can you see me now… good! mapping the results of mobile network monitoring

Can You Can You SeeSee Me Now… Me Now…Good!Good!

Mapping the Results of Mapping the Results of

Mobile Network MonitoringMobile Network Monitoring

Location Intelligence 2008Location Intelligence 2008 22

ContentsContents Introduction to TEMS™ Automatic and Customer DeliverablesIntroduction to TEMS™ Automatic and Customer Deliverables Defining and Targeting the Market Service AreaDefining and Targeting the Market Service Area

Most desirable conditionsMost desirable conditions Selecting the best geospatial method – differing ideasSelecting the best geospatial method – differing ideas

Creating a service boundary based on population densityCreating a service boundary based on population density Achieving the Service Area CommitmentAchieving the Service Area Commitment

Segmenting the service area – formulating BINsSegmenting the service area – formulating BINs Determining dividable and non-drivable areasDetermining dividable and non-drivable areas The Grid Overlay analysis approachThe Grid Overlay analysis approach

The Importance of geodata and Metadata The Importance of geodata and Metadata The role of road classificationsThe role of road classifications Further refining the analysis with land-use geodataFurther refining the analysis with land-use geodata The final contractual drivable BIN modelThe final contractual drivable BIN model

ResultsResults ConclusionsConclusions


Introduction…Can You See Me Now?Introduction…Can You See Me Now?

What TEMS™ Automatic Does – Some BackgroundWhat TEMS™ Automatic Does – Some Background A better way to monitor a wireless mobile networkA better way to monitor a wireless mobile network

• Much faster Much faster

• Does not require a technician to walk staggering distancesDoes not require a technician to walk staggering distances

• It’s an automated “can-you-hear-me-now” guy!It’s an automated “can-you-hear-me-now” guy! TEMS ™ Automatic advantagesTEMS ™ Automatic advantages

• Provides round-the-clock data measurements Provides round-the-clock data measurements

• Eliminates the cost of drive test engineersEliminates the cost of drive test engineers

• Fully scaleable and customizable Fully scaleable and customizable

TEMSTEMS™ Automatic’s system-wide testing assures mobile ™ Automatic’s system-wide testing assures mobile carriers are providing the high-quality voice and data carriers are providing the high-quality voice and data

services their customers demand.services their customers demand.


TEMSTEMS™ Automatic – the Works™ Automatic – the Works The Mobile Testing Unit (MTU)The Mobile Testing Unit (MTU)

• Insures wide-spread random circulationInsures wide-spread random circulation

• Small “black box”, no bigger than a small DVD playerSmall “black box”, no bigger than a small DVD player

• Installed in the truck of taxicabs or other fleet vehiclesInstalled in the truck of taxicabs or other fleet vehicles

While the vehicle is operating, TA autonomously collects valuable air While the vehicle is operating, TA autonomously collects valuable air interface wireless data which is sent via the air to a secure data centerinterface wireless data which is sent via the air to a secure data center

• RSSIRSSI

• Voice ClarityVoice Clarity

• Signal StrengthSignal Strength

• Mobile terminated callsMobile terminated calls

• Dropped CallsDropped Calls

• Failed to connectFailed to connect


What the customer gets for their moneyWhat the customer gets for their money

• A minimum percentage of area covered my MTUs – typically A minimum percentage of area covered my MTUs – typically between 50% to 90%between 50% to 90%

• Progress is evaluated at the middle and end of the monthProgress is evaluated at the middle and end of the month

• Access to all collected dataAccess to all collected data

• Monthly customized technical reportsMonthly customized technical reports

Defining and Targeting the Market Service Area: Defining and Targeting the Market Service Area:

Where Best to Offer the Service for Optimal ResultsWhere Best to Offer the Service for Optimal Results The two vexing problems we encountered:The two vexing problems we encountered:

1.1. What defines the customer’s service area and how do we What defines the customer’s service area and how do we define it?define it?

2.2. What constitutes “coverage” within the service area?What constitutes “coverage” within the service area?

i.e., How does Ericsson get credit – and get paid – for i.e., How does Ericsson get credit – and get paid – for successfully analyzing the customer’s network? successfully analyzing the customer’s network?


Tools and DatasetsTools and Datasets

• What: What: Desktop mapping applicationDesktop mapping application = MapInfo Professional = MapInfo Professional

• Why: Because it was there!...No, because it is widely Why: Because it was there!...No, because it is widely recognized in the wireless telecom industry as a reliable tool recognized in the wireless telecom industry as a reliable tool for market analysisfor market analysis

• What: What: Base map geodata Base map geodata = Tele Atlas MultiNet™ U.S. = Tele Atlas MultiNet™ U.S.

• Why: Because it was also there!...No, because it’s good!Why: Because it was also there!...No, because it’s good!

• What: What: Demographic dataDemographic data (both map and attribute) = U.S. (both map and attribute) = U.S. Census sold by MapInfoCensus sold by MapInfo

• Why: Sole source (Uncle Sam) and it’s also good & cheap!Why: Sole source (Uncle Sam) and it’s also good & cheap! Seeking the most desirable conditions – To begin the process of Seeking the most desirable conditions – To begin the process of

determining what geographic region defines the service area, it determining what geographic region defines the service area, it was necessary to identify the most desirable places to host the was necessary to identify the most desirable places to host the network monitoring service…while excluding less desirable areasnetwork monitoring service…while excluding less desirable areas

• High-volume vehicular traffic – including taxicabs (MTU)High-volume vehicular traffic – including taxicabs (MTU)

• Lots of mobile phone usersLots of mobile phone users


Goal: Good combination of high-volume mobile phone calls made Goal: Good combination of high-volume mobile phone calls made by urban consumers in places where taxicabs can easily reachby urban consumers in places where taxicabs can easily reach

How do we segregate such places How do we segregate such places and and what data do we use to what data do we use to show this on a map?show this on a map?

Seeking the best methods – some ideas put forthSeeking the best methods – some ideas put forth

• Corporate or municipal map boundariesCorporate or municipal map boundaries

ProsPros Readily availableReadily available InexpensiveInexpensive Easy to useEasy to use

Cons (me)Cons (me) Too encompassing of lower Too encompassing of lower populated areaspopulated areas Insufficiently detailed to Insufficiently detailed to showshow concentrations of high concentrations of high volume trafficvolume traffic Ignores Ignores unincorporatedunincorporated areas with high population areas with high population concentrationsconcentrations


• Road Density Road Density (The Premise: more roads = more cars = more people)(The Premise: more roads = more cars = more people)

ProsPros We have itWe have it Easy to explain Easy to explain (to customer)(to customer)

Cons (me, again)Cons (me, again) Digitized road density alone is too Digitized road density alone is too difficult to define and segregatedifficult to define and segregate Arbitrary and not accurately Arbitrary and not accurately measurable in street centerline format measurable in street centerline format (the most common format for digitized (the most common format for digitized roads)roads)

• Population Density – the best indicatorPopulation Density – the best indicator

Pros (me)Pros (me) Correlation between Correlation between relatively high population relatively high population and high vehicular volumeand high vehicular volume Correlation between Correlation between large populations and large populations and increased mobile phone increased mobile phone useuse Yields a finer level of Yields a finer level of spatial detailspatial detail

ConsCons Slightly more expensiveSlightly more expensive Moderate spatial query Moderate spatial query difficultydifficulty Needs careful explanation to Needs careful explanation to “non-spatial thinking” audience“non-spatial thinking” audience


Creating a service boundary based on population densityCreating a service boundary based on population density

• Data set-up – polygons and tabular (attribute) informationData set-up – polygons and tabular (attribute) information– Defining the overall area of interest (AOI) from with the Defining the overall area of interest (AOI) from with the

metropolitan statistical area (MSA)metropolitan statistical area (MSA)

– First step in narrowing down the service areaFirst step in narrowing down the service area

Orange County included at customer’s

request

Los Angeles MSA boundary


– Selecting the corresponding census blocks to fit within the MSASelecting the corresponding census blocks to fit within the MSA

Block

Block Group

Census Tract


– ““Populating” the block groups with demographic dataPopulating” the block groups with demographic data Census block groups are empty polygons at this pointCensus block groups are empty polygons at this point Demographic data are separate – in tabular formatDemographic data are separate – in tabular format The two sets are joined by a unique block ID number called The two sets are joined by a unique block ID number called

BKG_KEYBKG_KEY

– Population density is derived by dividing raw population by the Population density is derived by dividing raw population by the area of each block group (in square miles)area of each block group (in square miles)

Raw Population from data CDRaw Population from data CD

Area of PolygonArea of Polygon= Population Density= Population Density


• Using the population density results to define the service Using the population density results to define the service

boundaryboundary

– Three ranges of population density were established with distinct Three ranges of population density were established with distinct

numeric thresholdsnumeric thresholds

– First step in narrowing down the service areaFirst step in narrowing down the service area

– Threshold guidelines follow those set by the U.S. Census BureauThreshold guidelines follow those set by the U.S. Census Bureau

Dense Urban: Dense Urban: 10,000 or, greater, persons per square mile10,000 or, greater, persons per square mile

Urban: Urban: 1,000 to 9,999 persons per square mile1,000 to 9,999 persons per square mile

Suburban: Suburban: 300 to 999 persons per square mile300 to 999 persons per square mile

– Thematic mapping of the three ranges revealed somewhat Thematic mapping of the three ranges revealed somewhat

predictable population patterns and trends in metro areaspredictable population patterns and trends in metro areas

– Also revealed not-so-predictable patterns such as densely Also revealed not-so-predictable patterns such as densely

populated “edge cities”populated “edge cities”


Thematic map is useful, but far too jagged to effectively segregate areas of common densitiesThematic map is useful, but far too jagged to effectively segregate areas of common densities


Polygons of merged block groups make it easier to isolate areas of common densityPolygons of merged block groups make it easier to isolate areas of common density


– Making a business case: where to restrict service?Making a business case: where to restrict service?

– The DecisionThe Decision: The merger between the : The merger between the Dense UrbanDense Urban and and UrbanUrban layers form the service boundary or “service polygon”layers form the service boundary or “service polygon”

– The service polygon is the basis for the service level agreement The service polygon is the basis for the service level agreement (SLA) with the customer(SLA) with the customer

– Geographically defines the contractual commitment Geographically defines the contractual commitment

– Only data collected within the service polygon will count towards Only data collected within the service polygon will count towards meeting the monthly coverage targetsmeeting the monthly coverage targets

Suburban omitted

Service not requested by customer


Achieving the Service Area CommitmentAchieving the Service Area Commitment The next spatial challenge came from addressing the question of what The next spatial challenge came from addressing the question of what

constitutes TEMS™ Automatic coverage within the service polygon, and how we constitutes TEMS™ Automatic coverage within the service polygon, and how we – the geospatial analyst – display this coverage– the geospatial analyst – display this coverage

MTU circulation inside the service boundary is established by MTU circulation inside the service boundary is established by contractual agreement with the customercontractual agreement with the customer

• Coverage percentage must be met on a monthly basisCoverage percentage must be met on a monthly basis

• There are hefty penalties for missing the markThere are hefty penalties for missing the mark Segmentation of the service area polygon – the primary stepSegmentation of the service area polygon – the primary step

• The entire polygon is divided into 400 x 400 meter (0.25 mi.) parcels The entire polygon is divided into 400 x 400 meter (0.25 mi.) parcels called BINs, for our purposes (0.16 sq. km or 0.062 sq. mi.)called BINs, for our purposes (0.16 sq. km or 0.062 sq. mi.)

• TEMS™ Automatic must collect a TEMS™ Automatic must collect a minimum minimum of ten measurement of ten measurement samples while the host vehicle is traversing the BINsamples while the host vehicle is traversing the BIN

• If ten samples or more are collected, the BIN is declared to be “lit If ten samples or more are collected, the BIN is declared to be “lit up” and counts toward the monthly target service coverage of 80%, up” and counts toward the monthly target service coverage of 80%, in this casein this case

• In other wordsIn other words: TEMS™ Automatic must cover, or light up, 80% of : TEMS™ Automatic must cover, or light up, 80% of the total the total drivable drivable BINs to meet the monthly contractual commitmentBINs to meet the monthly contractual commitment


Drivable vs. Non-drivable BIN: The Great DebateDrivable vs. Non-drivable BIN: The Great Debate

• A GivenA Given: Some surface areas are undrivable by automobile or : Some surface areas are undrivable by automobile or unlikely to be reached by taxicab on a regular basisunlikely to be reached by taxicab on a regular basis

– Water bodiesWater bodies

– Barren landBarren land

– Dirt roadsDirt roads

– Gated communitiesGated communities

– Wooded terrain/ ParklandWooded terrain/ Parkland

– Unpaved surfacesUnpaved surfaces

– Restricted/ Military installationsRestricted/ Military installations

– Airport runwaysAirport runways

• Such non-drivable areas should not be included in the Such non-drivable areas should not be included in the coverage commitmentcoverage commitment

• Drivable areas are those with and abundance of surface roadsDrivable areas are those with and abundance of surface roads

• Determining what is non-drivable becomes a critical function Determining what is non-drivable becomes a critical function since the service provider does not want to be held since the service provider does not want to be held responsible for regions where data is difficult to collectresponsible for regions where data is difficult to collect

• How?How? Two competing methods: One good, the other less so Two competing methods: One good, the other less so


• How?How? Two competing methods (cont.) Two competing methods (cont.)

– Arithmetic approach Arithmetic approach – subtracting the total surface area of both – subtracting the total surface area of both

the land use and water body layers from the service area using the land use and water body layers from the service area using

MapInfoMapInfo

– NOTE: The land use layer from Tele Atlas’ MultiNet™ includes NOTE: The land use layer from Tele Atlas’ MultiNet™ includes

parks, golf courses, cemeteries, universities, large shopping parks, golf courses, cemeteries, universities, large shopping

malls, military installations, sports complexes, airports etc.malls, military installations, sports complexes, airports etc.

GIS analyst found the arithmetic method to be full of holes!GIS analyst found the arithmetic method to be full of holes!

Too nebulous; no way to determine drivability at the Too nebulous; no way to determine drivability at the

individual BIN levelindividual BIN level

Does not take into account areas Does not take into account areas notnot included in the land included in the land

use layer such as gated communitiesuse layer such as gated communities

Widely open to challenge and criticism by the customer as Widely open to challenge and criticism by the customer as

not spatially definednot spatially defined

Difficult to point to on a map (i.e. contract)Difficult to point to on a map (i.e. contract)


The Arithmetic ApproachThe Arithmetic Approach

with park and water layerwith park and water layer

Area = 1,647 square milesArea = 1,647 square miles

park and water layers subtractedpark and water layers subtracted

Area = 1,485 square milesArea = 1,485 square miles

Using the arithmetic approach 162 square miles or 2,622 BINs are non-Using the arithmetic approach 162 square miles or 2,622 BINs are non-drivable…but which ones? Can we point to them?drivable…but which ones? Can we point to them?


– The Grid Overlay Method The Grid Overlay Method – including or excluding individual – including or excluding individual BINs based on the type of roads that pass through it, as well as BINs based on the type of roads that pass through it, as well as other geographic drivability characteristicsother geographic drivability characteristics

Clearly defined; able to Clearly defined; able to establish individual BIN drivability as establish individual BIN drivability as “yes” or “no”“yes” or “no”

Yields a definite drivable/non-drivable BIN count better Yields a definite drivable/non-drivable BIN count better suited for calculating percent of coveragesuited for calculating percent of coverage

Less open to challenge due to its verifiable criteria Less open to challenge due to its verifiable criteria

Mutually agreeable when written into the contract or SOWMutually agreeable when written into the contract or SOW

The Importance of Geodata and Metadata in Generating The Importance of Geodata and Metadata in Generating the Drivable BIN Gridthe Drivable BIN Grid Drawing the base gridDrawing the base grid

• MapInfo Grid Maker ToolMapInfo Grid Maker Tool

• 400m x 400m cells to mimic the BIN database400m x 400m cells to mimic the BIN database


Drawing the base grid (cont.)Drawing the base grid (cont.)

• Overlaid on the service polygon – by this stage contractually Overlaid on the service polygon – by this stage contractually accepted by the customeraccepted by the customer

• Further refining the grid with a simple spatial query:Further refining the grid with a simple spatial query:

BaseGrid.Obj BaseGrid.Obj Entirely WithinEntirely Within Service.Obj Service.Obj

Out

In

25,773 cells (BINs)


– The resulting array is the base BIN count for the marketThe resulting array is the base BIN count for the market

– This is the denominator in the percent drivable/non-drivable formulaThis is the denominator in the percent drivable/non-drivable formula

The Role of Road Classifications – Looking at MetadataThe Role of Road Classifications – Looking at Metadata

• Isolating Isolating high traffichigh traffic volume and volume and free-flowingfree-flowing roads by their roads by their Functional Road Class (FRC)Functional Road Class (FRC)– FRC set by the geodata vendor (Tele Atlas) according to FRC set by the geodata vendor (Tele Atlas) according to

classifications set by state transportation authoritiesclassifications set by state transportation authorities

– Acceptable road classes range from Acceptable road classes range from primary interstate highways primary interstate highways (FRC 00-01) (FRC 00-01) to to local through roads (FRC 06)local through roads (FRC 06)


1. Interstate Highways FRC 00-01

2. Major Roads FRC 02-05

3. Local Roads FRC 06

• Local Roads (FRC 06) – The minimal acceptable road typeLocal Roads (FRC 06) – The minimal acceptable road type– ““Neighborhood” connecting roads Neighborhood” connecting roads with an outletwith an outlet to a major road to a major road

– Practical for taxicabs to traverse during random circulationPractical for taxicabs to traverse during random circulation

– Eliminates the need for cabs to double backEliminates the need for cabs to double back

• Unacceptable Roads – FRC 07-08Unacceptable Roads – FRC 07-08– Not conducive to optimal traffic volume or circulationNot conducive to optimal traffic volume or circulation

– Includes: dead ends, cul-de-sacs, gated communities, alleyways, foot Includes: dead ends, cul-de-sacs, gated communities, alleyways, foot paths and bicycle pathspaths and bicycle paths


• First stage of BIN drivability includes any BIN that contains First stage of BIN drivability includes any BIN that contains any portion of an acceptable FRCany portion of an acceptable FRC

FRC_00_06_Rds.Obj Intersects SecondStageGrid.Obj

Further Refining the Analysis with Land Use Geodata – Further Refining the Analysis with Land Use Geodata – Debate and CompromiseDebate and Compromise

• Another spatial challenge: does topography play a role in Another spatial challenge: does topography play a role in determining a BIN’s drivability?determining a BIN’s drivability?

• GIS analyst said…YES!GIS analyst said…YES!

• Simple Argument: parkland-type terrain along with water Simple Argument: parkland-type terrain along with water bodies should be classified as non-drivable since both lack a bodies should be classified as non-drivable since both lack a practical network of roadspractical network of roads

NOTE: By convention, the land use layer is collectively referred to as “parkland”, NOTE: By convention, the land use layer is collectively referred to as “parkland”, although it contains a variety of land use designations other than recreational parks.although it contains a variety of land use designations other than recreational parks.


• Not-so-simple answer to a vexing spatial challenge: Just how Not-so-simple answer to a vexing spatial challenge: Just how much parkland/water disqualifies a BIN from being drivable?much parkland/water disqualifies a BIN from being drivable?– This is only fair for a customer’s advocate to askThis is only fair for a customer’s advocate to ask

– Should a small neighborhood playground in the middle of an Should a small neighborhood playground in the middle of an otherwise urban area, discount an entire 0.16 sq. km cell criss-otherwise urban area, discount an entire 0.16 sq. km cell criss-crossed by numerous major roads?crossed by numerous major roads?

Does this situation… this…

400m x 400m BIN


• The 50% Compromise: The 50% Compromise: A BIN which has an area totaling 50% A BIN which has an area totaling 50% or greater park/water is deemed non-drivable, no matter how or greater park/water is deemed non-drivable, no matter how many roads traverse it.many roads traverse it.– Rationale Rationale When one-half or more of a BIN’s surface is When one-half or more of a BIN’s surface is

comprised of park/water, the probability of an MTU collecting ten comprised of park/water, the probability of an MTU collecting ten measurement samples is greatly diminishedmeasurement samples is greatly diminished

– Fifty-percent figure reached by mutual agreementFifty-percent figure reached by mutual agreement

– The customer found the rationale acceptable, especially when The customer found the rationale acceptable, especially when examples in the form of maps were providedexamples in the form of maps were provided

– Any threshold is acceptable – 75% or 80% or even 90% Any threshold is acceptable – 75% or 80% or even 90% park/waterpark/water

• Final Spatial Query – How much of a BIN is park or water?Final Spatial Query – How much of a BIN is park or water?– Tele Atlas’ MultiNetTele Atlas’ MultiNet™ land use and water layers did not come with ™ land use and water layers did not come with

an area measurement attributean area measurement attribute

– First step is to merge the two layers into oneFirst step is to merge the two layers into one

– Next, segment the now-seamless layer into BIN-sized dimensions Next, segment the now-seamless layer into BIN-sized dimensions by using the base grid as a “cookie cutter”by using the base grid as a “cookie cutter”


The Geo Cookie CutterThe Geo Cookie Cutter


– Each new park/water “slice” gets a distinct area measurement Each new park/water “slice” gets a distinct area measurement value in square kilometersvalue in square kilometers


– Query out all values Query out all values ≥ 0.08 sq. km (one-half of 0.16 sq. km)≥ 0.08 sq. km (one-half of 0.16 sq. km)

– The resulting values (park/water “big lots”) are used to eliminate The resulting values (park/water “big lots”) are used to eliminate non-drivable BINsnon-drivable BINs

– Query out all BINs that contain the newly-created big lotsQuery out all BINs that contain the newly-created big lots

– The resulting selection of BINs are non-drivable and thus The resulting selection of BINs are non-drivable and thus DELETED!DELETED!

The Final Contractual Drivable BIN ModelThe Final Contractual Drivable BIN Model

• Ericsson presents a map of the drivable BIN model as part of the Ericsson presents a map of the drivable BIN model as part of the service contract and is required to provide TEMS™ Automatic service contract and is required to provide TEMS™ Automatic service to a fixed percentage of these drivable BINsservice to a fixed percentage of these drivable BINs

• Most tactical decisions concerning where to deploy MTUs, how Most tactical decisions concerning where to deploy MTUs, how many taxicabs to use, or which cab companies to recruit are many taxicabs to use, or which cab companies to recruit are based on the final drivable BIN model based on the final drivable BIN model


How We Got Here – The Drivable BINHow We Got Here – The Drivable BIN

1.1. Areas of dense Areas of dense urban or urban urban or urban population densitypopulation density

2.2. Grid cell (BIN) Grid cell (BIN) completely within completely within the service the service boundaryboundary

3.3. BIN traversed by an BIN traversed by an FRC 00-06 road FRC 00-06 road segmentsegment

4.4. Introduce the parks Introduce the parks and water bodies and water bodies layerlayer

5.5. BIN whose surface BIN whose surface area is area is notnot comprised of 50% or comprised of 50% or more park/watermore park/water

6.6. Final drivable BIN Final drivable BIN modelmodel

22,21022,210Drivable BINsDrivable BINs

3,5633,563NonNon--drivable BINsdrivable BINs

25,77325,773Base BIN CountBase BIN Count

22,21022,210Drivable BINsDrivable BINs

3,5633,563NonNon--drivable BINsdrivable BINs

25,77325,773Base BIN CountBase BIN Count


ResultsResultsMain goal of the project was to develop a verifiable Main goal of the project was to develop a verifiable

methodology to determine the number of drivable BINs in a methodology to determine the number of drivable BINs in a given marketgiven market

Prior “non-spatial” efforts to calculate drivable BINs had Prior “non-spatial” efforts to calculate drivable BINs had potential pitfallspotential pitfalls Ill-defined and impreciseIll-defined and imprecise No practical way to articulate or describe in a SOW No practical way to articulate or describe in a SOW Unverifiable, especially by the customer—the ones that count!Unverifiable, especially by the customer—the ones that count! Open to challenge and criticism from both partiesOpen to challenge and criticism from both parties

A GIS leveraged the power of base map and demographic A GIS leveraged the power of base map and demographic geodata to arrive at a geodata to arrive at a spatially spatially quantitativequantitative method that is of method that is of benefit to both customer and service providerbenefit to both customer and service provider


ResultsResultsA GIS leveraged the power of base map and demographic A GIS leveraged the power of base map and demographic

geodata to arrive at a geodata to arrive at a spatially spatially quantitativequantitative method that is of method that is of benefit to both customer and service providerbenefit to both customer and service provider Certifiable and well-definedCertifiable and well-defined Has strict metrics and guidelines which can be verbalized and Has strict metrics and guidelines which can be verbalized and

described in contractual termsdescribed in contractual terms Adaptable to customer’s needsAdaptable to customer’s needs

• Larger market; include the suburban range in the market service areaLarger market; include the suburban range in the market service area• Cover more of a BIN, please; increase the drivable threshold to 75% of Cover more of a BIN, please; increase the drivable threshold to 75% of

park/waterpark/water

ROI very good!ROI very good! Major value from relatively low prices COTS desktop mapping Major value from relatively low prices COTS desktop mapping

application (MapInfo) and geodataapplication (MapInfo) and geodata Relatively small component of the overall business plan solved a Relatively small component of the overall business plan solved a

hugely important issue—where to provide service and how to get hugely important issue—where to provide service and how to get billed for itbilled for it

Effort set the framework for future contractsEffort set the framework for future contracts


ConclusionConclusion

TEMS™ Automatic is a powerful advanced solution to TEMS™ Automatic is a powerful advanced solution to automating mobile network monitoring and optimizationautomating mobile network monitoring and optimization

Ericsson had some challenges to overcome in offering its TA Ericsson had some challenges to overcome in offering its TA service to customersservice to customers

Geospatial practices solved several critical complexitiesGeospatial practices solved several critical complexities

You You Can Can See Me NowSee Me Now

Where best to provide TA service in a major market?Where best to provide TA service in a major market? GEOSPATIAL SOLUTIONGEOSPATIAL SOLUTION

How to define the boundary of this service?How to define the boundary of this service? GEOSPATIAL SOLUTIONGEOSPATIAL SOLUTION

How can the customer see where TA will collect data?How can the customer see where TA will collect data? GEOSPATIAL SOLUTIONGEOSPATIAL SOLUTION

How does Ericsson get paid for the service?How does Ericsson get paid for the service? GEOSPATIAL SOLUTIONGEOSPATIAL SOLUTION

Where is TA service not feasible or possible?Where is TA service not feasible or possible? GEOSPATIAL SOLUTIONGEOSPATIAL SOLUTION

How is all this written into a service contract?How is all this written into a service contract? GEOSPATIAL SOLUTIONGEOSPATIAL SOLUTION

can you see me now… good! mapping the results of mobile network monitoring

Documents

customers service area

market service area

service area commitment

location intelligence

service boundary

data services

minimum percentage of

collected data access