__STYLES__
This project provides an analysis for a large insurance company who are due to undergo an internal audit with regards to their complaint’s procedure.
Total Complaints = COUNTROWS( VALUES( ComplainsData[ID]))
Complaints with Satisfied Customers =
CALCULATE( [Total Complaints],
FILTER(ComplainsData, ComplainsData[Satisfaction Level] = "satisfied"))
Total Urgent Complaints =
COALESCE(
CALCULATE( [Total Complaints],
FILTER(Priorities, Priorities[Description] = "Urgent")),
0)
Avg Complaints Duration = AVERAGEX( ComplainsData, ComplainsData[Complaint Duration])
Open Complaints =
COALESCE(
CALCULATE([Total Complaints],
FILTER(Statuses, Statuses[Description] <> "Closed")),
0)
Closed Complaints =
COALESCE(
CALCULATE([Total Complaints],
FILTER(Statuses, Statuses[Description] = "Closed")),
0)
% Closed Complaints =
DIVIDE( [Closed Complaints], [Total Complaints], 0)
Cumulative Complaints =
CALCULATE( [Total Complaints],
FILTER( ALLSELECTED( Dates),
Dates[Date] <= MAX( ComplainsData[ComplainDate]) ) )
Cumulative Complaints LM =
CALCULATE( [Total Complaints Last Month],
FILTER( ALLSELECTED( Dates),
Dates[Date] <= MAX( ComplainsData[ComplainDate]) ) )
Total Brokers =
COUNTROWS(
VALUES( Brokers[BrokerID]))
% of All Broker Complaints =
VAR AllComplaints = CALCULATE([Total Complaints], ALL(Brokers[BrokerFullName]))
RETURN
DIVIDE([Total Complaints], AllComplaints, 0)
Top 3 Brokers with Most Complaints =
VAR BrokerRank = VALUES(Brokers[BrokerFullName])
RETURN
CALCULATE( [Total Complaints],
TOPN(3,
ALL( Brokers[BrokerFullName]),
[Total Complaints]),
BrokerRank)
Distinct Customers Who Raised Complaints =
COUNTROWS(DISTINCT(ComplainsData[CustomerID]))
Here I used distinct customers who raised complaints instead of just total complaints divided by total customers, as it occurred to me that one customer may have raised more than one complaint.
Distinct % Customers Who Raised Complaints =
DIVIDE( [Distinct Customers Who Raised Complaints], [Total Customers], 0)