Category Archives: Knowledge Management

If Instead of Trying to Replace, You Redeployed People — What Could You Accomplish?

The big push for AI is not to help you, but to achieve every executive’s dream of a perfect utopia where they have 24/7/365 robotic workers they don’t have to pay, feed, or even provide safe working conditions for. Where they have endless slave labour, workers with no rights, and only have to worry about counting the virtual dollars in their endlessly increasing bank accounts.

But anyone with a working brain, who doesn’t live in a fantasy world, who hasn’t given into the cognitive surrender brought on by excessive use of Gen-AI, knows that reality is far, far, away. The algorithms are dumber than doorknobs, hallucinate to various degrees on almost every response, and are only good at sounding right, NOT being right. Intelligent humans are still needed, more than ever (as AI has NOT changed the fundamentals of Procurement. It HAS Only Strengthened Them.)

While there is very little Gen-AI can do, there is a lot traditional AI, and even more that (A)RPA (the real agentic technology) can do if properly defined, constrained, and deployed — and in many back office functions, a lot of the data analysis and processing (still) done by humans can be done by machines (and could be done by machines for at least a decade — if not two). In Procurement, we’ve had invoice technology that could automate invoice processing error free 95% to 98% of the time for over a decade, auto-reorder technology based on stock levels, forecast changes, or production schedules for over two decades, technology for automatic contract creation based on clause templates and clause libraries for almost as long, and sourcing automation since the first major sourcing platforms hit the market.

If this was properly done, and 80% of the tactical bit-pushing time that, with fire-fighting, constitutes about 90% of a Procurement professional’s time, was eliminated — imagine what could happen. All high impact and high risk categories could be strategically sourced. All complex categories could be examined in detail, BoMs and production technologies optimized, and supplier relationships (and thus supply assurance) strengthened. And that’s just the start.

Procurement would have time to examine, shape, and even divert (and eliminate) demand. From the classic example of negating the need for more printers, paper, and printer ink by just ensuring every employee had a second monitor at their desk and a tablet for mobile document receipt and review to a more modern example of elimination of expensive cell phones for non-sales on-demand employees by Whatsapp (and cheap subscription) mandates or elimination of expensive office leases in areas where most employees are/work remote most of the time and only a few hot-swap desks at a work-sharing centers (and the ability to book / rent meeting rooms for occasional meetings) is acceptable (as they all use laptops anyway), demand shaping can result in major organizational cost savings.

Moreover, Procurement could even go beyond demand shaping and reduction to true value identification by helping the departments they serve define, and redefine, what value actually is and how best to achieve that value when going to market.

A great example of this is how IKEA approached its use of AI in customer service. As per this great summary on LinkedIn by Alberto, when IKEA’s AI bot deflected 47% of calls, instead of calling it a win, firing half it’s staff, and moving on, IKEA did two things.

They asked what the AI bot wasn’t helping with and what concerns still had to be handled by the customer support team.
They retrained and redeployed over half of their customer support team to handle the most common inquiry, and built a ONE BILLION DOLLAR business around it. (So Far! It’s IKEA. And they’re just getting started.)

To clarify, many (potential) customers weren’t calling just about missing parts or issues understanding the assembly instructions. They were calling to ask what they should buy to meet their needs. “What works in a small living room.”

They needed basic interior design advice. So IKEA trained a significant portion of their customer service workforce as interior designers, and generated over €1 billion in additional business in the first year simply by spending the time to figure out what customers needed before they could make a purchase decision (interior design advice and the identification of products IKEA offered that would meet the design criteria) and giving them exactly what they needed.

Imagine how much value Procurement could add to the business if, instead of reducing staff with automation, the C-Suite retrained (or, if the existing staff doesn’t have the education/experience, replaced that staff with an equal amount of more senior personnel) and redeployed this suddenly freed up staff to act as an internal value identification consultancy that brings Procurement (cost management, risk mitigation, and supply assurance) best practice to the rest of the business.

Think about that before you try to replace real intelligent talent with unintelligent talentless AI (and find yourself in the bog of eternal stench that results from your lack of foresight).

Today’s Procurement Leaders Aren’t Enough for Tomorrow

Mr. Matthew Buckingham recently posted on LinkedIn that the strongest Procurement leaders today share three traits:

(commercial) curiosity — and an understanding of where value is
(constructive) courage — and the willingness to challenge the business
(crystal) clarity — and the ability to simplify complexity

These are all great, and necessary, skills, but not enough to survive tomorrow where supply chains break daily, technology is in flux, and your processes can’t adapt (fast enough).

In order to survive the simultaneous supply chain (due to unpredictable, and constantly escalating, geopolitical situations) and technology (due to the Agentic AI [Hype] wave) turmoil that is coming, tomorrow’s procurement leader is also going to need:

(colossal) creativity — to build a flexible supply chain that can change on a moment’s notice
(constant) crusader — to convince the C-Suite that traditional Procurement is dead

The organization is going to have to

dual/tri-source everything from at least two/three locales,
have contracts with primary and secondary couriers in each locale,
be aware of alternate ports / commercial air cargo carriers out of alternate airports for shipping (and have them on speed dial in case of need),
have potential back up suppliers (who came in second) in case of supplier failure,
near (real)-time monitoring in place not just for communications, missed communications, missed milestone dates, and other indicate KPIs but events that are likely to impact a supplier’s performance and/or availability,
pre-defined response plans for region, supplier, carrier, [air]port, etc. availability, and
the ability to reallocate and change plans literally overnight …
while treating long-term contracts (or at least long-term expectations of fulfillment) as a thing of the past … there is no guaranteed supply, or even price protection, if the supplier becomes unavailable or goes bankrupt

Proactively building a supply chain and supporting technology infrastructure capable of being reactive in real time is going to take a lot more creativity and crusading than what was ever needed before in Procurement.

Curiosity, Clarity, and Courage is just the baseline.

Find a leader who’s ready!

Forget Best in Class, Hype, or Futurism — If You Want To Improve, Mature!

As you know, and as we’ve written about repeatedly, the hype cycles for orchestration and Gen-AI are in full swing (even though both should be declining, they are both picking up steam, likely due to the ridiculous amount of money spent on marketing — which includes vendors buying analyst studies and reports that focus on areas where they look good).

Consultancies are not only trying to promote and sell you these technologies as a panacea for all your technology ills, but also trying to tell you that it’s what the best-in-class do and, by the way, that if you want to be best-in-class, you have to upgrade all of your processes (with their help) to those that the best-in-class use (whatever that means).

Furthermore, both are trying to tell you what the Future of Procurement is in 2030, 2035, 2040, etc.

And the reality is that NONE of this helps you. Not one bit.

As we have repeatedly pointed out, most of the currently hyped technology is still in experimental/beta stages. This is not technology that will help you mature. In fact, if you are not an industry leader, and mature in your processes, it may actually hold you back because you need to be a mature industry leader with your Procurement organization running smoothly to have the time and experience to properly evaluate these technologies and where they might fit in your organization.

Furthermore, every organization is different. As a result, what is a best practice for one organization may not be a best process for another. In fact, it might not even be relevant. While you will need to improve your processes, and streamline them for digitization, there is no set of fixed processes you can just plug and play and succeed.

And, don’t pardon my French, why the fuck would you care about what Procurement will be like in 5, 10, 15, 25 years. That does NOT solve your problem today. You care about what a better organization would like today and how to get there. That’s it. Just like the journey of a thousand miles begins with a single step (and possibly a single kick in the ass), the path to success is continual improvement, and, simply put, doing better tomorrow than you are doing today.

This means that the key to success is good old maturity levels, current state assessments, and simple step-by-step plans to get from one level to another. Nothing fancy. Nothing tech-centric. And definitely nothing hyped!

While the doctor admits he did get a little tired of the plethora of these maturity maps that appeared in rapid succession in the late 2000s and early 2010s, including the one he did, it was much preferable to today where the dearth of these, and simple advice, is deafening. The help that is desperately needed is not there — replaced by (Gen-AI generated) (Gen-)AI and orchestration hype, not how they can (and cannot) support the solutions you need.

[Plus, let’s not forget that analyst firms and consultancies tend to ignore government regulations and industry compliance (except in country-specific studies), day-to-day pain points (because they aren’t sexy and won’t sell the hype), and, unless they can make a quick-buck (or get a major uptick in eyeballs), changing global conditions that require (temporary) supply chain pivots.]

So, if you truly want to improve, find a maturity model that walks you through the process and knowledge improvements you need to

get to where you should have been when you started Procurement
get to where you should be today
prepare for the next 3 to 5 years (since no one looks beyond that anymore)
slowly build out a foundation that will take you beyond that (without another massive investment)

That’s it. That’s how you make progress. And how you do it without flushing Millions of Dollars down the (Big X) consulting toilet.

Need a starting point? You can still download the classic paper the doctor wrote back in 2012, that was sponsored by BravoSolution (acquired by Jaggaer), on Taking the First Step on Your Next Level Supply Management Journey which describes the levels of maturity from standardization and complexity reduction (which is typically the first step an organization takes on its journey), to operational excellence (which is typically the second step an organization takes on its journey), to strategic business enablement (which is when it typically becomes best in class).

If you do a web search, you will find others from the big consultancies, but this gives you an idea of what to look for in a model that you can build a progress plan on. Where do you start, where will go next, and where do you want to end up. Note that a good model is tech free. Tech should support your growth, not the other way around. (In other words, it’s never Tech-First or AI-First, it’s solution first, and then you identify the right tech.)

And if you need help with a current state assessment, or flushing out a roadmap from one level to the next, or where you are now to standardization and complexity reduction, hire a niche consultancy who will take a no-nonsense approach to get you there at a reasonable cost. (This shouldn’t cost millions of dollars in a transformation project. Depending on your organizational size and complexity, somewhere in the low six figures should typically be enough to get your started, or mid to high five figures if you want to just focus on a few core areas at a time. But definitely NOT seven figures. That comes during the transformation process once you have identified the tech you need, and NOT the tech everyone is trying to shove down the proverbial throat.)

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.

Enterprises have a Data Problem. And they will until they accept they need to do E-MDM, and it will cost them!

This originally published on April (29) 2024. It is being reposted because MDM is becoming more essential by the day, especially since AI doesn’t work without good, clean, data.

insideBIGDATA recently published an article on The Impact of Data Analytics Integration Mismatch on Business Technology Advancements which did a rather good job on highlighting all of the problems with bad integrations (which happen every day [and just result in you contributing to the half a TRILLION dollars that will be wasted on SaaS Spend this year and the one TRILLION that will be wasted on IT Services]), and an okay job of advising you how to prevent them. But the problem is much larger than the article lets on, and we need to discuss that.

But first, let’s summarize the major impacts outlined in the article (which you should click to and read before continuing on in this article):

Higher Operational Expenses
Poor Business Outcomes
Delayed Decision Making
Competitive Disadvantages
Missed Business Opportunities

And then add the following critical impacts (which is not a complete list by any stretch of the imagination) when your supplier, product, and supply chain data isn’t up to snuff:

Fines for failing to comply with filings and appropriate trade restrictions
Product seizures when products violate certain regulations (like ROHS, WEEE, etc.)
Lost Funds and Liabilities when incomplete/compromised data results in payments to the wrong/fraudulent entities
Massive disruption risks when you don’t get notifications of major supply chain incidents when the right locations and suppliers are not being monitored (multiple tiers down in your supply chain)
Massive lawsuits when data isn’t properly encrypted and secured and personal data gets compromised in a cyberattack

You need good data. You need secure data. You need actionable data. And you won’t have any of that without the right integration.

The article says to ensure good integration you should:

mitigate low-quality data before integration (since cleansing and enrichment might not even be possible)
adopt uniformity and standardized data formats and structures across systems
phase out outdated technology

which is all fine and dandy, but misses the core of the problem:

Data is bad (often very, very bad), because the organizations don’t have an enterprise data management strategy. That’s the first step. Furthermore this E-MDM strategy needs to define:

the master schema with all of the core data objects (records) that need to be shared organizational wide
the common data format (for ids, names, keys, etc.) (that every system will need to map to)
the master data encoding standard

With a properly defined schema, there is less of a need to adopt uniformity across data formats and structures across the enterprise systems (which will not always be possible if an organization needs to maintain outdated technology either because a former manager entered into a 10 year agreement just to be rid of the problem or it would be too expensive to migrate to another system at the present time) or to phase out outdated technology (which, if it’s the ERP or AP, will likely not be possible) since the organization just needs to ensure that all data exchanges are in the common data format and use the master data encoding standard.

Moreover, once you have the E-MDM strategy, it’s easy to flush out the HR-MDM, Supplier/SupplyChain-MDM, and Finance-MDM strategies and get them right.

As THE PROPHET has said, data will be your best friend in procurement and supply chain in 2024 if you give it a chance.

Or, you can cover your eyes and ears and sing the same old tune that you’ve been singing since your organization acquired its first computer and built it’s first “database”:

Well …
I have a little data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

Oh, data, data, data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

It has nonstandard fields
The records short and lank
When I try to read it
The blocks all come back blank

I have a little data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

My data is so ancient
Drive sectors start to rot
I try to read my data
The effort comes to naught