Try to understand it using auto translate 😂. Lokad content always interesting for me since not a lot of people cover material management in aviation MRO
- What are these typical operation research topics that I'm saying don't work? - 11:55 - First Time series in demand forecasting - Doesn't work well for unusual demands - For example, where you have consumers who buy switches one at a time and construction companies who buy 500 at a time. - The order for 500 is announced well in advance, while the one offs are immediate, yet a time series will not differentiate between these cases and squash the demand together - For substitutions in fashion - if the wrong size is there - can't sell it, but if its a slightly different color, the customer wil likely still take it - Diapers and market basket effects - Diapers are expensive and have high brand loyalty on average - However it's not the loss of the diaper sale that is the most impactful - it's the fact that parents will then not buy all of their other groceries at the hypermarket if the diapers aren't there. - Time series also hides the fact that the future is blurry and in which direction - Deterministic forecasting works pretty well with consistent values - But a deterministic forecast of something like a soup in a supermarket with promos and demand swings of >100% it makes no sense to generate a point forecast - 1st order effects can be measured such as impact of promotion, but those indirect 2nd order effects e.g. consumer behaviour changes are hugely critical to take into account - 27:15 - For example a spare parts organization of an aircraft company had a recommendation to purchase a part, the employees said absolutely not! - It seemed a reasonable recommendation to make - however it was a spare part for a 747 - and since the part had a 30 year life, and the 747s are being deprecated within the next 10 years there was no need for it - Another interesting effect in airlines is the one-way standard. - A plane is allowed to have a part matching the old standard, however as soon as a part passing the new standard is placed - you must only use new parts going forward. - This means if you have inventory of old and new parts - each time you replace with a new part- you are modifying the composition of your demand for spare parts across your flotilla - Just because we don't know what to optimize for, doesn't mean we can't find out - 29:17 - It just can't be done in a top down cartesian way in which we split the problem down into constituent pieces and come up with an answer that way - We arrived at the need for supply chain scientists to operate under the idea of Experimental Optimization - To optimize you must create logic to generate a decision - you will then have people who object - Their reasons for objecting are typically correct - Use anecdotes to find the reasons it won't work - Then we will feedback into the dollarized/financialized decision making system to add the constraints and requirements that will meet the edge cases which are critical to that customer - For example with the spare parts problem we had taken into account the lifespan of the part, but not the lifespan of the plane itsself - In our supply chain books we tell you the demand is a Gaussian, lead times are a Gaussian - is there any way to falsify this? no, it's in the abstract, divorced from reality - 31:50 - Our goal is to make a mathematical model , maximized for modeling reality, not necessarily mathematical simplicity - An important part of the process is making sure to present the results to the customer in a specific way - not just "here are your optimal stock levels" but - "where should I put my first Euro of inventory investment?" - 80% customers know what they're doing - so this list of prioritized investments in purchasing, manufacturing, or inventory levels is reasonable - though sometimes they may be missing something obvious - Working with a german MRO company - Retrofit and repairs are 2 different things - Repairs are - engineer says this part needs to be fixed, replace - Retrofits are - the manufacturer has some doubts about a part and requires a push to replace within a month - You can't mix push and pull demands together - they act completely differently - You push a big spike of parts - and now all of your spares for that part are synchronized
Try to understand it using auto translate 😂. Lokad content always interesting for me since not a lot of people cover material management in aviation MRO
- What are these typical operation research topics that I'm saying don't work? - 11:55
- First Time series in demand forecasting
- Doesn't work well for unusual demands
- For example, where you have consumers who buy switches one at a time and construction companies who buy 500 at a time.
- The order for 500 is announced well in advance, while the one offs are immediate, yet a time series will not differentiate between these cases and squash the demand together
- For substitutions in fashion
- if the wrong size is there - can't sell it, but if its a slightly different color, the customer wil likely still take it
- Diapers and market basket effects
- Diapers are expensive and have high brand loyalty on average
- However it's not the loss of the diaper sale that is the most impactful - it's the fact that parents will then not buy all of their other groceries at the hypermarket if the diapers aren't there.
- Time series also hides the fact that the future is blurry and in which direction
- Deterministic forecasting works pretty well with consistent values
- But a deterministic forecast of something like a soup in a supermarket with promos and demand swings of >100% it makes no sense to generate a point forecast
- 1st order effects can be measured such as impact of promotion, but those indirect 2nd order effects e.g. consumer behaviour changes are hugely critical to take into account - 27:15
- For example a spare parts organization of an aircraft company had a recommendation to purchase a part, the employees said absolutely not!
- It seemed a reasonable recommendation to make - however it was a spare part for a 747 - and since the part had a 30 year life, and the 747s are being deprecated within the next 10 years there was no need for it
- Another interesting effect in airlines is the one-way standard.
- A plane is allowed to have a part matching the old standard, however as soon as a part passing the new standard is placed - you must only use new parts going forward.
- This means if you have inventory of old and new parts - each time you replace with a new part- you are modifying the composition of your demand for spare parts across your flotilla
- Just because we don't know what to optimize for, doesn't mean we can't find out - 29:17
- It just can't be done in a top down cartesian way in which we split the problem down into constituent pieces and come up with an answer that way
- We arrived at the need for supply chain scientists to operate under the idea of Experimental Optimization
- To optimize you must create logic to generate a decision - you will then have people who object
- Their reasons for objecting are typically correct
- Use anecdotes to find the reasons it won't work
- Then we will feedback into the dollarized/financialized decision making system to add the constraints and requirements that will meet the edge cases which are critical to that customer
- For example with the spare parts problem we had taken into account the lifespan of the part, but not the lifespan of the plane itsself
- In our supply chain books we tell you the demand is a Gaussian, lead times are a Gaussian - is there any way to falsify this? no, it's in the abstract, divorced from reality - 31:50
- Our goal is to make a mathematical model , maximized for modeling reality, not necessarily mathematical simplicity
- An important part of the process is making sure to present the results to the customer in a specific way - not just "here are your optimal stock levels" but - "where should I put my first Euro of inventory investment?"
- 80% customers know what they're doing - so this list of prioritized investments in purchasing, manufacturing, or inventory levels is reasonable - though sometimes they may be missing something obvious
- Working with a german MRO company
- Retrofit and repairs are 2 different things
- Repairs are - engineer says this part needs to be fixed, replace
- Retrofits are - the manufacturer has some doubts about a part and requires a push to replace within a month
- You can't mix push and pull demands together - they act completely differently
- You push a big spike of parts - and now all of your spares for that part are synchronized
Awesome summary! Cheers, Joannes