Export Data Evaluation

Introduction

This export in Excel format contains per data evaluation subject (which can also be found in the dashboard) various fields that are used to calculate the total Data Evaluation. This concerns the evaluation in the data language that's currently chosen by the logged in user.

Using this export, together with the technical settings (in XML format or in Excel format), the data evaluation can be recalculated.

The page below explains in detail how this data is calculated.

The data evaluation can be exported from two different pages using the Export button

in EZ-web:

1. In Suppliers tab. From this page, the Export button exports the data evaluations of all currently visible suppliers for which there is authorization horizontally (one column per field: the subjects can be found in the column headings). Click here for an example.

2. In the Dashboard. From this page, the Export button exports the data evaluation of this one supplier vertically (per field one row: the subjects are found per line in the first column). Click here for an example.

A lot of data is needed to achieve the correct calculation, which is why this export is less easy to read. Looking for a clear roadmap on how to improve data evaluation as a supplier? Or curious about which elements a supplier can improve the data as a customer?

Then use the export data evaluation Advisory Report.

The decision was made to display rounded numbers to increase readability. As a result, the weighting may not exactly match the technical settings.

The choice was made to display the figures rounded to increase readability. As a result, the weighting may not exactly match the technical settings.

Rounding may also cause the same weighted average to result in a different number of stars. For example, the weighted average of unrounded 3.249 or 3.2501 are both rounded 3.25. However, in the first case, 3 stars will be colored yellow and in the second case 3.5.

LowerLimit and TopLimit

The premise of the rating calculation is that the number of stars is determined first for each subject.

For each subject, a minimum (LowerLimit) and a maximum (TopLimit) are determined. These can be found in the technical settings in XML format or in Excel format.

The Lower and TopLimit can be an absolute value or percentage of a related value (RelatedData).

The LowerLimit can be higher than the TopLimit: for some topics, a low number or percentage is desired (such as Latest Article Import or Missing Available Articles).

Then the following applies:

LowerLimit: if a topic is equal to or greater than this limit in number or percentage, the supplier will receive no stars for this topic.
TopLimit: if a topic is smaller or equal in number or percentage than this limit the supplier receives 5 stars for this topic.

While for another topic, a higher value results in more stars (e.g. articles with specification). Then the following applies:
LowerLimit: if a topic is equal to or less than this limit in terms of number or percentage then the supplier will receive no stars for this topic.
TopLimit: if a topic is larger or equal in number or percentage than this limit the supplier will receive 5 stars for this topic.

If the supplier's number or percentage is between the LowerLimit and TopLimit, it will count proportionally.

For example: a supplier has delivered 90% of the articles with a GTIN. The LowerLimit=80, the TopLimit=100. The supplier will score 2.5 stars for this article.

If a supplier has delivered 80% then the score will be 0.

RelatedData

When percentages are calculated by topic, the _value is plotted against RelatedData. This can be found in the Export Data Evaluation in the second _value field per topic (see below {Subject}_{RelatedData}_Value). Which RelatedData is used per topic can be found in the technical settings in XML format under RelatedData.

Often these are the AvailableArticles as found in the General tab (listed in the RelatedData as AvailableArticles). But sometimes other RelatedData are used.

This enables to determine per classification for which articles an evaluation is important and which articles are excluded because this evaluation does not matter for these articles. If this is the case, RelatedData states which classifications are then used.

See Classification tab, second section "Articles in classification with mandatory data" where this is explained in detail.

RelativeWeight

Once the number of stars for each subject has been determined, the weighted average can then be calculated.

A weighting is set for each subject: the RelativeWeight. This can be found in the technical settings in XML format or in Excel format under RelativeWeight. This can be used to calculate the multiplier for evaluating a specific subject of a vendor:

divide the RelativeWeight by the sum of all RelativeWeights¹.

¹It may happen that a subject is not applicable at all for a supplier. For example, if a supplier is not normalized for some reason. The topic will not be included in the weighted average (in the sum of all RelativeWeights).

Also, if RelatedData is 0, it means that for this supplier this topic is not important and will not count in the weighted average. For example, if a supplier has no articles where certificates are important.

If a topic does not count, this can be seen in the Export Data Rating: these cells are empty (not to be confused with 0, in which case the topic is counted). Because of this, weightings for suppliers can be different.

Field descriptions

The field descriptions, present in the first row for a horizontal export and in the first column for a vertical export:

Relation

Name supplier

GLN

GLN supplier. This is sorted by the horizontal Data valuation export.

TotalEvaluation

Final Score: the weighted average of all data evaluations per topic rounded to two decimal with a value between 0 and 5. This rating is displayed in stars in various screens.

It is calculated by summing the _TotalEvalutionPart of all subjects.

TotalWeight

The sum of all RelativeWeight of the subjects, applicable to this supplier

{Subject}_Value

{Subject}_{RelatedData}_Value

{Subject}_Evaluation

{Subject}_TotalEvaluationPart

{Subject}_TotalEvaluationToGain

Four or five fields are present for each dashboard topic that counts in a vendor's data rating.

{Subject}:

These are the topics that count in the data rating for this vendor.

Click on the description for an explanation of this topic and a step-by-step plan to achieve the maximum score for this topic if you haven't already.

For all of the above topics, the following columns are present or may be present:

_Value	The value of the subject being counted with. If there is only one _Value per topic (i.e., if there is no _{RelatedData}_Value listed with this topic) then it is an absolute number and the Lower- and TopLimit will also be absolute.
_{RelatedData}_Value	Optional. This contains the RelatedData used to calculate for this topic for this vendor. If there is a second _Value for the same subject then a percentage is calculated using the two _Value fields. The Lower- and TopLimit are then also percentages. For each subject, it is indicated if RelatedData data is calculated and what the RelatedData means: for example, "Articles with Logo" (ArticlesWithLogo_Value) versus the "Available articles" (ArticlesWithLogo_AvailableArticles_Value). The percentage for this topic is calculated as follows: "_Value" / "_{RelatedData}_Value" x 100.
_Evaluation	The unweighted rating of this particular topic where 5 is the highest attainable. This shows what the score is on this subject. To determine this, the _Value (if this is an absolute number) or the percentage calculated using _{RelatedData}_Value is compared to the Lower- and TopLimit. See above for how this works. The number that rolls out of this is the _Evaluation of this topic.
_TotalEvaluationPart	The weighted rating of this particular subject: how much does this topic contribute to the final score (TotalEvaltuation) at this moment. This is calculated as follows: ("_Evalution" x RelativeWeight for this topic) / the sum of all RelativeWeights that count for this vendor. The TotalEvaluation is calculated by adding up all the _TotalEvaluationPart.
_TotalEvaluationToGain	This is the section of the total of 5 stars (TotalEvalution) that have not yet been achieved with this topic and can be improved. When all subjects the _TotalEvalutionToGain is added to the TotalEvaltuation the result is 5: the maximum score in stars.