Often more data ends up complicating the decision making process rather than making it easier. Multiple variables presenting conflicting views has become disturbingly common. Similarly, not all measures are created equal. There are serious downsides of failing to account for data generating processes of these series. Our flagship data product, Data Significance index, is produced as a set of self-contained series designed to deliver definitive information about respective topic.
Empirical Foresight provides several iterations of value-addition to the raw data. Data Significance indexes are released as monthly, quarterly & yearly series and are organised based on various classification categories. The indexes combine available measures by employing detailed harmonisation, weighting & other mathematical techniques. We have automatic triggers to test & ensure that the indexes exhibit the expected behaviour based on their original components.
The publications usually contain tables, charts, background notes, comparative analysis and few interesting visualisations to highlight the implications.
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