Line chart

Hi NimaiAhluwalia 

Yes, this is possible, but the decision point needs two calculated coordinates:

X position: the negative value of Decision Point, because the chart uses days before the forecast period. For example, a decision point of 56 should be plotted at -56.
Y position: the forecast accuracy at that specific point on the line.

Because the available accuracy values are only at -90, -60, and -30 days, the Y value normally needs to be calculated using linear interpolation.

For example:

Decision Accuracy =
VAR X =
-'Forecast'[Decision Point]

VAR Y90 =
'Forecast'[Forecast Accuracy - 3 month ahead]

VAR Y60 =
'Forecast'[Forecast Accuracy - 2 month ahead]

VAR Y30 =
'Forecast'[Forecast Accuracy - 1 month ahead]

RETURN
SWITCH (
TRUE (),

X >= -90 && X <= -60,
Y90
+ DIVIDE ( X + 90, 30 )
* ( Y60 - Y90 ),

X > -60 && X <= -30,
Y60
+ DIVIDE ( X + 60, 30 )
* ( Y30 - Y60 ),

X > -30 && X <= 0,
Y30,

BLANK ()
)

The last condition requires a business decision. For decision points later than 30 days before the forecast, such as 15 or 5 days, you must decide whether to:

keep the one-month accuracy value, as in the example above, or
extrapolate using the slope between the two-month and one-month values.
Native Power BI approach

I would use two aligned line charts:

The first chart contains the normal accuracy lines at -90, -60, and -30.
The second chart contains only one point per country:
X-axis: -[Decision Point]
Y-axis: Decision Accuracy
Legend: Country

Add error bars to the second chart using small upper and lower bounds:

Decision Lower =
[Decision Accuracy] - 0.004

Decision Upper =
[Decision Accuracy] + 0.004

This assumes the percentage is stored as a decimal, such as 0.84. If it is stored as 84, use approximately 0.4 instead.

In the Analytics pane:

Add error bars by field.
Use Decision Lower and Decision Upper.
Set the relationship to Absolute.
Match the error-bar color to the series color.
Hide the regular marker, axes, gridlines, background, and legend on the helper chart.
Give both charts exactly the same X- and Y-axis minimum and maximum values, and place the helper chart over the original chart.

Power BI supports field-based upper and lower bounds and formatting of error-bar width and endpoint markers.

Do not add the decision points directly to the original line series. For countries whose decision point is later than -30, Power BI would extend the line from -30 to the decision point, which is not what the example shows.

For a more robust solution, I would use Deneb and layer:

a line mark for forecast accuracy;
a short vertical rule mark for each decision point.

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