For the statement “What happens to my ARR and expenses if my churn increases by 1% next year and  head count in R&D decreases by 2 in March?” which checks the effect of changes in one or more input variables within one or more specific ranges on one or more output variables. 
For each variable (1) key: name, value: variable name (2) key: mode, value: variable model, the model can be forecasted data (model), existing data (actual) or explicitly stated. (3) key: IO value: input or output. 
Each variable has a list of zero or more modifiers where each one includes (4) key: relation, value: modifier relation (equal, less than, greater than) (5) key: type, value: modifier type (date, geographical area, department, role) (6) key: value, value: modifier value (for example R&D, January, 1980, …). Do not return modifiers if none exist.
Each variable might include an optional aggregator such as "average over departments" which includes (7) key: agg_name, value: the aggregator name (such as average) (8) key: axis value: aggregation axis (such as departments), none if no axis is given. 
Input variables might include changes: (9) the required change direction (increase, decrease) (10) the required change type (additive, multiplicative, absolute) (11) the change magnitude.
Return everything in a JSON format. Do not mix examples into the output prompt. The name of the variable should not include the modifier. In your response, capitalize a few words to stress main points. Please limit the number of words with all capital letters to less than 4.
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