Confusión sexual

Each requirement has been categorized into one of the following categories of business objective from the eTOM framework:

 TTM reduction for customised offerings / Revenue increase / Cost reduction / Convergence / Churn reduction / Customer satisfaction increase / Increase customer insight / Revenue assurance

Business Area Operation al Area Business goal Req.

Id Big Data requirement

Technical area

Acq Ana Cur Sto Usa General General Customer

satisfaction increase

T1 Improve customer experience management by gathering and using huge amounts of data coming from different sources and in different formats in order to have a wider insight of the customer and his habits, needs, likes and dislikes.

X X X X X

Cost reduction

T2

Reduce costs (administration, capEX, opEX) including IT cost control by reduce storage space (thanks to compression or enhancement of data compression techniques). Big Data software cannot be more expensive than traditional one for the same functionality.

X X X X

Cost

reduction T3

Integration of traditional corporate business intelligence systems with new Big

Data technology so that existing hardware is leveraged X X X X X Increase

customer insight

T4

Identify patterns in data to drive insights about consumer behaviour. Quick access to the customer's historical file: bills, payment behaviour, call detail trends, etc. Quickly and accurately process data in near real-time.

X

Increase customer

insight

T5 Obtain a complete view of customers including all relevant sources. Connect data

from all customer interactions to form a 360 degree view X X X Increase

customer insight

T6

Analytics tools which enable powerful querying and manipulation by non- programmers or statisticians. Big Data tools must be easy to use and quickly provide the required information in a comprehensive manner. Visualise data for analytics and metrics (especially for business-technical users)

X

Reduce TTM T7

Real-time reaction. Easy implementation of any data model from any data source with no decrease in performance (real time). Quickly start processing new data types as they become needed. Quick re-programming and minimisation if IT involvement.

Business Area Operation al Area Business goal Req.

Id Big Data requirement

Technical area

Acq Ana Cur Sto Usa

Strategy T8

Clear and stable regulatory framework so Telco&Media players can design a Big Data strategy to fulfil it. There is no need to spend a huge amount of money to discover only later that the planned strategy is not able to be carried out because it is not compliant with current laws

X X X X

Increase customer insight

T9

Identify where do relevant conversations for the sector mostly take place. Retrieve and correlate information such as: number of followers, number of people following, influence rate per follower /followed, contact intensity, mood attributes, recommendations to and by others, school, lifestyle, opinions about products owned, opinions about customer service, opinion, etc.

X X X

Increase customer

insight

T10 Analyse unstructured data with regard to sentiment, topic and other intangible

aspects of text X X Marketing , Product and Customer Operation, Support and Readiness TTM reduction for customised offering T11

Quick availability of different data formats. Different data formats can be attached and retrieved to/from a customer dossier (voice, free text, logs, video and audio, etc.) and later be used for analysis. Different accents and moods must be handled in voice recordings. As for text, CRMs memos might contain typos and hyphens that must be also dealt with.

X

T12 Reduce data loading time X

T13 Need for flexible models that easily adapt to new data sources X

T14

Advanced customer segmentation thanks to demographical data combined with usage data calls in order to identify "user communities" and reveal further information concerning customers

X X X

T15 Reduce time-to-market. The use of Big Data tools should benefit and speed up

marketing processes X X

T16 Build customised offers based on customer loyalty and other behavioural data X X X Fulfilment Cost

reduction T17

Reduced efforts and administrative workload. Real time data feed including early

data curation mechanisms for a better data quality X X X X X

Revenue

increase T18

Assess revenue leakage in the order-to-cash process by ensuring the process can

Business Area Operation al Area Business goal Req.

Id Big Data requirement

Technical area

Acq Ana Cur Sto Usa

Convergence T19

Close gaps in calculation differences across multiple vendors and heterogeneous networks (E.g.: Analyse 500 TB of data from call detail records and inter-carrier invoices daily to help communication service providers identify cost savings and improve services)

X X X

Convergence T20 Integration of data coming from different sales channels. Identification of sales

channel for every operation (PoS, web, call centre, SMS campaign, etc.) X X X

Churn

reduction T21

Optimized service time to customers by improving average speed of answer (enhance customer experience). The most important information across multiple domains must be quickly available at Customer Care

X

Assurance Revenue

assurance T22

Interface to network inventory solutions, service activation solutions and networks discovery information, including several network generations and technologies from different vendors. This information must be presented in a comprehensible way so that non-technical staff can interpret it

X X TTM reduction for customised offering

T23 Price & Product mix optimization for immediate automatic customised offerings X

Churn

reduction T24

Conduct predictive churn management analytics. Analyse customer and social

data in order to prevent churn X

Revenue

increase T25

Cross-selling: Convergent offering for different services and networks (fix and

mobile) X X X X

Customer satisfaction

increase

T26 Location-based marketing: Real time cross-sectorial offerings based on customer

location X X X

Revenue

assurance T27

Business impact analysis: Incorporate the necessary information to keep track of

the business impact of offerings X X X X

Billing Churn

reduction T28

Improvement of real-time services for consumption and billing so that customers can retrieve in real time the information concerning their consumption, for all technologies

Business Area Operation al Area Business goal Req.

Id Big Data requirement

Technical area

Acq Ana Cur Sto Usa

Service Operation, Support and Readiness TTM reduction T29

Optimise service deployment operational time according to historical data

related to every involved node and service platform X X

Fulfilment

Customer satisfaction

increase

T30

Optimized service delivery time to customers. End-to-end real time service measurement. Ensure the process across different platforms and service delivery (e.g. analyse how much time is required for CDR data collection -different services, different times- )

X X X Assurance Increase customer insight T31

Real-time analytics should be able to retrieve information about the subscriber that is available from surrounding systems, network, social networks, etc. CDR and social network information combined in real time. SID model to include social media information (unified information system).

X X X

Revenue

assurance T32

Real-time SLA management and service assurance. Respond to network issues

based on SLAs X X X

Billing

Increase customer

insight

T33 Fast access to billing historical data including multiple data formats, historical

bills and ongoing consumption X X X

Resource Operation, Support and Readiness Revenue assurance T34

Availability of network operational information such as: Call attempts per cell, Cell failures per cell, Handover request per BSC, Calls connected, Calls cleared by user termination, PDP creation time, node attach requests, node attach success rate, Call establishment time, APN usage statistics, including different

technologies (e.g. wireless generations)

X X X X

Fulfilment Revenue

assurance T35

Tools to efficiently plan, process and predict network growth based on past capacity utilization, marketing demand and service consumption trends. Mix network information with social network information in order to anticipate social events that might require additional resources (traffic forecast)

X X X

T36

Accurate real-time network information to accelerate the provisioning success rate. Ability to acquire network and systems information in order to optimise provisioning processes

Business Area Operation al Area Business goal Req.

Id Big Data requirement

Technical area

Acq Ana Cur Sto Usa

Assurance Revenue

assurance T37

Network inventory information including data from network elements, such as cell towers, routers, media gateways, session controllers, switches, etc. Unify different networks with different resources under the same operational framework

X X X

T38

Retrieve and correlate information about network capacity management & resource utilization in order to predict network resource exhaustion in a timely manner

X X X

T39

Network optimisation: Identification of potential problems gathering information from social media (e.g. many similar tweets coming from the same location) and automatic actuation on the network. Reduction of energy consumption based on predictions (e.g. certain BS can be switched off during off peak hours)

X X

Billing Revenue

assurance T40

Consolidated convergent billing: Ability to correlate and analyse billing

information from services delivered by heterogeneous networks, combining CDRs and information data coming from different sources (TV, internet, voice, etc.)

X X X

Supplier/p

artner Fulfilment

Revenue

assurance T41

Point of sales location strategy. Determination of new points of sales' location

based on demographical data X X

Billing Revenue

assurance T42

Identify cost savings and improve services (e.g. analyse TB of data from call detail

records and inter-carrier invoices daily to help communication service providers) X X

Table 6: Requirements for Telco

In document Uso de semioquímicos en el control de plagas. Estudios básicos y de aplicación (página 38-200)