Category Archives: Finance

Modern Strategies for Supply Chain Finance

The strategies for success haven’t changed much in the past few decades, but for some reason still aren’t in widespread practice. So we’re going to review the best practices from two decades ago and then indicate what else you should be doing.

1. Open Account and Letter of Credit Balancing

It’s critically important to understand your organization’s cost of capital versus your supplier’s cost of capital. Open account terms, for example, may bear lower fees than a letter-of-credit based transaction, but they can also restrict a seller’s access to working capital financing and increase its costs of working capital. The additional cost borne by the supplier for accepting extended payment terms, for example, could be finding their way back into your cost of goods sold.

2. Better Forecast Accuracy

One of the best ways to take cost out of the supply chain is to take unnecessary inventory out of the chain, as this just leads to additional storage, overhead, and financing costs and losses when it has to be cleared at considerable markdowns.

3. Supplier Cost Reduction

Depending on where your primary supply base is located, (up to) half of your suppliers might be struggling to access financing at acceptable terms. It might be their top issue, even above reliability of component and raw material supply! Their cost reduction is your cost reduction and your best chance at good supply chain finance strategies!

Building on these foundations, today you need to be considering:

4. Deep Tier Financing

Making sure your suppliers’ critical suppliers have access to fair and affordable financing so they can manufacture and sell their products affordably to your suppliers’ and not inflate your supplier’s cost which would inflate your cost.

5. Sub-Tier GPO

If you are relying extensively on a few key raw materials or components across your product lines, and if those are in short supply, costly, or volatile, buy the raw materials on behalf of your sub-tier supply base and sell it back at cost.

6. 0 Days DPO

Pay cash-strapped suppliers who would have to borrow at loan shark rates of interest immediately. It’s that simple. You’re paying for their overhead, so if your cost of finance is 1/5 or 1/10 of their’s, then, even if you risk borrowing occasionally, it just makes good financial sense.

7. Inventory Financing

Either enable your supplier to get financing based on their inventory materials and components and the goods they are going to produce, or create your own inventory financing solution for them.

The reality is that the standard techniques of JIT (and forcing suppliers to sit on inventory), increasing DPOs to the maximum legally allowed, and pretending EPD is a substitute for financing is NOT financing, only hurst the supplier, and only hurts you.

There’s No Cost Savings If It Doesn’t Hit the P&L

Anytime costs go up — due to oil spikes, tariffs, raw material shortages, generic inflation, etc. — which is, sadly, the majority of the time — the first word out of every solution and software provider’s mouth is how their solution will generate savings … which, sadly, almost never materialize.

Yes, they show up on the sourcing award, on the new spot-buy Procurement, in the (temporary) workforce reduction from automation, etc. — but that’s not what hits the balance sheet, and definitely not what hits the profit & loss statement. What hits the balance sheet is how much actually gets paid out to obtain the products or services (not just the unit costs, but the delivery costs, including expediting when forecasts or planning is off), what gets paid for all spot-buys (including those that don’t go through RFQ but instead the first punch out with product the user wanted), and how much loss occurs when the automation doesn’t catch errors and when exceptions require hiring a FT resource at an outsourced Procurement operation to deal with them (at 3X the cost of the internal resource you let go).

The reality is that all of the “savings” the majority of software and solution providers deliver results in cost transfers to other line items in the organization, the totals on the balance sheet don’t change, and nothing hits the P&L.

Even worse, when the “savings” strategy is too aggressive, it usually results in the introduction of additional risk into the supply chain and, eventually, something breaks where the required mitigation ends up costing way more than the “savings” that was identified, which not only results in no savings hitting the balance sheet, but a significant additional expense which results in a loss on the P&L, resulting in the CFO correctly claiming that Procurement didn’t save a dime (and, in fact, somehow drove up costs), which results in the CEO claiming it’s time to bring in a new Gen-AI-based solution to cut costs and a useless Big X consulting firm to tell you how. (And we all know how that’s going to turn out!)

So if you want to ensure you stay in control of all relevant organizational spend, you need to produce results that hit the P&L. That means you need to reduce overall outlays on the balance sheet, which means you need to stop looking at short-term savings that cost more than they deliver and start looking at long-term expense reduction efforts.

The best way to do that is to prevent unnecessary expenses, not to try and shave additional margin off of categories that you have strategically sourced multiple times and are already below market and within 1% or 2% of optimal. Look for allocations that mitigate risk and the associated disruption costs. Find ways to improve forecast accuracy and balance stock to prevent stock-outs, minimize the need for expediting, and prevent overstock that will have to be liquidated later. Ignore the new hype experimental tech and instead focus on tried-and-true last generation tech that will be low cost, highly accurate, and capable of addressing the majority of your needs when you adequately define your process workflows, break them up into tasks, and identify appropriate automation tech for each task. (And if you do need AI, classic AI works best, especially when you pick classic AI designed for a specific task.)

Instead of trying to replace people with overpriced tech, focus on trying to find augmented intelligence solutions that will make your employees up to ten times as productive while allowing them to appropriately source and procure every single category. Instead of outsourcing critical or difficult categories to third parties, get your people training and, if necessary, work-along-side category experts to help them improve. Instead of using outdated methodologies to classify your categories and strategies, like the Kraljic Matrix, step up to something modern like the Busch-Lamoureux Exact Purchasing methodology which will help you understand what you truly need to be effective in each category.

In other words, don’t focus on the savings — focus on getting the spend right and overall spend will decrease, generating more savings than any single effort ever would.

There’s No Cost Management UNLESS It’s By Organizational Design

Cost Management is what thought leaders and analysts have been talking about for 25+ years in Procurement (and is something that has been discussed on SI since its founding in 2006), but not something that is typically realized.

It’s more than just strategic sourcing, contract [lifecycle] management to capture the agreements and obligations, e-procurement, and 3-way matching for cost assurance (and obtainment), but rarely does an organization even achieve these (and that’s why up to 30 to 40 cents of every negotiated savings dollar never materializes).

It’s even more than including Procurement in NPD and NPI (which is where 80% to 90% of the cost is baked in), or in supply chain / logistics network (re) design, which still isn’t the case in the majority of organizations.

It’s a fundamental organizational realignment from traditional budgeting, pricing, forecasting and spend planning based on historical spend and revenue to dynamic budgeting, pricing, forecasting and spend management based on real-time market data as categories come up for sourcing or renewal, internal organizational spend increases or decreases (on hires or fires; internal development projects; assets are acquired, fully paid off, or divested) where budgets are defined based on real-time market data and updated forecasts when a sourcing event is kicked-off, pricing is adjusted based on actual costs and expected market tolerance to standard margins/mark-ups, forecasts are re-run using advanced curve fitting models with the most recent data, and spend planning is adjusted based on all of the prior updates.

The “when a sourcing event is kicked-off” is the key — not when it’s planned, when it needs to happen because the company has decided to introduce a new product, accelerate a planned event due to an expected demand or cost increase, or a supply chain disruption has necessitated emergency replacement of supply.

The harsh reality is that if a chip or RAM factory was just wiped out by a natural disaster or fire (which happens about once a decade), prices are going up. Doesn’t matter what you spent last year, this year is a whole new type of ball game — especially if supply routes become cut off and your only options are longer sea routes, air routes, or new (already overloaded) suppliers in new regions that aren’t cut off.

And any savings or cost avoidance success needs to be measured against the average market price at the time.

But, as pointed out by this article in Supply Chain Digest on how to get From Supply Chain Cost Cutting to Cost Management, this is not what happens every time a market shock hits, executive pressure rises, and the organization is told to take costs out fast.

As the article continues, the danger is not the mandate itself. It is what repeated, reactive cost-cutting does to the supply chain’s long-term health. It can lead to diminishing returns on cost cuts, weaken operational effectiveness, and narrow options the next time volatility strikes.

And it’s all due to a hidden problem with the traditional approach. Namely static budgets create the wrong conversation. Because, when supply chain performance is judged primarily against an absolute dollar budget, leaders often get pulled into debates about compliance instead of outcomes and, even worse absolute-dollar metrics can also steer attention toward the biggest cost line items, even when those costs enable profitable growth.

According to the author, the solution is to ditch static dollar budgets, assess performance through an adaptive lens that aligns with margin assessment, and report costs as a percentage of revenue. Which is great advice, but doesn’t really help you transition the organization to being cost management (vs the current method of cost mandating that is completely divorced from reality and regularly results in organizational failure) focussed.

That’s where the Busch-Lamoureux Exact Purchasing model comes into play. When you align around exact purchasing, and segment your spend into the pocket cube, you realize that for all of your high complexity, high risk, and/or high impact categories, you need to either architect the cost model and the supply chain around it, monitor market conditions in real time (and possibly trigger [re]-sourcing events as a result), or continuously monitor input pricing as well as the price points an average consumer will pay across your markets at different volume levels and adjust your cost and revenue model accordingly.

You no longer plan around fixed costs and prices for the next year, that never happens, but around evolving market realities. And if your price point adjustments are limited, then you know you need to scale back on service commitments, marketing during a downward market trend (when consumers don’t have time to buy), or overpriced sales personnel just adding to expenses with no identifiable return. i.e. Spend is reallocated as appropriate to keep the organizational profitable and productive during extreme events or market conditions while other companies can’t adapt due to lack of category management structure and organizational alignment around what is actually being bought as they still operate off of a spreadsheet that represents a fictional model of non-reality.

Primary ProcureTech Concern: Tightening Credit Conditions

The world runs on money, regardless of what form it comes in. Gold, cash, or credit. Credit is particularly important because it helps an organization bridge between cash cycles.

Why?

If economic downturns or inflationary pressures arise quickly, then credit will also tighten.

Impact Potential

If the organization, or its suppliers, needs credit to produce and distribute the goods for sale, the lack of interim credit could lead to reduced inventories and sales and even bankruptcies.

Major Challenges/Risks

Economic Market Prediction:
Predicting whether the economy is going to grow, stay flat, or recess (or depress) is the first challenge, as that’s a leading indicator of credit markets.

Credit Market Prediction:
Based on the projected economic changes, predicting the base and prime rate changes, availability of credit, and the future cost to your organization and your primary suppliers.

Alternative Credit Sources:
If your primary sources are projected to become considerably more expensive or restrict credit access, can you identify alternate sources? Moreover, how much will those cost, how long to establish the relationships, and how reliable will they be?

Alternative Credit Arrangements:
If right now you are just using loans or lines of credit, maybe you need to consider early payment discounts, invoice factoring, or alternative supply chain based credit arrangements.

Final Words

Credit conditions depend heavily on economic conditions, so this is yet another reason you need a good economist.

Who’s Funding Your ProcureTech Vendor?

This question is more important now than ever! Not only is the RCD (Relative Corporate Debt) of many FinTech companies too high right now (See: Calculating RCD), signalling a decline in customer service and potential abandonment, if not outright vendor failure down the road, but the ongoing viability of many VC and PE firms, or at least their ability to support their investments, is also in question.

Many firms are too heavy on AI plays that are still losing as much as $4 (or more) for every $1 of revenue they take in, requiring massive ongoing investments to maintain. Even big PE funds only have so much cash to burn, and the only way they can do this is to liquidate assets and holdings if they can, or, in the worst case, simply write off losses (and associated future costs) of those holdings they can’t liquidate.

Softbank’s end-of-year investment in OpenAI really puts this into perspective, as chronicled by Mr. Klein of Curiouser.AI and Berkley in this LinkedIn post.

As far as I am concerned, this is bad news for any of SoftBank’s FinTech holdings that may require funding in the next few years, and a warning to make sure you don’t select / continue / depend on any of their FinTech holdings where they have a large or majority stake until verifying those holdings are profitable and likely to stay that way! (Now, SoftBank has traditionally had very good investment chops, so it’s likely the majority of holdings are profitable …)

However, they aren’t the only firm making huge over-investments in AI and weighting the portfolio down with companies that might never see a profit. This means that this warning also applies to many other Tech investment funds, starting with Thrive, Dragoneer, Altimeter, and Coatue who also have large stakes in OpenAI. They could all end up in the position where they are going to have to sell off / dump assets to maintain the ridiculous losses OpenAI is seeing, and any holdings not performing well will likely be the first to go / get dropped. (Remember that the average age of the first three of these groups is 15 years, and they are [becoming] modern SaaS/AI heavy, whereas Softbank Capital has been investing for 30 years, and is a lot more diversified. Softbank may be able to weather a complete crash in OpenAI valuation if it occurs. But these other firms may not!)

But, as we noted, the real warning is not for SoftBank or these other mega funds (in the significant 8 and 9 digit range) that have funds to weather a storm. It is for the smaller funds, especially those less than 1 Billion, that are too AI heavy.

As a result, when selecting any FinTech platform, you need look at the portfolio of any investment player with a substantial majority stake. If a large segment of the portfolio of a significant/majority investor is “AI” companies losing money hand over fist, then the vendor of that FinTech platform cannot be considered a stable vendor if it is not profitable. This is because you can’t count on the fund having the resources to support the vendor to profitability, even if vendor is a fund darling. This is the case even if the RCD calculation looks good! A lot of the smaller funds can’t afford an AI crash given the AI-heavy focus of their SaaS portfolio.

(Face it. An AI crash is coming. Too much valuation against too little return, and investors only have so much patience. The only thing we don’t know is how severe the crash is going to end up being. Is it going to be a minor drop across the tech markets or a major crash like the 2008 housing crash or the 1999/2000 dot com crash?)