We refine critical context from deep data pools through expert techniques and intensive analysis
The breadth and depth of information relating to foreign direct investment (FDI) is vast and complex.
Collecting and analysing this information requires a rigorous and robust methodology, especially to determine whether data is contextually important or redundant.
The breadth and depth of information relating to foreign direct investment (FDI) is vast and complex.
Collecting and analysing this information requires a rigorous and robust methodology, especially to determine whether data is contextually important or redundant.
Methodology
Data Gathering
We gather data from verified sources such as UNCTAD, FDI Markets and World Bank Group.
Data Analysis
We apply data reduction techniques including Factor Analysis and Principle Component Analysis.
Score Generation
Post-analysis, our rich algorithms organically generate the scores for each country.
Index Production
Our software automatically compiles country scores into an index and ranks them in order.
Proprietary indexes
Our unique methodology forms the backbone of all our proprietary FDI indexes, such as our flagship Global FDI Attractiveness Index.
Multiple data reduction techniques, such as Exploratory Factor Analysis (EFA), were used to remove any redundancies and duplications which may exist between correlated variables.
This highly analytical approach yields greater contextual information and more accurate results for our indexes.
Customised indexes
We can develop customised FDI indexes based on investor objectives, inputs and historical performance.
This is achieved by applying AI-driven automated machine learning (AML) processes to primary and secondary external data, as well as the internal data provided by your organisation.
Where AML processes are not possible or plausible, we can apply alternate data reduction techniques such as Principle Component Analysis (PCA).
Interested in our
methodology?
Drop us a line.
