Category Archives: Decision Optimization

Will the Trade Wars Be Good for Advanced Sourcing?

Trump is imposing tariffs. China is retaliating. And this is just the beginning. As a result, supply risk and the need for spend forecasting is finally becoming real. But is it becoming real enough for organizations to take action? It’s hard to say. But one thing we do know is that the only way organizations can progress forward is to better understand not only the risks, but the costs.

What are the risks? Many. What are the costs? Significant. And how can you know of either? In the first case, you need to monitor the news, the sentiment of the responses in regards to the news, crowd-source some predictions, and run some advanced analytics on all this data to determine the probability of something happening — and sticking.

And in the second case, you build should cost models with current data, and projected data, to determine the impact of a tariff on the total cost of ownership of the product. This means that a simple RFX or Auction platform is just not enough – an organization needs a platform with deep should cost modelling and the ability to create what-if should-cost models based on projected and anticipated changes.

But even that’s not enough. If the projected increases are significant, then the organization will, at the very least, need to reallocate global supply chains to insure that products, which are currently sourced from multiple suppliers and/or locations, are being exported from and imported into the most cost effective locales the organization has access to. And if this is not enough to keep costs under control, then the organization may need to even source from additional suppliers (in different locations) or re-source the entire category (to the extent possible).

But it’s hard to figure all of this out without an optimization backed sourcing platform. Hopefully this is the kicker that is needed to get these powerful analytical platforms into the hands of more Sourcing and Procurement organizations, as these platforms are desperately needed and reduce spend on analyzed categories by an average of 10%+ year-over-year, making their ROI immense.

But, alas, only time will tell. But if bankruptcy could be on the line (when a tariff wipes out the entire profit margin), maybe this time these platforms will finally take hold.

How Many Billions Are Lost Each Year to Dumb Sourcing?

Today I saw an article entitled E-Sourcing is Dead, Long Live Intelligent Sourcing Systems and all I could say is what parallel world did this article materialize from? Given that we’ve had Strategic Sourcing Decision Optimization with multi-line item support, freight brackets, and carrier support for 17 years, advanced analytics algorithms with smart trend projection and outlier analysis for just as long, and easy access to pretty much all market and public sector buy data in e-friendly countries for over a decade, this should be the case. But it’s not.

We’re not even in a position to say half of mid-size or larger organizations even have anything resembling a modern e-Sourcing solution, and only a small fraction of those have embedded optimization capability, and only a small fraction of their customers actually use it. In reality, e-Sourcing is barely alive and just coming into it’s own. After all, the oompa-loompa empire is only valued at about Two point Five Billion … and in software terms, that’s pretty puny when you consider the market valuations of companies like SAP (approx 107B) and Oracle (approx 220B) … either of these companies could easily buy out the oompa-loompas and put them back in the chocolate factory on a whim! (Which would be a shame since they make great coders.)

But regular readers will know this to be the case, as it’s been SI’s core lament for a decade now — and the market still doesn’t look poised to change. Even though, as SI has stated over and over (and over) again, the average year-over-year savings from the proper application of optimization backed sourcing is 10% across the board. That means if you’re sourcing 105M, that’s 10.5M in savings that could be yours, as soon as you can attack all 100M of spend. If it takes an average of 3 years to get through all spend, that’s 3.5M a year for easy taking. But you’re probably sourcing closer to 1.05 Billion, which means you’re overspending by an average of 105 million, or 35 Million each year. That’s a lot of money, but obviously not enough to take notice.

So obviously we need bigger numbers. How much money is lost in the economy overall each year due to the lack of application of advanced, optimization backed, sourcing? While it’s pretty hard to get a firm grasp on OPEX in the US, and how much of that is addressable by optimization-backed sourcing (as payroll can’t be optimized, only outsourced services, and taxes are taxes), the US Census keeps good data on CAPEX, and in 2015, CAPEX was 1.65 Trillion! Ten Percent of that is 165 Billion. If, and this is an overly aggressive estimate, 10% of that was optimized, that still leaves 149 Billion on the table in the US alone. The US is about one forth of the global market, and assuming CAPEX / OPEX ratios are about equal, this says, globally, that’s about 600 Billion from CAPEX alone left on the table each year because companies aren’t optimizing spend. SIX HUNDRED BILLION. And that’s a lower, lower bound estimate. Is that number big enough for you???

There Are At Least 12 Risk Disconnects … but One You Should Never Overlook!

Over on Spend Matters Pro [membership required], the maverick is running a 12-part Pro series on The 12 Supply Risk Disconnects that Destroy Value that you really should check out. These disconnects not only increase Procurement and Supply Management risks across the board, but often end up destroy all the hard-earned value Procurement tried to extract from the sourcing event or push into the contract.

All of the risks are important, but the most critical in SI’s view is the disconnect between risk and cost. Why?

  1. Not only can one identifiable supply chain disruption not only wipe out all the savings, but increase cost beyond the current solution but
  2. Only an understanding of the true cost of risk will convince most stakeholders and executives to look beyond cost, reliability, marketing differentiation, or whatever else matters most to them. Money talks, and (potential) loss is the one thing that gets noticed.

As the maverick points out, supply risk basically overlays the dimensions of external VUCA (volatility, uncertainty, complexity and ambiguity) on top of the quality value stream and you have to minimize TCO in the face of varying levels of risk. This creates the challenge of how to place a price tag on that risk and another price tag on the cost of mitigating those risks, which is driven both by the outside-in risk you face and also your current level of risk management capabilities. Which is easier said than done, but without a solid understanding of the cost of risk, and an ability to model it against the cost of a buy, you can’t truly optimize your overall total cost of ownership, of a potential buy.

But you need to, and you need to acquire an optimization-backed sourcing solution to model the true cost of each option to make risk-aware Procurement decisions. Because then, as SI pointed out in an earlier post, you can not only Define [True] Procurement Success, but enable it.

How Should You Define Procurement Success?

This question is encased in a nut that’s quite tough to crack. We hinted at the importance of defining it three years ago in our post that asked how do you define Procurement success which noted that if you consider the art of the Strategic Sourcing Process, the Category Management Process, or the Contract Management Lifecycle, you [not only] see that they all start about the same at a high-level but that a key requirement of each step is an acceptable definition of success.

This means that if you want to be successful, you need a good definition of success but what should it be?

If you ask the CFO, she will say it should be cost savings! Reduce the outflow!

If you ask the Chief Engineer, it should be the best quality and reliability money can buy!

If you ask the Production Chief, it should be rock solid supply availability.

If you ask the CMO, it should have the most unique gee-whiz features on the market for the biggest marketing splash.

If you ask the VP of Sales, it should be the product that comes with the most value-adds so they can command the greatest price.

And so on.

On SI, we have repeatedly said the definition of procurement success should always be the outcome that brings the most value to the organization, but this can be hard to define when there are a number of competing viewpoints on what value is.

However, we can define Value as the outcome that balances the tradeoff between the goals of the respective stakeholders for maximum return against an agreed upon value scale that normalizes a dollar of savings (for the CFO) against a reliability metric (for the Chief Engineer) against an expected availability metric (for the Production Chief) against a feature differential against the market average (for the CMO) against a value-add differential (for the VP of Sales) [etc].

Now, you might be wondering how you do that? The answer is simple: define an expected dollar value. It’s not as hard to do as you think (as long as you have the [big] data and the model and the software to calculate it)!

The CFO metric is easy, a dollar of savings is a dollar of savings.

The reliability metric is not that much harder. A failure rate of 90% vs 93% during the warranty period has an incremental cost equal to 3% of the units times replacement cost (which is base product cost + processing cost if outside of supplier warranty or processing cost + return cost if inside supplier warranty) and this cost can be amortized per unit.

The supply availability metric is involved, but still easy to define. First you have to calculate an expected chance of disruption based on it. Once you do, the cost can be approximated as follows: (% chance of disruption * % length of disruption x cost per day of disruption) amortized by units. If there is 10% chance of disruption, then you expect one every 10 years, for the estimated length of time, at the estimated cost per day, and amortize that cost over each unit purchased each year. Not perfect, but a good approximation. To find the conversion from expected availability percentage to chance of disruption, you mine your data and extrapolate the multiplier. Easy peasy (with a modern cognitive or deep analytics platform).

The CMO metric is tricky. Just how much better is that gee-whiz feature? Probably not nearly as important as the CMO claims. To figure out an approximate dollar value per unit here, you will have to mine historical data to see the incremental marketing value from the company’s “most differentiated” or “feature rich” products compared to its “least differentiated” or “feature poor” products as compared to the estimated market share each product obtained. If “feature rich” products typically command an extra 10% of market share, each unit is valued at a premium of 10%.

The value-add is easy — mine the historical data to extract the dollar value of each “value-add” available to the company.

Then, to find the optimal trade-off during a sourcing event, build a multi-objective optimization model that maximizes the overall value generated from these goals.

In other words, what used to be downright impossible is now pretty straight forward with strategic sourcing decision optimization and cognitive sourcing.

Good Working Capital Management is More than Just Timing Payables and Receivables

A few years ago we ran a post on the essence of good working capital management. We noted that, at least from a basics point of view, all one really has to do is:

  • Get a grip on receivables.

    When are the customer payments for sales due? The reimbursements from suppliers for reaching volume tiers due? The tax rebates?

  • Get a clear picture on fixed payables.

    What is the average monthly payroll? Overhead? And projected supplier invoices?

  • Get a good estimate of average disruption costs.

    If a receivable isn’t received on time, what’s the impact? Especially if it could impact a supplier payment schedule which needs to be maintained to insure timely supply.

This is the foundation, but in today’s unstable and unpredictable business environment, that’s not enough to maximize working capital management. To maximize working capital management, one has to maximize the value of the capital. In order to maximize working capital, you need to know when to use capital for internal costs, for supplier payments, and for investments. This means one also has to:

  • Understand the value of early supplier payments.

    Not just the value of the early payment discount, but the overall value to the supplier. If they don’t have to borrow at a cost of capital two or three times the buying organization, and then pass that cost on to the buyer in their overhead, that’s a big potential savings to the organization — even if they have to borrow.

  • Understand the organization’s cost of borrowing.

    If the organization can borrow at a low interest rate of 3% or 4% a year in their home market, whereas a supplier can only borrow at a high interest rate of 12% to 20% in their market, the organization can save by borrowing. But you don’t borrow just to save on costs, you borrow to profit. If you can accelerate production and accelerate profitable sales, borrowing is sometimes a pittance. And if you have good investment opportunities, that could also be a good reason to borrow.

  • Understand the organization’s investment opportunities.

    How much from accelerating production? Improving the process? Investing in R&D? Investing in subsidiaries.

Then, when you have all of this information, you do one more step:

  • Build a Working Capital Optimization Model

    and run it. Input all the receivables, payables, disruption costs, early payment opportunities, borrowing opportunities, and investment opportunities and let an optimization-backed cognitive system help you put a plan in place to not only manage working capital, but profit from it.