Table A2 Coding scheme for data analysis...

Table A2

Coding scheme for data analysis

Themes and categories {515}	Representative data
Options {262}
Assortment sizes	We need to address the influencing factors. If done rigorously, we would have to monitor write-offs and unlist products where we do not succeed in reducing food waste. Customer services would need to go down. (HM02)
Delivery pattern	A further lever is the adjustment of delivery patterns, e.g., through ultra-fresh warehouses in which perishable products can be processed in a short time. (SM02)
Differentiating inventory service levels	At least one tomato variant must still be available in any case. Substitution effects are taken into account within the product groups. Availability indicators are both product and time specific: e.g., 95% on Saturdays and 97% on weekdays for the fruits and vegetables assortment. (DC02)
Discounting of overstocks	Discounting is a common practice, however, still a completely manual process. The implementation depends on the time management of the store, but employees should have time for this. (SM02)
Donations	We also cooperate with food banks. They come once a week and pick up the groceries. […] We are also happy that we do not have to dispose it. (DC01)
Food waste monitoring and analysis	In the past, the focus was mainly on the store, but today we focus on the entire supply chain. […] A central unit monitors losses along the entire supply chain and acts as an advisor for procurement, forecasting, and replenishment operations. (SM02)
Forecasting store demand	Great progress is expected through full automation and algorithms. Everyone is 100% convinced that it will get better, but it is unclear how far it can be pushed. (DC02)
Further processing internally	Products close to the expiration date are removed from the shelves. There are several options for how products can be utilized. Each store has its own catering and kitchens. […] Fruits and vegetables can be further processed to convenience products. (HM02)
Imperfect produce	Offering imperfect produce reduces losses at the farming stage. Those products were marketed with several campaigns. However, customer acceptance is limited. (SM03)
Inbound product flows	The decision of whether fresh products should be kept in stock at our warehouse is crucial. […] An alternative is cross-docking, where the goods are only transshipped in the warehouse and then delivered directly to the store. (HM02)
Min. Order quantities and pack sizes	We are constantly in exchange with procurement to adjust order quantities and packaging. A good example is sausage products, where we only sell 60% on average. Then we have three options: unlist the product, waste the remaining 40%, or adjust the package size. (HM01)
Order cycles and volumes	Lead times can be coordinated with the supplier to keep batches small. This reduces the stock and thus the risk of food waste, however, it is very costly. (WS01)
Picking operations	FEFO picking in the warehouse ensures that first to expire products leave the warehouse first, with positive effects on the remaining shelf life. (SM03)
Push allocation of warehouse stocks	A special case is product allocation, i.e., goods that have not been ordered but still need to be distributed to the stores because of decreasing shelf life. We try to allocate goods based on past turnover and store frequency. (DC03)
Quality inspection	There is a separate department for quality control that inspects incoming goods based on predefined quality characteristics. (DC02)
Secondary channels	Last resort is the sale to secondary channels, e.g., remnant dealers, where products are sold at a 70–80% discount. (WS01)
Shelf merchandising	Especially highly perishable products are frequently checked. A new delivery must always be placed behind or below the old inventory. […] Product circulation should be applied in each refilling process. (DC01)
Sourcing approach	Supplier dependency also plays an important role. How reliable are my suppliers? It happens from time to time that trucks stop at the borders. […] Weather but also transport routes might cause fluctuations in supply. (DC03)
Supplier collaboration	Cooperation with suppliers is a good option. Here, forecast data is passed on to the processing industry. […] Continuity of the information chain would be the goal, whether in competition or not. An interconnected supply chain would improve forecast accuracy. (SM02)
Take-back agreements	In case inventory cannot be sold, returning batches to the processing industry is also an option. However, this depends on the supplier relationship. (WS01)
Transshipment between stores	Exchanging goods within the network is an option in case there is a big difference in sales between the stores. Products are then simply re-distributed with the next delivery. (DC01)
Barriers {186}
Brand image	An excessive discounting also has negative effects. The customers' quality perception might suffer when there are 30% off stickers everywhere. (SM03)
Cannibalization effect	Customers already know our discounting logic. They come into the store, look at the expiration date, wait two days, and then buy the product for the discounted price. (SM02)
Competitive pressure	Competition plays an important role. It is already extreme in the German market and still getting more difficult. Without competition, we could educate our customers. (SM02)
Data protection regulation	A project with a digital delivery ticket has failed due to data protection reasons. Data protection is very strong here and a limiting factor. (DC03)
Data quality	A huge amount of data is already available, but the quality, i.e., the validity of the data, is so far not yet guaranteed. (DC01)
Employee qualifications and motivation	The onboarding of qualified employees is and will remain a problem. So attempts are made to cover as much as possible with automated systems. (HM01)
Incentive misalignment	Procurement managers are aiming to buy as cheap as possible, what is often achieved through quantity discounts. (DC04)
Inventory transparency	Even the most intelligent system is of no use if the information is missing. […] It would be much easier if customers would withdraw the products following the FEFO principle. […] In the end, we do not know the expiration dates of products on our shelves. (SM03)
IT integration	[…] However, a lot of stakeholders have to be involved: suppliers, procurement, POS systems, etc. This is going to be a huge IT project. […] Our IT systems are not Microsoft or Apple, where you can easily connect other interfaces. (DC03)
Processing costs	From a process perspective, a two-stage discounting is not beneficial due to high processing costs. […] A two-stage discounting would have caused an additional cost of x EUR per day and store. This adds up to a significant cost factor. (DC03)
Network density	Only nearby stores are considered for reallocation. Returning products to the warehouse is mostly too much effort. Logistics costs eat up potential earnings. (DC01)
Food law regulation	We could do a lot more without the strict regulations. It is really difficult for us, as only food banks are accepted partners. […] The liability for products given to food sharing is still a limiting factor. (DC04)
Subjectivity of quality	Quality standards for fruits and vegetables are quite subjective. Decisions are mostly made based on a visual inspection. (DC01)
Supplier dependency	Adjusting minimum order quantities jointly with the supplier is often a problem. As a small player in the market, you often don't stand a chance here. (SM02)
Impact {67}
Very high	Great progress is expected through full automation and algorithms. Everyone is 100% convinced that it will get better, but it is unclear how far it can be pushed. (DC02) Most successful initiative is the cooperation with food banks, because it simply means saving food from disposal. (OS02)
High	Another highly important measure is the smart overstock allocation from the warehouses to the stores. […] This is a big step in the right direction. […] First results indicate that this is an effective tool. (SM03) The selection of suitable inbound flows for products is crucial as shelf life is consumed by stock-keeping. (HM02)
Med	You can control a lot via purchasing modalities, and the subsequent implications are also interesting. The first step is purchasing: here, you could go in the direction of packaging and more precise disposition. (DC03) How reliable are my suppliers? It happens from time to time that trucks stop at the borders. […] Weather but also transport routes might cause fluctuations in supply. (DC03)
Low	Towards the end of the shelf life, the supplier can also only dispose the products. (WS01) Redistribution of goods is only applicable for selected products. It should not occur in the standard assortment, as cold chain issues might emerge. (DC02)

Themes and categories {515}	Representative data
Options {262}
Assortment sizes	We need to address the influencing factors. If done rigorously, we would have to monitor write-offs and unlist products where we do not succeed in reducing food waste. Customer services would need to go down. (HM02)
Delivery pattern	A further lever is the adjustment of delivery patterns, e.g., through ultra-fresh warehouses in which perishable products can be processed in a short time. (SM02)
Differentiating inventory service levels	At least one tomato variant must still be available in any case. Substitution effects are taken into account within the product groups. Availability indicators are both product and time specific: e.g., 95% on Saturdays and 97% on weekdays for the fruits and vegetables assortment. (DC02)
Discounting of overstocks	Discounting is a common practice, however, still a completely manual process. The implementation depends on the time management of the store, but employees should have time for this. (SM02)
Donations	We also cooperate with food banks. They come once a week and pick up the groceries. […] We are also happy that we do not have to dispose it. (DC01)
Food waste monitoring and analysis	In the past, the focus was mainly on the store, but today we focus on the entire supply chain. […] A central unit monitors losses along the entire supply chain and acts as an advisor for procurement, forecasting, and replenishment operations. (SM02)
Forecasting store demand	Great progress is expected through full automation and algorithms. Everyone is 100% convinced that it will get better, but it is unclear how far it can be pushed. (DC02)
Further processing internally	Products close to the expiration date are removed from the shelves. There are several options for how products can be utilized. Each store has its own catering and kitchens. […] Fruits and vegetables can be further processed to convenience products. (HM02)
Imperfect produce	Offering imperfect produce reduces losses at the farming stage. Those products were marketed with several campaigns. However, customer acceptance is limited. (SM03)
Inbound product flows	The decision of whether fresh products should be kept in stock at our warehouse is crucial. […] An alternative is cross-docking, where the goods are only transshipped in the warehouse and then delivered directly to the store. (HM02)
Min. Order quantities and pack sizes	We are constantly in exchange with procurement to adjust order quantities and packaging. A good example is sausage products, where we only sell 60% on average. Then we have three options: unlist the product, waste the remaining 40%, or adjust the package size. (HM01)
Order cycles and volumes	Lead times can be coordinated with the supplier to keep batches small. This reduces the stock and thus the risk of food waste, however, it is very costly. (WS01)
Picking operations	FEFO picking in the warehouse ensures that first to expire products leave the warehouse first, with positive effects on the remaining shelf life. (SM03)
Push allocation of warehouse stocks	A special case is product allocation, i.e., goods that have not been ordered but still need to be distributed to the stores because of decreasing shelf life. We try to allocate goods based on past turnover and store frequency. (DC03)
Quality inspection	There is a separate department for quality control that inspects incoming goods based on predefined quality characteristics. (DC02)
Secondary channels	Last resort is the sale to secondary channels, e.g., remnant dealers, where products are sold at a 70–80% discount. (WS01)
Shelf merchandising	Especially highly perishable products are frequently checked. A new delivery must always be placed behind or below the old inventory. […] Product circulation should be applied in each refilling process. (DC01)
Sourcing approach	Supplier dependency also plays an important role. How reliable are my suppliers? It happens from time to time that trucks stop at the borders. […] Weather but also transport routes might cause fluctuations in supply. (DC03)
Supplier collaboration	Cooperation with suppliers is a good option. Here, forecast data is passed on to the processing industry. […] Continuity of the information chain would be the goal, whether in competition or not. An interconnected supply chain would improve forecast accuracy. (SM02)
Take-back agreements	In case inventory cannot be sold, returning batches to the processing industry is also an option. However, this depends on the supplier relationship. (WS01)
Transshipment between stores	Exchanging goods within the network is an option in case there is a big difference in sales between the stores. Products are then simply re-distributed with the next delivery. (DC01)
Barriers {186}
Brand image	An excessive discounting also has negative effects. The customers' quality perception might suffer when there are 30% off stickers everywhere. (SM03)
Cannibalization effect	Customers already know our discounting logic. They come into the store, look at the expiration date, wait two days, and then buy the product for the discounted price. (SM02)
Competitive pressure	Competition plays an important role. It is already extreme in the German market and still getting more difficult. Without competition, we could educate our customers. (SM02)
Data protection regulation	A project with a digital delivery ticket has failed due to data protection reasons. Data protection is very strong here and a limiting factor. (DC03)
Data quality	A huge amount of data is already available, but the quality, i.e., the validity of the data, is so far not yet guaranteed. (DC01)
Employee qualifications and motivation	The onboarding of qualified employees is and will remain a problem. So attempts are made to cover as much as possible with automated systems. (HM01)
Incentive misalignment	Procurement managers are aiming to buy as cheap as possible, what is often achieved through quantity discounts. (DC04)
Inventory transparency	Even the most intelligent system is of no use if the information is missing. […] It would be much easier if customers would withdraw the products following the FEFO principle. […] In the end, we do not know the expiration dates of products on our shelves. (SM03)
IT integration	[…] However, a lot of stakeholders have to be involved: suppliers, procurement, POS systems, etc. This is going to be a huge IT project. […] Our IT systems are not Microsoft or Apple, where you can easily connect other interfaces. (DC03)
Processing costs	From a process perspective, a two-stage discounting is not beneficial due to high processing costs. […] A two-stage discounting would have caused an additional cost of x EUR per day and store. This adds up to a significant cost factor. (DC03)
Network density	Only nearby stores are considered for reallocation. Returning products to the warehouse is mostly too much effort. Logistics costs eat up potential earnings. (DC01)
Food law regulation	We could do a lot more without the strict regulations. It is really difficult for us, as only food banks are accepted partners. […] The liability for products given to food sharing is still a limiting factor. (DC04)
Subjectivity of quality	Quality standards for fruits and vegetables are quite subjective. Decisions are mostly made based on a visual inspection. (DC01)
Supplier dependency	Adjusting minimum order quantities jointly with the supplier is often a problem. As a small player in the market, you often don't stand a chance here. (SM02)
Impact {67}
Very high	Great progress is expected through full automation and algorithms. Everyone is 100% convinced that it will get better, but it is unclear how far it can be pushed. (DC02)Most successful initiative is the cooperation with food banks, because it simply means saving food from disposal. (OS02)
High	Another highly important measure is the smart overstock allocation from the warehouses to the stores. […] This is a big step in the right direction. […] First results indicate that this is an effective tool. (SM03)The selection of suitable inbound flows for products is crucial as shelf life is consumed by stock-keeping. (HM02)
Med	You can control a lot via purchasing modalities, and the subsequent implications are also interesting. The first step is purchasing: here, you could go in the direction of packaging and more precise disposition. (DC03)How reliable are my suppliers? It happens from time to time that trucks stop at the borders. […] Weather but also transport routes might cause fluctuations in supply. (DC03)
Low	Towards the end of the shelf life, the supplier can also only dispose the products. (WS01)Redistribution of goods is only applicable for selected products. It should not occur in the standard assortment, as cold chain issues might emerge. (DC02)

Note(s): { } = Number of codes

Source(s): Created by authors

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