Category Archives: Procurement Innovation

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.

To Manage Innovation, Governments Must Fix Procurement … And Take Care Where AI is Concerned!

A recent article on Civil Service World noted two things that attracted my attention:

  1. To manage innovation, governments must fix procurement
  2. Too often, contracts in AI do not give governments powers to investigate algorithms or the data they are trained on. As a result, they risk taking the blame when things go wrong without the means to find out why.

Public Procurement is expensive. Very expensive. Given that it represents 12% of the annual GDP of an average developed economy, that is a huge amount of spend. Given that the overspend in most departments of most jurisdictions is likely as bad as in the private sector, which means, depending on the category, is likely in the 4% to 6% range at a minimum (based on the results high performing organizations see when implementing best-in-class processes and technology), that means a minimum of 1/2% of GDP is being wasted annually, but based on the fact that most public sector projects exceed initial budgets and timelines, we’d bet that the overspend is double that and at least 1% of the annual GDP. That’s a lot of waste — 770 Billion on the top 10 economies. Furthermore, that assumes that all of the spend is necessary and well planned. (There is likely considerably more savings with better demand planning, more operational efficiency, better project planning, etc. We’re just stating that the savings on committed spend alone is likely 10%.)

The article notes that despite the strategic importance of Procurement, it’s rarely seen as a priority and is more often treated as a standardized compliance function, rather than a tool for strategic investment and, in some cases, has become synonaomous with absurdity, due to an accumulation of rules so complex that even those administering them cannot interpret them creates the perverse incentive of doing the least risky thing to avoid individual liability. As a result, governments end up buying obsolete technologies that make them vulnerable, because innovation evolves so rapidly, and forces them to buy more. The cycle repeats, budgets balloon, and public capabilities diminish.

And, unfortunately, public procurement is a brick-and-mortar process, still more suited to bulk-buying precisely describable goods, accounting for them, and moving onto the next purchase. Innovation is different: you do not know today what is going to be possible tomorrow, even when you are the one inventing the tech. While governments work in one-off projects, innovation is made of ever-changing, always-fleeting products.

Furthermore, those in charge of procuring these technologies are not technologists. Public procurement is professionalized in only 38% of OECD countries, so even if officials had the incentive to experiment, they would not have the expertise.

To combat this, the authors of the article propose that Procurement systems should be like good software, fluid, flexible, and constantly evolving. However, as they note, this will take more than changing rules. As they note, it will take talent that are experts in what they are buying. It will take the treatment of Procurement as a strategic function, with clear lines for advancement for all personnel (as studies have shown that even a marginal improvement in skill can yield significant reductions in costs, times, and contracting complexity). Thirdly, they will need a federated data environment to make use of modern technology. (Especially if they want to use AI.)

This is just the start of what is necessary. There needs to be regular training. There needs to be specialization to different types of functions and purposes. There needs to be a rewrite of rules to focus on the right outcomes, not just a plethora of rules designed to prevent previously undesirable outcomes. There needs to be clear paths from buyer to public organization CPO to department head, not just paths of advancement within the Procurement function. There needs to be a focus on what’s best for the public being served, not best to minimize the risk to the buyer. And a willingness to accept that their may be a few mistakes made here and there as new buyers learn the ropes, while a willingness to weed out anyone that “makes a mistake” in order to give a contract to a supplier who is not the best fit (and do so in exchange for a kickback).

But most importantly, if they acquire AI technology, they also need to acquire the right to investigate the algorithms being used, the data it is trained on, the results of prior training, and the right to inspect any changes to the algorithms, data, and training. Otherwise, you can never trust any AI technology you might want to acquire.

Because governments need to apply the most appropriate AI-enhanced technology more than the private sector, but are the least likely to be able to use them properly.

Do You Have Continuous Cost Control?

If not, you should, because with tariffs rising, markets falling, inflation out of control, sales dropping (as entire markets are cut off with sanctions and trade wars), we’ve gone beyond the point where every dollar counts to the point where every penny counts on every purchase because those pennies add up as every 100 purchases is a dollar and every 100,000 purchases is $1,000 and when money is as tight as it is now, that is actually value (especially for an organization making millions of purchases a year).

And right now, organizations are wasting a lot of dollars through the entire purchasing process. From poor sourcing strategy and process, to poor sourcing and negotiation, through poor purchasing execution, and poorer logistics management, to poor invoice and payment management. Every step without good cost control adds cost to the process, at a time when you need to be taking cost out just to survive.

And we know organizations are losing across the board because the following is required to keep costs in control:

  • good processes at each step
  • (near) real time market intelligence at each step
  • good systems supporting each step
  • continuous monitoring at each stage

And we’ve never seen an organization, even a best-in-class organization, that has all of this for their Procurement department. In fact, it’s rare to find an organization that has more than half of this. It’s now at the point where your organization may not survive if it does not have:

  • well defined processes for
    • supplier discovery and management
    • sourcing
    • contract award and management
    • procurement, on-and-off contract
    • invoice management and accounts payable
    • logistics and warehousing
    • ongoing analysis
  • (near) real-time market intelligence at each step
    • current, financially stable, accessible suppliers
    • current commodity costs, average overhead costs by region, tariffs, etc.
    • current best practices, standard clauses, and insurable risks
    • market availability, quality, delivery times, remaining contractual commitments
    • current entity information, payment terms, standard processing times, community intelligence on supplier OTD
    • carrier availability, costs, surcharges, etc.
    • changes in spend trends and curves, etc.
  • good systems/modules supporting each step
    • supplier 360 module (not just SIM/SRM/SPM .. all supplier data and interactions)
    • sourcing (RFX) management
    • contract negotiation tracking, signing, and ongoing management
    • e-Procurement that supports ALL purchases through the system
    • I2P with automated invoice processing and workflows
      (85% should be touchless on implementation, 95%+ over time)
    • logistics booking and carrier monitoring
    • best in class spend and performance analysis that updates at least daily
      (and regularly re-runs best-in-class trend and outlier analysis and alerts you to unexpected changes)
  • … with built-in alerting when something unexpected happens or doesn’t happen on schedule / as expected

And you don’t. But you need this now more than ever. So, if you don’t have:

  • processes, define them; they can be basic to start; for example, classic 7-step sourcing is enough to start (even though there are some more refined 11 step processes)
  • market intelligence, get yourself some; in particular, supplier discovery as some of your suppliers will go out of business, be unreachable, or get too expensive in the days to come; cost modelling for major spend categories to understand true costs for better negotiations because even if it only shaves half a percentage point on average, that’s still 500K on a 1M category (and you can get some of these solutions for under 100K a year), and those hundreds of thousands quickly add up to millions; and major news/event monitoring to pinpoint emerging risks as fast as possible
  • modules supporting the entire S2P process, acquire them; note that most of these don’t need to be BiC; for example, all of the major suites will tout the tens or hundreds of millions their big customers have “saved” with their solution, but what they won’t tell you is that at least 90% of that savings simply resulted from the client implementing a good process supported by a tool with a decent workflow solution; in other words, you don’t need the multi-million dollar solution (to start), you’ll see the same benefit from a six figure suite that is better than average in the key modules that matter to you (especially since it will take you years to master the new processes it will support, meaning that for a big suite, it’s usually five years or more before you can see more value than just going with a basic solution given that the journey to Best in Class, as determined by Hackett in the mid moughts, is at least eight years)
  • continuous data modelling and analysis, start now; with your spend analysis and performance tool updated at least daily

you need to make a plan to incrementally acquire what you are missing, most critical need first, until you do. (Remember, don’t try a big bang implementation. No matter what the vendor or Big X will tell you, those always end in big booms.)

Stop Being Clueless. It’s Time for Revenge of the Nerds!

Last week we tried to further demystify the marketing madness for you by clarifying that spend orchestration is essentially Clueless for the popular kids.

This is really important because there is no difference between a “spend” orchestration and a plain old “regular” orchestration provider, and neither provides any value whatsoever if you don’t have any spend management (i.e. procurement) systems in place to actually process the spend. Otherwise, the best you get is intake to nowhere … which just provides your stakeholders yet another avenue to ask “where’s my stuff” and another reason to say “I thought this new system was supposed to make you more efficient” and get more impatient when their stuff doesn’t arrive any faster.

In other words, unless you have a hodge-podge of best-of-breed systems that cover most, if not all, of the source-to-pay process, that don’t interconnect, and the systems are old and don’t support multiple roles (or charge full license fees for each user, even a 99% read-only role, that access the users), there is no value in an orchestration, as we’ve said many times (including in our post on how Marketplace Madness is Coming.

What you need is not spend orchestration but spend defenestration — you need to throw any and all unnecessary spend out of the window, and that requires spend investigation, need verification, negotiation, observation, and payment verification. That requires spend analysis, demand forecasting and management, fact-based market insight, adherence to contracts and plans, proper procurement platforms, and proper payment validation platforms.

Moreover, it requires proper utilization of these platforms. And that requires Human Intelligence (HI!), skill, and deep (deep) Procurement knowledge. Geek skill and Procurement nerdiness. The nerdiness to use a best-in-class spend analysis and seek out the opportunity that a pre-packaged analytics routine will never find (because you’ve already stared at that report ten times and found nothing after the second time [wonder why?]). The nerdiness to examine the forecasts and use best-in-class forecasting techniques on real (and up-to-date) sales and market demand data. The nerdiness to pour through market cost data for materials, standard overhead costs, energy costs, water costs, differential costs for different production models, and cost models presented to you by third parties and the supplier to pinpoint the right the model, the right data to feed it with, and the true production cost at different volume levels — and then use this in a fact-based market data negotiation. Then, when you cut an agreement, the nerdiness to make sure it is encoded in the right systems and properly executed on as well as the nerdiness to follow the market over time and detect any inflections that would require you to change direction. And, finally, the nerdiness to make sure the platform is configured to properly m-way match every invoice, detect any attempts to fraudulently change the amount, terms, and payee, and only pay for goods and services received on the agreed upon schedule. In other words, if you want to truly succeed at Procurement, forget about the Clueless — It’s time for the Revenge of the Nerds!