Lucent Technologies CentreVu Call Management System Release 3 Version 5 Manual

							  Trunk Performance Report CentreVu CMS R3V5 Forecast  585-215-825
Trunk Performance Report Example5-7
Table 5-1:  Trunk Performance Report Description
Report Heading What It Means
ACDThe ACD of the trunk group(s) in the report.
PrintedThe date and time the report was run.
__ to __The start and stop dates of the historical data 
CentreVu CMS used in the 
report.
Trunk Group No. 
NameThe number and name of the trunk group(s) included in the report.
Avg/Use TrunkThe average number of seconds each trunk in the trunk group was in use 
during the average busy intrahour interval.
Busy Interval CCSThe Centum Call Seconds (CCS) for the trunk group during the average 
busy intrahour interval. CCS is the number of 100-second increments in 
which the trunk was busy during the intrahour interval.
Usage Rate 
(Erlangs)The average number of trunks that were seized at any point in time 
during the busy interval.
Estimated Blocking 
(%)The estimated percentage of incoming ACD calls, during the busy 
interval, that were blocked because all trunks in the trunk group were 
busy.
Objective Blocking 
(%)The objective blocking percentage specified in the trunk groups profile. 
Actual Number 
TrunksThe actual number of trunks in the trunk group on the last day in the 
specified time period.
Estimated Trunks 
RequiredThe number of trunks the trunk group should have had to make the 
Estimated Blocking % equal the Objective Blocking%.
Days UsedFor each trunk group, the number of days in the specified time period 
where the number of trunks equaled the number of trunks on the last day 
of the time period.
Days ExaminedThe total number of days in the time period.
Incomplete Busy 
IntervalsIf incomplete data has been considered in the calculation, this is the 
number of busy intervals used in the calculation which are marked 
incomplete. If incomplete data was not considered, this number will be 0. 
						

							  Trunk Performance Report CentreVu CMS R3V5 Forecast  585-215-825
Trunk Performance Report Example5-8 
						

							  How the Forecast System Generates Data CentreVu CMS R3V5 Forecast  585-215-825
General Information6-1
6 How the Forecast System Generates Data
General Information6
This chapter describes how the Forecast subsystem generates the data for a 
forecast. Algorithms are included for the following:
l“Call Volume/Agents Forecast Reports” 
l“Requirement Reports” 
l“Trunk Performance Report” 
This information is provided to help you understand forecasting. 
						

							  How the Forecast System Generates Data CentreVu CMS R3V5 Forecast  585-215-825
Call Volume/Agents Forecast Reports6-2
Call Volume/Agents Forecast Reports6
This section includes all of the algorithms used for Call Volume/Agents 
Forecast Reports. For the 
CentreVu™CMS to use the algorithms for 
forecasting, you must first define the following types of information: 
lWhich dates of data to use
lWhich forecast method to use.
Algorithm for 
Current and 
Seasonal Data 
Points
6
Forecasting uses algorithms to find data points. A data point is a day of 
historical data and can be current or seasonal. These data points are 
used in calculations. The Call Management System calculates the 
algorithms for you, so you will see only the results. You can vary the 
results you get by changing the information in the report input windows. 
Refer to the timeline below as you go through the steps of the algorithm 
and encounter the different variables (for example, C1, S0, etc.).
Current Data Points6Figure 6-1 describes which dates of data to use for the current data 
points.
Figure 6-1:  Current Data Points Graphic Example
current 
data todayforecast
day
C4 C3 C2 C1 C0
xxxy
z
Time (days or weeks)
x = 1 or 7 days (Number of days between historical data points)
y = days from today to C1
z = days from today to forecast day 
						

							  How the Forecast System Generates Data CentreVu CMS R3V5 Forecast  585-215-825
Call Volume/Agents Forecast Reports6-3
You use Current Data Points for all of the Call Volume/Agents Forecast 
Reports based on historical data. The system does the following:
1. Gets todays date
2. Determines the day-of-week of the forecast day
3. Calculates the number of days from today to the forecast day (z)
4. Assigns X for the value of the number of days between historical 
data. Acceptable values are 1 or 7
5. Finds the most recent historical day (C1) and the number of days 
from today to that day (y) as follows:
a. If the number of days between each data point is 1 (x = 1), then 
C1 is yesterday and y = 1.
b. If the number of days between each data point is 7 (x = 7), then 
C1 is the most recent historical day which is the same day-of-
week as the forecast day. “y” is the number of days from today 
to C1.
6. Finds the remaining historical days C2, C3, and C4.
a. C2 = C1 - x
b. C3 = C2 - x
c. C4 = C3 - x. 
						

							  How the Forecast System Generates Data CentreVu CMS R3V5 Forecast  585-215-825
Call Volume/Agents Forecast Reports6-4
Example 1: Current 
Data Points
6
Assume that today is 5/24/97 and you have entered the following 
parameters for a report:
l6/1/97 as the forecast date
l1 as the number of days between historical data points
lCurrent trending.
The current data points are determined as shown below.
Figure 6-2:  Current Data Points Example= today
= current data points (C1 = 5/23, C2 = 5/22, etc.)= forecast day
T
11
18
25W
10
17
24
31 T
9
16
23
30 M
8
15
22
29 S
7
14
21
28S
6
13
20
27F
12
19
26MAY 1997T
8
15
22
29W
7
14
21
28 T
6
13
20
27 M
5
12
19
26 S
4
11
18
25S
3
10
17
24F
9
16
23
30JUNE 1997
123
4512 
						

							  How the Forecast System Generates Data CentreVu CMS R3V5 Forecast  585-215-825
Call Volume/Agents Forecast Reports6-5
Seasonal Data Points6Figure 6-3 shows which dates of data to use for the seasonal data points.
Figure 6-3:  Seasonal Data Points Graphic Example
If seasonal trending is used, the algorithm continues:
7. Gets the seasonal trend base date.
8. Finds season day S0. S0 = seasonal trend base date + z.
9. Finds the closest seasonal day S1. S1 = seasonal trend base 
date -y
10. Finds the remaining seasonal days S2, S3, and S4.
a. S2 = S1 - x
b. S3 = S2 - x
c. S4 = S3 - x.
Number
of Calls
Carried
(NCC)seasonal seasonal trend
base dateseason
daycurrent 
data todayforecast
day
S4 S3 S2 S1 C4 C3 C2 C1S0 C0
Time (days or weeks)
x = 1 or 7 days (Number of days between historical data points)
y = days from today to C1
z = days from today to forecast daydata
x x x y z xxx y z 
						

							  How the Forecast System Generates Data CentreVu CMS R3V5 Forecast  585-215-825
Call Volume/Agents Forecast Reports6-6
Example 2: Seasonal 
Data Points
6
Assume that today is 5/28/96, and you have entered the following 
parameters for a report:
l6/5/97 as the forecast date
l7 as the number of days between historical data points
lSeasonal trending with the base date = -364.
The current and seasonal data points are determined as shown below:
Figure 6-4:  Seasonal Data Points Example= seasonal trend base date
= seasonal data points= season day
= today
= current data points= forecast day
(S1=5/23, S2=5/16, etc.)
(C1=5/22, C2=5/15, etc.)
T
12
19
26W
11
18
25 T
10
17
24 M
9
16
23
30 S
8
15
22
29S
7
14
21
28F
13
20
27MAY 1996T
9
16
23
30W
8
15
22
29 T
7
14
21
28 M
6
13
20
27 S
5
12
19
26S
4
11
18
25F
10
17
24JUNE 1996
234
562
3 1
1
31
T
11
18
25W
10
17
24
31 T
9
16
23
30 M
8
15
22
29 S
7
14
21
28S
6
13
20
27F
12
19
26MAY 1997T
8
15
22
29W
7
14
21
28 T
6
13
20
27 M
5
12
19
26 S
4
11
18
25S
3
10
17
24F
9
16
23
30JUNE 1997
123
4512 
						

							  How the Forecast System Generates Data CentreVu CMS R3V5 Forecast  585-215-825
Call Volume/Agents Forecast Reports6-7
Algorithm for 
Forecast Calls 
Carried
6
This section includes all of the algorithms used to calculate Call 
Volume/Agent Forecast Reports:
l“Forecast Methods” 
l“Algorithm for FCC Intraday” 
l“Algorithm for FCC Special Days” 
l“Algorithm for Number of Agents Required” 
l“Algorithm for Estimated Margin.”
Forecast Methods6This algorithm computes the Forecast Calls Carried (FCC) for each 
intrahour interval in the following reports:
lLongterm
lFinancial
lCurrent Day
lHypothetical
lHypothetical Financial.
The algorithm computes the FCC using one of four forecast methods:
lNo trending (weighted average of data)
lSeasonal trending
lCurrent trending
lExpected calls.
The algorithm for each forecast method is presented on the following 
pages.
NoteThe expected calls method is not applicable for Current Day 
reports, and seasonal trending is not applicable for Hypothetical 
reports. 
						

							  How the Forecast System Generates Data CentreVu CMS R3V5 Forecast  585-215-825
Call Volume/Agents Forecast Reports6-8
No Trending (Weighted Average of Data): 
1. Find the Weighted Average of Calls Carried (WACC) for the current 
data.
a. Multiply the Number of Calls Carried (NCC) in each intrahour 
interval for historical days C1 through C4 by the assigned data 
weights.
b. Add the weighted data together, and divide that sum by the 
sum of the individual weights.
The equation for WACC is as follows:
where 
W1 through W4 are the corresponding data weights.
2. Divide the Change Factor (CF) by 100. For example, if the CF were 
100, this step would produce a value of 1.
3. Multiply the factors found in the previous two steps to get the FCC 
for each intrahour interval.
WACCW1xNCCC1()W2xNCCC2()W3xNCCC3()W4xNCCC4() +++
W1W2W3W4+++ -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- =
FCCWACC ()CF
100 ----------[]=