Sales and Marketing Analytics: Navigating Uncharted Waters How to Transform While You Perform

Transcription

1 Cognizant White Paper Sales and Marketing : Navigating Uncharted Waters How to Transform While You Perform The year 2009 finds the world in a state of unprecedented economic angst and uncertainty. Medical device and diagnostics suppliers, once largely immune to economic downturns, now are following other industries in finding ways to get the most out of every customer relationship and interaction. To do so, many companies have realized they must become much better at converting commercial data into true customer insights through the use of sales and marketing analytics. For many device companies, it s daunting to address the gaps that exist in their sales and marketing analytics capabilities. The challenge is compounded by the fact that companies wanting to improve their business/customer insights capabilities must do so while continuing to meet aggressive sales and profit goals. So, device companies must find a way to transform while they perform. This white paper discusses how your company can make quick and steady progress toward true sales and marketing insights by deploying a framework that incorporates tools and processes, coupled with a focus on enabling IT infrastructure. This transformation can be completed while continuing to perform, so as to achieve both top-line revenue and bottom-line profit growth. Getting Started: The Framework Figure 1 below shows a framework that can be used to facilitate the transformation of your sales and marketing analytics capabilities. Let s start with a short description of each element of this framework, including why it s important and typical challenges faced by medical device companies, and then move on to its application. This framework can be used as an effective diagnostic tool, discussed in the subsequent section, to help understand your company s current performance and to serve as a blueprint to prioritize potential improvement efforts. Customer Master Formulary/Plan Customer Master Data Bridge Formulary/Plan Files Data Bridge Files Direct Sales Data Direct Sales Data Contracts/Discounts Procedure Data Demographics Demographics DATA Charter Account Performance Rep Performance New Product Uptake Account Performance Rep Performance New Product Uptake Field Field Reporting Reporting Local Market Analysis Local Market Analysis PERFORMANCE MEASUREMENT CUSTOMER/ BUSINESS INTELLIGENCE ENGINE STRATEGIC ANALYTICS Sales Force Size/Structure Sales Force Size/Structure Tradeoff Analysis Tradeoff Analysis Pricing/Contracting Strategy Marketing Mix Optimization Forecasting IT Infrastructure TACTICAL ANALYTICS Account/Physician Segmentation Territory/Rep Performance Account/Physician Segmentation Territory/Rep Performance Analysis Marketing Program ROI Analysis Incentive Comp Analysis Territory Alignment Marketing Program ROI Account Targeting Incentive Comp Analysis Territory Alignment Figure 1: Sales and Marketing Framework white paper

2 Charter: Setting the Table for Success Overarching a company s sales and marketing analytics effort should be a well-defined and agreed-upon charter. Without a solid charter, it is likely that the analytics efforts will not be well aligned to key business objectives, will not enjoy business buy-in and ownership, and ultimately will not have the impact they should. The time and monetary resources invested in a strong analytics practice can be quite large, so crafting a solid charter is a critical success factor. Key aspects of such a charter include agreement on functional scope, ownership/accountability and sponsorship. Companies that excel in sales and marketing analytics generally have very strong organizational support from the highest levels of the company, with strong executivelevel understanding about the importance of such analytics. Many device companies struggle to empower the analytics function. Typical challenges include: Weak sponsorship. Unwillingness to mandate or force common analytics approaches across businesses. Highly fragmented responsibility for and approach to analytics. Data: Sales and Marketing DNA As in all such processes, data is the basic raw material of sales and marketing analytics. There are a myriad of data sources available to medical device marketers today. Secondary data sources can provide a very solid basis of customer and competitor understanding, including much information at the account (e.g., hospital or IDN) level and at the end user (e.g., surgeon, lab tech, hospital administrator) level. Most companies today augment available secondary data with a wide range of primary data. Typical primary data sources range from key account profile data gathered by the sales force, to qualitative and/or quantitative market research of key customers conducted by outside agencies. As data sources have increased in number and in complexity, several challenges are typically faced by medical device marketers. Key issues: How do we agree on a single version of truth? Which data sources are appropriate for which purpose? How often do we need to refresh the data? What is the data governance process, and who has ownership over it? In our experience, the best way to improve a company s sales and marketing analytics capabilities is simply to boost the robustness of data sources and governance processes. It makes little sense to invest tens or hundreds of thousands of dollars in advanced analytics applications if there is little internal agreement on the completeness and veracity of the underlying data. Performance Measurement: Turning Data into Information Sales and marketing data has little value if it s not used to actively measure and improve performance. Every medical device company has some level of performance-tracking capability today. That capability may be as basic as providing monthly or quarterly standard reports of their sales at the institution or account level. It can be as complex as providing data cubes that enable power users to conduct ad hoc queries to understand market share trends by customer segment and by product line. Generally, however, performance measurement capability in the medical device segment tends to lag behind other industries, including financial services, consumer goods and pharmaceuticals. The challenges outlined in the data discussion above quickly expand in most commercial operations once that data is put to work in performance measurement and tracking. There are several important issues on which companies must gain alignment: Timeliness. How do we ensure reports are disseminated in a timely enough manner to enable our organization to act on them? Determining the appropriate number and type of reports. How do we avoid overwhelming the business with an unmanageable volume of reports? Determining appropriate mix of standardized and ad hoc or customized reports. What is the right degree of flexibility to provide to the businesses? 2 white paper

3 Format/ease of use. What format enables the best and fastest insights and actions to be taken? Degree of actionability. How do we make sure our reports go beyond simple data summaries, to providing action-oriented insights? Tactical/Ad Hoc : Understanding Impact and ROI A major step in evolving the sales and marketing analytics capability is to move from straightforward performance tracking, to the analysis of that performance. Depending on the specific medical device sector and how one goes to market, there can be dozens if not hundreds of relevant and insightful analyses. A major challenge is providing sufficient focus to the analytical challenge, to the point that the organization agrees on which analytics should be captured, based on data availability, market dynamics and analytical capability. The following are examples of questions that can arise at any time: What causes better performing reps to achieve superior market share? What was the return on investment of the targeted program we ran with a set of surgeons last month? How balanced is the earnings opportunity and workload across our territories? Why is our latest product underachieving in the Northeast but having great uptake in the Southwest? How many reps achieved quota last year, and was the mix of variable compensation appropriate? Why are we getting better e-commerce results from one segment than another? How effective is our field service deployment? Key issues range from organizational questions, to technology questions, including the following: Organizational: Should analytics be performed in a centralized or decentralized manner, or should they be outsourced entirely? Do we have the required skill sets internally to conduct necessary analysis? If not, do we build or buy that capability? Scope: What are the most important analytics to conduct? Technology: What applications/tools should be used? Standard tools vs. customized tools? Strategic : The End Game The ultimate goal for sales and marketing analytics is putting in place tools, processes and business rules to optimize sales and marketing investment and to develop predictive models to maximize the effectiveness of the sales and marketing organization. Because data availability in the medical device sector has lagged behind other associated industries such as pharma and insurance, we expect there are relatively few device companies that have achieved strong success in integrated strategic analytics. Examples: Understanding trade-offs between investment in the sales force and investment in contracting. Forecasting demand by account or by segment. Optimizing the mix of spend between sales force, tech support, traditional marketing programs and emerging marketing variables such as social networking sites. The technology barriers to success in this area can be daunting. There are many business intelligence and analytics platforms from which to choose. In addition, there can be significant organizational barriers, as well. An example is the tension between centralized and decentralized approaches. A centralized approach, in which analysis is conducted by a core home office staff of highly skilled analysts, offers the advantages of consistency and more complex analysis. Advocates of decentralized approaches point to the need to customize analysis to account for local dynamics. Ultimately, either approach can succeed, but going back to the charter, there must be strong organizational alignment and support of the chosen approach. When done well, the insights and outcomes stemming from strong strategic analysis are powerful. However, given the fact that the investment required can be very high, there is high risk, too. white paper

4 IT Infrastructure: Enabling the Process Underpinning this entire analytics cycle is the need for a solid IT infrastructure. IT is so central to the success of initiatives in this area that it is usually advisable to conduct an IT assessment early in the process to understand how well systems and architecture will enable (or impede) progress in this framework. The analytics capabilities of many device companies have evolved over time, and so too have the supporting data and IT infrastructure. As a result, the architecture is often fragmented, inflexible and not readily adaptable to the changing needs of the business. Typical sales and marketing IT infrastructure problems/issues include: Architecture is not scalable. Solution does not leverage existing/common architecture. Lack of key master files customer, account. Processes are predominantly manual (insufficient automation). The transform while perform theme is especially relevant in the IT infrastructure area. Because of the systems incremental evolution described above, major gaps typically exist between the current and ideal sales and marketing IT infrastructure. However, moving quickly to the ideal state is often unrealistic, given the cost, time and disruption to the business that is likely to be incurred. Therefore, more pragmatic solutions that enable commercial continuity are often better solutions. Applying the Framework: Let the Transformation Begin An appropriate way to begin to make progress in your sales and marketing analytics capabilities is to conduct a current-state assessment. While greatly simplified, included here are tools that can be used to understand your organization s current level of performance compared with industry benchmarks. Figure 2 illustrates what best-in-class performance might look like on each key dimension. Very few, if any, device companies have achieved these levels of capability on each element, but it provides a vision of how your organization might progress over time. Charter Sales/marketing analytics scope is well defined with strong organizational support Clear organizational ownership and accountability exists Senior management is fully supportive of analytics function Data Governance process exists with clear ownership and accountability All key sales and marketing data is believed by sales and marketing to be fully robust Secondary data has been vetted and supplemented with relevant primary data There is an agreed upon "single source of truth" Performance Measurement Robust tracking processes in place for all key dimensions A process exists to identify appropriate reports for standardization Clear process in place to determine which reports are needed, both standard and customized Tactical/Ad Hoc Clear process in place to determine which analyses should be standardized/repeated Best practice standard analyses are identified and documented Analytical requests are prioritized / filtered based on objective business criteria Reports are highly intuitive, Service level agreements allowing for users of all skill exist and are consistently levels to use met Strategic IT Infrastructure All strategic analytics are Centralized data store tightly aligned to key objectives across businesses exists All strategic analytics are tightly aligned to key processes (e.g., strategic planning process) Processes exist to measure accuracy and impact of analyses Strategic analysis processes are well documented Systems/architecture is scalable to facilitate future growth All data and analytics processes have been assessed and automated where possible There is a well designed strategy of push vs. pull dissemination All key data is readily available at the right level Reports are highly action oriented, including alerts and flags applications are well integrated with other systems Reliable history of all key data exists Service level agreements exist and are consistently met BI platform is well aligned to needs and capabilities of key users All key data is well integrated Robust customer and/or account master data files exist Figure 2: Sales and Marketing Performance Benchmarks 4 white paper

5 Building on these benchmarks, Figure 0n page 6, is an assessment tool that can be used to gauge your organization s current level of performance in each area. For each area in the framework, key success dimensions have been identified. For each, a range of capabilities is articulated using three statements, one each to describe different levels of capability, from basic, to the more advanced core, to the best-in-class excellent level. This tool, or something similar, can be used to quickly identify key areas of improvement in your company s sales and marketing analytics. It is likely that you will find your organization has room to improve on several dimensions in this framework. As such, it is important to prioritize the most important improvement opportunities, and to do so, an appropriate set of decision criteria is required. Decision criteria can include some of the following: Technical Feasibility Effort and Cost Scalability and Flexibility Alignment to Corporate IT Standards Alignment with Key Business Objectives Time to Implement Fit with Personnel Capabilities Total Cost of Ownership Not all of these criteria are equally applicable to all framework areas. For example, total cost of ownership is likely only relevant for the IT infrastructure dimension. Figure 4 on page 7 shows an illustrative assessment conducted by a device company. The company embarked on an informal assessment to gauge its current state on each dimension. For each item, a score of 1 is assigned if the capability level is basic, if the level is core and 5 if the level is excellent. For each area, a simple average is calculated to prioritize areas of improvement. For the company in this illustration, there is room for improvement in all areas of the framework. Not surprisingly, that s true for most companies. It seems clear, however, that the biggest overall issue is upstream, in the data area. While the analytics processes seem reasonably robust, it is likely that the effectiveness of the analysis is weak because there are fundamental problems with the data inputs. Additionally, key stakeholders are most likely not buying into the results. In the charter area, there appears to be poor alignment on ownership/accountability, making it a candidate for a key initial priority as well, given the strategic importance of getting the charter right. It s clear from this cursory assessment that before a lot of time and energy is spent enhancing the tactical and strategic analytics, focus should be concentrated on data and performance measurement. Obviously, this illustration is overly simplified. However, it demonstrates the value of using an analytics framework with a solid assessment process and set of prioritization criteria in order to develop a road map for improvement. We ve helped clients conduct very robust assessments comprising key stakeholder interviews, surveys, KPI benchmarking and other elements. The assessment depth is greater, but the basic approach is similar to that outlined here. Conclusions Achieving sales and marketing analytics capability is increasing in importance as markets become more competitive and pressure increases to maximize the impact of new product launches. It is essential, though, that organizations continue to perform while they transform/upgrade their analytics capabilities. A simple but powerful framework can be used to understand your organization s current capability and to provide a roadmap for improvement. 5 white paper

6 Capability Statements Area Category Basic Core Excellence Charter Data Performance Measurement Ad Hoc/Tactical Strategic IT Infrastructure Scope Accountability Sponsorship Data Governance Data Robustness Data Completeness Single Source of Truth Data granularity Historical data availability Data integration and alignment Existence of Relevant Data Masters Measuring right dimensions (e.g., sales force, product, account/customer) Consistency/Standardization # and mix of standard and customized reports Ease of Use Actionability Timeliness Standardized vs. Ad Hoc Capability Consistency/Standardization Prioritization of analysis Timeliness of analysis Alignment with corporate and business objectives Alignment with corporate and business processes Impact analysis Process documentation Data Warehousing & Management Scalability Process Automation Information Dissemination Consistency of Technology Business Intelligence Tool/ Platform Figure : Assessing Current State scope is very poorly defined There is no clear ownership for analytics function There is no clear executive sponsor for analytics function No standardized governance process exists Sales and marketing stakeholders have little confidence in key data Only basic data exists at the account/customer level No agreement on need for single version of truth Little key data is available at the right level Historical data is not available or inconsistent Little integration of key data sets There is little organizational agreement on need for master files (e.g., customer master) There is little agreement (and therefore poor tracking) of key metrics to track There is little or no standardization of reports across BU's or SF's It is left to individual teams/brands to determine reporting strategy Reports are not easy to access and interpret Reports simply summarize data, don't contain actionable insights Key users complain about timeliness of reports No process exists for determining which analytics should be standardized or repeated There is little/no consistency in tactical analytics workload is determined largely based on who requests it Key users complain about timeliness of analysis Strategic analytics not well synched to key business needs Timing of analytics not sychronized with corporate processes No effort undertaken to determine impact of investment in analytics Strategic analysis processes are not documented Separate and disparate databases exist across businesses scope is somewhat well defined and supported There exists some degree of ownership over analytics There is generally strong/broad support for analytics function Sales/marketing analytics scope is well defined with strong organizational supportscope is somewhat well defined and supported Clear organizational ownership and accountability exists Senior management is fully supportive of analytics function Basic governance process exists Governance process exists with clear ownership and accountability Sales and marketing stakeholders All key sales and marketing data is believed generally have confidence in key data by sales and marketing to be fully robust There is agreement on key Secondary data has been vetted and account/customer level data, and it supplemented with relevant primary data is relatively complete There is agreement on the need for a There is an agreed upon "single source single source of truth and efforts to of truth" achieve it All key data is readily available at the right level Reliable history of all key data exists is well integrated Most key data is available at the right level Robust history of most key data is available Some key data is relatively well inte- All key data is well integratedtomer grated for ease of use & interpretation and/or account master data files exist There is agreement on need for master files, and progress is being made Measurement/tracking of key performance dimensions is reasonably good Some report standardization exists across BU's or SF's Efforts have been made to rationalize the # and mix of reports across BU's or SF's Robust tracking processes in place for all key dimensions Robust tracking processes in place for all key dimensions A process exists to identify appropriate reports for standardization Clear process in place to determine which reports are needed, both standard and customized Reports are getting better in terms of Reports are highly intuitive, allowing for access and usability but still not great users of all skill levels to use Reports identify some key trends and flags or alerts Timelines exist and are generally achieved Progress is being made on which analytics should be institutinalized We re beginning to identify and standardize the best analytics across the organization A robust process for determining which analysis to conduct is in place or being put in place Timelines exist and are generally achieved Strategic analytics are beginning to be aligned to key objectives Strategic analytics are beginning to be aligned to key processes Some effort undertaken to determine impact of investment in analytics Need for documentation is understood but not yet achieved Databases are somewhat centralized Architecture is not sufficiently flexible or scalable sufficiently Architecture is somewhat but not scalable Most data and analytics processes are very manual No attention paid to merits of push vs. pull dissemination applications are very poorly \integrated with other systems User requirements not well understood in BI tool choice Reports are highly action oriented, including alerts and flags Service level agreements exist and are consistently met Clear process in place to determine which analyses should be standardized/repeated Best practice standard analyses are identified and documented Analytical requests are prioritized / filtered based on objective business criteria Service level agreements exist and are consistently met All strategic analytics are tightly aligned to key objectives All strategic analytics are tightly aligned to key processes (e.g., strategic planning process) Processes exist to measure accuracy and impact of analyses Strategic analysis processes are well documented Centralized data store across businesses exists Systems/architecture is scalable to facilitate future growth Many processes are labor intensive, All data and analytics processes have been but a roadmap exists for improvement assessed and automated where possible Agreement exists on appropriate information dissemination and progress is being made There is reasonable integration with other systems Key BI users are understood and to some degree accomodated There is a well designed strategy of push vs. pull dissemination applications are well integrated with other systems BI platform is well aligned to needs and capabilities of key users 6 white paper

7 Capability Statements Area Category Basic Core Excellence Points Average Charter Data Performance Measurement Ad Hoc/Tactical Strategic IT Infrastructure Scope Accountability Sponsorship Data Governance Data Robustness Data Completeness Single Source of Truth Data granularity Historical data availability Data integration and alignment Existence of Relevant Data Masters Measuring right dimensions (e.g., sales force, product, account/customer) Consistency/Standardization # and mix of standard and customized reports Ease of Use Actionability Timeliness Standardized vs. Ad Hoc Capability Consistency/Standardization Prioritization of analysis Timeliness of analysis Alignment with corporate and business objectives Alignment with corporate and business processes Impact analysis Process documentation Data Warehousing & Management Scalability Process Automation Information Dissemination Consistency of Technology Business Intelligence Tool/ Platform scope is very poorly defined There is no clear ownership for analytics function There is no clear executive sponsor for analytics function No standardized governance process exists Sales and marketing stakeholders have little confidence in key data Only basic data exists at the account/customer level No agreement on need for single version of truth Little key data is available at the right level Historical data is not available or inconsistent Little integration of key data sets There is little organizational agreement on need for master files (e.g., customer master) There is little agreement (and therefore poor tracking) of key metrics to track There is little or no standardization of reports across BU's or SF's It is left to individual teams/brands to determine reporting strategy Reports are not easy to access and interpret Reports simply summarize data, don't contain actionable insights Key users complain about timeliness of reports No process exists for determining which analytics should be standardized or repeated There is little/no consistency in tactical analytics workload is determined largely based on who requests it Key users complain about timeliness of analysis Strategic analytics not well synched to key business needs Timing of analytics not sychronized with corporate processes No effort undertaken to determine impact of investment in analytics Strategic analysis processes are not documented Separate and disparate databases exist across businesses scope is somewhat well defined and supported There exists some degree of ownership over analytics There is generally strong/broad support for analytics function Sales/marketing analytics scope is well defined with strong organizational supportscope is somewhat well defined and supported Clear organizational ownership and accountability exists Senior management is fully supportive of analytics function Basic governance process exists Governance process exists with clear ownership and accountability 1 Sales and marketing stakeholders All key sales and marketing data is believed generally have confidence in key data by sales and marketing to be fully robust 1 There is agreement on key Secondary data has been vetted and account/customer level data, and it supplemented with relevant primary data is relatively complete There is agreement on the need for a There is an agreed upon "single source single source of truth and efforts to of truth" achieve it All key data is readily available at the right level 1 Reliable history of all key data exists is well integrated 1 Most key data is available at the right level Robust history of most key data is available Some key data is relatively well inte- All key data is well integratedtomer grated for ease of use & interpretation and/or account master data files exist 1 There is agreement on need for master files, and progress is being made Measurement/tracking of key performance dimensions is reasonably good Some report standardization exists across BU's or SF's Efforts have been made to rationalize the # and mix of reports across BU's or SF's Robust tracking processes in place for all key dimensions Robust tracking processes in place for all key dimensions A process exists to identify appropriate reports for standardization Clear process in place to determine which reports are needed, both standard and customized Reports are getting better in terms of Reports are highly intuitive, allowing for access and usability but still not great users of all skill levels to use Reports identify some key trends and flags or alerts Timelines exist and are generally achieved Progress is being made on which analytics should be institutinalized We re beginning to identify and standardize the best analytics across the organization A robust process for determining which analysis to conduct is in place or being put in place Timelines exist and are generally achieved Strategic analytics are beginning to be aligned to key objectives Strategic analytics are beginning to be aligned to key processes Some effort undertaken to determine impact of investment in analytics Need for documentation is understood but not yet achieved Databases are somewhat centralized Architecture is not sufficiently flexible or scalable sufficiently Architecture is somewhat but not scalable Most data and analytics processes are very manual No attention paid to merits of push vs. pull dissemination applications are very poorly \integrated with other systems User requirements not well understood in BI tool choice Reports are highly action oriented, including alerts and flags 1 Service level agreements exist and are consistently met 1 Clear process in place to determine which analyses should be standardized/repeated Best practice standard analyses are identified and documented Analytical requests are prioritized / filtered based on objective business criteria Service level agreements exist and are consistently met All strategic analytics are tightly aligned to key objectives All strategic analytics are tightly aligned to key processes (e.g., strategic planning process) Processes exist to measure accuracy and impact of analyses 1 Strategic analysis processes are well documented Centralized data store across businesses exists Systems/architecture is scalable to facilitate future growth 5 Many processes are labor intensive, All data and analytics processes have been but a roadmap exists for improvement assessed and automated where possible 5 Agreement exists on appropriate information dissemination and progress is being made There is reasonable integration with other systems Key BI users are understood and to some degree accomodated There is a well designed strategy of push vs. pull dissemination applications are well integrated with other systems BI platform is well aligned to needs and capabilities of key users Figure 4: Representative Assessment 7 white paper

8 About the Authors Richard Lincoff leads Cognizant s Medical Device practice. Richard s industry experience includes Johnson and Johnson and Merck where he was in field sales and a number of internal positions. In addition, prior to coming to Cognizant, Richard was SAP s Life Sciences Principal and previously was a Vice President at Ernst & Young/Cap Gemini leading their Life Sciences CRM practice Bruce Carlson heads the Chicago office of marketrx, a Cognizant company, and leads the firm s work in the medical device segment. Bruce has been in the life science industry for twenty years, both as a consultant and sales and marketing leader within the diagnostics business. He has led sales and marketing consulting engagements with life science clients in over thirty countries around the world and previously led a global cross-functional device development team. us at inquiry@cognizant.com for more information. About marketrx, a Cognizant company Cognizant s marketrx combines analytics, technology and market research to provide solutions that enable our customers to improve returns on their sales and marketing investments. We deliver measurable and actionable results that significantly improve the performance of product portfolios and sales forces. The Cognizant-marketRx combination offers a fully integrated solution that supports global Life Sciences companies in the pharmaceuticals, biotechnology and medical devices segments and allows clients to benefit from improved efficiency, effectiveness, higher productivity and lower total cost of operations. About Cognizant Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting and business process outsourcing services. Cognizant s single-minded passion is to dedicate our global technology and innovation know-how, our industry expertise and worldwide resources to working together with clients to make their businesses stronger. With more than 40 global delivery centers and approximately 61,700 employees as of December 1, 2008, we combine a unique onsite/offshore delivery model infused by a distinct culture of customer satisfaction. A member of the NASDAQ-100 Index and S&P 500 Index, Cognizant is a Forbes Global 2000 company and a member of the Fortune 1000 and is ranked among the top information technology companies in BusinessWeek s Hot Growth and Top 50 Performers listings. Start Today For more information on how to drive your business results with Cognizant, contact us at inquiry@cognizant.com or visit our website at World Headquarters 500 Frank W. Burr Blvd. Teaneck, NJ USA Phone: Fax: Toll Free: inquiry@cognizant.com European Headquarters Haymarket House Haymarket London SW1Y 4SP UK Phone: +44 (0) Fax: +44 (0) infouk@cognizant.com India Operations Headquarters #5/55, Old Mahabalipuram Road Okkiyam Pettai, Thoraipakkam Chennai, India Phone: +91 (0) Fax: +91 (0) inquiryindia@cognizant.com Copyright 2009, Cognizant. All rights reserved. No part of this document may be reproduced, stored in a retrieval system, transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the express written permission from Cognizant. The information contained herein is subject to change without notice. All other trademarks mentioned herein are the property of their respective owners.