INTRODUCTION-QUALITY ASSURANCE

This view is dedicated to those who are interested in giving/getting additional information about the quality of food which have some form of impact on food quality management. The efficiency of quality management and assurance could certainly be greatly improved if information was available/purchased together with the product.

Traceability provides a tool for remote quality assurance by finding spots in the value chain that are important with respect to provision of information. Different strategies for exposing information along a value chain can be modeled and implemented. Which strategy to select will depend upon several factors and which type of actor that has stakes in the information quality. Exchange and sharing of traceability information describes different strategies while this section may provide insights about what they actually mean from different viewpoints.

OPINIONS/FACTS

Purchasing information along with the product

One way of securing that quality information actually is available, is to make information part of the business relationship between actors in the value chain. Thus, information is part of the product that is purchased from upstream business partners. Information can be delivered along with the product or separately through electronic information interchange and/or postal services.

How an exchange of quality data in advance of the shipment of goods will help avoid returns

Certain properties about the environment may expose goods to conditions that directly reduce the quality of the product itself. One example of such quality information is the documentation that a product has been suitably refrigerated throughout the supply chain is extremely important for many food stuffs. Other food stuffs need specific humidity ranges to maintain the quality. By introducing traceability events in the value chain that are directly targeting such properties, buyers and sellers can use traceability functionality to collect relevant data along the chain in a timely manner and use this data for decision support. Decision support is very relevant in different situations like packing, transporting and receiving goods. Good algorithms exist that can be used along with the data to calculate how quality is reduced along the chain as a function of time and environmental factors.

Such data can further be used to calculate remaining shelf life in a dynamic manner.

How to avoid repeating costly analysis along the chain

The availability of quality information about a food unit at one actor in a value chain does not necessarily mean that such information is exploited later in a food chain. This is especially valid for analytical information captured through use of analysis in laboratories.

If such information is not made available for other chain members along the value chain, either because of lacking information sharing or dead-ends in the value chain, analyses may need to be retaken to recreate such information (when applicable). The implementation of traceability along the chain may firstly document that such analyses exist, and secondly provide means for accessing such information. Information holes or dead ends in a value chain do, however, introduce challenges that need to be overcome to anyway get access to such information. Several alternatives exist for meeting such challenges:

• Using information on the traceable unit to find a starting point for tracing such information (like brand name, production site, production date etc.).
• If a chain traceability systems exist, information 'holes' may be identified by building up traceability graphs. A traceability graph may identify actors who are not publishing core traceability information. Such actors can then possibly be made more transparent by their trading partners that have registered sent/received goods to/from them. This can then indirectly be used to create a relationship between incoming and outgoing traceable units using information about the trace event generated by their trading partners. The granularity of such a system will of course be coarse since actors without electronic traceability system need to be managed as a "black hole". Trace events may however reduce the possible number of involved traceable units in the search for analytical information.
• Actors may create electronic systems that publish analytical data related to their specific trace units which can be shared through a Web portal, exchanged with trading partners either in a business-to-business fashion or through relevant central repositories.

How TraceCore can help to transport quality related information in parallel to the product

Electronic information can travel much faster than physical goods since the information can be transported in computer networks. Thus, information regarding products can be received and used immediately to document that the products to be received later have the necessary quality and be used for preparation of receiving these goods.

Standardised exchange of such information enables the receiving partners to interpret and apply the information correctly with respect to the internal business processes. TraceCore is suggested as a standard for exchange of traceability information and can thus help in providing a tool for reliable and fast exchange of relevant traceability information.

How to obtain access to real quality data instead of relying on internal or external certification

The granularity of information that can be provided by an organization related to food items has been quite coarse in manual trade and traceability systems. This can be explained by several facts like the industrialization of food production, fast through-put of additives and raw materials through the organization, few data collection points and problems with integration of processes and information.

Originally, the production and monitoring equipment was mainly mechanic or analog and could as such not be captured and directly related to specific items. Thus, general information like ingredients, nutrition, recipes etc could be made available for specific product types while other information like environmental data, origin of raw materials and additives were lost during the production and refinement processes. A way to document processes and products has been to issue certificates related to quality and several other product properties (like, e.g., origin, and sustainability).

The introduction of digital technology and electronics into the production and monitoring equipment enables possibilities for a much more fine-grained granularity of information both related to time, location. Contextual parameters can now be digitally stored along with property information and be correlated with the flow of physical goods through the value chain. Quality data can thus theoretically be made available for every food item produced and shipped from any food producer. Many types of quality data can be captured and stored within the companies as well as in the transport between companies.

A major challenge for almost all companies is to integrate and condensate contextual data in such a way as to produce information that is relevant for the other actors in the value chain. An important fact is that different stakeholders will have different requirements and different needs related to the content and granularity of the information.

Traceability systems will need to make adaptive systems and user interfaces to enable different stakeholders a view of the quality data that meets the requirements and business processes relevant for that stakeholder.

The availability of quality data collected along the chain

Availability of data which regards quality will differ greatly in a value chain. While some actors may believe in openness, product differentiation and value-added information, other actors may be afraid or less eager to expose detailed information about the product.

The development of electronic and digital infrastructures enable data collection in almost all parts of a value chain. Unfortunately, these data will often not be accessible or interesting for other purposes than local control and monitoring of the food production. Most of the food producing actors may, however, expose much more information today about quality because of the availability of technology to disseminate quality information a rather fine granularity. This information as the food items themselves, will have a shelf life. When a food item has been consumed, used or discarded, many parts of the collected information will loose value for most of the stakeholders in the value chain. It is thus important to also implement stock management of data in addition to stock management of food. Some kind of data will have a historical use for certain actors, especially for purposes like statistics, planning, forecasting, and other analysis.

The type and need for quality data for the value chain members should thus be analysed with respect to the different stakes and requirements the stakeholders have related to specific data. Long-term storage of data comes with a cost, especially if the data is to be made accessible outside the issuing organization. Others aspects to consider is whether the product type which has quality data attached still is in production, is dependent of certain additives which is no longer available, change properties when other additives or processes have been applied etc.

Automated quality assessment of a food product

The availability of data related to exposure in time to environmental factors like temperature, light, humidity, cross-storage, etc., can be used to calculate or at least reason about the quality of a product related to, e.g., remaining shelf-life, optimal usage, and eventually changes in where to deliver certain goods. These data can at the same time provide a quality certification for the buyer of the product as well as providing information for decision support relevant for where and when to use/ship the product.

Analytical and other methods that analyse the actual product can provide detailed information about the expected state or origin of the product. Later analysis can be used to re-certify that the product has not been tampered with, replaced by another product, or have had a rapid decrease in quality because of environmental exposure.

Automated data capture and decision support can be used as tools for assessing quality in more or less real-time, giving an instrument for improvement and optimisation relevant to supply-chain management, pricing, marketing etc.