Selected example interview quotes that led to emergence of aggregated dimensions
| Aggregate dimension | Interview quote |
|---|---|
| Automation of routine planning processes | We actually saw a quite a lot of automation possibilities. For example, if you plan to make changes in the listings … How many retail stores would have a certain SKU and so on. So, this is typically a super manual process … CPG companies people communicate (in advance) and then they fit them into their own tools and so on. However, you could completely just automate and have the machine kind of take into account those changes. – Solution Provider |
| We stated that if their data quality is sufficient, they wouldn’t need to send us orders manually, as the system could handle this automatically. – FoodCo | |
| Synchronization of volume and delivery schedules | We notice the bigger discrepancies and investigate the reason for difference in volumes or delivery times. We discuss it with retailers if the differences are large enough. - FoodCo |
| I have one concrete example, where a manufacturer and a retailer had agreed on a promotion. However, the retailer later moved promotion one week later, while manufacturer was not informed (of the change) … It was only through this collaboration they realized and addressed the discrepancy … The outcome was that we will use this collaboration and never miss a promotion again. – Solution Provider | |
| Proactive exception management | There are exception limits that (identify) if the data (received replenishment forecasts) that we just read into our system varies a lot from the forecast that we have for that certain retailer … It then raises an exception and then some manual review is needed. – Solution Provider |
| This approach also allows for better handling of exceptions, such as changes in assortment, seasonal variations and shifts in order patterns. – Solution Provider |
| Aggregate dimension | Interview quote |
|---|---|
| Automation of routine planning processes | We actually saw a quite a lot of automation possibilities. For example, if you plan to make changes in the listings … How many retail stores would have a certain SKU and so on. So, this is typically a super manual process … CPG companies people communicate (in advance) and then they fit them into their own tools and so on. However, you could completely just automate and have the machine kind of take into account those changes. – Solution Provider |
| We stated that if their data quality is sufficient, they wouldn’t need to send us orders manually, as the system could handle this automatically. – FoodCo | |
| Synchronization of volume and delivery schedules | We notice the bigger discrepancies and investigate the reason for difference in volumes or delivery times. We discuss it with retailers if the differences are large enough. - FoodCo |
| I have one concrete example, where a manufacturer and a retailer had agreed on a promotion. However, the retailer later moved promotion one week later, while manufacturer was not informed (of the change) … It was only through this collaboration they realized and addressed the discrepancy … The outcome was that we will use this collaboration and never miss a promotion again. – Solution Provider | |
| Proactive exception management | There are exception limits that (identify) if the data (received replenishment forecasts) that we just read into our system varies a lot from the forecast that we have for that certain retailer … It then raises an exception and then some manual review is needed. – Solution Provider |
| This approach also allows for better handling of exceptions, such as changes in assortment, seasonal variations and shifts in order patterns. – Solution Provider |
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