’s still only a probability. As a result, nothing should ever be fully automated where money is concerned. The tools should be used for their recommendations, and if the recommendations are good, and the risk is low, most of the tactical data processing and event management should be automated, but the decisions should ALWAYS be made by a human, who should be involved at every decision point. Even if that decision is verifying the system recommendation. It only takes one miscalculation due to an incomplete data source to project a wrong trend, rush an auction, lock in a price 3X what you are paying now, only for it to fall in a month later when a factory (which went offline temporarily due to a manmade or natural disaster) comes back online and the supply-demand balance returns to normal. And while you may have stocked out for two weeks, those losses will be orders of magnitude less than paying 3X at a contract you have to honour (unless you want to get dragged into court).

Now, if you really want to make money, forget all this Autonomous and Agentric AI BS, look for Augmented Intelligence solutions that make your staff two, three, five, and even ten times more efficient, purchase those, and, remembering that the US infrastructure is crumbling fast (and not going to get renewed under a Republican administration that is more interest in trickle-on economic tax cuts for its billionaires than ensuring you have running water), it’s time to remember how the smart made money in ancient Rome — public bathhouses and latrines. Time to invest in your own desalination facilities and be ready when the public wells run dry. After all, “Pecunia Non Olet“.

With Great Data Comes Great Opportunity!

In fact, it can quadruple your ROI from a major suite.

Not long ago, Stephany Lapierre posted that your team may only be realizing <50% of the ROI from your Ariba or Coupa investment, to which, of course, my response was:

50% of value on average? WOW!

Let’s break some things down.

A suite will typically cost 4X a leaner mid-market offering which is often enough even for an enterprise just starting it’s Best in Class journey (that will take at least 8 years, as per Hackett group research in the 2000s).

Moreover, even if the enterprise can make full use of the suite it buys for 4X, at least 80% of the “opportunity” comes from just having a good process, technology, baseline capability and automation behind it. That says you’re paying 4X to squeeze an additional 20% worth of opportunity in the best case.

On average, it takes 2 to 3 years to implement a suite (on a 3 to 5 year deal). So maybe you’re seeing an average of 66% functionality over the contract duration.

As Stephany pointed out, bad data leads to

  • increased supplier discovery and management times
  • invoice processing delays and errors
  • increased risk and decreased performance insight

As well as an

  • inability to take advantage of advanced (spend) analytics
  • inability to build detailed optimization models
  • decreased accuracy in cost modelling and market prediction

This is even more problematic! Why? These are the only technologies found to deliver year-over-year 10%+ savings! (This is where the extra value a suite can offer comes from, but only with good data. Otherwise, at most half of the opportunity will be realized.)

Thus, one can argue an average organization is only getting 66% of 25% of 80% of its investment against peers (based on 2/3rd functionality, the 4X suite cost, and the baseline savings available from a basic mid-market application that instills good process and cost intelligence) and 50% of 20% (as it is able to take advantage of at most half of the advanced functionality offered by the suite due to poor and incomplete data). In other words, at the end of the day, we’d argue an average company is only realizing 23% of the potential value from an opportunity perspective!

However, as one should rightly point out, the true value of a suite is not the value you get on the base, it’s the ROI on that extra spend that allows for 20% more opportunity than a customer can get from lesser peer ProcureTech solutions.

For example, let’s say you are a company with 1B of spend with a 100M opportunity.

If tackling 20M of that opportunity requires advanced analytics, optimization, and extensive end-to-end data, it’s likely that you’ll never see that with an average mid-market solution with limited analytics, no optimization, and only baseline transactional data. If the company paid an extra 1.5M over 3 years for this enhanced functionality, then the ROI on that is 13X, which is definitely worth it.

Moreover, if the suite supports the creation of enhanced automations, you could get more throughput per employee and realize the base 80M with half or one quarter of the workforce, which would lead to a lowering of the HR budget that more than covers the baseline cost.

However, ALL of this requires great data, advanced capability, and the in-house knowledge to use both. This is only the case in the market leaders. As a result, we’d argue that the majority of clients are only realizing about 25% of the suite’s potential — when sometimes the only thing standing in their way of realizing the rest is good data.