Organizational Chart Data to Hierarchy Data - table provided

Hi , rhaddad87 

Here are the steps you can refer to :
(1)We need to convert our table in Power Query Editor, you can put this code in "Advanced Editor" in your Power Query:

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45W8k3MS0xPLVLSUQpILUrLL8pFCBgpxepEK7nmFuTkV6amAgUQUgYoUkZY5DBM86nMywNShmBZKAfCjwUA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Name = _t, #"Reports To" = _t, #"Number of Direct Reports" = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"Name", type text}, {"Reports To", type text}, {"Number of Direct Reports", Int64.Type}}),
    #"Removed Columns" = Table.RemoveColumns(#"Changed Type",{"Number of Direct Reports"}),
    #"Added Index" = Table.AddIndexColumn(#"Removed Columns", "Index", 0, 1, Int64.Type),
    #"Removed Columns1" = Table.RemoveColumns(#"Added Index",{"Index"}),
    #"Added Index1" = Table.AddIndexColumn(#"Removed Columns1", "Index", 1, 1, Int64.Type),
    test = Table.ReorderColumns(#"Added Index1",{"Index", "Name", "Reports To"}),
    #"Added Custom" = Table.AddColumn(test, "Custom",  (x)=>if List.IsEmpty(Table.SelectRows(test,(y)=>y[Name]=x[Reports To])[Index]) then null else Table.SelectRows(test,(y)=>y[Name]=x[Reports To])[Index]{0} ),
    #"Removed Columns2" = Table.RemoveColumns(#"Added Custom",{"Reports To"}),
    #"Changed Type1" = Table.TransformColumnTypes(#"Removed Columns2",{{"Index", type text}, {"Custom", type text}})
in
    #"Changed Type1"

The result table is like this:

(2)We can apply data to Power BI Desktop, then we need to click "New Column" to create two calculated columns in Power BI Desktop:

Path = PATH('Table'[Index],'Table'[Custom])

Rank = PATHLENGTH('Table'[Path]) -1

(3)Then we can meet your need  , the result is as follows:

If this method does not meet your needs, you can provide us with your special sample data and the desired output sample data in the form of tables, so that we can better help you solve the problem.

Best Regards,

Aniya Zhang

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