Problems Faced Before ERP Implementation

Problems Faced Before ERP Implementation Some data, coming from SAP R/3, goes directly into SAP NetWeaver BI data marts. But the rest, which comes from diverse systems that handle billing, customer relationship management (CRM), mediation, provisioning, and prepaid sales, goes first to a third-party extract/transform/load (ETL) system. The ETL system takes the data from every call that customers make every payment, every service call, and more and transforms it based on business rules before storing it in a third-party database About Reliance Infocomm Reliance Infocomm is the outcome of the late visionary Dhirubhai Ambanis (1932-2002) dream to herald a digital revolution in India by bringing affordable means of information and communication to the doorsteps of Indias vast population. Make the tools of Infocomm available to people at an affordable cost, they will overcome the handicaps of illiteracy and lack of mobility, Dhirubhai Ambani charted out the mission for Reliance Infocomm in late 1999. He saw in the potential of information and communication technology a once-in-a-lifetime opportunity for India to leapfrog over its historical legacy of backwardness and underdevelopment. Working at breakneck speed, from late 1999 to 2002 Reliance Infocomm built the backbone for a digital India 60,000 kilometres of fibre optic backbone, crisscrossing the entire country. The Reliance Infocomm pan-India network was commissioned on December 28, 2002, the 70th birth anniversary of Dhirubhai. This day also marked his first birth anniversary after his demise July 6, 2002. Reliance Infocomm network is a pan India, high capacity, integrated (wireless and wireline) and convergent (voice, data and video) digital network, designed to offer services that span the entire Infocomm value chain infrastructure, services for enterprises and individuals, applications and consulting. The network is designed to deliver services that will foster a new way of life for India. Clarify clarify CRM is the product of clarify Inc. Customer Relationship Management is a comprehensive business strategy, focused on the process of acquiring, managing, retaining and partnering with selective customers to create superior long-term value for the company and the customers. In a nutshell, CRM strives to identify customers who provide the greatest return to the company, and to optimize relationships with those customers. CRM features Segmenting customers Responding uniquely to the best customers Having a 360 degree view, of a customer Measuring and driving down the cost of customer acquisition Attracting customers using the totality of the experience you provide Need for CRM Customers have the upper hand in most purchase transactions They are inherently less loyal They have rising expectations They no longer tolerate companies that dont get the basics right Advantages of CRM To gain a better understanding of customers wants and needs Allows companies to gather and access information about customers buying histories, preferences, complaints, and other data so they can better anticipate what customers will want. The goal is to instill greater customer loyalty. Used in association with data warehousing, data mining, call centers and other intelligence-based applications Faster response to customer inquiries Increased efficiency through automation Obtaining information sharable with business partners Deeper understanding of Customers Increased marketing and selling opportunities Identifying the most profitable customers Improved products and services through customer feedback Clarify Design Philosophy Flexible Wherever possible rules are held as data in the application Customizable Extremely easy to change look and functionality of screens Can add new fields, tables and relationships to the database Upgradeable We want you to be able to stay current easily Highly scaleable High volume with good response times Comprehensive and open data model More flexibility than most people need Can use any SQL-based tools for reporting, etc Internationalize Ability to deal with multi-currency, different languages, etc Workflow orientated Strong ownership paradigm so nothing falls through the cracks Use of standards The new applications include Clarify Customer Portal which stores customer information and lets customers communicate with a company via methods such as E-mail and online chat. Clarify eOrder lets customers shop online then takes orders and manages them through fulfillment; it works in conjunction with Clarify eConfigurator which determines customer needs and then helps configure complex products. Clarify eMerchandising lets businesses draw from customer analysis data and develop personalized marketing campaigns and product offerings Clarify Applications Call Center: ClearCallCenter Front end for Contact Center Agents Manages overall customer interaction Can be used as sales application 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 Force Automation: ClearSales Handles prospects and leads Sales force automation Provides management of all aspects of the selling cycle, from lead through completed order. Provides an enterprise-wide view of sales and support activities in accounts for ongoing relationship management activities Customer Support: ClearSupport Is a trouble management system Single point of contact for service requests and problem reporting Comprehensive technical support management system, Handles calls that involve service requests, questions, etc. DSS is a data warehousing department that caters to the needs of the management by delivering vital information to business users to make timely and accurate decisions for business growth leading to effective and efficient operations to gain a competitive edge in the marketplace. DSS is a system that Collects data from multiple sources, Summarizes data as per business needs and creates reports at business operations DSS enables business users to centrally monitor and analyse information, monitor various events and enable them to react to those events by providing a single view of business information. DSS is a business-centric data warehousing department with an integrated workflow mechanism that supports streamlined business processes. It delivers high performance access to all information and applications on CRM, Billing, Product and Network domains. CRM applications delivered by a DSS enable business user to analyse number of customers, trends and usage patterns of individual customers, individual customer records, etc. It also holds information about customer service like Interaction and Cases handled by Call Center, Number of Interactions, Interaction Category, Number of Cases, Case Status, Case Category, etc. Product applications provide all pertinent information about the usage and performance of various products like SMS, R-Connect, R-World etc. Billing applications provide all pertinent information about the billing and outstanding of RIM customers. It holds in information of ADC Service Status, Billing Circle, CIOU Code, Channel Code, Channel Type, City, Customer Type, No.of Invoices, and No. of Payments, OG Barred Status, OTAF Month, Payment Option, Rate Plan, Service wise, Month wise, Zero Payment wise Billing Status. DSS offers three kinds of reports namely: OLAP Reports (http://dss.ril.com/) Business Intelligence Reports (http://dssbi.ril.com) Ad hoc Reports based on the data requested by the business user ETL The acronym ETL is used to describe the processes used by DSS to obtain data from external sources and make it usable to the DSS applications. ETL stands for Extract, Transform and Load. Extraction is the process of selecting and pulling data from the operational and external data sources, in order to prepare it for the warehouse. Also called Data Extraction. A good extraction is based on a Business Rule. Business rules are applied to data using constraints. There are two basic ways that the extract process is performed. Either the system providing information will give the DSS team a feeder file. This file will than be accepted by DSS and used to load tables. The other option is for the DSS team to write SQL code and actually perform in place extractions from source systems. In both of these cases, the timing, data volume estimates and source systems impacts need to be considered Transformation is the process of manipulating data. Any manipulation beyond copying is a transformation. Process includes cleansing, aggregating, and integrating data from multiple sources. Example: Address1, Address2, Address3 could be concatenated as one single field. Transformation is the biggest, most complicated, most resource intensive and most important of DSS process. The transformation takes raw, unclean, unformatted, unsynchronized, sparse, and often corrupt data sources and standardizes, cleans and matches it up enough to make it useful for further analysis. . BO Business Objects is a reporting tool for SQL compliant databases. It allows users to prepare custom reports from a number of databases simultaneously, which in turn facilitates advanced reporting and data analysis. Loading is the last step in the ETL process. Loading is nothing more than taking the outputs from the transformation process and putting it into an Oracle table. The process of moving extracted, transformed into the data warehouse. Generally the data is loaded to the Target table. Target table holds 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 allows you to analyze data from operative SAP applications as well as all other business applications and external data sources such as databases, online services and the Internet. The Administrator Workbench functions are designed for controlling, monitoring and maintaining all data retrieval processes. The SAP Business Information Warehouse enables Online Analytical Processing (OLAP), which processes information from large amounts of operative and historical data. OLAP technology enables multi-dimensional analyses from various business perspectives. The Business Information Warehouse Server for core areas and processes, pre-configured with Business Content, ensures you can look at information within the entire enterprise. In selected roles in a company, Business Content offers the information that employees need to carry out their tasks. As well as roles, Business Content contains other pre-configured objects such as InfoCubes, queries, key figures, characteristics that make BW implementation easier. With the Business Explorer, the SAP Business Information Warehouse provides flexible reporting and analysis tools for analyses and decision-making support in your enterprise. You analyze the dataset of the Business Information Warehouse by defining queries for Infocubes using the BEx Query Designer. By selecting and combining InfoObjects (characteristics and key figures) or reusable structures in a query, you determine the way in which you navigate through and evaluate the data in the selected InfoProvider. The layout of the report needs to be pre-defined before design. Reports are the final deliverable to the users. The process of report definition starts with requirement and ends with its development and testing by Business Analysts. During this process the Business Analysts interacts with report developer closely and fine tunes the outcomes in a back and forth form of process. The developer in turn technically chooses the InfoObjects (characteristics and key figures) already defined in the cube that needs to become part of the report. Benefits From the day we started operating our business, our managers had information about the traffic, how the products we launched into the market were performing, how our customers were using them, how we were acquiring new customers, and our customer interactions, Gupta explains. All these things helped us to provide services with lower costs, which is one of the reasons we were able to win the market. SAP NetWeavers ability to span corporate silos and offer a single view of corporate information lets the DSS team deliver solutions 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 Infocomms success possible. An aggregate enhances performance by duplicating the data from an InfoCube and storing it in a summarized form so you can access it quickly for reporting. If you want great performance results with reports and you do use aggregates. Using SAP NetWeavers aggregate tool lets you increase flexibility while designing and can sometimes let you meet more than one business requirement with the same model. SAP Opportunities: 1. Integration Integration can be the highest benefit of them all. The only real project aim for implementing ERP is reducing data redundancy and redundant data entry. If this is set as a goal, to automate inventory posting to G/L, then it might be a successful project. Those companies where integration is not so important or even dangerous tend to have a hard time with ERP. ERP does not improve the individual efficiency of users, so if they expect it, it will be a big disappointment. ERP improves the cooperation of users. 2. Efficiency Generally, ERP software focuses on integration and tend to not care about the daily needs of people. I think individual efficiency can suffer by implementing ERP. the big question with ERP is whether the benefit of integration and cooperation can make up for the loss in personal efficiency or not. 3. Cost reduction It reduces cost only if the company took accounting and reporting seriously even before implementation and had put a lot of manual effort in it. If they didnt care about it, if they just did some simple accounting to fill mandatory statements and if internal reporting did not 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. People are accurate, not software. What ERP does is makes the lives of inaccurate people or organization a complete hell and maybe forces them to be accurate (which means hiring more people or distributing work better), or it falls. Challenges Even though the company started its DSS before the sales side launched, it still had to deal with multiple data sources across heterogeneous platforms a common issue for most organizations working with business intelligence (BI), and a challenge perfect for SAP NetWeaver Business Intelligence (SAP NetWeaver BI). Data granularity More granular models require higher data loads and more maintenance. While designing a model, its critical to keep the principles of star schema in mind. Star schema is generally considered the simplest data warehouse schema, and its characterized by very large fact tables that contain the primary information in the data warehouse in conjunction with smaller dimension tables that contain information about particular attributes of the data in the larger fact table. With this in mind, your model should achieve data summarization by a factor of 1:3 so that youre not working with more than 33 percent of your source data. Dimensions Group your information objects into dimensions so that each dimension has a balanced number of records, and put frequently used characteristics into one dimension so you can cut down on the number of table JOINs needed for the OLAP processor to churn out the data. Data deletion If you want to scale, you need to have a data-deletion process in place that the application owners have clearly agreed to and understood, and you need to have the deletion process in place at the modeling stage. Navigational attributes By using navigational attributes in SAP NetWeaver, you can maintain data consistency when dimensions change slowly, and you can reduce data-storage requirements, but you have to analyze this during the modeling stage to get the benefits. Problems the company would have been forced to have multiple copies and different views of the same data. Implementation Timetable 1999 Forms and begins construction of fiber-optic networks Late 2002 Launches and creates first Bl application March 2003 Has commercial launch Mid 2003 DSS starts rolling out Bl application July 2003 Gains 1 million new subscribers Late 2003/ early 2004 Bl applications roll out to additional locations. Six Critical Recommendations Guptas initial decision-support team of three people augmented by BI consultants from around the world has now grown to 65 staff members and counting. Gupta and his DSS team offer some critically important recommendations to those planning an SAP NetWeaver BI implementation. 1] Plan to scale. One way or another, all BI systems get bigger. Some get bigger because businesses keep generating data they dont really need, but most often products, pricing, and markets become increasingly complex, which is true for Reliance Infocomm. In order to compete, the company must span diverse geographies and offer a variety of products and services as business analysts identify shifting customer needs. In addition, the sheer growth in the number of customers presents the most obvious scalability issue. We are expecting the business to grow from 14 million customers to 20 million customers by the end of 2006, Gupta says. Those are the kinds of estimates we have to work with. 2] Involve the business. Simple at first glance, this fundamental rule is often overlooked but is critical to a DSS. At Reliance Infocomm, each analytic application has a business sponsor who owns the application, in addition to business analysts who help to translate the business requirements into IT implementation terms. This all affects how the DSS team sets up InfoCubes for the business units. How you model your business requirement with SAP NetWeaver is the most important thing, Gupta notes. If your model is bad, its not going to work and the information is never going to come out. So, mapping all your business objects into a multidimensional cube is the most important step and SAP NetWeavers features are excellent for modeling. When its time to build analytic applications, the DSS team builds only solutions that have clear business owners attached. This is critical for two reasons: First, business owners 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 will get launch support to correct unforeseen problems quickly, as well as see that the users start putting the applications to use. How many awesome applications are built each year that fail for lack of use or business alignment? For this DSS team, that just doesnt happen. 3] Ensure data trust. Another problem with many BI installations is a lack of user trust of the systems, and it can happen at any level numbers dont match in front of a line-of-business manager or customers on the other end of the phone dispute the information available to your call-center employees. Business analysts, Gupta says, can be invaluable in resolving problems as the DSS team consolidates data from disparate systems into layers for the InfoCubes. Sometimes there can be a problem with the interpretation of the data, adds Arun Dhall, lead architect for Reliance Infocomms DSS team. For example, when you look at the number of customers acquired yesterday, people who just filled out the application form could be new customers, but as weve defined it, when a person actually registers with the network, thats when they become a customer. Its these common definitions used across the business especially when the numbers are both essentially accurate that build ongoing positive momentum for DSS applications. 4] Delete! Delete! Delete! At 3.5 terabytes (TB) in SAP NetWeaver and 30TB altogether, Reliance Infocomms DSS system is one of the largest in the world, but that doesnt mean it has to grow astronomically. To combat data bloat, We have very clear data-retention policies in place that decide how long the data is stored, Gupta says. We have 400 million records coming over per day, so if we were going to store all this information, it would be multi-hundred TB by now. This again, Gupta says, comes back to the business owners who understand that theres a cost to keeping information and who must decide how long they really need it. From an IT perspective, this policy not only keeps your data growth under control, it helps force the business managers to focus on what they really need from the DSS to achieve the desired results. 5] Dont skimp on look and feel. Many in-house applications are functional, but they look terrible and are hard to understand, which can adversely affect the success of the application more than IT bugs. You should be able to make a report that is not complicated and is easy to understand, Gupta says. If you give users a complex report, they will never use it. At every level, Reliance Infocomm employees are using DSS. Part of every application rollout is end-user education, and the company is now at the point where product managers want their own data marts so they can analyze the information themselves. Also, Gupta says, the information should come out fast. The largest Reliance InfoCube has close to 1 billion rows, and yet it generates consistent response times that let employees act in less than a minute. 6] Always chase and never give up. Guptas DSS team lives by this motto, which basically means that IT is empowered to push hard to find or chase down answers to any technical question or goal. The DSS team is very persistent, Gupta says, and it comes down to a culture of believing that anything is possible. If we can think it, we can do it, says Pramod Kejriwal, development lead for the DSS team. Our philosophy is we dont believe in giving anything up very easily. The philosophy has infected the business owners, too. Anything they think they need to help do their business in a better way, they ask; they should be thinking about business, not [whether something] is technically possible. Into the Future For now, the numbers clearly speak to Reliance Infocomms DSS success: More than 1,500 active users across India, 250 concurrently, more than 150 applications, more than 300 online analytical processing (OLAP) reports, more than 300 SAP NetWeaver BI reports, more than 200 monthly ad hoc reports all working with more than 24TB of data which make Reliance Infocomms DSS, an in-house implementation, one of the largest data warehouses in the world. More fundamentally important, though, is the fact that business users have adopted the DSS implementation as the single and most authentic source of corporate information, Gupta notes, which speaks to the companys ability to scale into the future. On the drawing board, Gupta looks forward to information broadcasting and implementing creative collaboration rooms using a revamped SAP NetWeaver Visual Composer (in SAP NetWeaver 2004s), management cockpit, planning and simulation model, data mining (APD), and actively working on even higher-performance analytics by using SAP Business Intelligence Accelerator (SAP BI Accelerator; also part of SAP NetWeaver 2004s) as an appliance tool with separate hardware that can index an InfoCube, which you can then use to run very fast queries. Whatever comes next, Reliance Infocomm has used SAP NetWeaver BI to create a DSS capable of handling one of the worlds largest BI workloads both now and in the future. Challenges with SAP: 1. Expensive This entails software, hardware, implementation, consultants, training, etc. Or you can hire a programmer or two as an employee and only buy business consulting from an outside source, do all customization and end-user training inside. That can be cost-effective. 2. Not very flexible It depends. SAP can be configured to almost anything. In Navision one can develop almost anything in days. Other software may not be flexible.