Monthly Archives: March 2024

The Best Way Procurement Chiefs Can Create a Solid Foundation to Capitalize on AI

As per our recent post on how I want to be Gen AI Free, the best way to capitalize on Gen-AI is to avoid it entirety. That being said, the last thing you should avoid is the acquisition of modern technology, including traditional ML-AI that has been tried and tested and proven to work extremely well in the right situation.

That being said, if you ignore the reference to Gen-AI, a recent article on Acceleration Economy on 5 Ways Procurement Chiefs Can Create a Solid Foundation had some good tips on how to go about adopting ML-AI with success.

The five foundations were quite appropriate.

1. Organize

A plan for

  1. exactly where the solution will be deployed,
  2. what use cases it will be deployed for,
  3. how valid use cases will be identified, and
  4. how the solution is expected to perform on them.

There’s no solution, even AI, that can do everything. Even limited to a domain, no AI will work for all situations that may arise. As a result, you need a methodology to identify the valid use cases and the invalid use cases and ensure that only the valid uses cases are processed. You also need to ensure you know the expected ranges of the answers that will be provided. Then you need to implement checks to ensure that no only are only valid situations processed but that only output in an expected range is accepted in any automated process, and if anything is outside the expected norms anywhere, a human with appropriate education and training is brought into the loop.

2. Create a Policy

No technology should be deployed in critical situations without a policy dictating valid, and invalid, use. Moreover, any technology definitely shouldn’t be used by people who aren’t trained in both the job they need to do and proper use of the tool. Even though most AI is not as dangerous as Gen-AI, any AI, if improperly used, can be dangerous. It’s critical to remember that computers cannot think, and only thunk on the data they are given (performing millions of calculations in the time it takes an average person to perform two). As such, the quality of output is limited both to the quality of data input and the knowledge built into the model used. Neither will be complete or perfect, and there will always be external factors not considered, which, even if normally not relevant, could be relevant — and only an educated and experienced human will know that. (Moreover, that human needs to be involved in the policy creation to ensure the technology is only used where, when, and how appropriate.)

3. Understand Your Platform(s) of Choice

Just like there are a plethora of Gen-AI applications, a lot of different vendors offer AI applications, and even if most are similar, not all are created equal. It’s important to understand the similarities and differences between them and select the one that is right for your business. (Consider the algorithms and models used, the extent of human validated training available, typical accuracy / results, and the vendor’s experience in your use case in particular when evaluating an AI solution.)

4. Practice

Introducing new tools requires process changes. Before introducing the tool, make sure you can execute the associated process changes, first by executing training exercises on the different types of output you might get and then, possibly by way of a third party who uses a tool on your behalf, using real inputs and associated outputs. While the AI may automate more of the process, it’s even more critical that you respond appropriately to parts of the process that cannot be automated or where the application throws an exception because the situation is not appropriate to either the use of AI or the use of the AI output. (And if you don’t get any exceptions, question the AI … it’s not likely not working right! And if you get too many exceptions, it’s not the right AI for you.)

5. ALWAYS Ask Yourself: “Does that Make Sense?”

Just like Gen-AI hallucinates, traditional AI, even tried-and-true AI that is highly predictable, will sometimes give wrong results. This will usually happen if bad data slips in, if the use case is on the boundary of expected use cases, or the external situation has changed considerably since the last time the use case arose. Thus, it’s always important to ask yourself if the output makes sense. For tried-and-true AI where the confidence is high, it will make sense the vast majority of the time, but there will still be the occasional exception. Human confirmation is, thus, always required!

With proper use, AI, unlike Gen-AI (which fails regularly and sometimes hallucinates so convincingly that even an expert has a hard time identifying false results), will give great results the majority of the time — so you should seek it out and implement it. Just also implement checks and balances to catch those rare situations it doesn’t and put a human in the loop when that happens. Because traditional use-cases are more constrained, and predictable, it’s a lot easier to identify and implement these checks and balances. So do it … and see great success!

Last Friday Was International Women’s Day. You Made a Big Fuss. Well, What Did You Do This Week?

This is taken from a LinkedIn post the doctor posted on Monday, March 11. It’s being reposted here for those who don’t follow LinkedIn and because, as expected, he hasn’t heard a single peep from any organization that was spewing platitudes last Friday as if praise one day a year was doing enough.

If you truly celebrate women, then please tell me:

What are you doing TODAY to

  1. increase the number of women in Management, STEM, Executive Suites, and Investment Firms,
  2. close the pay gap that is still 15% to 30% across these areas,
  3. encourage women to join your company to pursue their career, and
  4. enable the work life balance they need to be AS or MORE successful than their male counterparts?

As most of you are probably well aware from the deluge of “we support and honour our female leaders who … ” posts on LinkedIn last Friday, International Women’s Day was last Friday (2024-Mar-08). I stayed silent, as usual, because I found the majority of them very upsetting.

While some of the posts were very sincere, and some came from individuals I know had the best of intentions:

  1. Lip service does nothing to address the four major issues above.
  2. The lip service I saw in some of these posts was about as meaningful as a token thank you card at the annual Christmas party.
  3. Few addressed the real issues women still face in “traditional” workspaces run, and dominated, by men.
  4. Those few that honoured teams with equal representation or greater, or at least statistically average representation (in companies in fields where women are currently only 25% of the workforce, like STEM) have done nothing to educate their peers on how important this is and how successful they are because of it.

If you are a leader in a company (with actual employees) that truly cares, then I challenge you to celebrate their achievements and capability every day, and once a month make a post on efforts your company is taking to increase the number of women, close the pay and rank gaps, and support their work life balance, either through hiring, training, support for community programs that do such or at least make a post on the stellar accomplishments they have accomplished that would put an average salesman to shame.

And to keep doing this until they have the equality, and the respect they deserve.

The simple facts are

  1. women are half the population,
  2. are just as capable of men (as there is NO difference between average IQ scores), and
  3. should be half the workforce.

If women are not half the workforce at your company (or at least not represented statistically in line with the average representation in the field your company is in), it’s not their lack of achievement, dear men, it’s yours!

The Public Sector is Giving Procurement Integrity A Bad Name … Can the Private Sector Fix It?

A recent article over on Global Government Forum on Procurement Integrity: A Big Problem That’s Worse Than Most Organizations Think, pointed out that errors, fraud and abuse in procurement cost governments and organizations millions of dollars every year, and even though recent headlines in the US (TriMark, Booz Allen Hamilton), UK (NHS, Royal Mail), and Canada (ArriveCan) are starting to shine the light on the extent of (public sector) procurement fraud, the problem is still bigger than you think. Much bigger.

Current estimates are that organizations, across the public and private sectors, lose 5% per year due to procurement errors, abuse, and fraud. Given that Global GDP is about 85 Trillion dollars, at 5%, that’s 4 TRILLION dollars estimated to be lost annually to errors, abuse, and fraud. And that’s probably a low-ball estimate due to the fact that we just calculated that Over One TRILLION dollars will be wasted on IT software and services due, primarily, to lack of knowledge and/or outright stupidity (and not malicious intent, but if it’s easy for consultancies and third parties to considerably over bill for legitimate goods and services that you need, imagine how much they are fleecing you for goods and services that you don’t need and may not even receive).

It’s highly likely that the true cost of errors, abuse, and fraud (internal, collusion, and external) is closer to 10% of total GDP, or close to EIGHT TRILLION. That’s at least twice the GDP of every country on the planet except China and the United States. That’s a BIG PROBLEM, which is definitely not being helped by the 100M to Multi Billion Procurement Frauds being reported almost monthly across major western economies — and multi-million dollar fines don’t repair the damage. (They don’t even come close.)

This is damage which Procurement needs to repair — because Procurement is the only department that has any hope of putting proper procedures, processes, and platforms in place to minimize the errors; training the organizational employees on proper procedures and monitoring the implementations to prevent abuse; and putting in place proper detection systems to detect, and prevent, potential fraud and quickly identify and track it when it happens.

Unless all the bucks go through, and stop at, a modern Procurement department run by a CPO who puts in place proper people, processes, and platforms, loss is going to continue to run rampant. Which means that while the public sector is failing us daily, the Private sector has to step up and restore the integrity of Procurement. It can start by utilizing some of the the techniques in the linked article, and continue by continually learning and implementing the best technology and processes it finds to not only uncover significant savings in inflationary times, but return integrity and trust into big business, and give governments who have lost their way a model to follow.

And for more details on Bad Buying to avoid, and how to achieve Procurement with Purpose, the doctor suggests you start by following the great public procurement defender, Peter Smith.

The Power of Optimization-Backed Sourcing is in the Right Sourcing Mix Across Scales of Size and Service

the doctor has been pushing optimization-backed sourcing since Sourcing Innovation started in 2006. There’s a number of reasons for this:

  • there is only one other technology that has repeatedly demonstrated savings of 10% or more
  • it’s the only technology that can accurately model total cost of ownership with complex cost discounts and structures
  • it’s the only technology that can minimize costs while adhering to carbon, risk, or other requirements
  • it’s one of only two technologies that can analyze cost / risk, cost / carbon, or other cost / x tradeoffs accurately

However, the real power of optimization-backed sourcing is how it can not only give you the right product mix, but the right mix across scales. This is especially prevalent when doing sourcing events for national or international distribution or utilization. Without optimization, most companies can only deal with suppliers who can handle international distribution or utilization. This generally rules out regional suppliers and always rules out local suppliers, some of whom might be the best suppliers of goods or services to the region or locality. While one may be tempted to think local suppliers are irrelevant because they will struggle to deliver the economy of scale of a regional supplier and will definitely never reach the economy of scale of a national (or international) supplier, unit cost is just one component of the total lifecycle cost of a product or service. There’s transportation cost, tariffs, taxes, intermediate storage, and final storage (of which more will be required since you will need to make larger orders to account for longer distribution timelines) among other costs. So, in some instances, local and regional will be the overall lowest cost and keeping them out of the mix increases costs (and sometimes increases carbon and risk as well).

When it comes to services, the right multi-level mix can lead to savings of 30% or more in an initial event. the doctor has seen this many times over his career (consulting for many of of the strategic sourcing decision optimization startups) because while the big international players can get competitive on hourly rates where they have a lot of resources with a skill set, when it comes to services, there are all in-costs to consider, which include travel to the client site and local accommodations. The thing with national and international services providers is that they tend to cluster all of their resources with a certain skill set in a handful of major locations. So their core IT resources (developers, architects, DBAs, etc.) will be in San Francisco and New York, their core Management consultants will be in Chicago and Atlanta, their core Finance Pros in Salt Lake City and Denver, etc. So if you need IT in Jefferson City, Missouri, Management in Winner, South Dakota, or accounting in Des Moines, Iowa, you’re flying someone in, putting them up at the highest star hotel you have, and possibly doubling the cost compared to a standard day rate.

However, simple product mix and services scenarios are not the only scenarios optimization-backed sourcing can handle. As per this article over on IndianRetailer.com, retailers need to back away from global sourcing and embrace regional (and even local) strategies for cost management, supply stability, and resilience. They are only going to be able to figure that out with optimization that can help them identify the right mix to balance cost and supply assurance, and when you need to do that across hundreds, if not thousands, of products, you can’t do that with an RFX solution and Microsoft Excel.

Furthermore, when you need to minimize costs when a price is fixed, like the price of oil or airline fuel, you need to maximize every related decision like where to refuel, what service providers to contract with, how to transport it, etc. When it can cost up to $40,000 to fuel a 737 for a single flight (when prices are high), and you operate almost 7,000 flights per day with planes ranging from a gulf stream that costs about $10,000 to refuel to a Boeing 747 that, in hard times, can cost almost $400,000 to refuel, you can be spending $60 Million a day on fuel as your fleet burns 10 Million gallons. Storing those 10 Million gallons, transporting those 10 Million gallons, and using that fuel to fuel 7,000 planes takes a lot of manpower and equipment, all of which has an associated cost. Hundreds of thousands of associated costs per day (on the low end), and tens of millions per year. Shaving off just 3% would save over a million dollars easy. (Maybe two million.) However, the complexity of this logistics and distribution model is beyond what any sourcing professional can handle with traditional tools, but easy with an optimization backed platform that can model an entire flight schedule, all of the local costs for storage and fueling, all of the distribution costs from the fuel depots, and so on. (This is something that Coupa is currently supporting with its CSO solution, which has saved at least one airline millions of dollars. Reach out to Ian Milligan for more information if this intrigues you or how this model could be generalized to support global fleet management operations of any kind.)

In other words, Optimization-Backed Sourcing is going to become critical in your highly strategic / high spend categories as costs continue to rise, supply continues to be uncertain, carbon needs to be accounted for, and risks need to be managed.

One of these things is not like the other — it’s the right choice!

Note the Sourcing Innovation Editorial Disclaimers and note this is a very opinionated rant!  Your mileage will vary!  (And not about any firm in particular.)

Three bids for that spend analytics project from the three leading Big X firms come in at 1 Million. One bid for that spend analytics project from a specialized niche consultancy you pulled out of the hat for bid diversity comes in at 250 Thousand. Which one is right?

Those of you who only partially paid attention to the education Sesame Street was trying to impart upon you when you were growing up will simply remember the “one of these things is not like the other” song and think that any of the bids from the Big X firm is right and the niche consultancy is wrong because it’s different, and therefore must be thrown out because it’s too low when, in fact, it’s just as likely that the three bids from the Big X firms that are wrong and the bid from the niche consultancy that was right.

Those of us who paid attention knew that Sesame Street was trying to show us how to detect underlying similarities so we could properly cluster objects for further analysis. What we should have learned is that the Big X bids were all the same, built on the same assumption, and can be compared equally. And that the outlier bid needed further investigation — a further investigation that can only be undertaken against an appropriately sized set of sample set of bids from other specialized niche consultancies to compare against. And without that sample set of bids, you can’t properly evaluate the lower bid, which, the doctor can tell you, is just as likely to be closer to correct than what could be wildly overpriced Big X bids.  (Newer firms often have newer tech and methods — and if these are the right methods and tech for your problem … )

As per our recent post, if you want to get analytics and AI right, most of these guys don’t have the breadth and depth of expertise they claim to have (as most don’t have the educational background to know just how broad, deep, and advanced AI and analytics can get, especially when you dig deep into the math and computer science and all of the variable models and strengths and weaknesses, and instead are trained on what is essentially marketing content from AI and analytics providers). In the group that sells you, there will be a leader who is a true expert (and worth his or her weight in platinum), a few handpicked lieutenants who are above average and run the projects, and a rafter of juniors straight out of private college with more training in how to dress, talk, and follow orders than training in actual analytics … and no guarantee they even have any real university level mathematics beyond basic analysis in operational research (and thus a knowledge of what analytics is and isn’t and can and can’t do).  And unless you know what you need, and why, you can’t judge the response.  (Furthermore, you can’t expect them to figure out your problem and goals with only partial information!)

While there was a time big analytics projects were (multi) million dollar projects, that was twenty years ago when Spend Analysis 1.0 was still hitting the market; when there were limited tools for data integration, mapping, cleansing, and enrichment; and when there weren’t a lot of statistics on average savings opportunities across internal and external spend categories. Now we have mature Spend Analysis 3.0 technologies (some taking steps towards spend analysis 4.0 technologies); advanced technologies for automatic data integration, mapping, cleansing, and even enrichment; deep databases on projects and results by vertical and industry size; extensive libraries for out-of-the-box analytics across categories and potential opportunities; and a whole toolkit for spend analysis that didn’t exist two decades ago. This new toolkit, built by best of breed vendors used, and sometimes [co-]owned by these best of breed niche consultancies (that don’t try to do everything, and definitely don’t pretend they can), allows modern spend analysis projects to be done ten times as efficiently and effectively, in the hands of a master — a master that isn’t necessarily on your project if you hire a Big X or Mid-Sized Consultancy without doing your homework, vetting the proposal, and vetting the people. [See when should you be using Big X.]

In contrast, a dedicated niche consultancy should have all these tools, and only have masters on the project who do these projects day in and day out. Compared to the bigger consultancies who don’t specialize in these projects, which will have a team of juniors using the manual playbook from the early 2000s, and one lieutenant to guide them. That’s often why sometimes their project bids are five times as much — and why you should be inviting multiple niche best-of-breed consultancies to bid on your project as well as multiple Big X consultancies (including those that are truly focusing on analytics and AI, and you can identify some of these by their recent acquisitions in the area) and be focusing in just as much on the six figure bids for the one that provides the best value, not just the seven figure Big X bids.  (And, FYI, if you invite enough Big X, you might find some come in at six figures and not seven because they have acquired the newer tech, took the time to understand your request, and figured out how they could get you the same value for less cost, leaving you funds for the follow on project where you should consider the Big X!)

(This is also the case for implementations. The Big X always have a rafter on the bench to assign to any project you give them, but there’s no guarantee any of them have ever implemented the system you chose before, or if they did, no guarantee they’ve ever connected it to the systems you need to connect to. You need specialists if you want a new system implemented as cost effectively as possible, especially if its a narrow focused specialist application and not a big enterprise application the Big X always implements. At the end of the day, even if you’re paying those specialists 500 or more an hour because getting a system up in 2 months at 40K is considerably better than a small team of juniors taking 4 months at 200 an hour and a total cost of 80K.  But again, mileage will vary — if the solution you select is a Big X partner, then the Big X will be best.  If it’s a solution they never heard of, you will need to evaluate multiple bids from multiple parties. )

Remember, where any group of vendors on the same page are concerned, All of us is as dumb as One of us!

Don’t fall for the Collectivism MindF6ck! that if multiple parties agree on something, that’s the right answer!  the doctor does NOT want to do say it again, but since a month still is not going by where he’s hearing about niche consultancies being thrown out for “being too cheap” or “obviously not understanding the problem” (which means the enterprise throwing them out is too uninformed and not recognizing that the Big X bids could just as likely the outliers because they aren’t inviting enough expert consultancies to the table), apparently he has to keep writing (and screaming) this truth. (the doctor isn’t saying that you can’t get a million dollars of value from some of these consultancies, just that you won’t by giving them a project they are not suited for;  again, see when should you use big X to identify when that million dollar project will generate a five million ROI — it’s people doing these projects at the end of the day, and where are those people?)

Remember, most of these firms got big in management, or accounting and tax, or marketing and sales consulting, not technology consulting. The only reason these big consultancies started offering these services is because of the amount of money flowing into technology, money which they want, but while the best of the best of the best in more traditional accounting, management, and marketing fields flocked to them, the best of the best in technology flocked to startups and c00l big tech firms  Now, some of these firms double downed, went and recruited those people, built small teams, learned, bought tech companies to expand the team, and now have great offerings in a number of areas.  But we have tens of thousands of tech companies for a reason, not everyone can build every type of technology, and not everyone can be an expert in every type of technology.  So while they will have expertise in some areas, they just can’t have expertise in all areas.  No one can.  Find the best provider for you.  Sometimes it will be Big X.  Sometimes Mid-Market.  Sometimes Niche.  It all depends on your problem at hand.)

And yes, sometimes the niche vendor will be wrong and woefully undersize the project or your needs.  But as per the above, if you don’t do give them a chance, and deep dive into their bid, how will you know?

 

Did you ever try eating a mitten? the doctor bets some of those clients did! (He feels you’re not all there if you think glorified reporting projects should still cost One Million Dollars by default and might actually try to eat your mittens! [Joking, but you get the point.]  Deep analytics projects that require the most advanced tech, especially AI tech, will cost a lot, but standard spend analysis, sales analysis, etc. where we have been iterating and improving on the technology for two decades should not.)