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Problems Confronted Before ERP Implementation

Some data, via SAP R/3, runs directly into SAP NetWeaver BI data marts. But the rest, which comes from diverse systems that manage billing, customer relationship management (CRM), mediation, provisioning, and pre-paid sales, will go first to a third-party remove/transform/load (ETL) system. The ETL system requires the data from every call that customers make - every repayment, every service call, and much more - and transforms it predicated on business guidelines before stocking it in a third-party database

About Reliance Infocomm

Reliance Infocomm is the outcome of the past due visionary Dhirubhai Ambani's (1932-2002) goal to herald an electronic trend in India by bringing affordable method of information and communication to the doorsteps of India's vast population.

"Make the various tools of Infocomm available to people at an inexpensive cost, they will defeat the handicaps of illiteracy and lack of range of motion", Dhirubhai Ambani charted out the mission for Reliance Infocomm in late 1999. He observed in the potential of information and communication technology a once-in-a-lifetime chance of India to leapfrog over its historical legacy of backwardness and underdevelopment.

Working at breakneck swiftness, from later part of the 1999 to 2002 Reliance Infocomm built the backbone for a digital India - 60, 000 kilometres of fibre optic backbone, crisscrossing the whole country. The Reliance Infocomm pan-India network was commissioned on December 28, 2002, the 70th - beginning wedding anniversary of Dhirubhai. Today also proclaimed his first beginning anniversary after his demise July - 6, 2002.

Reliance Infocomm network is a skillet India, high capacity, included (wireless and wireline) and convergent (voice, data and video) digital network, made to offer services that course the whole Infocomm value chain - infrastructure, services for companies and individuals, applications and consulting. The network is designed to deliver services that will foster a fresh life-style for India.

Clarify

clarify CRM is the merchandise of clarify Inc.

Customer Romantic relationship Management is a comprehensive business strategy, centered on the procedure of acquiring, handling, keeping and partnering with selective customers to make superior long-term value for the business and the customers.

In a nutshell, CRM strives to recognize customers who provide the greatest go back to the company, and to optimize connections with those customers.

CRM features -

Segmenting customers

Responding uniquely to the best customers

Having a 360 level view, of your customer

Measuring and driving a car down the price tag on customer acquisition

Attracting customers using the totality of the knowledge you provide

Need for CRM

Customers have upper submit most purchase transactions

They are inherently less loyal

They have rising expectations

They no more tolerate companies that don't get the basics right

Advantages of CRM

To gain an improved understanding of customer's needs and needs

Allows companies to gather and access information about customers' buying histories, choices, problems, and other data to allow them to better assume what customers will want.

The goal is to instill increased customer loyalty.

Used in association with data warehousing, data mining, call centers and other intelligence-based applications

Faster reaction to customer inquiries

Increased efficiency through automation

Obtaining information sharable with business partners

Deeper understanding of Customers

Increased marketing and advertising opportunities

Identifying the most profitable customers

Improved products and services through customer feedback

Clarify Design Philosophy

Flexible

Wherever possible guidelines are organised as data in the application

Customizable

Extremely easy to improve look and functionality of screens

Can add new fields, tables and connections to the database

Upgradeable

We want you to definitely be able to stay current easily

Highly scaleable

High level with good response times

Comprehensive and open up data model

More flexibility than most people need

Can use any SQL-based tools for confirming, etc

Internationalize

Ability to deal with multi-currency, different languages, etc

Workflow orientated

Strong ownership paradigm so little or nothing falls through the cracks

Use of standards

The new applications include Clarify Customer Portal which stores customer information and lets customers communicate with an organization via methods such as E-mail and online chat. Clarify eOrder enables customers shop online then can take purchases and manages them through fulfillment; it works in conjunction with Clarify eConfigurator which decides customer needs and then helps configure complicated products. Clarify eMerchandising allows businesses bring from customer analysis data and develop individualized marketing promotions and product offerings

Clarify Applications

Call Middle: ClearCallCenter

Front end for Contact Middle Agents

Manages overall customer interaction

Can be used as sales software or as a front-end to ClearSupport for hybrid sales/service. Operates in both relationship-based call centers and high-volume, "one and done" sales environments

Sales Make Automation: ClearSales

Handles leads and leads

Sales drive automation

Provides management of most areas of the selling circuit, from lead through completed order. Provides an enterprise-wide view of sales and support activities in accounts for ongoing romantic relationship management activities

Customer Support: ClearSupport

Is a trouble management system

Single point of contact for service demands and problem reporting

Comprehensive tech support team management system, Holders calls that involve service requests, questions, etc.

DSS is a data warehousing office that caters to the needs of the management by delivering essential information to business users to make well-timed and accurate decisions for business growth resulting in effective and efficient operations to gain a competitive border available on the market.

DSS is a system that Collects data from multiple sources, Summarizes data according to business needs and creates information at business operations

DSS permits business users to centrally keep an eye on and analyse information, screen various events and enable these to react to those events by providing an individual view of business information. DSS is a business-centric data warehousing office with a workflow device that supports streamlined business functions. It delivers high performance usage of all information and applications on CRM, Billing, Product and Network domains.

CRM applications delivered by way of a DSS allow business user to analyse number of customers, fads and usage patterns of individual customers, individual customer files, etc. In addition, it keeps information about customer support like Connections and Cases completed by Call Center, Number of Interactions, Interaction Category, Number of instances, Case Status, Circumstance Category, etc.

Product applications provide all essential information about the use and performance of varied products like Text message, R-Connect, R-World etc.

Billing applications provide all relevant information about the billing and excellent of RIM customers. It retains in information of ADC Service Position, Billing Circle, CIOU Code, Channel Code, Route Type, City, Customer Type, No. of Invoices, no. of Repayments, OG Barred Status, OTAF Month, Payment Option, Rate Plan, Service wise, Month wise, No Payment wise Billing Position.

DSS offers three varieties of reports particularly:

OLAP Records (http://dss. ril. com/)

Business Intelligence Accounts (http://dssbi. ril. com)

Ad hoc Studies based on the data requested by the business enterprise user

ETL

The acronym ETL is used to describe the processes utilized by DSS to acquire data from exterior sources and make it usable to the DSS applications. ETL stands for Extract, Transform and Fill.

Extraction is the process of selecting and tugging data from the operational and exterior data sources, to be able to prepare it for the warehouse. Also called Data Extraction. An excellent extraction is dependant on a 'Business Guideline'. Business guidelines are applied to data using constraints.

There are two basic techniques the extract process is conducted. Either the machine providing information will give the DSS team a "feeder file". This data file will than be accepted by DSS and used to fill desks. The other option is for the DSS team to create SQL code and actually perform in place extractions from source systems. In both of these situations, the timing, data volume estimations and source systems influences need to be considered

Transformation is the process of manipulating data. Any manipulation beyond copying is a change. Process includes purifying, aggregating, and integrating data from multiple sources.

Example: Address1, Address2, Address3 could be concatenated as you solitary field.

Transformation is the biggest, most complicated, most source intensive and most important of DSS process. The change takes uncooked, unclean, unformatted, unsynchronized, sparse, and often corrupt data sources and standardizes, cleans and matches it up enough to make it useful for further research.

.

BO

Business Things is a reporting tool for SQL compliant databases. It allows users to get ready custom reviews from a number of databases together, which in turn facilitates advanced confirming and data evaluation.

Loading is the last part of the ETL process. Launching is nothing more than taking the outputs from the change process and adding it into an Oracle desk. The procedure of moving extracted, altered in to the data warehouse. Usually the data is packed to the mark table. Target stand supports the intermediate or final results of any part of the ETL process. The target of the entire ETL process is the data warehouse.

BW

The SAP Business Information Warehouse gives you to analyze data from operative SAP applications as well as all other business applications and external data options such as directories, online services and the web. The Administrator Workbench functions are suitable for handling, monitoring and keeping all data retrieval procedures.

The SAP Business Information Warehouse enables Online Analytical Handling (OLAP), which steps information from large amounts of operative and historical data. OLAP technology permits multi-dimensional analyses from various business perspectives. THE BUSINESS ENTERPRISE Information Warehouse Server for center areas and techniques, pre-configured with Business Content, ensures you can try information within the complete enterprise. In picked roles in a firm, Business Content offers the information that employees need to carry out their tasks. Aswell as functions, Business Content is made up of other pre-configured items such as InfoCubes, queries, key numbers, characteristics that produce BW implementation easier.

With the Business Explorer, the SAP Business Information Warehouse provides adaptable reporting and research tools for analyses and decision-making support in your venture. You review the dataset of the Business Information Warehouse by determining questions for Infocubes using the BEx Query Artist. By selecting and mingling InfoObjects (characteristics and key figures) or reusable set ups in a query, you determine the way in which you get around through and measure the data in the determined InfoProvider. The design of the report must be pre-defined before design. Accounts are the last deliverable to the users.

The procedure for report definition starts off with need and ends with its development and testing by Business Analysts. During this process the Business Analysts interacts with record developer meticulously and fine music the final results in a back and forth form of process. The builder in turn technically decides the InfoObjects (characteristics and key characters) already identified in the cube that needs to become area of the report.

Benefits

"From your day we started working our business, our professionals experienced information about the traffic, how the products we launched in to the market were undertaking, how our customers were utilizing them, how we were acquiring new customers, and our customer connections, " Gupta points out. "Each one of these things helped us to provide services with lower costs, which is one of the reason why we were able to win the marketplace. "

SAP NetWeaver's capacity to span corporate silos and give you a one view of corporate information enables the DSS team deliver alternatives quickly and accurately. For instance, approximately 95 percent of the data is loaded from non-SAP systems, with 18 million records processed daily, and SAP NetWeaver is the key factor that made Reliance Infocomm's success possible.

An aggregate enhances performance by duplicating the data from an InfoCube and stocking it in a summarized form so you can get access to it quickly for confirming. If you'd like great performance results with reviews - and also you do - use aggregates. Using SAP NetWeaver's aggregate tool lets you increase versatility while planning and will often enable you to meet more than one business necessity with the same model.

SAP Opportunities:

1. Integration

Integration can be the highest good thing about them all. The only real project shoot for employing ERP is minimizing data redundancy and redundant data admittance. If this is set as a goal, to automate inventory posting to G/L, then it could be a successful task. Those companies where integration is not so important or even dangerous generally have trouble with ERP. ERP will not improve the specific efficiency of users, so if indeed they expect it, it'll be a huge disappointment. ERP enhances the assistance of users.

2. Efficiency

Generally, ERP software targets integration and have a tendency to not value the daily needs of individuals. I think specific efficiency can go through by utilizing ERP. the big question with ERP is if the good thing about integration and assistance can make up for the loss in personal efficiency or not.

3. Cost reduction

It reduces cost only when the company took accounting and reporting very seriously even before execution and had put a great deal of manual work in it. If indeed they didn't care about it, if they just do some simple accounting to fill up mandatory statements and if internal reporting didn't exists of has not been fincancially-oriented, then no cost is reduced.

4. Less personnel

Same as above. Less reporting or accounting personnel, but more sales assistants etc.

5. Accuracy

No. Folks are accurate, not software. What ERP will is makes the lives of inaccurate people or group a whole hell and maybe forces these to be correct (this means hiring more folks or distributing work better), or it falls.

Challenges

Even though the company began its DSS prior to the sales part launched, it still experienced to cope with multiple data options across heterogeneous programs - a common issue for some organizations working with business intelligence (BI), and a challenge exquisite for SAP NetWeaver Business Intelligence (SAP NetWeaver BI).

Data granularity - More granular models require higher data tons plus more maintenance. While making a model, it's critical to keep carefully the principles of celebrity schema at heart. Star schema is normally considered the simplest data warehouse schema, and it's really characterized by very large fact tables which contain the principal information in the info warehouse together with smaller dimension dining tables which contain information about particular characteristics of the data in the larger fact table. With this in mind, your model should achieve data summarization by one factor of 1 1:3 so that you're not working with an increase of than 33 percent of your source data.

Dimensions - Group your information objects into sizes so that each dimension has a balanced number of details, and put frequently used characteristics into one aspect and that means you can lessen the number of table JOINs needed for the OLAP cpu to turn out the info.

Data deletion - If you want to scale, you must have a data-deletion process set up that the application owners have plainly agreed to and comprehended, and you need to have the deletion process in place at the modeling stage.

Navigational traits - By using navigational attributes in SAP NetWeaver, you can maintain data regularity when measurements change slowly, and you may reduce data-storage requirements, nevertheless, you have to investigate this during the modeling stage to get the benefits.

Problems

the company could have been forced to have multiple copies and various views of the same data.

Implementation Timetable

1999 Forms and begins engineering of fiber-optic networks Late

2002 Launches and creates first Bl program March

2003 Has commercial introduction Mid

2003 DSS starts moving out Bl software July

2003 Gains 1 million new subscribers Late 2003/

early 2004 Bl applications move out to additional locations.

Six Critical Recommendations

Gupta's first decision-support team of three people - augmented by BI consultants from about the world - has grown up to 65 workers and counting. Gupta and his DSS team offer some "critically important" recommendations to prospects planning an SAP NetWeaver BI execution.

1] Plan to scale. One way or another, all BI systems get bigger. Some get bigger because businesses keep creating data they don't actually need, but frequently products, charges, and market segments become increasingly intricate, which holds true for Reliance Infocomm. To be able to compete, the company must span diverse geographies and give you a variety of products and services as business experts identify shifting customer needs. In addition, the sheer growth in the number of customers presents the most apparent scalability issue. "We are expecting the business to develop from 14 million customers to 20 million customers by the finish of 2006, " Gupta says. "Those are the kinds of quotes we have to use. "

2] Involve the business. Simple at first glance, this fundamental guideline is often overlooked but is crucial to a DSS. At Reliance Infocomm, each analytic request has a business sponsor who "owns" the application form, in addition to business analysts who help translate the business enterprise requirements involved with it implementation conditions. This all affects how the DSS team sets up InfoCubes for the business units.

"The method that you model your business requirement with SAP NetWeaver is the most crucial thing, " Gupta records. "Should your model is bad, it's not going to work and the info is never heading to come out. So, mapping your business things into a multidimensional cube is the most crucial step - and SAP NetWeaver's features are excellent for modeling. "

When it is time to build analytic applications, the DSS team builds only solutions that have clear companies attached. This is critical for two reasons: First, companies come to the DSS team only with business-driven needs (as opposed to IT offering what it thinks the business might need). Second, the DSS team knows it'll get unveiling support to improve unexpected problems quickly, as well as observe that the users start putting the applications to utilize. How many magnificent applications are designed each year that fail for insufficient use or business position? For this DSS team, that just doesn't happen.

3] Ensure data trust. Another problem with many BI installations is too little end user trust of the systems, and it can happen at any level - numbers don't match in front of a line-of-business director or customers on the other end of the telephone dispute the information open to your call-center employees. Business analysts, Gupta says, can be important in resolving problems as the DSS team consolidates data from disparate systems into layers for the InfoCubes.

"Sometimes there may be a difficulty with the interpretation of the info, " gives Arun Dhall, lead architect for Reliance Infocomm's DSS team. "For instance, when you go through the number of customers acquired yesterday, people who just filled out the application form form could be 'new customers, ' but as we've described it, when a person actually registers with the network, that's when they become a customer. " It's these common definitions used over the business - particularly when the volumes are both essentially appropriate - that build ongoing positive momentum for DSS applications.

4] Delete! Delete! Delete! At 3. 5 terabytes (TB) in SAP NetWeaver and 30TB totally, Reliance Infocomm's DSS system is one of the major on the globe, but that doesn't mean it has to grow astronomically. To combat data bloat, "We've clear data-retention policies in place that determine how long the info is stored, " Gupta says. "We have 400 million files coming over per day, so if we were heading to store all of this information, it would be multi-hundred TB by now. "

This again, Gupta says, comes back to the business owners who understand that there's a cost to keeping information and who must decide how long they actually need it. From an IT point of view, this policy not only retains your data growth under control, it can help force the business managers to concentrate on what they really need from the DSS to achieve the desired results.

5] Don't skimp on appear and feel. Many in-house applications are efficient, but they look awful and are hard to comprehend, which can adversely affect the success of the application more than IT insects. "You ought to be able to make a written report that is not complicated and is not hard to understand, " Gupta says. "If you give users a complicated report, they will never use it. " At every level, Reliance Infocomm employees are employing DSS. Part of each software rollout is end-user education, and the business is now at the main point where product managers want their own data marts to allow them to analyze the information themselves. Also, Gupta says, the information should turn out fast. The major Reliance InfoCube has near to 1 billion rows, yet it generates consistent response times that let employees act in under a minute.

6] Always chase rather than give up. Gupta's DSS team lives by this motto, which basically means that IT is empowered to press difficult to find - or run after down - answers to any technological question or goal. The DSS team is very continual, Gupta says, and it comes down to a culture of thinking that anything can be done.

"If we can think it, we can do it, " says Pramod Kejriwal, development business lead for the DSS team. "Our idea is we don't believe in presenting anything up very easily. " The idea has infected the business owners, too. "Anything they think they have to help do their business in a much better way, they ask; they must be considering business, not [whether something] is technically possible. "

Into the Future

For now, the quantities clearly speak to Reliance Infocomm's DSS success: A lot more than 1, 500 lively users across India, 250 concurrently, more than 150 applications, more than 300 online analytical processing (OLAP) accounts, more than 300 SAP NetWeaver BI reports, more than 200 regular monthly ad hoc information - all dealing with more than 24TB of data - which make Reliance Infocomm's DSS, an in-house implementation, one of the greatest data warehouses in the world.

More fundamentally important, though, is the fact that business users have implemented the DSS execution as "the solo and most legitimate source of commercial information, " Gupta records, which talks to the company's ability to size in to the future.

On the pulling board, Gupta appears forward to information broadcasting and putting into action creative cooperation rooms using a revamped SAP NetWeaver Aesthetic Composer (in SAP NetWeaver 2004s), management cockpit, planning and simulation model, data mining (APD), and positively focusing on even higher-performance analytics by using SAP Business Intellect Accelerator (SAP BI Accelerator; also part of SAP NetWeaver 2004s) as an machine tool with distinct hardware that can index an InfoCube, which you can then use to perform very fast inquiries.

Whatever comes next, Reliance Infocomm has used SAP NetWeaver BI to make a DSS capable of handling one of the world's largest BI workloads - both now and in the future.

Challenges with SAP:

1. Expensive

This requires software, hardware, implementation, consultants, training, etc. Or you can work with a programmer or two as a worker in support of buy business consulting from an outside source, do all customization and end-user training inside. That may be cost-effective.

2. Not so flexible

It is dependent. SAP can be configured to almost anything. In Navision one can develop almost anything in days. Other software may not be adaptable.

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