The COIN Tool is easier to use on a larger screen. It makes use of freezing some rows and columns to show the data in context. However, on a laptop this may leave only a small corner of the window available for inspecting the data.

To help this, either:

• Hide rows and columns by selecting a (range of) column(s)/row(s), right clicking and selecting “Hide”. You can un-hide by selecting the range of rows/columns in which the hidden rows/columns are, right-clicking and selecting “Unhide”.
• Shrink rows/columns by simply dragging them and making them smaller.

The COIN Tool is built in Excel in order to be accessible to the widest range of users, and also aims to provide maximum flexibility in accommodating many different possible composite indicator structures and methodological approaches. This combination results in a large Excel file, which can be slow to work with due to its size and the way that Excel works.

To make the COIN Tool experience as user-friendly as possible, we recommend that you disable automatic workbook calculation. This is done as follows:

• Go to the “File” menu
• Go to Options -> Formulas -> Workbook calculation and set to MANUAL

This will make the COIN Tool much faster to use, but remember to manually re-calculate formulas when needed by pressing F9, or the "Calculate" button in the bottom left of the screen.

Go back to the Database tab. Check that you have entered a code for every level (sub-pillar, pillar, sub-index, index), for every indicator. Any deviations (e.g. “p.1” instead of “p.01”) will cause errors. See Section 3.1 and Box 1 for more details.

Also if you are copying in names from other spreadsheets, be extremely careful you are not copying in merged cells, as this may paste over hidden cells in the COIN Tool, and will cause the Framework tab to stop working.

This is probably due to an encoding error in the Database tab. Check that:

• Missing data is denoted as “n/a” (without the inverted commas), and nothing else
• Data is formatted as numbers and not text

Unit and indicator codes have not been altered from default values (“unit.xxx” and “ind.xxx”)

This is most likely due to an error in indicator definition - see previous point.

If the indicator tabs such as Winsorisation and IndCorrel work, but the tabs relating to aggregation (Rebalancing onwards) do not, this means you likely have an error in the specification of the indicator structure and/or weights. Check that:

• You have entered a code for every level (sub-pillar, pillar, sub-index, index), for every indicator. Any deviations (e.g. “p.1” instead of “p.01”) will cause errors. See Section 3.1 and Box 1 for more details.
• The weights have been specified for each indicator (Database tab) and aggregation level (Framework tab)

The direction has been specified for each indicator

The COIN Tool is “friendly-user” software: the user has to be friendly to the software, and careful to input values and parameters correctly, otherwise errors easily ensue.

If there are unfixable errors (after trying the solutions above), it is likely that you have either:

• Altered cells that are not meant to be altered (any cells not light blue or turquoise)
• Deleted or added the cells themselves rather than the contents
• Entered data or parameters in a way that does not follow the instructions of the manual (see previous points, and carefully re-read particularly the instructions in Section 3).

If you can’t find your error, it may be easier to start again with a clean version of the COIN Tool. If errors persistently occur, there may also be a bug - please contact jrc-coin@ec.europa.eu if you think this is the case.

The COIN Tool is available at K4P project page

COIN is an abbreviation of “Composite Indicator”. COIN is also the abbreviated name of the European Commission’s Competence Centre for Composite Indicators and Scoreboards, at the Joint Research Centre, which created the COIN Tool.

See Section 1.3 for an example of some usage cases. At an absolute minimum, you need to specify your index in the Database and Framework tabs. We always recommend to check your data in the Statistics, Winsorisation and TreatedData tabs, and to check relationships in the IndCorrel tab. You may then see your scores in the Heatmap, Scores and Rankings tabs.

• Data coverage: A rule of thumb is at least 65% data for every unit and indicator. Anything less than that, and you should consider removing indicators or units, unless there are compelling reasons not to. Imputation is effectively informed guesswork, so more data coverage is always better.
• How many indicators: There is a balance between including many indicators to try to fully cover the concept, and having a streamlined framework with good data coverage and easy interpretation. Typically, a framework might include 30-40 indicators and still be easy to interpret. Consider that each indicator represents a chunk of information, and there is only so much information that can be packed into a single number (your index), so as the number of indicators increases, the amount of information retained in the final score from each indicator will decrease. This is why it is better not to build a very large framework, unless you do not intend to aggregate all indicators to a single index. On the other hand you should also be careful to include enough indicators to give a reasonable picture of the overall concept.
• Number of aggregation levels: This should be defined by breaking down the concept you are trying to measure into dimensions and sub-dimensions. Many frameworks simply consist of two aggregation levels: indicators -> pillars -> index. Complex frameworks may make use of all four aggregation levels of the COIN Tool. It is quite rare in practice that an index exceeds four aggregation levels.
• Which aggregation and normalisation method to use: The default methods here are the arithmetic average and the min-max normalisation method respectively. These are the easiest to understand and communicate. We would recommend to depart from these only if there is a good reason to do so.
• Skewness and kurtosis thresholds: The recommended thresholds are 2 and 3.5 respectively, which represent a roughly normal distribution. See Box 4 for more information.
• How many points to Winsorise: This should be taken in context of how many units you have. If you have 100 units and you Winsorise five, this is only 5% of the total and should have a small impact on the overall distribution. If you only have ten units and you Winsorise five, this has a much larger impact. Caution should be exercised in particular when Winsorising more than 10% of the total number of units.

Visit our website at Knowledge for Policy where you can a number of resources on methodology, including the Handbook on Constructing Composite Indicators: Methodology and User Guide, many reports and audits, and academic papers.

We also organise the following events:

• An annual training course and community of practice on composite indicators (“JRC Week on Composite Indicators and Scoreboards”) - see the Events page on our website
• COIN Open days (see COIN Open Days on our website), where organisations are able to come to the JRC in Ispra and receive feedback and assistance their composite indicator from the COIN team
• Ad-hoc training on request, subject to availability

Please contact jrc-coin@ec.europa.eu for further information.

Please cite the User Guide as: Becker, W., Benavente, D., Dominguez Torreiro, M., Moura, C., Neves, A., Saisana, M., Vertesy, D., COIN Tool User Guide, 2019, ISBN 978-92-76-12385-9, doi:10.2760/523877