What are the steps to integrate probabilistic forecasting into the supply chain of an Aerospace MRO (i.e, similar to your work with Air France Industries), particularly when I'm a minor player (employee) handling it independently without any investment capital, but rather as part of my job responsibilities?
Additionally, as you have discussed in your YouTube videos and articles, is forecasting truly the answer, or should the focus be more on reengineering the supply chain or implementing other process modifications across different levels?
I would have very much preferred the answer to this question to be different, to have a nice incremental path that could be made available to all employees; it would have made the early life of Lokad much easier while competing against Big Vendors.
Then, don't underestimate what a supposedly "minor" employee can do. Apathy is one of the many diseases touching large companies. When nobody cares, the one person who genuinely care ends up steering the ship. All it takes to point out the obvious as many people it takes. The flaws of the "legacy" supply chain solutions are not subtle, they are glaring.
Forecasting is a mean to an end, but just a mean. Focusing on forecasting as a "stand-alone thingy" is wrong. This is the naked forecast antipattern, see https://www.lokad.com/antipattern-naked-forecasts/
I appreciate your candid response. After exploring the antipatterns and the QSC philosophy, I've realized that some organizations are not as API-minded by design (culturally). Steering the ship towards the QSC feels like stepping on leadership toes, potentially making one a martyr for the cause. But I love this analogy and have been doing so ever since this remark. Additionally, I've observed that pride often leads people to prefer internal ideas over external suggestions. Navigating emotional intelligence, professional tact, and business interactions has taught me that leadership often takes precedence over coding numerical recipes.
Hypothetically, consider a B2B aerospace enterprise with historically intermittent and messy data. It would require extensive collaboration with functional experts to create the JPM you've described. Many leaders (nodes) downstream believe data sharing is already enough and are protective of their proprietary information, necessitating new agreements. These entities also have become adversarial or just unaware, focusing on their metrics without considering broader supply chain impacts.
For example, an MRO might prioritize production metrics. service, and profits, ignoring how this gamification affects the supply chain (upstream) and ultimately the end consumer. From your lectures and Lokad TV, I've learned that a well-built data pipeline is foundational to a successful QSC initiative. The biggest risk to the QSC is organizations unwilling to share their data, compounded by a lack of understanding of what data is necessary. Often, we are seeking out unknown data while navigating political hurdles (red tape) to access even a few fields from another node's table.
My question is:
How did you navigate democratizing and evangelizing the need for data sharing in a multi-echelon supply chain with differing philosophies? Did you accomplish this challenge through courageous leadership and democratization of the QSC?
For instance, when one MRO highlights issues while others are content, or when subcontractors and upstream vendors resist sharing lead time data due to proprietary or incentive concerns, how did you handle it? I truly think there is a cultural and fundamental problem with some of our industry's supply chain's philosophy of data sharing.
So, we can share via flat files (with red tape), but is that truly sustainable? Or should that be just enough to show proof of value? We are probably stuck not knowing what is needed to share. And so perhaps there is hope, but again, once an organization gets a whiff of what the other is up to, they may block your sharing capabilities due to poor policy and lack of understanding of the objective. "You're trying to forecast?! We already do that, trust our numbers! [Buys 1000, uses none of it for 5 years, no one held responsible, money lost]"
Thank you for your answer 7 months ago. It certainly helps!
What are the steps to integrate probabilistic forecasting into the supply chain of an Aerospace MRO (i.e, similar to your work with Air France Industries), particularly when I'm a minor player (employee) handling it independently without any investment capital, but rather as part of my job responsibilities?
Additionally, as you have discussed in your YouTube videos and articles, is forecasting truly the answer, or should the focus be more on reengineering the supply chain or implementing other process modifications across different levels?
Unfortunately, in supply chain, things can be done "a small piece" at a time. It just doesn't work. See
https://www.lokad.com/blog/2021/9/20/incrementalism-is-the-bane-of-supply-chains/
I would have very much preferred the answer to this question to be different, to have a nice incremental path that could be made available to all employees; it would have made the early life of Lokad much easier while competing against Big Vendors.
Then, don't underestimate what a supposedly "minor" employee can do. Apathy is one of the many diseases touching large companies. When nobody cares, the one person who genuinely care ends up steering the ship. All it takes to point out the obvious as many people it takes. The flaws of the "legacy" supply chain solutions are not subtle, they are glaring.
In MRO, it boils down to: uncertainty must be embraced and quantified, varying TATs matter as much as varying consumptions, etc. See an extensive review of the challenges that need to be covered https://www.lokad.com/tv/2021/4/28/miami-a-supply-chain-persona-an-aviation-mro/
Forecasting is a mean to an end, but just a mean. Focusing on forecasting as a "stand-alone thingy" is wrong. This is the naked forecast antipattern, see https://www.lokad.com/antipattern-naked-forecasts/
For an overview on how to get a supply chain initiative organized, and launched, see https://www.lokad.com/tv/2022/7/6/getting-started-with-a-quantitative-supply-chain-initiative/
Hope it helps,
I appreciate your candid response. After exploring the antipatterns and the QSC philosophy, I've realized that some organizations are not as API-minded by design (culturally). Steering the ship towards the QSC feels like stepping on leadership toes, potentially making one a martyr for the cause. But I love this analogy and have been doing so ever since this remark. Additionally, I've observed that pride often leads people to prefer internal ideas over external suggestions. Navigating emotional intelligence, professional tact, and business interactions has taught me that leadership often takes precedence over coding numerical recipes.
Hypothetically, consider a B2B aerospace enterprise with historically intermittent and messy data. It would require extensive collaboration with functional experts to create the JPM you've described. Many leaders (nodes) downstream believe data sharing is already enough and are protective of their proprietary information, necessitating new agreements. These entities also have become adversarial or just unaware, focusing on their metrics without considering broader supply chain impacts.
For example, an MRO might prioritize production metrics. service, and profits, ignoring how this gamification affects the supply chain (upstream) and ultimately the end consumer. From your lectures and Lokad TV, I've learned that a well-built data pipeline is foundational to a successful QSC initiative. The biggest risk to the QSC is organizations unwilling to share their data, compounded by a lack of understanding of what data is necessary. Often, we are seeking out unknown data while navigating political hurdles (red tape) to access even a few fields from another node's table.
My question is:
How did you navigate democratizing and evangelizing the need for data sharing in a multi-echelon supply chain with differing philosophies? Did you accomplish this challenge through courageous leadership and democratization of the QSC?
For instance, when one MRO highlights issues while others are content, or when subcontractors and upstream vendors resist sharing lead time data due to proprietary or incentive concerns, how did you handle it? I truly think there is a cultural and fundamental problem with some of our industry's supply chain's philosophy of data sharing.
So, we can share via flat files (with red tape), but is that truly sustainable? Or should that be just enough to show proof of value? We are probably stuck not knowing what is needed to share. And so perhaps there is hope, but again, once an organization gets a whiff of what the other is up to, they may block your sharing capabilities due to poor policy and lack of understanding of the objective. "You're trying to forecast?! We already do that, trust our numbers! [Buys 1000, uses none of it for 5 years, no one held responsible, money lost]"
Thank you for your answer 7 months ago. It certainly helps!
Respectfully,