Step 2: Collecting the data

Collecting data can the most time-intensive step in the assessment. Therefore it is important to carefully consider which information you need to collect from the life-cycle actors.

2. 1. Choose quantitative or scales-based approach

It is possible to conduct a scale based or quantitative assessment:

Scales-based approach: Data are either qualitative e.g yes/no or quantitative (numerical)
Quantitative approach: Data are only quantitative (numerical)

This choice depends on different factors including:

The type of data that is required to support decision making: in case of assessing a single product and aggregated data is required to support the business , the scales-based is recommended since aggregating indicators into topic and single scores with the quantitative approach is only possible when comparing products or supply chains.
The type of data that is available and how the practitioner prefers to work: while most social data is qualitative, business who are familiar with product life cycle assessments are used to working with exact quantitative figures.

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2.2 Selecting social topics on basis of relevance

Whether or not to include all social topics in your assessment depends on the goal of the assessment. A distinguishment is made between a compact and a broad assessment

A compact assessment is intended for internal communication. It includes a strict selection of social topics, for example, the top 5 material social topics. Therefore a compact assessment demands less resources than a broad assessment. One limitation of a compact assessment is that it does not fully support comparing products, unless the list of social topics included in the assessments is the same.
A broad assessment can be used for external communication. It differs from a compact assessment by including all social topics proposed in the handbook. The documentation of a broad assessment also needs to be more detailed.

2.2. Define most relevant social topics and indicators

For a compact assessment the most relevant social topics will need to be identified. For example, some companies apply a filter-based risk assessment to determine relevance, with specific and overall risks being captured by a risk filter. Other companies define relevance based on materiality to prioritise topics based on importance for the business and stakeholder perception. Note that the handbook does not prescribe how relevance should be defined.

Check the relevance of the performance indicators, as these are not always applicable to all life-cycle actors. Where not applicable, evidence needs to be provided and documented in the assessment. Data for a performance indicator should be collected only from stakeholder groups which have been determined as relevant.

Example scale-based case study | The company wants to use the results for external communication therefore a broad assessment needs to be conducted in which all social topics were taken into account. The worker indicators such as wages were identified as not being relevant for the stakeholder group consumers and the consumer indicators such as experienced well-being were identified as not being relevant for stakeholder groups workers and communities. Download the case study

2.3. Collect data

Data can now be collected per performance indicator and for each life-cycle stage using data collection questionnaires . For the quantitative approach data should be collected by working hour, but otherwise by the value generated (e.g. $ or €) or by mass (e.g. ton).Two questionnaires for data collection have been created for the scale-based and quantitative approach, which can be used for the data collection.

Before sending out the questionnaire,it is crucial to create awareness internally and externally on why you are conducting the assessment and what effort is needed from your internal departments and suppliers.We have developed a general introduction which can support companies in creating internal and external awareness.

A practical problem is that value-chain actors can provide generic data across an entire company whilst the company produces different products in different locations. Therefore for the quantitative approach, if necessary, quantitative data should be allocated to the specific product. If needed, allocate general data to product level.It is preferable to gather data specific to a given product

When the data comes back it is important to assess the quality of the data. A data quality matrix to assess the quality of the data is available here.

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