Trial value

When you request a free 90-day trial of Telko Manager® you are not only assessing your network performance and revealing cells with low QoS, but also your company is getting a fraction of these savings.

Savings in reducing the MTBR

There are three main sources of savings when you reduce the Mean Time Between Repairs (MTBR) to re-establish Quality of Service (QoS) as soon as possible. These revenue savings come from cutting down the following:

1. Yearly ARPU loss due to performance degradations

The number of cells with performance degradation reported per year is

, which can be calculated by multiplying (B) by 12.

Also, if we divide the number of active subscriptions (C) by the number of cells in the network (A), we'll obtain the average number of subscriptions per cell, which is

... (E).

Considering these results, the number of subscriptions affected yearly by performance issues is

×

=

... (F)

We have measured an average

7%

drop in voice and data usage during performance degradations, such as reduced accessibility, congestion, call drops and low throughput. If you have measured this consumption reduction due to low QoS in your network, you can change this number by clicking

The mean time to detect a performance degradation is

3 days

in most networks. Telko Manager® reduces this period to 0 due to its near real-time processing capabilities. If your average detection time is faster or slower considering your current team and their tools, you can change this number below.

The yearly ARPU loss due to performance degradations, which can be saved with Telko Manager®, is

.

Check the

for more details.

2. Revenue loss caused by cells without traffic

Due to transmission issues, coverage loss, hardware failures, among other causes, around

cells may lose traffic per month in a commercial network whose size is specified in (A). The amount of traffic loss is usually

70%

, while the remaining 30% is saved by neighboring cells. If you have statistics regarding cells with traffic loss in your network, you can change the suggested values by clicking

The revenue loss caused by cells without traffic, which can be saved with Telko Manager®, is

.

Check the

for more details.

3. Yearly revenue loss due to cancelled subscriptions

On a monthly basis

10%

of cells with performance issues are detected long after the degradation started. In those cases, we have measured a

1.3%

increase in cancelled subscriptions after 3 or more weeks of poor quality of service. If you have statistics regarding this effect in your network or would like to try different numbers, click

Every time a user cancels their subscription, half their Customer Lifetime Value (CLTV) is lost forever in average. To estimate this figure, we assume a

3%

monthly churn and negligible costs (in other words, we are interested in the lifetime revenue loss). Note, you can input your monthly churn below.

Then, the CLTV will be given by ARPU / monthly churn =

/

% =

... (M).

The yearly revenue loss due to cancelled subscriptions, which can be saved with Telko Manager®, is

.

Check the

for more details.

If we add up the three main sources of savings analyzed in this section, reducing the MTBR by using Telko Manager® can generate

annually.

Savings in finding previously undetected performance degradations

These are hidden cases to manual detection that our software will find. For this exercise we only consider the savings for expediting their detection and not the revenue loss already incurred by these cases. We estimate that Telecom carriers with plenty of resources and staff monitoring their network may not be finding 20% of all performance issues, while operators with unoptimized networks may have more than 30% percent of undetected cases. Feel free to adjust this number based on your current situation.

The savings in reducing the MTBR get increased by this percentage since more cells with performance issues will be detected and repaired in a shorter time. Therefore, the yearly savings in finding previously undetected performance degradations will be

%×

=

.

Productivity gain

By reducing the detection time of performance degradations, Telko Manager® allows engineers to focus on planning and optimization tasks, providing a valuable boost in productivity.

Remember that Telko Manager® does not charge per number of users, but for the number of cells under monitoring. So, feel free to input as many engineers as you believe will take advantage of this software.

Telko Manager® saves at least

2 hours

of manual analysis a day to every engineer who is responsible for a set of cells in your network. We assume that an engineer splits his working day between performance monitoring, optimization tasks and some planning. Nevertheless, you can change the following variable based on the amount of time your team spends on performance monitoring daily.

The hours saved in a year to all engineers is calculated as

×

×365×(5/7) =

, considering a five-day working week (5/7).

In order to estimate the value of this productivity gain, you can input the average hourly wage of an engineer in your company below.

Finally, the productivity gain will be

×

=

.

Call center complaints reduction

The proportion of mobile consumers with a reason to complain is

4%

according to an Ofcom Quality of Customer Service Research. However, the proportion of those who had a reason to complain who went on to make a complaint is

65%

. Furthermore, the most common reason to complain is poor service performance caused by network problems, which accounts for

67%

of all complaints. If you would like to use your own call center statistics, click

Let's assume the number of complaints your call center receives is proportional to the time it takes to solve a network problem, i.e. the sum of both the detection time and the repair time. Also, we'll consider that a repair takes in average

15 days

to be done after an issue has been detected. You may change this period next.

Since Telko Manager® can reduce drastically the detection time by

days, network problems will be solved in

/(

+

)×100% =

% less time, having a similar impact on the number of complaints.

Considering your active subscriptions, the number of complaints that your company will potentially avoid is

×

%×

%×

%×

% =

.

With the intention to monetize this reduction in calls, we've set an average call center agent hourly wage of

USD 3.00

and a

five-minute

call duration. However, you can modify these numbers by clicking

To sum up, savings related to fewer call center complaints can amount to

×

×(

/60) =

.

More recommendations and new users

Customer satisfaction surveys have shown that approximately

29%

of users recommend their mobile operator to family and friends for its network quality. These recommendations, however, can't be expected from customers whose serving cells are not performing well. Telko Manager® shortens customers' poor experience interval by reducing the time it takes to solve a network problem, so that they can keep promoting your services and capture new users for your company.

Let's say your user base grows

5%

on an annual basis. Then, the number of new users attracted by your network quality is

%×

%×

=

.

You may try a different recommendation percentage and input your base growth by clicking

The yearly cell failure probability equals 12 times (B) divided by (A), this is 12×

/

=

.

Also, the solution interval of a performance issue is the sum of the detection time and the repair time. Note that this interval is reduced from

days to

days thanks to our software near real-time detection capabilities. Then, the fraction of the year with good service is currently (1 -

×(

/365)) =

; whereas, with Telko Manager® this fraction will be (1 -

×(

/365)) =

.

This represents an improvement of (

/

- 1)×100% =

% in the amount of time your network will provide a good service and your customers will recommend it.

Taking into account that each new user generates a revenue stream during their active subscription period, we can employ their CLTV (with negligible costs) to estimate the total revenue that additional customers will bring to your company due to the increased number of recommendations. Then, the CLTV will be given by ARPU / monthly churn =

/

% =

.

To conclude, the new users total revenue will be

%×

×

=

.