Tspendo (Telecom Spend Optimizer)

www.tmanco.ch - toni.lazazzera@tmanco.ch - 091.930-9663

About Tspendo ( www.tspendo.ch )

Tspendo is a software tool developped by Tmanco SA, it performs an X-ray of your mobile telephony invoice (detailed billing files from the carrier) and produces the current report. This report enables you to visualize the trends, verify the tariffs, identify opportunities for optimization and quantify the potential gains. Such insights shall help evaluate the ROI of given projects, and therefore define & prioritize initiatives for cost optimizations, such as: inventory cleanup project, contract negociation, TEM deployment (Telecom Expense Management), etc.

WARNING: this report is produced automatically based on the information found in the carrier's billing-files (eg: Swisscom Mobile - Invoice Reporting Raw Data). The information provided here shall be interpreted with care and considered in the context of the specific customer, it shall not be seen as a "ready-to-use answers" to trigger actions without prior validation by a telecom specialist.

Mobile analysis for customer DEMO

 

Scope RDS_TSPENDO-DEMO-1910-2002
Optimization NATEL go
Level RADA
Date 2020-06-16
 

 
Scope: defines a given set of data analyzed (eg: a given period of months or a limited group of invoices)

Optimization: the type of optimization performed by the present report. Tspendo also generates other reports with other kind of optimizations (eg: Swisscom CMN).

Level : defines the level of details of this report

01) Executive summary

go to index

This report analyses the mobile telephony spend for the customer DEMO-REPORT. It highlights anomalies or opportunities that can be exploited to reduce the spend, and also quantifies the savings that could be achieved.

Brief overview

This analysis was based on 5 months of data (Swisscom Invoice Reporting files from 2019.10 to 2020.02).
We extrapolated a yearly spend of 394000 CHF/year for a total of 272 mobiles (last period), which gives an average of 120 CHF/month per mobile

The analysis revealed 18.7% potential savings, subdivided between Long-term and Quick-win as illustrated in this bar-graph:

81% 1% 17%

Important: please check the section 02) Validation of source data used for the analysis to ensure that the underlying data (used to build this report) is complete. Otherwise the information provided in this report may not be accurate and should be corrected before you can use it

Costs by category

The table hereafter provides a summary of the costs, subdivided by category. For more details, see section 03) Invoice Verification & Overview

Category nb_Units Unit chf/unit chf chf/yr %chf graph %chf
Subscriptions 1327 mobiles x months 92.42 122639 294334 74.7% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Roaming Tel 49084 Minutes 0.42 20804 49931 12.7% |||||||||||||
International Tel 41683 Minutes 0.26 10798 25917 6.6% |||||||
Roaming Data 1391501 Mb 0.01 8521 20452 5.2% |||||
National Tel 87687 Minutes 0.01 1217 2922 0.7% |
Roaming SMS 1802 SMS 0.13 231 554 0.1% |
National SMS 2189 SMS 0.0 8 19 0.0% |
National Data 6968904 Mb 0.0 0 0 0.0% |
International SMS 1747 SMS 0.0 0 0 0.0% |
TOTAL 164222 394133 100.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Savings opportunities

The table hereafter provides a summary of the potential savings identified. The hyperlinks in the table bring you to the sections with further details.

Savings opportunities diff/yr %diff Graph %chf
Quick-win 67000 17.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
04) Inventory verification & optimization 0 0.0%
09) NATEL go optimization 67000 16.9% |||||||||||||||||
Medium / Long-term 7000 1.8% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
05) Usage policy / Top users 0 0.0%
06) Usage policy / Business hours 4000 1.0% |
07) Least Cost Routing 1000 0.3% |
08) Room for negociation 2000 0.5% |
GRAND TOTAL 74000 18.7% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

01.1) Invoice Verification

Tspendo does not have sufficient information to verify that your invoice is correct
but section 03) Invoice Verification & Overview provides you further details per category and enables you to verify that:

If you find any divergence, this may reveal billing errors causing extra costs and therefore a potential saving, however further investigation may then be needed to confirm that the divergences are not due to other factors before claiming a refund from the provider

01.2) Quick win

We identified 67000 CHF/year as quick savings (17.0%) which could be achieved within 1-3 month by terminating unused lines or choosing the best subscription & option for each mobile.

01.3) Medium / long term savings

We also identified further long-term savings around 7000 CHF/year (1.8%) which could be achieved within 3-12 months through initiatives such as negociation, by enforcing usage policy or by implementing a technical solutions for call-routing.

Important: for medium / long term savings, we considered only 40% of the savings identified in each section (rule of thumb), to take into account that:

01.4) Process optimization through TEM

Considering the management of the mobile fleet of 272, we estimated that it probably requires ~0.5 FTE to manage it (order subscriptions/equipment, activate options, verify invoices, allocate costs, support users, etc.) , and using a TEM solution could probably reduce that workload by ~0.3 FTE

01.5) Enforcing usage policies through TEM

The long-term savings highlighted above show the impact that enforcing usage policies can have on the costs
Here are the type of actions that can drive users to lower their average cost/month or use the fix phone instead of their when possible :

TEM is a key component to achieve these savings, by enabling the design of custom reports and the automatic distribution to hundreds/thousands of users every month

Index

01) Executive summary

01.1) Invoice Verification

01.2) Quick win

01.3) Medium / long term savings

01.4) Process optimization through TEM

01.5) Enforcing usage policies through TEM

02) Validation of source data used for the analysis

02.1) Swisscom files imported

03) Invoice Verification & Overview

03.1) Costs by category

03.2) Evolution by month

03.3) Subscriptions & Options

03.4) National Tel

03.5) International Tel

03.6) International Tel / Top countries

03.7) Roaming Tel

03.8) Roaming Tel / Top countries

03.9) Roaming Data

04.0) Roaming Data / Top countries

04) Inventory verification & optimization

04.1) Mobiles with zero traffic

05) Usage policy / Top users

05.1) Overview of potential savings by category (traffic costs only)

05.2) National Tel

05.3) National Data

05.4) International Tel

05.5) Roaming Tel

05.6) Roaming Data

05.7) SMS / MMS

05.8) List of top mobiles (present in one or more Goup 1)

06) Usage policy / Business hours

06.1) International Tel

06.2) Roaming Tel

06.3) Roaming Data

07) Least Cost Routing

07.1) International Tel

07.2) Roaming Tel

08) Room for negociation

08.1) Billing increment

09) NATEL go optimization

09.1) Subscription costs used for the simulation

09.2) Recommended changes, nb of mobiles involved and resulting saving

09.3) Summary per Pareto group

09.4) Number and kind of subscriptions BEFORE / AFTER the recommended changes

09.5) Sample mobile for each kind of downgrade/upgrade

09.6) Detailed list of mobiles and recommended change

02) Validation of source data used for the analysis

go to index

02.1) Swisscom files imported

The table below shows the months imported for the analysis, and the nb. of mobiles found in the Swisscom files.

DeliveryPeriod chf_billed in_billitem in_itemized no_traffic no_detail graph %ok/missing
2019.10 35047 261 257 4 0 ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2019.11 33246 263 257 6 0 ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2019.12 33435 265 256 9 0 ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2020.01 32655 266 258 8 0 ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2020.02 29838 271 261 10 0 ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

03) Invoice Verification & Overview

go to index

03.1) Costs by category

The table below shows how costs are distributed by categories.

Category nb_Units Unit chf/unit chf chf/yr %chf graph %chf
Subscriptions 1327 mobiles x months 92.42 122639 294334 74.7% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Roaming Tel 49084 Minutes 0.42 20804 49931 12.7% |||||||||||||
International Tel 41683 Minutes 0.26 10798 25917 6.6% |||||||
Roaming Data 1391501 Mb 0.01 8521 20452 5.2% |||||
National Tel 87687 Minutes 0.01 1217 2922 0.7% |
Roaming SMS 1802 SMS 0.13 231 554 0.1% |
National SMS 2189 SMS 0.0 8 19 0.0% |
National Data 6968904 Mb 0.0 0 0 0.0% |
International SMS 1747 SMS 0.0 0 0 0.0% |
TOTAL 164222 394133 100.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

03.2) Evolution by month

The table below shows the monthly evolution over the whole period available.

DeliveryPeriod Subscriptions Natl_Tel Natl_Data Intl_Tel Roam_Tel Roam_Data Other Total Graph
2019.10 24322 150 0 2510 5827 2170 65 35047 ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2019.11 24386 277 0 2220 4445 1851 63 33246 ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2019.12 24660 232 0 2069 4619 1797 55 33435 ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2020.01 24529 181 0 2146 4087 1682 28 32655 |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2020.02 24741 375 0 1852 1824 1019 25 29838 |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

03.3) Subscriptions & Options

The table below shows the subscriptions and options billed for the last month, as well as the average tarif billed per unit. A tarif in parentheses means the subscription/option was never billed for a full month and the tarif is therefore an approximation

Some manual check is needed to ensure the invoice doesn't contain obvious errors that may result in undue costs

Category Subscription Last_Month Nb_Subscr Subscr_Tarif
Subscription Multi Device Option 1 additional device 2020.02 12 10.11
Subscription Multi Device Option 2 additional devices 2020.02 1 15.72
Subscription NATEL go Company voice 2020.02 5 8.47
Subscription NATEL go Europe 2020.02 48 114.9
Subscription NATEL go Global 2020.02 35 278.16
Subscription NATEL go Neighbours 2020.02 8 96.76
Subscription NATEL go Swiss voice 2020.02 1 18.14
Subscription NATEL go Swiss standard 2020.02 161 42.33
Data Option - Roaming Data Travel 200 MB Europe 2020.02 3 6.0
Data Option - Roaming Data Travel 200 MB Global 2020.02 2 8.42
Data Option - Roaming Data Travel 200 MB Global plus 2020.02 2 18.13
Data Option - Roaming Data Travel 1 GB Europe 2020.02 10 18.73
Data Option - Roaming Data Travel 1 GB Europe, autorenewal 2020.02 1 22.31
Data Option - Roaming Data Travel 1 GB Global 2020.02 10 24.73
Data Option - Roaming Data Travel 3 GB Europe, autorenewal 2020.02 1 44.81
Data Option - Roaming Data Travel 3 GB Europe 2020.02 1 48.54
Data Option - Roaming Data Travel 3 GB Global 2020.02 1 60.04
Data Option - Roaming Data Travel 1 GB Global Plus 2020.02 3 86.49
Data Option - Roaming Data in zone Europe, standard tariff 2020.02 1 5.05

03.4) National Tel

Category %Min Minutes billed_tarif billed_chf chf/yr %chf graph %chf
Tel Fix 33.1% 29042 0.03 780 1872 64.1% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Tel SpecialNb 3.2% 2806 0.15 431 1035 35.4% |||||||||||||||||||||||||||||||||||
Tel Mob NonSwisscom 14.6% 12841 6 14 0.5% |
Tel Mob Swisscom 21.9% 19247
Tel Fix OnNet 27.1% 23750
TOTAL 100.0% 87687 0.01 1217 2922 100.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

03.5) International Tel

The table below shows the costs and traffic for calls from Switzerland to International

d_intl_group %Min Minutes billed_tarif billed_chf chf/yr %chf graph %chf
Group 1 79.6% 33164 0.19 6151 14764 57.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Group 2 8.0% 3345 0.17 565 1356 5.2% |||||
Group 3 9.6% 3985 0.65 2582 6196 23.9% ||||||||||||||||||||||||
Group 4 2.2% 902 1.26 1139 2735 10.6% |||||||||||
Group 5 0.4% 159 2.26 360 864 3.3% |||
Group ? 0.3% 125
TOTAL 100.0% 41683 0.26 10798 25917 100.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

03.6) International Tel / Top countries

The table below shows the costs and traffic for international calls, with the top 10 countries (calls made from Switzerland to International)

Category Country %Min Minutes billed_tarif billed_chf chf/yr %chf graph %chf
Top10 United States 15.3% 6375 0.48 3085 7404 28.6% |||||||||||||||||||||||||||||
Top10 Germany 22.6% 9424 0.09 828 1987 7.7% ||||||||
Top10 United Kingdom 7.9% 3291 0.22 713 1712 6.6% |||||||
Top10 France 17.0% 7080 0.06 415 996 3.8% ||||
Top10 Australia 0.9% 370 1.02 378 908 3.5% ||||
Top10 Austria 2.2% 931 0.4 373 895 3.5% ||||
Top10 Hungary 2.6% 1085 0.33 355 853 3.3% |||
Top10 Russian Federation 0.9% 378 0.87 328 789 3.0% |||
Top10 Costa Rica 0.3% 129 2.44 314 754 2.9% |||
Top10 South Africa 1.1% 449 0.67 303 727 2.8% |||
Other Group 3 4.7% 1943 0.66 1279 3071 11.9% ||||||||||||
Other Group 4 2.2% 902 1.26 1139 2735 10.6% |||||||||||
Other Group 2 8.0% 3345 0.17 565 1356 5.2% |||||
Other Group 5 0.4% 159 2.26 360 864 3.3% |||
Other Group 1 13.7% 5690 0.06 357 858 3.3% |||
Other Group ? 0.3% 125
TOTAL 100.0% 41683 0.26 10798 25917 100.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

03.7) Roaming Tel

The table below shows the costs and traffic for Roaming calls (calls made or received while abroad)

o_roam_zone_tel %Min Minutes billed_tarif billed_chf chf/yr %chf graph %chf
Zone A 45.1% 22114 0.2 4482 10758 21.5% ||||||||||||||||||||||
Zone B1 5.7% 2808 0.04 113 272 0.5% |
Zone B2 2.1% 1053 0.68 721 1730 3.5% ||||
Zone B3 7.5% 3702 1.34 4952 11886 23.8% ||||||||||||||||||||||||
Zone C 20 0.58 11 28 0.1% |
Zone C1 1.0% 514 0.33 171 411 0.8% |
Zone C2 6.0% 2953 0.47 1387 3328 6.7% |||||||
Zone C3 4.5% 2193 2.53 5553 13327 26.7% |||||||||||||||||||||||||||
TOTAL 100.0% 49084 0.42 20804 49931 100.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

03.8) Roaming Tel / Top countries

The table below shows the Roaming costs and traffic for the top 10 countries (calls made or received while abroad)

Category Country %Min Minutes billed_tarif billed_chf chf/yr %chf graph %chf
Top10 United States 9.9% 3496 1.4 4905 11773 28.2% ||||||||||||||||||||||||||||
Top10 Kenya 1.6% 554 3.31 1835 4404 10.6% |||||||||||
Top10 Oman 1.3% 474 3.2 1518 3643 8.7% |||||||||
Top10 Germany 21.4% 7554 0.2 1489 3575 8.6% |||||||||
Top10 Pakistan 0.7% 260 3.71 967 2320 5.6% ||||||
Top10 China 0.9% 327 1.73 564 1354 3.2% |||
Top10 Portugal 6.5% 2313 0.19 429 1029 2.5% |||
Top10 Spain 2.9% 1025 0.42 427 1026 2.5% |||
Top10 United Kingdom 3.5% 1246 0.31 383 920 2.2% ||
Other Zone A 28.2% 9973 0.18 1752 4206 10.1% ||||||||||
Other Zone C3 2.6% 903 1.36 1232 2957 7.1% |||||||
Other Zone C2 7.4% 2626 0.31 822 1974 4.7% |||||
Other Zone B2 3.0% 1053 0.68 721 1730 4.1% ||||
Other Zone C1 1.5% 514 0.33 171 411 1.0% |
Other Zone B1 7.9% 2808 0.04 113 272 0.7% |
Other Zone B3 0.6% 205 0.23 47 113 0.3% |
Other Zone C 0.1% 20 0.58 11 28 0.1% |
TOTAL 100.0% 35359 0.49 17393 41743 100.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

03.9) Roaming Data

The table below shows the costs and traffic for Roaming calls (calls made or received while abroad)

o_roam_zone_dat %Mb Mb billed_tarif billed_chf chf/yr %chf graph %chf
Zone A 75.1% 1044299 2296 5511 34.6% |||||||||||||||||||||||||||||||||||
Zone B1 19.1% 266277 0.01 2300 5520 34.7% |||||||||||||||||||||||||||||||||||
Zone B2 3.5% 48315 0.02 791 1900 11.9% ||||||||||||
Zone C 2.3% 32222 0.04 1130 2712 17.0% |||||||||||||||||
Zone D 10 10.7 112 269 1.7% ||
TOTAL 100.0% 1391125 6630 15913 100.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

04.0) Roaming Data / Top countries

The table below shows the Roaming costs and traffic for the top 10 countries (data usage while abroad)

Category Country %Mb Mb billed_tarif billed_chf chf/yr %chf graph %chf
Top10 United States 6.8% 94786 0.01 1164 2793 17.6% ||||||||||||||||||
Top10 Kenya 0.9% 11904 0.05 646 1551 9.7% ||||||||||
Top10 Germany 19.8% 276108 579 1391 8.7% |||||||||
Top10 Italy 6.6% 92083 419 1006 6.3% ||||||
Top10 Tanzania, United Republic of 0.3% 4314 0.07 295 709 4.5% |||||
Top10 Oman 0.1% 2033 0.12 245 588 3.7% ||||
Top10 Pakistan 0.2% 3126 0.07 218 524 3.3% |||
Top10 India 1.2% 17314 0.01 217 520 3.3% |||
Top10 United Kingdom 4.9% 68305 200 481 3.0% |||
Other Zone A 43.7% 607801 1096 2631 16.5% |||||||||||||||||
Other Zone B1 11.1% 154176 0.01 918 2205 13.9% ||||||||||||||
Other Zone C 1.6% 22748 0.02 371 890 5.6% ||||||
Other Zone B2 2.6% 36411 145 349 2.2% ||
Other Zone D 10 10.7 112 269 1.7% ||
TOTAL 100.0% 1391125 6630 15913 100.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

04) Inventory verification & optimization

go to index

04.1) Mobiles with zero traffic

The following table shows 1 mobiles which apparently didn't generate any traffic during the whole period analyzed. If these lines are not used and would be terminated, then it would save 101 CHF per year

Warning: a mobile may be used to receive calls or for emergency situations, in which case it could be normal that it didn't generate any traffic but that doesn't mean that it could be terminated

Subscription AccessNumber chf_billed nb_Min nb_Mb nb_SMS
NATEL go Company voice 0790000574 42.33 0 0 0
TOTAL 1 mobiles 42.33 0 0 0

05) Usage policy / Top users

go to index

By sorting the mobiles top-down according to their cost, we look at what portion of the mobiles generates the first 20% of the costs (Paretto group 1), what portion generates the next 20% of the costs (group 2), etc up to group 5

We also look at the average cost/month per mobile for each group. Then we estimate what the savings could be if users of groups 1 & 2 could be moved one group down in terms of average cost/month.

05.1) Overview of potential savings by category (traffic costs only)

The table herafter presents the yearly costs per traffic category, as well as the potential savings if users of group 1 & 2 could lower their average cost/month to the next group down.

The graph shows the percentage of mobiles for each of the 5 groups, where each group generates 20% of the costs:
Group 1 = top users Group 2 Group 3 Group 4 Group 5 = bottom users

Each category is then analyzed indivually in this section. At the end of the section you'll find a list of all mobiles which belong to group 1 or 2 in one or more of the categories

Category chf/yr diff/yr %diff Group 1 (top users) Group 5 (bottom users) Graph
National Tel 2922 -123 -4.2% 4 mobiles x 11 chf/month |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
National Data
International Tel 25917 -3783 -14.6% 4 mobiles x 100 chf/month 116 mobiles x 3 chf/month ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Roaming Tel 49931 -6802 -13.6% 5 mobiles x 152 chf/month 126 mobiles x 6 chf/month |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Roaming Data 20452 -3303 -16.2% 6 mobiles x 54 chf/month 73 mobiles x 4 chf/month ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SMS/MMS 574 -120 -20.9% 2 mobiles x 4 chf/month |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
TOTAL 19 mobiles x 345 chf/month 142 mobiles x 46 chf/month ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

05.2) National Tel

GROUP mobiles units chf %units %chf chf/unit chf/m/m new_chf diff_chf chf/yr diff/yr %diff %mobiles graph %mobiles
1 4 1696 231 3.1% 19.0% 0.14 11 179 -51 554 -123 -22.2% 3.4% |||
2 5 27 224 18.4% 8.24 8 224 539 4.2% ||||
3 6 124 269 0.2% 22.1% 2.17 8 269 646 5.1% |||||
4 6 1510 247 2.7% 20.3% 0.16 8 247 593 5.1% |||||
5 97 51679 245 93.9% 20.1% 245 588 82.2% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
TOTAL 118 55038 1217 100.0% 100.0% 0.02 2 1166 -51 2922 -123 -4.2% 100.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

05.3) National Data

05.4) International Tel

GROUP mobiles units chf %units %chf chf/unit chf/m/m new_chf diff_chf chf/yr diff/yr %diff %mobiles graph %mobiles
1 4 2533 2001 9.2% 18.5% 0.79 100 1254 -747 4803 -1794 -37.3% 2.5% |||
2 7 4219 2194 15.3% 20.3% 0.52 62 1365 -829 5266 -1989 -37.8% 4.3% ||||
3 11 3793 2145 13.8% 19.9% 0.57 39 2145 5149 6.8% |||||||
4 23 4816 2247 17.5% 20.8% 0.47 19 2247 5393 14.3% ||||||||||||||
5 116 12174 2209 44.2% 20.5% 0.18 3 2209 5303 72.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
TOTAL 161 27537 10798 100.0% 100.0% 0.39 13 9222 -1576 25917 -3783 -14.6% 100.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

05.5) Roaming Tel

GROUP mobiles units chf %units %chf chf/unit chf/m/m new_chf diff_chf chf/yr diff/yr %diff %mobiles graph %mobiles
1 5 12944 3820 34.5% 18.4% 0.3 152 2335 -1485 9170 -3565 -38.9% 2.8% |||
2 9 4306 4203 11.5% 20.2% 0.98 93 2854 -1348 10087 -3236 -32.1% 5.1% |||||
3 14 5359 4440 14.3% 21.3% 0.83 63 4440 10656 7.9% ||||||||
4 24 5075 4151 13.5% 20.0% 0.82 34 4151 9964 13.5% ||||||||||||||
5 126 9801 4188 26.1% 20.1% 0.43 6 4188 10053 70.8% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
TOTAL 178 37488 20804 100.0% 100.0% 0.55 23 17970 -2834 49931 -6802 -13.6% 100.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

05.6) Roaming Data

GROUP mobiles units chf %units %chf chf/unit chf/m/m new_chf diff_chf chf/yr diff/yr %diff %mobiles graph %mobiles
1 6 122347 1624 15.5% 19.1% 0.01 54 800 -824 3899 -1979 -50.8% 4.3% ||||
2 13 141369 1733 17.9% 20.3% 0.01 26 1182 -551 4160 -1323 -31.8% 9.4% |||||||||
3 19 130398 1727 16.5% 20.3% 0.01 18 1727 4146 13.7% ||||||||||||||
4 28 232443 1693 29.4% 19.9% 0.01 12 1693 4065 20.1% ||||||||||||||||||||
5 73 162937 1741 20.6% 20.4% 0.01 4 1741 4179 52.5% |||||||||||||||||||||||||||||||||||||||||||||||||||||
TOTAL 139 789496 8521 100.0% 100.0% 0.01 12 7145 -1376 20452 -3303 -16.2% 100.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

05.7) SMS / MMS

GROUP mobiles units chf %units %chf chf/unit chf/m/m new_chf diff_chf chf/yr diff/yr %diff %mobiles graph %mobiles
1 2 363 43 12.3% 18.0% 0.12 4 20 -22 103 -53 -51.6% 2.0% ||
2 5 293 52 9.9% 21.8% 0.18 2 24 -27 125 -66 -53.4% 5.1% |||||
3 10 476 48 16.1% 20.3% 0.1 48 116 10.2% ||||||||||
4 20 840 50 28.4% 21.0% 0.06 50 120 20.4% ||||||||||||||||||||
5 61 983 45 33.3% 18.8% 0.05 45 108 62.2% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
TOTAL 98 2956 239 100.0% 100.0% 0.08 189 -50 574 -120 -21.0% 100.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

05.8) List of top mobiles (present in one or more Goup 1)

There are 77 mobiles which are in a 'Group 1' or in a "Group 2" for one or more of the categories listed above

The table below shows the list of these mobiles and indicates the group the mobile belongs to for the given category: Group 1, Group 2, Group 3, Group 4, Group 5

Mobile Total Natl Tel Natl Data Intl Tel Roam Tel Roam Data SMS Other costs
0790000018 2807 256 711 448 0 1390
0790000057 1974 381 943 45 29 574
0790000009 1800 0 437 618 106 13 625
0790000103 1711 66 52 201 1390
0790000006 2246 1 8 766 67 10 1390
0790000032 1721 139 190 1390
0790000083 1643 488 382 145 1 625
0790000049 1465 75 1390
0790000058 1462 115 754 16 574
0790000015 1827 435 0 1390
0790000037 1738 0 24 292 16 12 1390
0790000010 1729 0 252 84 2 1390
0790000054 1622 0 222 8 1390
0790000008 1598 6 149 50 0 1390
0790000060 1574 161 21 1390
0790000070 1556 0 81 84 1390
0790000016 1471 2 1469
0790000021 1443 2 1441
0790000034 1442 1 1441
0790000003 1268 1 27 644 111 483
0790000041 1139 8 32 295 224 4 574
0790000185 949 636 26 74 211
0790000042 897 11 173 147 352 0 211
0790000188 830 0 438 156 22 0 211
0790000051 520 1 8 91 207 211
0790000272 84 44 39
0790000261 83 44 38
0790000017 1441 1441
0790000024 1434 1 42 1390
0790000073 1431 2 11 10 16 1390
0790000026 1407 2 6 8 1390
0790000194 1404 13 1390
0790000071 1394 3 0 1390
0790000014 1393 0 1 1390
0790000023 1392 1 1390
0790000035 1391 0 1390
0790000020 1391 0 1390
0790000027 1391 0 1390
0790000012 1391 0 1390
0780000004 1390 1390
0790000007 1390 1390
0790000031 1390 1390
0790000062 1390 1390
0790000128 1390 1390
0790000129 1390 1390
0790000148 1390 1390
0790000163 1390 1390
0790000199 1390 1390
0790000259 1390 1390
0790000091 1312 339 134 4 834
0790000033 1170 0 58 469 67 574
0790000028 1169 1 359 482 111 3 211
0790000118 1084 0 453 54 0 574
0790000050 1050 153 199 123 574
0790000069 1012 0 316 98 22 0 574
0790000119 992 2 449 57 483
0790000046 889 0 170 144 574
0790000044 872 10 16 108 112 625
0790000164 784 0 288 217 67 211
0790000053 771 1 18 443 89 6 211
0790000078 743 2 415 113 0 211
0790000105 686 99 185 190 211
0790000196 668 20 436 0 211
0790000127 577 0 58 166 139 211
0790000150 547 317 1 16 0 211
0790000243 538 44 494
0790000087 520 0 56 138 112 0 211
0790000214 520 275 33 211
0790000011 494 12 55 60 152 2 211
0790000093 415 12 49 142 211
0790000157 333 36 78 7 211
0790000138 319 14 80 13 211
0790000171 225 1 4 8 211
0790000231 214 44 169
0790000249 87 44 42
0790000258 81 44 36
0790000238 78 44 33

06) Usage policy / Business hours

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This section analyses the period when costs are generated, looking for costs generated during business-hours and which could be avoided (or reduced) if we assume that the user is probably in an office with the possibility to use a fix phone or wifi (for data)

Warning: to simulate the cost of routing the calls through the fix network, we normally take the info from the fix-telephony call details. If such detail is not provided, then we assume the fix cost is the mobile cost / 3 (for international) or /2 (for roaming)

06.1) International Tel

The cost 'fix_chf' is the cost if the call would be made from the office in Switzerland using the fix network. This cost has been calculated using the tariffs found in the fix-telephony files

If users would use the fix phone at least for half of the calls during the period 'Week 09-18', then this would save an average of 1270 CHF per year

Period billed_chf fix_chf new_chf diff_chf diff/yr %diff %chf graph %chf
Week 00-06 36 12 36 0.3% |
Week 06-09 556 427 556 5.2% |||||
Week 09-18 7808 6750 7279 -529 -1270 -6.8% 72.3% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Week 18-21 1295 1622 1295 12.0% ||||||||||||
Week 21-24 372 521 372 3.5% ||||
Week-end 729 695 729 6.8% |||||||
TOTAL 10798 10029 10269 -529 -1270 -4.9% 100.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

06.2) Roaming Tel

The cost 'fix_chf' is the cost if the call would be made from an office abroad, using the fix network. As a rule-of-thumb, we assumed that the cost would be half of the mobile cost (conservative approach, the cost may actually be lower).

If users would use the fix phone at least for half of the calls during the period 'Week 09-18', then this would save an average of 5846 CHF per year

Period billed_chf fix_chf new_chf diff_chf diff/yr %diff %chf graph %chf
Week 00-06 576 288 576 3.3% |||
Week 06-09 769 384 769 4.4% ||||
Week 09-18 9743 4871 7307 -2435 -5846 -25.0% 56.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Week 18-21 3566 1783 3566 20.5% |||||||||||||||||||||
Week 21-24 1345 672 1345 7.7% ||||||||
Week-end 1390 695 1390 8.0% ||||||||
TOTAL 17393 8696 14957 -2435 -5846 -14.0% 100.0% ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

06.3) Roaming Data

The cost 'wifi_chf' is the cost if the mobile would use the wifi network instead of 3G, therefore 0.

If users would use the WIFI for at least half of the traffic made during the period "Week 09-19", then this would save an average of 2685 CHF per year

Period billed_chf fix_chf new_chf diff_chf diff/yr %diff %chf graph %chf
Week 00-06 1138 1138 17.2% |||||||||||||||||
Week 06-09 529 529 8.0% ||||||||
Week 09-18 2237 1118 -1118 -2685 -50.0% 33.7% ||||||||||||||||||||||||||||||||||
Week 18-21 626 626 9.5% ||||||||||
Week 21-24 315 315 4.8% |||||
Week-end 1782 1782 26.9% |||||||||||||||||||||||||||
TOTAL 6630 5511 -1118 -2685 -16.9% 100.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

07) Least Cost Routing

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07.1) International Tel

The table below shows the costs and traffic for calls from Switzerland to International

If these calls were routed through the fix network (mobile to office, then office to international), this could save an average of 1789 CHF per year .
Such least-cost-routing requires a special solution. That solution consists of an equipment installed centrally and a cuscope-software installed on each mobile device. The cuscope software makes the whole process transparent to the user. More work would be needed to evaluate the feasability and estimate the ROI

An example of such solution: www.sosoftware.com

The graphic represents the percentage of the total that could be saved, and highlights the categories that would benefit the most from such routing

WARNING: this simulation is only performed if we have the fix-telephony details available, otherwise this section is meaningless

d_intl_group %chf %Min Minutes billed_tarif new_tarif billed_chf new_chf diff_chf chf/yr diff/yr %diff %difftot graph %difftot
Group 1 57.0% 79.6% 33164 0.19 0.19 6151 6311 160 14764 384 2.6% 1.5% |
Group 2 5.2% 8.0% 3345 0.17 0.24 565 796 231 1356 554 40.9% 2.1% |
Group 3 23.9% 9.6% 3985 0.65 0.49 2582 1947 -634 6196 -1523 -24.6% -5.9% ||||||
Group 4 10.6% 2.2% 902 1.26 0.71 1139 637 -501 2735 -1204 -44.0% -4.6% |||||
Group 5 3.3% 0.4% 159 2.26 2.26 360 360 864
TOTAL 100.0% 100.0% 41683 0.26 0.24 10798 10053 -745 25917 -1789 -6.9% -6.9% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

07.2) Roaming Tel

3

The table below shows the costs and traffic for Roaming calls (calls made or received while abroad)

Using the same type of solution as for the International calls, it is possible to use a call-back feature so that you are charged for an incoming-roaming call instead of outgoing-roaming (this is usually cheaper).

The column new_chf shows a simulation on what the cost would be if the mobile was called-back from the office, and then the call to the destination is initiated from the office. All that being transparent to the users thanks to a cuscope software installed on the device.

Using such mechanism could save an average of 1183 CHF per year

.

The graphic represents the percentage of the total that could be saved, and highlights the categories that would benefit the most from such routing

o_roam_zone_tel %chf %Min Minutes billed_tarif new_tarif billed_chf new_chf diff_chf chf/yr diff/yr %diff %difftot graph %difftot
Zone A 25.8% 62.5% 22114 0.2 0.46 4482 10086 5604 10758 13450 125.0% 32.2% |
Zone B1 0.7% 7.9% 2808 0.04 0.35 113 973 860 272 2064 757.5% 4.9% |
Zone B2 4.1% 3.0% 1053 0.68 0.46 721 482 -238 1730 -572 -33.1% -1.4% |
Zone B3 28.5% 10.5% 3702 1.34 0.62 4952 2288 -2664 11886 -6395 -53.8% -15.3% |||||||||||||||
Zone C 0.1% 0.1% 20 0.58 0.74 11 15 3 28 8 28.3%
Zone C1 1.0% 1.5% 514 0.33 0.46 171 233 62 411 150 36.6% 0.4% |
Zone C2 8.0% 8.4% 2953 0.47 0.37 1387 1100 -286 3328 -686 -20.6% -1.6% ||
Zone C3 31.9% 6.2% 2193 2.53 0.78 5553 1718 -3834 13327 -9202 -69.0% -22.0% ||||||||||||||||||||||
TOTAL 100.0% 100.0% 35359 0.49 0.48 17393 16899 -493 41743 -1183 -2.8% -2.8% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

08) Room for negociation

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This section identifies areas that may have room for negociation. The indicated savings are rough estimations of what may be achievable, unless these areas were already taken into consideration.

08.1) Billing increment

The EU regulation states that roaming calls shall be billed in 1 sec. increment after the first 30 sec. Swisscom bills roaming calls in 60 sec. increments and this generates, in this case, an extra cost of 4473 CHF per year

.

While it would not be possible for Swisscom to modify the billing increment, this point can be addressed by ensuring that the tariffs are adjusted to compensate for the extra costs.

o_roam_zone_tel used_minutes billed_minutes billed_chf new_chf diff_chf chf/yr diff/yr %diff
Zone A 22114 24748 4482 4093 -389 10758 -934 -8.7%
Zone B1 2808 2906 113 84 -29 272 -70 -25.8%
Zone B2 1053 1175 721 613 -107 1730 -258 -15.0%
Zone B3 3702 4061 4952 4470 -482 11886 -1156 -9.7%
Zone C 20 24 11 9 -2 28 -4 -17.4%
Zone C1 514 593 171 142 -28 411 -68 -16.6%
Zone C2 2953 3130 1387 1248 -138 3328 -332 -10.0%
Zone C3 2193 2460 5553 4866 -686 13327 -1647 -12.4%
TOTAL 35359 39099 17393 15529 -1863 41743 -4473 -10.7%

09) NATEL go optimization

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This section shows the results of the NATEL go optimization performed to identify the best subscription for each user. It presents the recommended Upgrade/Downgrade for each mobile and quantifies the saving that would result from these changes.

From the 272 mobiles present on the invoice the last month of the period (2020.02) we found 253 mobiles that had one of the following NATEL go subscription: Swiss, Neighbours, Europe, Global. And from them, we analysed 234 mobiles which had the same NATEL go subscription over the full 5 months period

From these 234 mobiles 70 mobiles would benefit from a Downgrade or Upgrade , resulting in a total saving of -66784.8 CHF/year

About NATEL go

Metodology

Limitations

09.1) Subscription costs used for the simulation

The following NATEL go subscriptions & costs were found in the Swisscom files (Invoice Reporting) and were used for the simulation

Subscription (full name) Subscription (short name) CHF/month
NATEL go Company voice Comp 8.47
NATEL go Swiss standard Swiss 42.33
NATEL go Neighbours Neighb 96.76
NATEL go Europe Europe 114.9
NATEL go Global Global 278.18

09.2) Recommended changes, nb of mobiles involved and resulting saving

Operation Old New mobiles diff/mob/yr diff/yr diff_period Abo Neighb Europe Global %diff graph %diff
DOWNGRADE Global Europe 7 -1202 -8414 -3506 -5712 0 0 2206 12.6% |||||||||||||
Neighb 1 -518 -518 -216 -907 0 6 686 0.8% |
Swiss 19 -2002 -38039 -15850 -22401 953 1228 4373 57.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Europe Neighb 5 -140 -703 -293 -455 0 161 0 1.1% |
Swiss 28 -511 -14311 -5963 -10128 1595 2563 0 21.4% |||||||||||||||||||||
Neighb Swiss 6 -461 -2769 -1154 -1632 478 0 0 4.1% ||||
UPGRADE Europe Global 1 -1399 -1399 -583 816 0 0 -1400 2.1% ||
Neighb Europe 1 -360 -360 -150 91 0 -241 0 0.5% |
Swiss Europe 2 -134 -268 -112 726 -336 -502 0 0.4% |
NO CHANGE Global Global 6 0 0 0 0 0 0 0 0.0% |
Europe Europe 12 0 0 0 0 0 0 0 0.0% |
Neighb Neighb 1 0 0 0 0 0 0 0 0.0% |
Swiss Swiss 145 0 0 0 0 0 0 0 0.0% |
TOTAL 234 -954 -66784 -27827 -39602 2690 3215 5865 100.0% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

 Legend

diff/yr = total cost difference extrapolated to 1 year

diff/period = total cost difference over the 5 months period

Abo/Neighb/Europe/Global = cost difference for the 5 months period

GREEN    = DECREASE

ORANGE =   INCREASE

About methodology used for the simulations

For Abo costs

For traffic costs (Neighb/Europe/Global)

Limitations

09.3) Summary per Pareto group

If we adjust the subscription only for the top 5 mobiles, we can already achieve 20.5% of the savings, therefore -13677.6 CHF/year

And if we adjust the subscription only for the top 33 mobiles then we achieve 80.8% of the savings, therefore -53942.4 CHF/year

The above observation are visible in the following table which shows a "Pareto" distribution of the mobiles according to the saving

Pareto_group mobiles %mobiles %diff diff/m/m diff/yr diff_period graph %mobiles
Group 1 5 2.1% 20.5% -227 -13677.6 -5699 ||
Group 2 6 2.6% 19.8% -184 -13252.8 -5522 |||
Group 3 7 3.0% 19.3% -153 -12921.6 -5384 |||
Group 4 15 6.4% 21.1% -78 -14090.4 -5871 ||||||
Group 5 37 15.8% 19.2% -28 -12842.4 -5351 ||||||||||||||||
TOTAL 70 100.0% 100.0% -79 -66784.8 -27827 ||||||||||||||||||||||||||||||

09.4) Number and kind of subscriptions BEFORE / AFTER the recommended changes

This table provides an overview of how the situation will change. By looking at which subscriptions are reduced and which ones are increased, it provides an indication of how the current subscriptions may be over/under-dimensionned

Before_After Swiss Neighbours Europe Global Total Graph
BEFORE 147 8 46 33 234 ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
AFTER 198 7 22 7 234 |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

09.5) Sample mobile for each kind of downgrade/upgrade

The following table shows a sample mobile for each kind of change (Downgrade/Upgrade)

In this table, we can see what the cost-difference would be if we change the subscription from "Old" to "New"

Operation Old New mobile diff/yr diff_period Abo Neighb Europe Global
DOWNGRADE Global Europe 0790000020 -1898.4 -791 -816 0 0 25
Neighb 0790000062 -518.4 -216 -907 0 6 686
Swiss 0790000259 -2829.6 -1179 -1179 0 0 0
Europe Neighb 0790000033 -213.6 -89 -91 0 2 0
Swiss 0790000237 -871.2 -363 -363 0 0 0
Neighb Swiss 0790000092 -573.6 -239 -272 33 0 0
UPGRADE Europe Global 0790000057 -1399.2 -583 816 0 0 -1400
Neighb Europe 0790000003 -360 -150 91 0 -241 0
Swiss Europe 0790000028 -252 -105 363 -296 -172 0
NO CHANGE Global Global 0790000006 0 0 0 0 0 0
Europe Europe 0790000058 0 0 0 0 0 0
Neighb Neighb 0790000121 0 0 0 0 0 0
Swiss Swiss 0790000042 0 0 0 0 0 0

09.6) Detailed list of mobiles and recommended change

This section provides the detailed list of all mobiles which would benefit from a downgrade or upgrade

The mobiles are subdivided in 5 tables according to the Pareto group. See 09.3) Summary per Pareto group

For explainations about the information in these tables and the meaning of the colors, see 09.5) Sample mobile for each kind of downgrade/upgrade

Note: on the "TOTAL" row, the values in the columns Subscription / Neighbours / Europe / Global indicate the total difference for this Pareto group over the whole period of 5 months

 
List of mobiles in Pareto group 1

This is the top group of mobiles that, together, represent about 20% of the savings

mobile Operation Old New diff/yr Month diff_period Abo Neighb Europe Global
0790000259 Downgrade Global Swiss -2829.6 5 months -1179 -1179 0 0 0
2020-02 -235 -235 0 0 0
2020-01 -235 -235 0 0 0
2019-12 -235 -235 0 0 0
2019-11 -235 -235 0 0 0
2019-10 -235 -235 0 0 0
0790000194 Downgrade Global Swiss -2791.2 5 months -1163 -1179 8 8 1
2020-02 -235 -235 0 0 0
2020-01 -235 -235 0 0 0
2019-12 -235 -235 0 0 0
2019-11 -231 -235 0 3 0
2019-10 -223 -235 7 4 0
0790000199 Downgrade Global Swiss -2709.6 5 months -1129 -1179 2 4 44
2020-02 -210 -235 2 0 22
2020-01 -233 -235 0 2 0
2019-12 -235 -235 0 0 0
2019-11 -214 -235 0 0 20
2019-10 -235 -235 0 0 0
0790000148 - Terrey Tina Downgrade Global Swiss -2697.6 5 months -1124 -1179 26 12 16
2020-02 -233 -235 0 0 1
2020-01 -228 -235 3 3 0
2019-12 -232 -235 1 1 0
2019-11 -218 -235 1 1 14
2019-10 -211 -235 19 4 0
0790000073 Downgrade Global Swiss -2649.6 5 months -1104 -1179 28 6 41
2020-02 -235 -235 0 0 0
2020-01 -233 -235 0 0 2
2019-12 -231 -235 0 0 4
2019-11 -174 -235 27 0 33
2019-10 -229 -235 0 5 0
5 mobiles TOTAL -13677.6 5 months -5699 -5895 64 30 102

 
List of mobiles in Pareto group 2

This is the 2nd group of mobiles that, together, represent about 20% of the savings

mobile Operation Old New diff/yr Month diff_period Abo Neighb Europe Global
0790000128 Downgrade Global Swiss -2433.6 5 months -1014 -1179 10 10 146
2020-02 -232 -235 0 0 3
2020-01 -199 -235 0 0 34
2019-12 -211 -235 2 3 18
2019-11 -216 -235 1 4 13
2019-10 -153 -235 4 1 76
0790000054 Downgrade Global Swiss -2368.8 5 months -987 -1179 95 19 79
2020-02 -211 -235 15 0 7
2020-01 -216 -235 6 0 12
2019-12 -175 -235 7 4 48
2019-11 -191 -235 37 6 0
2019-10 -191 -235 27 6 10
0790000163 Downgrade Global Swiss -2253.6 5 months -939 -1179 0 139 101
2020-02 -216 -235 0 19 0
2020-01 -135 -235 0 0 100
2019-12 -200 -235 0 35 0
2019-11 -235 -235 0 0 0
2019-10 -151 -235 0 84 0
0790000129 - Michallat Kirsti Downgrade Global Swiss -2140.8 5 months -892 -1179 69 0 218
2020-02 -210 -235 25 0 0
2020-01 -100 -235 16 0 118
2019-12 -235 -235 0 0 0
2019-11 -205 -235 11 0 19
2019-10 -139 -235 16 0 80
0790000027 Downgrade Global Swiss -2047.2 5 months -853 -1179 47 106 173
2020-02 -140 -235 44 0 50
2020-01 -159 -235 0 58 17
2019-12 -225 -235 0 0 10
2019-11 -185 -235 2 42 5
2019-10 -142 -235 0 4 89
0790000049 Downgrade Global Swiss -2008.8 5 months -837 -1179 43 18 281
2020-02 -195 -235 6 2 31
2020-01 -196 -235 10 0 29
2019-12 -86 -235 2 13 133
2019-11 -230 -235 1 2 1
2019-10 -127 -235 22 0 85
6 mobiles TOTAL -13252.8 5 months -5522 -7074 264 292 998

 
List of mobiles in Pareto group 3

This is the 3rd group of mobiles that, together, represent about 20% of the savings

mobile Operation Old New diff/yr Month diff_period Abo Neighb Europe Global
0790000008 Downgrade Global Swiss -1980 5 months -825 -1179 218 132 4
2020-02 -234 -235 0 0 1
2020-01 -119 -235 116 0 0
2019-12 -120 -235 101 13 0
2019-11 -197 -235 0 37 0
2019-10 -153 -235 0 80 2
0790000071 Downgrade Global Swiss -1972.8 5 months -822 -1179 3 23 332
2020-02 -166 -235 0 11 57
2020-01 -102 -235 0 0 132
2019-12 -177 -235 0 4 53
2019-11 -184 -235 0 0 49
2019-10 -190 -235 0 6 37
0790000035 Downgrade Global Swiss -1953.6 5 months -814 -1179 60 73 232
2020-02 -212 -235 6 5 12
2020-01 -190 -235 12 7 25
2019-12 -107 -235 12 2 113
2019-11 -122 -235 10 52 51
2019-10 -181 -235 18 5 30
0790000020 Downgrade Global Europe -1898.4 5 months -791 -816 0 0 25
2020-02 -163 -163 0 0 0
2020-01 -162 -163 0 0 0
2019-12 -145 -163 0 0 18
2019-11 -163 -163 0 0 0
2019-10 -156 -163 0 0 6
0780000004 Downgrade Global Swiss -1795.2 5 months -748 -1179 38 304 89
2020-02 -230 -235 2 2 0
2020-01 -173 -235 15 45 0
2019-12 -30 -235 8 167 29
2019-11 -179 -235 0 16 39
2019-10 -133 -235 10 71 19
0790000015 Downgrade Global Europe -1668 5 months -695 -816 0 0 121
2020-02 -162 -163 0 0 0
2020-01 -159 -163 0 0 4
2019-12 -162 -163 0 0 0
2019-11 -47 -163 0 0 115
2019-10 -163 -163 0 0 0
0790000007 Downgrade Global Europe -1653.6 5 months -689 -816 0 0 127
2020-02 -141 -163 0 0 21
2020-01 -143 -163 0 0 20
2019-12 -113 -163 0 0 49
2019-11 -136 -163 0 0 27
2019-10 -154 -163 0 0 8
7 mobiles TOTAL -12921.6 5 months -5384 -7164 319 532 930

 
List of mobiles in Pareto group 4

This is the 4th group of mobiles that, together, represent about 20% of the savings

mobile Operation Old New diff/yr Month diff_period Abo Neighb Europe Global
0790000103 Downgrade Global Europe -1485.6 5 months -619 -816 0 0 197
2020-02 -163 -163 0 0 0
2020-01 -163 -163 0 0 0
2019-12 -54 -163 0 0 109
2019-11 -89 -163 0 0 73
2019-10 -148 -163 0 0 14
0790000057 Upgrade Europe Global -1399.2 5 months -583 816 0 0 -1400
2020-02 74 163 0 0 -88
2020-01 1 163 0 0 -161
2019-12 -57 163 0 0 -221
2019-11 -129 163 0 0 -292
2019-10 -472 163 0 0 -635
0790000037 Downgrade Global Swiss -1394.4 5 months -581 -1179 37 0 560
2020-02 -223 -235 0 0 11
2020-01 -213 -235 13 0 8
2019-12 -221 -235 0 0 13
2019-11 -83 -235 2 0 149
2019-10 160 -235 19 0 376
0790000070 Downgrade Global Swiss -1144.8 5 months -477 -1179 28 137 537
2020-02 -108 -235 0 113 14
2020-01 -41 -235 0 0 194
2019-12 -157 -235 26 15 37
2019-11 -120 -235 1 0 113
2019-10 -50 -235 0 7 177
0790000018 Downgrade Global Europe -1048.8 5 months -437 -816 0 0 379
2020-02 -152 -163 0 0 10
2020-01 41 -163 0 0 204
2019-12 -50 -163 0 0 112
2019-11 -155 -163 0 0 8
2019-10 -119 -163 0 0 43
0790000237 Downgrade Europe Swiss -871.2 5 months -363 -363 0 0 0
2020-02 -72 -72 0 0 0
2020-01 -72 -72 0 0 0
2019-12 -72 -72 0 0 0
2019-11 -72 -72 0 0 0
2019-10 -72 -72 0 0 0
0790000200 Downgrade Europe Swiss -840 5 months -350 -363 7 5 0
2020-02 -65 -72 7 0 0
2020-01 -72 -72 0 0 0
2019-12 -72 -72 0 0 0
2019-11 -72 -72 0 0 0
2019-10 -67 -72 0 5 0
0790000203 Downgrade Europe Swiss -835.2 5 months -348 -363 9 6 0
2020-02 -72 -72 0 0 0
2020-01 -70 -72 0 1 0
2019-12 -72 -72 0 0 0
2019-11 -60 -72 9 2 0
2019-10 -71 -72 0 1 0
0790000179 Downgrade Europe Swiss -818.4 5 months -341 -363 0 22 0
2020-02 -70 -72 0 1 0
2020-01 -72 -72 0 0 0
2019-12 -72 -72 0 0 0
2019-11 -64 -72 0 8 0
2019-10 -60 -72 0 12 0
0790000197 Downgrade Europe Swiss -782.4 5 months -326 -363 23 14 0
2020-02 -66 -72 0 4 0
2020-01 -69 -72 1 2 0
2019-12 -65 -72 6 0 0
2019-11 -66 -72 5 0 0
2019-10 -57 -72 9 5 0
0790000243 - Edie Giffy Downgrade Europe Swiss -729.6 5 months -304 -327 16 7 0
2020-02 -72 -72 0 0 0
2020-01 -72 -72 0 0 0
2019-12 -72 -72 0 0 0
2019-11 -51 -72 15 4 0
2019-10 -35 -37 0 1 0
0790000084 Downgrade Europe Swiss -698.4 5 months -291 -363 15 56 0
2020-02 -36 -72 0 35 0
2020-01 -72 -72 0 0 0
2019-12 -72 -72 0 0 0
2019-11 -57 -72 15 0 0
2019-10 -52 -72 0 20 0
0790000088 Downgrade Europe Swiss -698.4 5 months -291 -363 43 29 0
2020-02 -70 -72 1 0 0
2020-01 -72 -72 0 0 0
2019-12 -70 -72 2 0 0
2019-11 -32 -72 38 1 0
2019-10 -45 -72 0 26 0
0790000190 Downgrade Europe Swiss -679.2 5 months -283 -363 4 76 0
2020-02 -68 -72 1 2 0
2020-01 -65 -72 1 5 0
2019-12 -64 -72 0 7 0
2019-11 -70 -72 0 1 0
2019-10 -13 -72 0 58 0
0790000125 Downgrade Europe Swiss -664.8 5 months -277 -363 4 82 0
2020-02 -41 -72 1 29 0
2020-01 -69 -72 1 2 0
2019-12 -71 -72 0 0 0
2019-11 -37 -72 0 34 0
2019-10 -56 -72 0 15 0
15 mobiles TOTAL -14090.4 5 months -5871 -6768 186 434 273

 
List of mobiles in Pareto group 5

This is the 5th and last group of mobiles that, together, represent about 20% of the savings

mobile Operation Old New diff/yr Month diff_period Abo Neighb Europe Global
0790000023 Downgrade Global Swiss -621.6 5 months -259 -1179 174 95 651
2020-02 -7 -235 111 1 114
2020-01 -31 -235 61 0 142
2019-12 -167 -235 0 2 64
2019-11 -64 -235 0 13 157
2019-10 13 -235 0 76 172
0790000139 Downgrade Europe Swiss -578.4 5 months -241 -363 52 70 0
2020-02 -68 -72 3 0 0
2020-01 -68 -72 3 0 0
2019-12 -72 -72 0 0 0
2019-11 -61 -72 10 0 0
2019-10 31 -72 34 69 0
0790000092 Downgrade Neighb Swiss -573.6 5 months -239 -272 33 0 0
2020-02 -49 -54 5 0 0
2020-01 -49 -54 4 0 0
2019-12 -47 -54 6 0 0
2019-11 -48 -54 5 0 0
2019-10 -44 -54 10 0 0
0790000080 Downgrade Neighb Swiss -568.8 5 months -237 -272 35 0 0
2020-02 -53 -54 1 0 0
2020-01 -50 -54 3 0 0
2019-12 -37 -54 16 0 0
2019-11 -41 -54 12 0 0
2019-10 -53 -54 0 0 0
0790000109 Downgrade Europe Swiss -568.8 5 months -237 -363 33 92 0
2020-02 -50 -72 21 0 0
2020-01 -65 -72 1 5 0
2019-12 -68 -72 3 0 0
2019-11 1 -72 6 68 0
2019-10 -54 -72 0 18 0
0790000108 Downgrade Europe Swiss -544.8 5 months -227 -363 72 63 0
2020-02 -60 -72 12 0 0
2020-01 -66 -72 6 0 0
2019-12 3 -72 29 46 0
2019-11 -58 -72 13 0 0
2019-10 -45 -72 10 16 0
0780000003 Downgrade Europe Swiss -535.2 5 months -223 -363 87 53 0
2020-02 -70 -72 0 2 0
2020-01 -68 -72 3 0 0
2019-12 5 -72 72 5 0
2019-11 -57 -72 0 14 0
2019-10 -31 -72 10 30 0
0790000062 Downgrade Global Neighb -518.4 5 months -216 -907 0 6 686
2020-02 -180 -181 0 0 0
2020-01 264 -181 0 0 445
2019-12 11 -181 0 0 193
2019-11 -162 -181 0 5 13
2019-10 -147 -181 0 0 33
0790000013 Downgrade Europe Swiss -513.6 5 months -214 -363 120 29 0
2020-02 -67 -72 1 3 0
2020-01 -10 -72 62 0 0
2019-12 -50 -72 18 4 0
2019-11 -18 -72 32 21 0
2019-10 -66 -72 6 0 0
0790000072 Downgrade Neighb Swiss -501.6 5 months -209 -272 63 0 0
2020-02 -45 -54 9 0 0
2020-01 -49 -54 5 0 0
2019-12 -35 -54 18 0 0
2019-11 -31 -54 23 0 0
2019-10 -47 -54 6 0 0
0790000059 Downgrade Neighb Swiss -487.2 5 months -203 -272 69 0 0
2020-02 -47 -54 7 0 0
2020-01 -54 -54 0 0 0
2019-12 -8 -54 46 0 0
2019-11 -39 -54 15 0 0
2019-10 -54 -54 0 0 0
0790000085 Downgrade Europe Swiss -484.8 5 months -202 -363 3 157 0
2020-02 -56 -72 0 16 0
2020-01 -55 -72 2 14 0
2019-12 -31 -72 0 40 0
2019-11 -41 -72 0 30 0
2019-10 -18 -72 0 54 0
0790000066 Downgrade Europe Swiss -482.4 5 months -201 -363 55 107 0
2020-02 -68 -72 1 2 0
2020-01 -57 -72 0 14 0
2019-12 -64 -72 0 7 0
2019-11 -24 -72 1 45 0
2019-10 14 -72 51 35 0
0790000022 Downgrade Europe Swiss -451.2 5 months -188 -363 126 48 0
2020-02 -30 -72 23 19 0
2020-01 -64 -72 8 0 0
2019-12 -24 -72 47 0 0
2019-11 -22 -72 20 29 0
2019-10 -46 -72 25 0 0
0790000077 Downgrade Europe Swiss -422.4 5 months -176 -363 29 158 0
2020-02 -61 -72 5 5 0
2020-01 -66 -72 6 0 0
2019-12 -71 -72 0 0 0
2019-11 29 -72 14 87 0
2019-10 -5 -72 1 65 0
0780000001 Downgrade Europe Swiss -415.2 5 months -173 -363 138 51 0
2020-02 -62 -72 3 6 0
2020-01 -64 -72 5 2 0
2019-12 -39 -72 2 30 0
2019-11 54 -72 115 12 0
2019-10 -60 -72 11 0 0
0790000118 Downgrade Europe Swiss -403.2 5 months -168 -363 37 158 0
2020-02 -72 -72 0 0 0
2020-01 -72 -72 0 0 0
2019-12 -49 -72 17 5 0
2019-11 -59 -72 12 0 0
2019-10 86 -72 7 151 0
0790000060 Downgrade Global Europe -376.8 5 months -157 -816 0 0 659
2020-02 -17 -163 0 0 145
2020-01 -77 -163 0 0 85
2019-12 -110 -163 0 0 53
2019-11 48 -163 0 0 212
2019-10 0 -163 0 0 162
0790000119 Downgrade Neighb Swiss -372 5 months -155 -272 117 0 0
2020-02 -30 -54 24 0 0
2020-01 -15 -54 39 0 0
2019-12 -37 -54 16 0 0
2019-11 -25 -54 28 0 0
2019-10 -45 -54 8 0 0
0790000094 Downgrade Europe Swiss -367.2 5 months -153 -363 210 0 0
2020-02 21 -72 93 0 0
2020-01 -19 -72 52 0 0
2019-12 -54 -72 17 0 0
2019-11 -47 -72 25 0 0
2019-10 -52 -72 20 0 0
0790000003 Upgrade Neighb Europe -360 5 months -150 91 0 -241 0
2020-02 -19 18 0 -37 0
2020-01 -48 18 0 -66 0
2019-12 16 18 0 -2 0
2019-11 -113 18 0 -132 0
2019-10 15 18 0 -2 0
0790000069 Downgrade Europe Swiss -314.4 5 months -131 -363 64 168 0
2020-02 -25 -72 9 38 0
2020-01 -42 -72 14 16 0
2019-12 -12 -72 2 56 0
2019-11 -17 -72 30 24 0
2019-10 -33 -72 6 32 0
0790000065 Downgrade Europe Swiss -307.2 5 months -128 -363 102 132 0
2020-02 -58 -72 11 2 0
2020-01 -27 -72 6 38 0
2019-12 -62 -72 1 8 0
2019-11 1 -72 32 41 0
2019-10 19 -72 49 42 0
0790000032 Downgrade Global Europe -283.2 5 months -118 -816 0 0 698
2020-02 -161 -163 0 0 2
2020-01 -146 -163 0 0 17
2019-12 474 -163 0 0 638
2019-11 -149 -163 0 0 14
2019-10 -136 -163 0 0 26
0790000130 Downgrade Neighb Swiss -266.4 5 months -111 -272 161 0 0
2020-02 -53 -54 1 0 0
2020-01 -51 -54 2 0 0
2019-12 32 -54 86 0 0
2019-11 13 -54 67 0 0
2019-10 -51 -54 2 0 0
0790000028 - Libbie Ariel Upgrade Swiss Europe -252 5 months -105 363 -296 -172 0
2020-02 11 72 -27 -33 0
2020-01 -37 72 -60 -49 0
2019-12 -76 72 -133 -15 0
2019-11 -5 72 -53 -25 0
2019-10 2 72 -21 -48 0
0790000031 Downgrade Global Swiss -247.2 5 months -103 -1179 67 142 868
2020-02 -120 -235 0 0 114
2020-01 -29 -235 10 6 189
2019-12 18 -235 30 66 156
2019-11 52 -235 25 5 258
2019-10 -23 -235 0 63 148
0790000033 Downgrade Europe Neighb -213.6 5 months -89 -91 0 2 0
2020-02 -16 -18 0 1 0
2020-01 -18 -18 0 0 0
2019-12 -18 -18 0 0 0
2019-11 -18 -18 0 0 0
2019-10 -18 -18 0 0 0
0790000076 Downgrade Europe Neighb -165.6 5 months -69 -91 0 22 0
2020-02 -18 -18 0 0 0
2020-01 -18 -18 0 0 0
2019-12 -18 -18 0 0 0
2019-11 -17 -18 0 1 0
2019-10 2 -18 0 20 0
0790000050 Downgrade Europe Neighb -160.8 5 months -67 -91 0 24 0
2020-02 -14 -18 0 3 0
2020-01 -18 -18 0 0 0
2019-12 -18 -18 0 0 0
2019-11 -11 -18 0 6 0
2019-10 -4 -18 0 14 0
0790000081 Downgrade Europe Neighb -122.4 5 months -51 -91 0 39 0
2020-02 -16 -18 0 2 0
2020-01 -18 -18 0 0 0
2019-12 12 -18 0 30 0
2019-11 -13 -18 0 4 0
2019-10 -15 -18 0 2 0
0790000110 Downgrade Europe Swiss -100.8 5 months -42 -363 80 240 0
2020-02 56 -72 0 128 0
2020-01 -72 -72 0 0 0
2019-12 -56 -72 1 14 0
2019-11 5 -72 78 0 0
2019-10 24 -72 0 97 0
0790000002 Downgrade Europe Swiss -86.4 5 months -36 -363 5 323 0
2020-02 -43 -72 0 28 0
2020-01 16 -72 2 87 0
2019-12 -26 -72 0 45 0
2019-11 -4 -72 2 65 0
2019-10 22 -72 0 95 0
0790000025 Downgrade Europe Swiss -62.4 5 months -26 -363 221 116 0
2020-02 -43 -72 28 0 0
2020-01 63 -72 135 0 0
2019-12 -34 -72 37 1 0
2019-11 -72 -72 0 0 0
2019-10 62 -72 19 115 0
0790000074 Downgrade Europe Swiss -55.2 5 months -23 -363 40 301 0
2020-02 12 -72 2 82 0
2020-01 -10 -72 2 59 0
2019-12 -10 -72 3 58 0
2019-11 2 -72 29 46 0
2019-10 -16 -72 2 53 0
0790000001 Downgrade Europe Neighb -40.8 5 months -17 -91 0 74 0
2020-02 -18 -18 0 0 0
2020-01 -18 -18 0 0 0
2019-12 -17 -18 0 0 0
2019-11 -1 -18 0 16 0
2019-10 38 -18 0 56 0
0790000185 - Paulich Pat Upgrade Swiss Europe -16.8 5 months -7 363 -40 -330 0
2020-02 72 72 0 0 0
2020-01 63 72 -8 0 0
2019-12 -24 72 0 -97 0
2019-11 -114 72 -23 -163 0
2019-10 -4 72 -7 -69 0
37 mobiles TOTAL -12842.4 5 months -5351 -12701 1857 1927 3562

end