Monthly Archives: October 2023

Don’t Overlook the Network (that Corresponds to the Award)

According to a recent Forbes article on Supply Chain Software’s Best Return on Investment, per $1 Billion in company revenues, no supply chain application has a better return on investment (ROI) than network design! And the doctor couldn’t agree more.

Just like strategic sourcing decision optimization is the best bang for the buck in Source to Pay, with documented, average returns of up to 12% year-over-year (by multiple analyst firms) as it can minimize total landed cost, and even total cost of ownership in some cases (including internal inventory costs, waste costs, etc.) and not just bids, while ensuring all business constraints are adhered to, an optimization-backed network design application can help minimize overall organizational supply chain costs. This is because a supply chain network optimization platform can minimize transportation costs, intermediate warehousing costs, tariffs, waste, emergency replenishment in the case of an unexpected stock-out, carbon/GHG, etc.

Plus, as the article notes:

  • network design solutions are absolutely necessary to uncover business value when the production-distribution infrastructure is large (and not just because you just can’t model that infrastructure in a spreadsheet)
  • network design solutions can look at Total Cost to Serve (TCTS) across a wide-range of fixed and marginal costs (and identify unintended circumstances of network design changes that could cause marginal costs to skyrocket)
  • network solutions can allow for multiple scenarios to be defined and multiple models to be run and cross-model and cross-scenario Pareto analysis to be run, trade-offs to be analyzed, and the best decisions to be made

One point that should not be overlooked is that projects will take some time, and it’s not because of the complexity of the network modelling or the time it takes to run the scenarios (as modern computing architectures are super powerful and modern algorithms highly optimized to be efficient and take advantage of massively parallel processing), it’s because you need a lot of good, clean, data. It can take months (and months) just to identify, collect, clean, and enrich the data required for global supply network optimization. But once you do that, the ROI will be beyond the expectations you have for every other supply chain solution.

The article, which describes a project to redesign the spare parts supply chain for a global automotive manufacturer, resulted in a redesign that immediately reduced network costs by 4% and identified transportation cost reduction opportunities through consolidation and re-allocating of routes to a smaller set of 3PLs that will save another 2.5% at contract renewal time. In today’s climate, especially in direct supply chains, a savings of 6%+ across the entire supply chain, and not just one category, is phenomenal!

Plus, as the article notes, in the age of sustainability, reduced transportation mileage and fuller trucks also equate to significant reductions in carbon emissions. WHAT A BONUS!

Automation is Good Across the Board! But Automation still does NOT mean Automated.

Not that long ago, we penned Procurement Automation: Good. Automated Procurement: Bad because organizations that embrace the right digital technology do much better than their peers, but organizations that go all in and put too much trust in unproven technology without human oversight (while trying to run before they’ve learned how to walk) or good data (and then make worse decisions than having no technology at all, as recently determined by Gartner) are making a huge gamble while forgetting that it is the house who always wins. (And in this case the house is the technology provider that is charging you a lot of money for the technology that eventually fails and costs you time, money, and in the worst case, your job and/or business. But we digress.)

And while this blog is a Sourcing, Procurement, and related Supply Chain Technology blog, it was very happy to see a recent release from the Hackett Group, as advertised in a recent press release on yahoo! Finance / BusinessWire, that noted that while HR (and Humans are VERY important to successful Procurement Operations) operating costs increased significantly in 2023, Digital World Class organizations continued to spend significantly less than their peers while delivering more resiliency, employee productivity, and greater business value with less staff than their peers. The Hackett Group concluded that increased spend on technology plays a key part in driving the superior performance.

Other key metrics that Hackett pointed out is that companies with at least one business services function operating at Digital World Class levels see a five-year average performance premium over their industry medians -– an 80% improvement in net margin; 24% higher earnings before interest, taxes, depreciation and amortization; 89% greater return on equity; and 44% higher total shareholder return. (So imagine how good your organization would be doing if you were world class in Procurement and HR, and ensured that your organization always acquired, trained, retained, and promoted the best of the best.)

Hackett found that a key aspect of Digital World Class Organizations in HR, just like Procurement, was a greater use of technology (to the tune of 60% more likely to have and use the full capability of Human Capital Management applications).

There are a lot of great applications that a leading HR organization can employ that go beyond the specific applications mentioned of:

  • Human Capital Management
  • Time Sheet Management (for hourly employees / contractors)
  • Health (& Welfare) management

and, as Hackett points out, include the use of emerging technologies such as:

  • smart automation (not automated Gen AI applications)
  • advanced analytics
  • collaborative tools

For example, a good HR department will employ platforms that:

  • will use smart automation to onboard employees, ensure they get paid on a regular basis, ensure that their expense claims are properly routed and evaluated on a timely basis (and OCR use to reduce receipt processing), ensure that all information they enter on health/disability/etc. claims is auto-routed to the right third party systems (and not lost/transcribed wrong), etc.
  • will use advanced analytics to analyze its highest contractor/third party costs, determine what functions should maybe be brought (more) in-house, analyze it’s biggest employee benefit plan costs, optimize those costs (without reducing benefits), etc.
  • use collaborative tools for onboarding, training, and continued professional development, especially for remote learning and self-study

Just like a good Procurement department will employ platforms that

  • use smart automation to onboard suppliers, automatically distribute and collect RFPs, verify data that can be verified by a third party, do automated sanity checks, do initial analysis for presentation to a HUMAN, automatically generate POs from carts/contract schedules, automatically match, to the extent possible, invoices to POs, etc.
  • use advanced analytics to identify not only the greatest costs but the greatest opportunities available to the organization based on PPV (purchase price variance), market opportunities, consolidation, demand management, substitution, etc.
  • use collaborative tools to involve all stakeholders and make sure processes are automated to the extent possible

Because modern technology is far superior for tactical processing (thunking) than we are as humans. However, the leaders understand machines, while they can augment our intelligence with finely tuned applications, cannot think and leave the final decisions to the humans. Technology is applied appropriately for maximum success.

As Hackett says, the bottom line is that Digital World Class HR organizations are better at enabling their companies to succeed. They have streamlined the day-to-day transactional elements of their operations, and through systematic use of global business services and process automation have freed up an additional 12% of their teams’ efforts to focus on value-added activities. Now, they can more effectively focus on attracting, retaining, developing and engaging employees. The right digitalization helps people, and that’s why the right digitalization helps Procurement.

Need Some Procurement Principles? Balfour Beatty Published a Great Starting Point.

Google sometimes digs up the strangest things when you ask for Procurement News. One thing it recently dug up was the Balfour Beatty “Procurement Strategy” page, which wasn’t so much a strategy, but a set of principles that every organization should subscribe to. (Regardless of what industry they are in.)

So, if you’re wondering what principles you should adopt before you set your Procurement organization strategy, you can start with these seven principles:

  1. Become the customer of choice
  2. Ensure that we have the right, skilled people for the job, a strong talent pipeline and that we provide an environment where they excel
  3. Put in place processes that work, are compliant and transparent, making the best use of technology to deliver for our business and for our supply chain partners
  4. Mitigate and manage risk through early and closer integration with our supply chain partners
  5. Work together to identify market risks and forecasts
  6. Keep safety and wellbeing at the forefront of all that we do
  7. Prompt Payment for Suppliers

The great thing is they will lead to a great strategy as:

  • it covers talent, technology, and process transformation
  • it places importance on the supplier, the relationship, and the supplier sustainability
  • it covers CSR (corporate social responsibility)
  • it covers risk

In fact, the only principle that is missing is Sustainability, so if you add this eight principle

  1. Embrace sustainability in all that we do

We’re pretty sure that if you were to start here, you won’t go too far astray in the creation of your Procurement Strategy.

Will a Circular Economy Work with Leakage?

Sustainability is one of the big buzzwords, and the biggest verbal pushes, in today’s Procurement. (In practicality, most organizations won’t put their money where their mouth is and if the more sustainable solution is more than a point or two more cost-wise, environmentally damaging sweat-shop production, here we come!) We need to get there, because only an idiot would deny global warming (the last 13 years have seen 10 of the hottest year on record), and no one can deny the correlation between carbon emission, atmospheric carbon increase, and global warming. (You can argue just how much is due to carbon emission and how much due to other factors, many of which are indirectly caused by warming, but not that carbon is a problem.) Thus, even though we don’t know how much carbon reduction will help, we know it will, so we need to get there.

One big way to reduce carbon is to reduce production, which can done by reducing waste, which can be done through more refurbishment, repair, re-use, recycling, and reclamation — which are all part of the circular economy. Which is where we really need to get to (because waste is a problem — in addition to overflowing landfills that can pollute nearby water suppliers and make nearby land unfarmable, and even uninhabitable, think of the great pacific garbage patch and the containers of e-waste being sent to India, which has been a problem for well over a decade, see this 2010 article on the Times of India, and you start to get a grip on the magnitude of the problem).

But how efficient does the circular economy have to be to be effective? Theoretically, anything more that we do is one step better than what we are doing today, but, given that most products weren’t designed for recycle and reclamation, technologies for recycling and reclamation are immature and possibly carbon/generating themselves (especially if the answer is extract what we can, bury or burn the rest), and that there are breaks in the chain, is this leading to new waste that could possibly offset (or exceed) the expected (carbon) savings?

It’s a question Karolina Safarzynska, Lorenzo Di Domenico, and Marco Raberto recently tackled in an open-access paper on how the leakage effect may undermine the circular economy efforts available on nature.com. In the paper, the authors examine the impact of the circular economy on global resource extraction by way of an input-output analysis using an agent-based model of the capital sector. Through a detailed analysis they find that an appropriately structured circular economy economy can significantly reduce the extraction of iron, aluminum, and nonferrous metals if
implemented globally but the leakage effect may also cause some metal-intensive industries to relocate outside the EU, offsetting the circular economy efforts because an overlooked requirement for the circular economy is not just a reduction of waste, but a reduction of transport as transportation (air, rail, truck, and ship) contributes a significant amount of global carbon. In fact, if you go to Our World in Data, in the United States, the transportation sector accounts, like the energy (electricity and heat) sector, for approximately 30% of transportation emissions. The statistics right now are similar for the EU (24% for transportation and 28% for energy). So, if all of a sudden products need to be shipped halfway around the world to be recycled and reclaimed and the core materials shipped back, transportation-based emissions would increase significantly and possibly even overtake the extraction and raw material processing emissions!

In all fairness, we should note that the paper is pretty technical and metric heavy, and this is a bit of a simplification, but it’s the core idea we need to be aware of. It’s not an improvement if the carbon you take out of one segment is exceeded by changes in another. Just like we need to home/near-source for anything we can grow/mine/make at/near home, we also need to home/near reduce/reuse/refurbish/remanufacture/recycle whatever we can. It might be that the rare earths can only be mined in certain areas, but that doesn’t mean they have to be reclaimed and re-used there.

Gartner Inadvertently Makes the Case for NO AI in Supply Chains (which includes Source to Pay)

Gartner, which promotes the use of Generative AI in customer service, even though it did place Generative AI on the Peak of Inflated Expectations on the Hype Cycle for Emerging Technologies, just inadvertently made the best case for never, ever, ever using AI anywhere in the supply chain, including Source-to-Pay, and we love it!

In a press release on their newsroom in late September, where Gartner Says 80% of Supply Chain Not Accounted for in Current Digital Decision Models, the subheading clearly stated that Digital-to-Reality Gap Shows Current Technology Use Fails to Improve Outcomes for Supply Chain Decision Makers.

As a result of this “digital-to-reality” gap, Gartner’s research, based on an analysis of 600 survey responses of supply chain decision makers, not only found that current use of digital models to analyze trade-offs made no meaningful impact on the rate of good decision outcomes but actually found that slightly more bad decisions were made with the use of digital tradeoff analysis than without and marginally increased the percentage of bad decision outcomes. Moreover, More than half of supply chain leaders reliant on digital technology to make a recent strategic decision told us that they felt they would have landed on better decision outcomes without the use of their models, and our analysis suggests that they are correct.

In other words, if source-to-pay and supply-chain decision makers cannot even make decisions when relying on traditional, focussed, machine learning and modelling technology, there’s no chance an unpredictable probabilistic incarnation of Artificial Idiocy that randomly changes its output by the millisecond is going to make good decisions. And the reason is the same — just like traditional (guided) (machine learning) models require good data and a digital representation that covers the majority (if not the entirety) of the process and relevant variables, so do Generative AI models and, in just about every organization on the planet, this necessary digital representation DOES NOT EXIST!

As a result, applying AI without the data it needs to have even a snowball’s chance in h3ll to make a decision is pretty much guaranteed to lead you to worse decisions than you, or any other intelligent human with a decent understanding of the situation, will make without the use of any technology whatsoever.

You don’t need AI, you need end to end process modelling, data collection, data enrichment, data validation, and the ability to use those end-to-end digital tools, interpret the data and recommendations, and make good decisions off of that. And since, with the current rate of digitization, it’s unlikely the majority of organizations will go from 20% supply chain digitization to 80% supply chain digitization (which is the minimum level of digitization you should have before even considering any AI, even for inconsequential decisions) by the end of the next decade, you should not even have AI for decision making on your future roadmap before the next decade rolls around.

the doctor doesn’t say this often, but thank you, Gartner. (Because it really is the case that stupid is as stupid does.)