Category Archives: rants

What’s the Biggest Supply Chain Risk?

Us!

The biggest supply chain risks are not bankruptcy and plant failure, they are not unusual and damaging weather patterns, and they are not natural disasters. As clearly pointed out in the Supply Chain Risk Leadership Council (SCRLC) in their 2013 Emerging Risks in the Supply Chain study, the biggest risk is us — the human race — as a collective whole.

To see this, let’s review the fourteen (14) risks that were identified and discussed.

  • Climate Change
    A key contributor to climate change is the amount of carbon emissions we are producing. We keep burning oil, coal, and natural gas, and we keep doing so without any significant attempt to trap and sequester the carbon back in the ground it came from, allowing it to creep back into the atmosphere and increase the carbon dioxide percentage.
  • Global Supply Chains
    We keep outsourcing and offshoring even though, in May 2012, the total industrial capacity utilization in the U.S. was a mere 76.3%. To put that in perspective, one in every four plants is sitting idle at any one time.
  • Increasing Social Inequity
    Less than 1% of households control 40% of the world’s total financial wealth, with inequality ranging from their 34.5% share in the U.S. to their 70% share in China. And we don’t seem to be doing much about it, especially given the number of tax shelters available to the extremely wealthy in much of the developed world.
  • Gender Imbalance
    The one-child policy in China and the cultural history of favouring boys over girls in India has led to the situation where, in the next decade, there will be significantly more men of working, and marrying, age than women. People, trying to fix one problem, created this problem instead.
  • Population Increase
    Statistically speaking, we are expecting a population increase of almost 30% by 2050 where we expect the earth’s population to be 9 Billion people! We’re all contributing to this.
  • Population Migration
    It was only six years ago that the urban population exceeded the rural population. By 2050, we will have 70% of people living in urban areas. We are creating the mega-cities which, instead of being a sustainability boon, are, in many cases, an environmental nightmare.
  • Global Democratization
    What is likely to happen is that instead of replacing years of corruption, political repression, and economic disparity with stable democracies we are going to end up with the chaos and disorganization that could arise from new political systems being established by individuals with little governing experience.
  • Dependence on Information Technology
    We have come to rely on information technology to the point that when the software fails, we are immobilized. We allowed ourselves to become too reliant on technology.
  • Government Financial Crises
    Governments, run by politicians that we elect and allow to stay in office, around the world have taken on too much debt.
  • Government Social Policies
    In many countries, the majority view is that social policies are not properly funded, not equitably applied, and not equitable with those of whatever nation is currently being looked upon as the best role model for social governance. But we elected the government that created and maintains them.
  • Global Economic System Disruptions
    We created the rules that govern the financial systems that are starting to break down.
  • Social Media Threats
    Social engineering, anti-brand campaigns, and other socially-based attacks are all people-driven, not technology driven.
  • Global Mega Cities
    All over the world, we keep building mega cities and keep moving into them, creating extreme levels of congestion and infrastructure problems.
  • Aging Population
    Thanks in part to the baby boomers, we are getting older as a population. The number of people over 60 is growing at a rate that is 2.5 times the population growth rate.

In other words, directly or indirectly, people are the cause of the majority of supply chain risks, and that’s why supply chain visibility and third party management, focussing on the management of people, is so important.

(And while we’re all to blame, as hinted at in the study, the 1% deserve at least 34.5% of the blame! Their unequal tax treatment is a big reason we’re so deeply in debt and can’t adequately support social programs. Statistical models have demonstrated that their campaign contributions play a significant part in who gets elected and forms the governments that control our social, economic, and trade policies. They are collectively the biggest social inequality. And they could do the most towards moving us to sustainable energy models.)

Poor Working Conditions in the Supply Chain Start at Home!

Last month, we told you that new estimates put the driver shortage at 240,000 drivers and that it’s all our fault. Why? Despite the fact that 40,000 new commercial licenses are granted annually by the DOT (Department of Transportation), turnover is 100+ percent per year due to poor working conditions.

But it seems that poor working conditions aren’t limited to our drivers. It seems that our dock and warehouse workers are also getting the short end of the shaft when it comes to working conditions (to the point where the high salaries commanded by the dock workers, which can exceed $120,000 in the Port of LA for example, might not be worth it). As per this article in the National Business Review on why we should “stop hurting our container opening dock and warehouse workers”,

  • imported sea containers increasingly have toxic substances in them
    such as glues (from shoes), emitted gasses (from wood or MDF), and residue from fumigants,
  • unprotected workers who enter these containers can die
    and those who don’t typically get very sick and some develop long term health issues, including cancer, and
  • up to 30% of shipping containers contain dangerous levels of toxins
    with 18% of containers containing toxins at a level legally reportable as unsafe and almost 90% contain some toxic fumigant or volatile organic compound. WTF?

Kind of puts the salary demands in perspective when you consider that their jobs contain more potential dangers than a coal mine!

And if this isn’t bad enough, we also have the warehouse workers who, according to this recent infographic on Warehouse Safety and BLS data,

  • have a 14% of being injured on the job,
  • have a 3% chance of being seriously injured in a forklift accident on the job, and
  • have a 0.02% chance of being killed, most likely from a forklift accident!

Ouch! Our dock workers have it bad. Our drivers have it bad. And our warehouse workers have it bad. I think it’s time to stop focussing exclusively on the outsourced supply chain in a search for poor working conditions. There’s plenty of poor working conditions to fix here at home!

Keep Your Big Data. Big Brains Will Win in the End.

I have to admit that I’m sick of all this hype about big data and how it is the answer to all our problems. As I’ve said again and again, there’s no such thing as big data in business. Relative to our ability to process it, data has always been big. And, in business, big has always been meaningless. Furthermore, in business, we’ve always been able to process as much data as we need to in reasonable amounts of time if we made good technology decisions.

And I’m even sicker of the fact that some people think we can replace science with math and processes with computer programs. We never could, and for the foreseeable future, where AI (artificial intelligence) will not be a reality, we can’t. Thinking like this is what causes economists to latch onto, and promote, financial policies that, seem good in theory but, in practice, result in economic collapse when taken to extremes.

The reality is that science can never be replaced by math and automated prediction. Not only is the author of this HBR blog post on “why data will never replace thinking” right when he says that it’s only by trying to come up with our stories (hypothesis) beforehand, then testing them, that we can reliably learn the lessons of our experiences — and our data, but it’s only by coming up with hypothesis, and putting plans into actions that we can beat the competition and gain market share in the global market. Look at the giants of industry today. Did Apple become the dominant first in the e-Music industry by letting Microsoft, Sony, Samsung, etc. develop their music players and music stores first, analyzing customer responses, and then introducing their offering? Or did they become the dominant force by using their brains to try and figure out what the market, and customers, were missing, using the best creative and engineering talent to design a solution, and then releasing that product on the market? It was the latter solution — the solution that required big brains that won the market. Similarly, Walmart became the biggest retailer not by asking consumers want they wanted, but by predicting what the average consumer really wanted — a one-stop department store that met most of their basic needs at low prices with a consistent product and service offering across each store for the mobile consumer.

This isn’t to say that data isn’t important, it is, just that it won’t solve all your problems and that, beyond a certain point, more data doesn’t help. Remember, statistically speaking, you only need 384 data points to have 95% confidence with a confidence interval of 5 on a population of 1,000,000. If you want a confidence interval of 3, you only need 1,066 data points, and if you want a confidence interval of 1, you only need 9,513. Beyond a certain point, more data doesn’t add much confidence and the only way you’re going to get more insight is to see it inside your head.

So keep your big data. I’ll use my brain instead. How about you?

Procurement Key Issue 2013: CXO’s Still Don’t Get the Disconnect!

This week, the Hackett Group released their “2013 Procurement Key Issues” study. This study, which was likely the last hurrah from Pierre Mitchell as a Hackett Group Employee, found that some organizations are going deeper and broader to deliver borderless procurement services, which is good, but the one thing that blatantly stands out is that your average CFO, COO, and CEO still doesn’t understand the value of the Procurement Organization.

Before I explain, let me review a few of the key findings.

1. 82% of respondents state that increasing operational agility and flexibility is a key enterprise issue.

2. 65% of respondents state that pursuing game-changing innovation/technology is a procurement initiative planned for the next 12-24 months in support of enterprise strategy.

3. 76% of respondents state that expanding purchasing’s scope and influence is a major procurement-related issue in 2013.

4. 76% of respondents state that increasing innovation and product/service report is a major procurement-related issue in 2013.

5. 88% of respondents cite strategic sourcing as a major issue.

6. 81% of respondents cite category management as a major issue.

BUT

7. As a whole, respondents are projecting:

  • a 0.4% drop in the operating budget and
  • a 0.5% drop in the FTEs in the procurement function.

 

I think this calls for a WTF!

Strategy and category management require skilled resources with the right intelligence and toolsets. This requires adequate budget.

Innovation and agility require advanced skills, expertise, and market knowledge that requires a lot of supply market intelligence, outside information, and time to study mini- and mega-trends. This also requires adequate budget.

Scope of influence comes with results, and results require talented people with appropriate toolsets and knowledge. Again, this requires adequate budget.

Furthermore, we have the situation where budgets are not being cut equally. From what I’m gathering, for the fifth year in a row, Procurement Training budgets are being slashed or are non-existent! This is driving me nutz! This disconnect of separating expectations from budget is ridiculous, especially when the organization is supposed to be scored on value. Value is ROI. ROI is return on investment. In Procurement, this is defined as savings/avoidance/revenue increase over spend. This means that if spending $10K on training will give your category managers the capability they need to go negotiate another $100,000 of the TCO (Total Cost of Ownership) through unit price, logistics, and non-value added service savings, then you increase the budget by 10K because you are getting a 10X return!

If the goal is for the Procurement organization to deliver value, then they need the budget for the technology, supply market intelligence, and training they need to deliver that value. Otherwise, expecting them to do more with less (FTEs) is just stupid. Ludicrous in fact!

Why A True Supply Management Professional will Never be Replaced by Technology

As succinctly stated in this recent HBR headline, Algorithms Don’t Feel, People Do.

Also, algorithms don’t sense, read non-verbal cues, detect patterns in seemingly unrelated data, take risks, or form common bonds. They don’t feel, and they aren’t intelligent. And while their predictive capabilities are scary given enough data, they are not infallible, and when they do fail, they will fail in a big way. Let’s address these points one by one.

First of all, as noted by the author of the HBR article, algorithms don’t feel, and can’t predict how a person will respond to a message. Marshall McLuhan may have stated that the medium is the message, implying that the form of a medium embeds itself in the message and influences how a person will receive the message, but the reality is that, in today’s individualistic society, the message is what is interpreted by the recipient, and only someone with a shared understanding will be able to comprehend what that is and react accordingly. As a result, an algorithm can not negotiate.

Successful negotiation depends on a first party transmitting a message, agreeable to that first party, that the second party can accept, and, moreover, figuring out, of all of the possible messages that the second party might accept, which subset represent message that the second party are most likely to accept and which messages of the subset are the least distant from the desired message. An algorithm can compute which options are likely given certain assumptions, and which of these options are the least distance according to some metric, but cannot determine what assumptions to make. Only a person who can feel, and feel what the other party is feeling, can be the judge of what good assumptions are. And, secondly, algorithms cannot sense. They don’t feel, and they don’t have instinct — which requires real intelligence.

Thirdly, they can’t read non-verbal cues. Even if someone is stating that they may be agreeable to an offer, the reality is that they may have no intention of ever accepting the offer, and are only indicating the contrary to stall for more time. It’s often the case that such a person is not as good at masking their demeanor as they are at masking their words. It might be the case that their non-verbal cues give more away than they would like. Only a trained negotiator with years of experience and instinct can be the judge of this.

But even more importantly, they can’t detect patterns in unrelated data, as it’s typically the case they can only process specified data in specified ways. And a fixed data pool never tells the whole story. A fixed algorithm might not know that a fire today will impact resource availability in six months, that your main competitor is likely to go out of business do a massive loss in a patent infringement lawsuit, or that a new technology is going to make the current technology obsolete in 18 months, with prices and demand starting to plummet in six months. As a result, in each of these instances, the algorithm would buy (today) (at a much) higher (price) than it needs to.

Furthermore, algorithms don’t understand when to “trust your gut” and take a calculated risk such as betting the farm on a new technology or riding the spot-buy market when all signs point to locking in a price for three years. The reality is that real success often requires risk, and only a true pro will know when such a risk should be taken.

Finally, as algorithms are not intelligent, they don’t form common bonds with like-minded algorithms that would help them advance their company and their profession. Algorithms have their place, and properly used can take a great deal of tactical and low-value workload off of a Supply Management professional’s plate, but algorithms will never be smart enough to handle the strategic and high-value workloads without intelligent — human — supervision. Optimal is only optimal if all of the assumptions are valid and modelled. An expert will always be needed to define the assumptions, check the assumptions, verify the results, and tweak them according to an ever-changing Supply Management world.

In short, good technology can make you two, ten, and maybe even one hundred times more productive (depending on the metric), but it cannot replace you. So don’t be scared of new technology for your supply chain — embrace it. Given the ever-increasing demands being placed upon you, you will be glad that you did!