Analyze the Data

Are you ready to find some meaning in this data mayhem?

Let’s get you familiar with the structures and tools available on WikiRate to help you identify patterns and share your insights with the WikiRate Community and beyond!

Standard Research Metrics


Answers to standard research metrics are entered either individually via research projects or in bulk by imports. All researched answers must cite a public source and can be verified (checked) by other users. 

The standard Answer structure on WikiRate is:

Data Structure Image

These are the most granular form of the data on WikiRate and are the building blocks for analyses.

Want to design your own Standard Research Metric to capture data that is missing on WikiRate? Check out this step-by-step guide.

Calculated Metrics


On WikiRate, Calculated Metrics let you run all kinds of calculations and functions based on data from other Metrics. Just like in Excel or Google Sheets, you can use formulas to arrive at many other helpful values and find interesting insights.

We know this can be complicated, so don't hesitate to reach out to us if we can help.

Score Metric


A Score Metric standardizes the answers of another metric to a 0-10 scale. Simply put, you assign a maximum of 10 points to the different answer options of another metric, which can form the basis for any kind of rating.

For example:

Answer type

Number

Money

Category

Multi-Category

Data example

Greenhouse Gas Emitted 

(metric tonnes)

Corporation tax paid

(USD)

Supplier list disclosed

Whistleblowing mechanism(s) provided

Score example

0-100k = 10 points

101-200k= 9 points

201-300k= 8 points

301-400k= 7 points

401-500k= 6 points

501-600k= 5 points

601-700k= 4 points

701-800k= 3 points

801-900k= 2 points

901k > = 1 point

Unknown = 0 points

< 0 = 0 points

0-1mln = 2 point

1.1-100mln = 4 points

101-1bln = 6 points

1.1-10bln = 8 points

10.1bln > = 10 points

Yes = 10

Partial = 5

No = 0

Hotline = 2.5 points

Email = 2.5 points

Anonymous portal = 3.5 points

Focal point = 1.5 points

None of the above = 0 points

 

To create a Score Metric:

  • Select the “Calculations” tab on the page of the Metric you want to Score

  • Click the “Add new score” button. Make sure to check the Score you intend to create does not already exist!

  • Formulate the question that your Score aims to answer

  • Add any relevant Topics tags

  • Explain in the About section, the logic for scoring the Metric answers in this way

  • (optional) If your Score applies exclusively to a select number of Years or a specific Company Group add those

  • (optional) If you are not ready for this Score to be public you can set it to be “unpublished” and simply update that field to “publish” once it’s ready. Do note, that it will not be possible for other users to see or use this Score until it has been published

  • Finally click “Submit”.

 

Once the Score metric has been created, you can now specify what points you want to assign to the different Answer options.

Click the edit icon next to the Formula field.

For a metric with Category or Multi-category answers you can now enter the points in the value fields next to the corresponding answer options.

Note: if you want all answer options to be worth the same amount of points, you can tick the “equalize” box.

For a metric with Number or Money answers you can now enter the Formula that determines the answer intervals and corresponding points. 

Note: A score’s name is formed by adding the name of the scorer (user, Company or Research Group) to the end of the scored metric.

WikiRating


A WikiRating is a 0-10 rating computed as a weighted average of other 0-10 answers. To create a WikiRating, a number of Score or other WikiRating metrics are selected and assigned weightings.

For example, this WikiRating was designed by Fashion Revolution as part of the Fashion Transparency Index and rates a number of Standard Metric Answers that capture the company's approach to purchasing to create a purchasing practices rating.

To create a new WikiRating, click the ‘Add Metric’ button on the Metrics browse page and select the ‘Calculated’ tab and then the ‘WikiRating’ sub-tab. Next:

  • Add a Metric title that concisely describes what the WikiRating captures

  • Formulate the question that your WikiRating aims to answer

  • Add any relevant Topics tags

  • Explain in the About section,  the logic for rating companies in this way

  • (optional) If your WikiRating applies exclusively to a select number of Years or a specific Company Group, add those.

  • (optional) If you are not ready for this WikiRating to be public you can set it to be “unpublished” and simply update that field to “publish” once it’s ready. Note that it will not be possible for other users to see or use this Score until it has been published.

  • Finally click “Submit

Once the WikiRating has been created, you can now specify what metrics you want to include in the rating and the weight of those metrics.

Click the edit iconnext to the Formula field.

To add the Score or WikiRating metrics that you want to include in your WikiRating, click the ‘+ add metric’ button and use the filters to search through the list of suggested metrics.

To select a metric, tick the box next to the metric on the left side of the selection pane.

Once selected, the metric will move to the right side of the selection pane. To de-select, simply click the tick-box once more.

When you have selected all the metrics you want to include, click the ‘Add selected’ button.

 

Note: At this point your selection has not yet been saved. Only once you have clicked ‘Save and Close’ is your selection stored.

Now that you have made your metric selection, you can specify the weight you want to assign to the different Metrics.

Note: if you want the answers to all Metrics to be valued equally, you can tick the “equalize” box.

 

Finally click the  ‘Save and Close’ button.

Descendant


A Descendant Metric inherits answers from one or more ancestor metrics. Descendant metrics are used to pool the data from a set of similar input metrics. 

For example, when there are several standards that are asking the same question, like ‘what is the percentage of Women on the Board’, a Descendant Metric can combine the data from these different standards so that we can compare companies across these otherwise separate datasets.

To create a Decendant Metric, click the ‘Add Metric’ button on the Metrics browse page and select the ‘Calculated’ tab and then the ‘Descendant’ sub-tab. Next:

  • Add a Metric title that concisely describes what the Descendant Metric captures

  • Formulate the question that your metric aims to answer

  • Add any relevant Topics tags

  • Explain in the About section,  the logic for rating companies in this way

  • Select the Value Type

Note: It is important that the Value Type of your input metrics is the same as each other and the same as the Value type of the Descendant metric. Is this not the case? Check out the Formula metrics guide for suggestions on how to convert a dataset to another Value Type.

  • (optional) If your WikiRating applies exclusively to a select number of Years or a specific Company Group add those.

  • (optional) If you are not ready for this WikiRating to be public you can set it to be “unpublished” and simply update that field to “publish” once it’s ready. Do note, that it will not be possible for other users to see or use this Score until it has been published.

  • Finally click “Submit

Once the Descendant Metric has been created, you can now specify which input metrics you want to combine.

 
  • Click the edit iconnext to the Formula field.
  • To add the Metrics that you want to include in your Descendant Metric, click the ‘+ add item’ button and use the filters to search through the list of suggested metrics.
  • To select a metric, tick the box next to the metric on the left side of the selection pane. Once selected, the metric will move to the right side of the selection pane. To de-select, simply click the tick-box once more.
  • When you have selected all the metrics you want to include, click the ‘Add selected’ button.

Note: At this point your selection has not yet been saved. Only once you have clicked ‘Save and Close’ is your selection stored.

Now that you have made your metric selection, you can specify the order in which you want the input metrics to be queried.

Note: Descendant metrics follow a data hierarchy. The input metric you list first will be queried first. If that metric does not have an answer for the company in question, it will query the next input metric. That also means, when multiple input metrics have an answer for the same company, the input metric that appears first in the list will take precedence.

  • Finally click the ‘Save and Close’ button.

Formula


Like all Calculated Metric types, Formula metrics derive answers dynamically from the answers to other metrics. Formula metrics give you the flexibility to create formulae directly, while other calculated metric types have an interface for creating a specific type of formula.

More on how to create Formula metrics and examples of commonly used formulas coming soon!

Relationship Metrics


Companies do not operate in isolation. They are connected to each other and their decisions are shaped by and impact those related. It is therefore important that we capture these relationships and begin to map these networks of companies.  

Relationship metrics describe the relationship between two companies. Unlike other metrics on WikiRate, they can have compound answers, consisting of one “relationship answer” per relationship.

An example is the Relationship metric Shareholder Of.

A list of existing Relationship Metrics can be found here.

If the type of company relationship that you want to capture on WikiRate does not yet exist, you can create a new Relationship metric.

To create a new Relationship Metric, go to Add Metric.

Select the ‘Relationship sub-tab and fill out the following fields:

    • Add the Metric title that concisely describes the type relationship that you want to capture, as well as the Inverse Metric title which is the inverse of that relationship (e.g. ‘Supplied by’, and ‘Supplier of’)

    • Formulate the question that your Metric aims to answer

    • Add any relevant Topics tags

    • Explain in the About section, why this relationship is important to capture

    • (optional) If your Metric applies exclusively to a select number of Years or a specific Company Group add those.

    • (optional) If you are not ready for this Metric to be public you can set it to be “unpublished” and simply update that field to “publish” once it’s ready. Do note, that it will not be possible for other users to see or use this Score until it has been published.

    • Finally click “Submit

At the moment, Relationship metric answers can only be imported. Check out this guide on how to do just that!

Network-aware Metrics


Besides that companies are connected to each other, they also have leverage over their business relations. It is therefore important that we can analyze their performance and impact across these relationships, and hold them accountable for the relations they engage in.

Network-aware metrics dynamically measure a company’s performance based on the performance of related companies (like suppliers, subsidiaries and brand partners), by combining Relationship Metrics with other metric types in formulae. 

An example of this would be the metric “Greenhous gas disclosure rate of investees” which looks at what percentage of companies in an investors portfolio have disclosed their greenhouse gas emissions. 

A list of existing Network-aware Metrics can be found here

More on how to create Network-aware metrics and examples of commonly used formulas coming soon!

Answer dashboard


The Answer Dashboard is the place where you can search and filter all Metric Answers available on WikiRate.

The header of each column (Companies, Metric, Answer, Year) lets you sort the data either ascending or descending.

Use the filters to display only the records containing the selected value from the chosen field.

answer dashboard image

Widgets


WikiRate Labs a site dedicated to sharing data experiments that WikiRate community members create using WikiRate data.

An experiment on WikiRate Labs can be any technical effort to generate something useful from WikiRate data.

With its open data structure and it’s RESTful API, WikiRate makes it easy to develop widgets: dynamic interfaces that function like a window through which your community can engage with a specific dataset or research topic.

Different types of widgets are possible such as search or data visualizations tools (graphs, charts, maps) and they can be tailored to an audience.

For example, the widget developed by Clean Clothes Campaign, that allows users to search for a factory and learn what brands it supplies. Live data comes directly via the WikiRate API!

 

Check out our current experiments, or add a new one here.