Category Archives: Risk Management

Are You Doing Your Own Quality Spot Checks? And Should You Be?

By now, if you haven’t heard of the Kobe Steel Scandal, you’ve been living in a cave. (Which, in some organizations, is highly probably given that one of the tricks the CFO likes to do to Procurement when fiscal year end is approaching is to lock them in the basement until the mandatory savings objective is reached … hence our post yesterday on why every day is Halloween for some Procurement departments.).

This scandal is scary. Not only because the data falsification on strength could go back as far as 10 years on some batches, and who knows what bridges, high-rises, and busses that steel has gotten into (and even a .1 degradation, while not enough to jeopardize immediate safety, can impact expected life span and increase susceptibility to decay, making safety a concern down the road before inspection and maintenance schedules kick in).

But this brings up a good point? If more companies were doing more spot checks on shipped product and quality, instead of just trusting Kobe, would it have been 10 years before the scandal was exposed. Even if only a small percent of batches are affected, I highly doubt this would have been undetected for 10 years, even if only one bar or sheet in multiple shipments were tested.

This is an example of what happens when finance tries to get too greed or supply chains to lean by centralizing a function downstream. When one party is responsible for everything, one failure can reverberate up multiple chains undetected — and have potentially disasterous consequences. Now one might say this problem is solved by co-locating people on-site, but if those people never leave the site, even though you pay their salary, their work family is the people they work with day in and ay out and the existence of that company is their livelihood. Are you sure they won’t bow into the local culture and, if the culture dictates, defer to authority or collectively hide the shame?

Just like third party audits are needed, for critical materials, so are third party quality tests. Doesn’t have to be you, could be an independent organization set up between your co-opetition that does random independent quality spot-checks on 1 in 10 shipments and shares the data with everyone.

Just like a good Chef would never use an ingredient without insuring it’s quality, a good Procurement organization should never let a shipment be accepted without a high degree of confidence that it’s a quality shipment. And confidence like that only comes from organizational testing or trusted third-party independent testing. So don’t get too lean or too cheap — your organization, and the lives of its customers, could depend on it.

Are We About to Enter the Age of Permissive Analytics?

Right now most of the leading analytics vendors are rolling out or considering the roll out of prescriptive analytics, which goes one step beyond predictive analytics and assigns meaning to those analytics in the form of actionable insights the organization could take in order to take advantage of the likely situation suggested by the predictive analytics.

But this won’t be the end. Once a few vendors have decent predictive analytics solutions, one vendor is going to try and get an edge and start rolling out the next generation analytics, and, in particular, permissive analytics. What are permissive analytics, you ask? Before we define them, let’s take a step back.

In the beginning, there were descriptive analytics. Solutions analyzed your spend and / or metrics and gave you clear insight into your performance.

Then there are predictive analytics. Solutions analyzed your spend and / or metrics and used time-period, statistical, or other algorithms to predict likely future spend and / or metrics based on current and historical spend / metrics and present the likely outcomes to you in order to help you make better decisions.

Predictive analytics was great as long as you knew how to interpret the data, what the available actions were, and which actions were most likely to achieve the best business outcomes given the likely future trend on the spend and / or metrics. But if you didn’t know how to interpret the data, what your options were, or how to choose the best one that was most in line with the business objectives.

The answer was, of course, prescriptive analytics, which combined the predictive analytics with expert knowledge that not only prescribed a course of action but indicated why the course of action was prescribed. For example, if the system detected rising demand within the organization and predicted rising cost due to increasing market demand, the recommendation would be to negotiate for, and lock-in supply as soon as possible using either an (optimization-backed) RFX, auction, or negotiation with incumbents, depending upon which option was best suited to the current situation.

But what if the system detected that organizational demand was falling, but market demand was falling faster, there would be a surplus of supply, and the best course of action was an immediate auction with pre-approved suppliers (which were more than sufficient to create competition and satisfy demand)? And what if the auction could be automatically configured, suppliers automatically invited, ceilings automatically set, and the auction automatically launched? What if nothing needed to be done except approve, sit back, watch, and auto-award to the lowest bidder? Why would the buyer need to do anything at all? Why shouldn’t the system just go?

If the system was set up with rules that defined behaviours that the buyer allowed the system to take automatically, then the system could auto-source on behalf of the buyer and the buying organization. The permissive analytics would not only allow the system to automate non strategic sourcing and procurement activities, but do so using leading prescriptive analytics combined with rules defined by the buying organization and the buyer. And if prescriptive analytics included a machine learning engine at the core, the system could learn buyer preferences for automated vs. manual vs. semi-automated and even suggest permissive rules (that could, for example, allow the category to be resourced annually as long as the right conditions held).

In other words, the next generation of analytics vendors are going to add machine learning, flexible and dynamic rule definition, and automation to their prescriptive analytics and the integrated sourcing platforms and take automated buying and supply chain management to the next level.

But will it be the right level? Hard to say. The odds are they’ll make significantly fewer bad choices than the average sourcing professional (as the odds will increase to 98% over time), but, unlike experienced and wise sourcing professionals, won’t detect when an event happens in left-field that totally changes the dynamics and makes a former best-practice sourcing strategy mute. They’ll detect and navigate individual black swan attacks but will have no hope of detecting a coordinated black swan volley. However, if the organization also employs risk management solutions with real time event monitoring and alerts, ties the risk management system to the automation, and forces user review of higher spend / higher risk categories put through automation, it might just work.

Time will tell.

To Truly Be Successful at Supplier Risk Management, ADMIRE!

Now that we’ve carefully explained that you’re just not up to the task of preventing a black swan event, hopefully you have made risk management a priority. So, to help you understand, at a high level, what this is, we’re reprinting this classic post from 2010. Most of the articles out there get the basics wrong, but if you get them right, it’s not that hard to do a decent job (especially if you get a good platform to help you out). Enjoy!

Not only is supplier risk at the forefront of thought these days, but articles on it are at the forefront of online publications as well, including this recent article in Supply Chain Digest on the key drivers of successful supplier risk management. However, most of the articles miss the point.

For example, according to this article, the trick to successful supplier risk management is to:

  1. engage top-level management,
  2. segment suppliers based on relative risk,
  3. rigorously measure and manage risk,
  4. give category managers tools and training, and
  5. collaborate with key suppliers.

Which is all good advice that is fine and dandy, but it misses the point. Risk management is all about identify risks, identifying mitigations, monitoring risks, and executing mitigations at the appropriate time. Management support is important, but it doesn’t have anything to do with risk identification or mitigation. Segmentation is a good tactic as more attention needs to be placed on suppliers which represent more significant risks, but again it has nothing to do with risk identification or mitigation. The same goes for giving category managers tools and training. Collaboration is relevant only if the mitigation requires collaboration. In other words, in this list, the only key driver is the “rigorous management and mitigation of risk”.

The reality is that success depends on your ability to ADMIRE the situation. Specifically, the ability to:

  • Ascertain the risks,
  • Define the risks that could cause significant damage,
  • Monitor those risks,
  • Identify appropriate mitigations,
  • React when signs of the risk begin to materialize, and
  • Engage the supplier when collaboration is required to mitigate the risks and
  • rinse and repeat

That’s it. But don’t forget the rinse and repeat. The biggest risks today are not the biggest risks tomorrow, so you always have to be actively engaged in risk management. Always. And since there are always more risks than you can actively address and mitigate, at any particular time you need to focus on the major ones (but still monitor for, and evaluate, the rest and as soon as they become likely or potentially costly, elevate the priority so that a mitigation plan is prepared in time).

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The Black Swans are Gunning For You!

Maybe, after years of humming and hawwing you finally put a proper supply chain risk management program. Maybe you feel you’ve learned enough about disruptions to identify them early and react quickly and the threat of those black swans has been minimized. Maybe you just had the worst disruption in a decade and you know that there are few of them (outside of their native Australia), but many organizations, and the odds are that you won’t see them again for a decade. Maybe you’re safe. Maybe.

But what you don’t understand is these swans are angry. Very angry. And they have a right to be. How would you feel if you were, more or less, consider the ugly duckling compared to your white cousins. Ridiculed and reviled thanks to Dr. Taleb who called you out as the cause of every single unexpected event that few predict, especially when those events have devastating consequences. And to top it off, associated with your raging white cousins that are, the vast majority of the time, the perpetrators of the “swan attack”.

So what do you do when you’re angry? You get revenge. On the biggest targets. And what’s the biggest target? The modern, global supply chain.

And before you think the doctor‘s off his gourd, he knows that, 99.999% of the time your supply chain disruption is not the direct cause of a black swan attack, but that no matter how good you think you are at preventing and detecting black swan events, you’re not good enough. At least not yet.

How does he know this?

  1. The percentage of Procurement organizations that have dedicated risk management solutions is miniscule.
  2. The percentage of Procurement organizations that have dedicated risk management solutions and leading SRM solutions is smaller still.
  3. The percentage of Procurement organizations that have dedicated risk management solutions, leading SRM solutions, and modern strategic sourcing / supply chain optimization solutions is much smaller still.
  4. The percentage of Procurement organizations that have dedicated risk management solutions, leading SRM solutions, modern strategic supply sourcing / supply chain optimization, and six sigma level disaster planning capability is so much smaller still that it’s almost non-existent.

And the reality is that unless you’re at level 4, you’re not going to see enough of the potential disruptions headed your way to analyze their impact probability and potential severity, and you won’t even get a hint of coming big, “black swan” events, until the tsunami is right on top of you and there’s nothing you can do to get out of it’s way. As a recent post by the public defender  points out, events that seem unlikely, surprising, or virtually impossible do happen, more often than we expect, and our risk analysis, mitigation approaches and management actions should bear this in mind.

And most importantly, just because they are half a world away doesn’t mean that they won’t devastate your product line in two months when you’re supply can’t supply because their supplier didn’t supply because the raw material supplier couldn’t supply because the earthquake collapsed the mine — something you could have known two months ago with monitoring, which might have given you enough time to get your disaster recovery plan in place. You’ll still be affected. Costs will still go up. Workloads will still double. But you won’t be up the creek without a paddle (just in a more expensive boat with an un-preferred, less favoured one.)

Trump & Brexit Woes? Optimization is the Answer!

SI has been preaching the gospel of strategic sourcing decision optimization since day one, noting how it was the only way to not only achieve the year over year cost savings that could be identified by spend analytics but also identify additional value necessary for struggling under-staffed and under-budgeted supply management organizations to realize the value that was being demand of them. Year-over-year was key. During the noughts, thanks to the success of FreeMarkets and Ariba, everyone thought that e-Auctions were king, as the first e-Auction often returned 20%, 30%, or even 40% savings and the second a healthy 5% to 15% in a host of categories, but no one realized these savings were just a result of excess fat in supplier margins, shaved out by more aggressive, hungrier, competition looking for a chance to prove themselves and grow. Once the fat was trimmed, and inflation began to return near the end of the noughts, subsequent auctions not only failed to identify additional savings, but also resulted in cost increases.

SI knew this, as the early adopters were already beginning to experience this when SI started and multiple options for strategic sourcing decision optimization were available (CombineNet [now Jaggaer], Emptoris [now IBM], Iasta [now Determine], VerticalNet [now BravoSolution], Trade Extensions, and Algorhythm), but the auction providers had big marketing budgets (as a result of their big successes, % of savings contracts, and VC funding) and bigger mouths to spread the auction word. And by the time the blush faded from the rose, most organizations weren’t ready for what seemed to be complex solutions, so the focus turned to better RFX, should-cost models, spend analysis, and weighted evaluation models. This worked for simpler categories, and the fact-based negotiations shave the remaining fat while also identifying processes or unnecessary non-value add offerings that could be trimmed, and savings continued, but began to trail off. That’s why the leaders are slowly accepting decision optimization and why Trade Extensions has been growing aggressively year-over-year for the last five years or so.

But let’s face it … when 40% of the market still doesn’t have any Supply Management tool and only 20% of the organizations that due are leaders (which kind of explains the Hackett 8%), the adoption is still low and the usage still minimal. As long as savings can be squeaked out through other means (analytics, cost modelling, aggressive negotiation, GPOS, etc.), the average organization seems to be doing everything it can not to evolve. Cognitive Procurement is the buzzword, but cognitive dissonance is the reality.

But that could all be about to change. Why? Between Trump continually threatening new border taxes, border closings, and visa program overhauls and Brexit looming on the near-horizon, which will totally change the tax and border situation in Europe, supply chain costs are totally unknown for a large majority of global supply chains. Considering how many global organizations are headquartered (at least regionally) in the US or UK and how many more have their Procurement Centers of Excellence there (either in a distribution hub or a financial hub, of which New York and London are two of the biggest in the world), it’s looming chaos. Are your costs going up? If so, are they going up 10%, 20%, 100%? Are sources of supply going to be cut off due to trade bans? Is your best talent going to be locked out of the US or UK? It’s a nightmare waiting to happen. It’s enough to put even stock market traders into full panic mode.

So what do you do? You manage the risk? But how? Most of the traditional supply chain risk management platforms (Reslinc, Risk Methods, Achilles, etc.) are geared at supply chain visibility — attempting to identify potential disruptions [as a result of external or internal events] before they happen so that mitigation plans can be identified and put in place before they do. However, when the disruption is not an event but an unpredictable [and unaffordable] tax hike or border closing, these solutions, even those that reach level 5 on the Spend Matters scale, are pretty useless. That’s why Sourcing Innovation has recently stated that Supply Management Risk Management Needs to be Cranked to 11. (It’s important to go to 11.)

You see, the key to survival is “what if” the current supply chain becomes unsustainable due to a tax hike or border closing in the US or UK. Running a new scenario with all of the inputs except any lanes, countries of origins, and / or products where you expect to see disruptions, trade bans, or extreme import/export duties. And then running another new scenario under a different set of assumptions on lane, country, and/or product restrictions. Running scenarios at the product level and the category level. Running with current supply base, previous bidder supply base, and newly identified scenario supply base until you have a mitigation scenario that is acceptable and ready to go if something happens.

Only a good supply management decision optimization solution with what-if scenario support can do this – nothing else.

So, since we’ve all forgotten Kermit’s Lesson, this is what we’re left with. But considering how it will enhance your overall supply chain operations in these turbulent times, that’s not a bad thing.