How Do You Find Hidden Costs?

We all know that there is never a fixed arithmetic formula between the cost of producing, and transporting, the goods and services sold to us and the prices charged for them … sellers charge what they can get, and if we don’t do a good job of figuring out the true cost, which can be hard to do, chances are they are building in a hefty margin.

But the margin is only one hidden cost. There’s other hidden costs baked into the COGS by the supplier, some of which even they may not be aware of. But if you want to bring costs down, you have to find them. So where do you look?

Start by investigating each of the main production costs:

  • raw materials — what are your T1 suppliers paying to the T2 suppliers
  • energy — production always requires energy … but there isn’t always one rate
  • labour — if there is temp labour / contract labour involved, is it market rate
  • overhead costs — facilities, financing, etc. — these could be fixed, or they could not … for example, if the supplier has to borrow to fund operations until they get paid, what interest rate are they paying … and how does it compare to your rate? might be cheaper for you to pay them early in exchange for a discount that exceeds your cost of capital

That’s how you them. So what do you do next?

Come up with a plan to address any costs that look high:

  • if material costs are too high, can you buy on behalf of suppliers at a better rate? can you find alternative materials?
  • if the market is deregulated, can you help the supplier identify a better option? are energy requirements so large a supplier would do better off with its own plant? should you invest in it if there are multiple suppliers in the region paying absurdly high energy costs?
  • should you share labour negotiation and management best practices to help your supplier keep labour costs down
  • if suppliers have a high cost of capital, help them out … reduce their cost, reduce yours; maybe you can identify facility upgrades that would save them money

It’s not as easy as it sounds, but it’s not that hard either. Just takes data gathering and analysis.

Single Tier Risk Mitigation Strategies Don’t Mitigate Risk

… and, in fact, may increase it!

For example, let’s say that risk analysis identifies a disruption risk from southern china with the primary reason being unpredictable transportation due to labour and provider capacity uncertainty. Let’s also say that Procurement decides a good response to the risk is to just triple inventory and instead of working with a 3 week safety stock, works with a nine week. Problem solved, right? No! Problem exacerbated. Why?

Given that production is not likely to notice an issue and raise a flag until they get down to 1 or 2 weeks of stock, simply increasing stock levels is not going to speed up the time in which Procurement is notified of a potential issue. But even worse, if Procurement raises stock levels, chances are Procurement, or the supplier, will increase shipment sizes and send stock less often. This will increase the amount of time before Procurement could sense a problem because if shipment windows increase from 2 weeks to 6 weeks and a disruption happens one day after a shipment, it will be almost 6 weeks before Procurement identifies it, which could be too late for a recovery. Risk increased.

In fact, most mitigation strategies designed at a single tier actually have the potential to increase risk. Let’s take a few:

  • Dual Sourcing
    without careful planning, both suppliers could use the same Tier 2 source
  • Alternative Design
    that reduces / eliminates the need for one rare material in favour of another doesn’t reduce raw material risk of the other material is just as rare or the acquisition / production cost substantially higher
  • Financial Risk Monitoring
    for shakey suppliers doesn’t catch production shortcuts they might be taking to cut costs that increase risk that could result in catastrophic failures
  • Replacement Product Lines
    chances are the replacement product lines share parts and suppliers … you’ve actually increased risk from a disruption, not decreased it

To truly mitigate risk, you have to go multi-tier and work with your supplier to identify the most likely risks, and how to properly mitigate them.

For example, if the risk is:

  • factory shutdown
    you can work with the supplier to ensure a secondary geographically remote location has the ability to recreate the production line quickly
  • transportation shutdown
    have secondary shipment companies, and ports, lined up and ready to go if primaries go down … be ready to truck or rail longer or even airfreight in emergencies
  • financial stress
    the buyer may need to step in and float operations during new production line setup or new product design
  • raw material unavailability
    the options for alternate supply must be known in advance, as with the options for substitute material

But you’re not going to be able to figure out the right secondary location, transportation options, financial mitigation strategies, or raw material strategies on your own. Don’t try. Work with your strategic suppliers and get it right.

A Visual Metaphor …

Is the following a visual metaphor for:

  1. Supply Chain Bloggers at the latest M&A press conference,
  2. Spend Analysis Vendors at Data Mapping and Cleansing,
  3. Sourcing Consultants at Indirect Spend, or
  4. All of the Above?

You Decide!

Link

One Hundred and Thirty Five Years Ago Today …

The first standardized incandescent electric lighting system employing overhead wires, built by Thomas Edison, begins service in Roselle, New Jersey, just a year after Edison switched on the first steam-generating power station at the Holborn Viaduct in London, England.

In other words, while the vast majority of people alive today who were born in a first world country grew up with electric street lighting, it’s not that new. And when you consider the amount of time we’ve been on this planet from a scientific evidence point of view, it’s amazing how far technology has progressed since the delivery of the first stable feeds a little over 135 years ago …

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.