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Imarticus Newsletter Analytics Q3, 2015

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EDITION - III Newsletter ANALYTICS Q3, 2015

IN THIS ISSUEEDITORIAL 03A Word from the Managing Director 04Nikhil Barshikar 07OPINION 11Productization of Analytics 12 13Pritam Kanti Paul 14CTO and Co-Founder, BRIDGEi2iTRENDINGCustomizing Recommendation SystemTechniques for Next Best OffersR. RaghavendraSenior Director, HP Analytics Data LabsWHAT’S BREWING? NEWImarticus Goes Online NEWManagement Development ProgrammesOperational Risk MDP: Sneak PeekUNWINDImarticus Good Reads

EDITORIAL 03 Nikhil Barshikar Managing Director – Imarticus LearningDear Reader, Senior Director at HP Analytics Data Labs, makes a case for recommender systems that are based onAs business owners see the incremental value that collaborative filtering.analytics provides, demand for analytics continues itsupward trajectory. A fundamental shift is clearly Analytics for the Masses also means we relook at theunderway in how business users like to consume way our youth is trained on analytical tools and process.analytics: on-demand and more personalized. Analytics Imarticus offers many online programmes on analyticsfor the Masses means that analytics needs to be that are self-paced, instructor-led and are geareddemocratized, simplified and easily consumable. towards upskilling working professionals within a short span of time, while still ensuring quality, consistency andOne such path-breaking approach is ‘Productizing’ repeatability in training results. Check out a briefanalytics services, or in other words, creating products summary of the online programmes that we believe arebased on consistent and repeatable services. Many relevant to you on Page 11.businesses have shown an inclination to switch fromproject-based consulting to these product offerings as Diwali is also the time for new beginnings and ventures.they typify the ‘Decisions first’ approach and offer Imarticus is proud to announce the launch of ourseveral advantages, including accelerated delivery of Management Development Programmes (MDP) to catersolutions at a significantly cheaper cost. On the supply to your senior managers and high potential employees.side, technology and analytics vendors are embracing Buoyed by the overwhelming response to our Riskthese challenges rather well. We are delighted to have Management Round Table in August earlier this year, wePritam Kanti Paul, CTO and Co-Founder at BRIDGEi2i, have chosen Operational Risk as the topic for our veryput forth his views on the productization of analytics. In first MDP on 21st-22nd January, 2016. Please refer Pagesthis interesting read, he makes the case that neither a 12 & 13 for more details. We have many more analytics-pure product based nor a pure services based approach focused MDPs in the works – watch this space. We lookwill meet the requirements of most businesses, which is forward to your whole-hearted participation andwhere a hybrid offering comes in. suggestions for future workshops.When organizations discuss how to drive value from big We are very excited about what 2016 will bring and, asdata, they often focus on improving the customer always, we invite you to come visit us at our offices inexperience through big data analytics. We are already Mumbai, Bangalore and Chennai. We have also recentlyenjoying the benefits of the so-called collective revamped our website to cater to your requirements.intelligence, which is embedded in a lot of applications Please visit imarticus.org/corporate to learn more aboutwe use on a daily basis. Of course you are used to our corporate solutions. Please do get in touch with us atFacebook, Twitter or Linked.in suggesting people you corporaterelations@imarticus.com for anymight also know, or to Amazon recommending products requirements or suggestions to serve you better.that you might like. All of them have one thing incommon: the use of recommendation techniques to Best Wishes Alwaysfilter what statistically is most relevant for a particular Nikhil Barshikaruser. What started off as a novelty has turned into aserious business tool. These systems can be designed Founder & Managing Directorusing various approaches such as content-based orcollaborative filtering. In this issue, R. Raghavendra,

OPINION 04 Pritam Kanti Paul CTO and Co-Founder - BRIDGEi2iINTRODUCTION WORLD OF PRODUCTSThe concept of using business data to improve an A school of thought that says some analyticsorganization’s decision-making is not new. Modern problems could be solved with the help of IT softwareday businesses need a solution with the following and products alone.characteristics to solve their business problems: ADVANTAGES QUALITY OF INSIGHTS On demand, real time, granular, 4Faster deployment at a cheaper cost actionable insights with predictive and 4Access to user community prescriptive analytics 4Trial usage for a limited period of time 4Easy upgrades at lower cost IMPLEMENTATION TIME Short, without much disruption to DISADVANTAGES current processes 4Difficult to integrate due to inherent COST Somewhere between the licensing cost differences in business processes for off the shelf products and one time between companies analytics services implementation 4Needs longer time for customization ROI 4Sometimes too specific, niche and ‘small’ Faster ROI, measurable impact, sustainable advantage in the overall schemeNOT A BINARY SOLUTION 4Sometime regarded as black box andIn the current technologically savvy world, manycompanies are still approaching analytics genericimplementation either in the product form or in thepure services form. Let us spend some time to By design, an off the shelf product can satisfy only aunderstand the world of products and services and few basic requirements that are consistent acrossthen take a call on the way forward for analytics many businesses and cannot offer a tailor-madeimplementation. As you will see, the choice of solution. A product’s effectiveness, acceptability andsolution is not always binary. ease of usage would get diluted if the product tried to be everything for everyone! Remember Google Wave? The failure of Google Wave is one such example. In retrospect, among other things, the failure was attributed to its complicated user interface, resulting in a product that was a bit like email, a bit like an instant messenger and a bit like a wiki, but ultimately couldn't do any of the things any better than the existing solutions. continued...

OPINION 05WORLD OF SERVICES So, what are the key ingredients of a hybrid offering?A school of thought that says custom built servicesare the perfect solution to address business 1 EASY-TO-INTEGRATE PRESENTATION LAYERproblems. Actionable Dashboards User Interface for real ADVANTAGES time, easy to 4Granular and accurate recommendations consume insights that completely fulfil the needs of your 2 CONSUMPTION LAYER business 3 CUSTOMIZABLE ALGORITHMS 4Measurable impact Industry Business Business Hybrid 4Can easily support future needs of the Trends Scenarios Rules Algorithms business 4 REUSABLE FRAMEWORKS DISADVANTAGES Data Augmentation Data Management Hardware, Software (Multiple Data (Integrate, Clean, Architecture 4 High cost of designing the solution Create Attributes, 4 Longer implementation time Sources - Internal) 4 The cost of incremental services to meet Transform) business needs are equally high Now this is easier said than done. Let us illustrate this with a use case. 4 Apprehension to invest as the final BRIDGEI2I FORECASTING ENGINE outcome is not clear Forecasting Engine is a cloud-enabled, one-stop forecasting platform that automatically identifies theNeither an entirely off the shelf productized solution, best suited models for a series of data and generatesnor a pure service offerings can, in isolation, cater to accurate forecasts.the growing and complex needs of today’sorganizations. This creates a need for a hybrid The application uses advanced forecasting modelsoffering. along with more traditional models, and has proprietary algorithms to choose best models, andHYBRID ANALYTICS SOLUTION enable ‘what if’ simulations and back testing models.A business solution whose core analytics algorithmsand frameworks are readily available and are flexible IT IS TIME TO START THINKINGfor customization to suit business needs. ABOUT EMBEDDING ANALYTICS BENEFITS IN BUSINESS PROCESSES FOR DECISION MAKING 4Reduction in implementation time 4Customization and flexibility to changing PRODUCTIZATION OF ANALYTICS industry and business needs IS THE HOLY GRAIL THAT WILL 4Accurate granular recommendations that are HELP US REACH THE LAST MILE! accessible continued... 4Easy adoption without requiring too many changes to the core platform 4Affordable cost (Sandwiched between pure Products and pure Services) 4Future ready 4Strong customer support

OPINION 06CLIENT USE CASES CONCLUSION4 Commodity price forecasts for a Hi-Tech company We are at a juncture where the4 Fraud loss forecasting for a major financial hardware maturity can support the aspirations of algorithms and services company frameworks. With companies such as Google open sourcing their machine4 Demand forecasting for a niche manufacturing learning systems, it is certainly the right time to start thinking about company embedding analytics in business processes for decision making.4 Sales pipeline forecasting for a Hi-Tech company Productization of Analytics is the Holy Grail that will help us reach the lastThe use cases stated above have commonalities in mile!terms of frameworks and algorithms to choose thebest methods. However, the key differentiating factorin each of these use cases is a business rule engine,data management and pre-processing that optimizesforecasts to provide higher forecasting accuracy for alonger period of time. On similar lines, BRIDGEi2i isfocusing on building such platforms that we call“Technology Accelerators.” We have developedplatforms around:4 Model risk governance for financial services4 SKU recommendation engines for sales reps4 Customer experience tracking as well as lead management for marketing and salesCHEAT SHEETLet me leave you with one quick cheat sheet that canhelp you identify and design hybrid solutions. Somequestions you need to ask yourself are:4 Can the solution bring sustainable advantage to the business?4 Is the analytics solution easy to adopt without making much change to the existing processes?4 Does the solution have core components that cover the critical intelligence part of the solution?4 Does the architecture allow customization based on business processes?4 Is it future ready in terms of infrastructure and changes in data etc?4 Can the solution be embedded at the point of decision making?4 Is the solution affordable?4 Is there a scope for volume game?

TRENDING 07 CUSTOMIZING RECOMMENDATION SYSTEM TECHNIQUES FOR NEXT BEST OFFERS R Raghavendra Senior Director, HP Analytics Data LabsWith Contributions by: Rajeshwari Sinha, Analytics Lead-Banking & Telecom; Kumar Saurabh, Customer Analytics ExpertINTRODUCTION 4 Predictive analytics based approach whichCEOs are serious about customer engagement. Theywant their companies to be customer-obsessed, analyzes historical transaction data. For example,knowing what customers want before they want it. It's market basket analysis where if most customersnot just lip service. It’s a matter of dollars and cents: buy fries with burgers, it is highly likely that theconverting browsers into buyers. Companies are customer who will buy a burger will also buy fries.increasingly getting serious about customerengagement to provide better experiences as well as RECOMMENDER SYSTEMSproactively recommending customized products Another set of techniques is to understand thebased on customer’s purchasing patterns, customer’s likes, dislikes and preferences using ademographic information and interaction response recommendation system. Recommender systemsetc. to nurture loyalty and increase sales. are being used by an ever-increasing number of e- commerce sites to help consumers find products toNEXT BEST OFFERS purchase. What started off as a novelty has turnedCustomer engagement can happen at multiple touch into a serious business tool. Recommender systemspoints, offering opportunities for next best offers and use product knowledge—either hand-codedbuilding brand loyalty with a steady stream of knowledge provided by experts or “mined”revenue. A key strategy to improve customer knowledge learned from the behavior ofengagement is to prescribe the right product to the consumers—to assist customers through the often-right customer at the right time. This results not only overwhelming task of locating products they wouldin higher customer engagement but also ensures a gravitate towards. They represent a powerful methodbetter experience. This marketing strategy of next of enabling users to filter through loads ofbest offer is a widely sought after problem and there information and large product spaces, and therebyare many analytics solutions currently available. Data convert random browsers into loyal buyers.analytics play a key role in identifying and deployingthese opportunities. COLLABORATIVE FILTERING One approach to the design of recommenderNext best offer strategies can be deployed in multiple systems is collaborative filtering, which has beenways: highly successfully in e-commerce. It is a popular recommendation algorithm that bases its predictions4 Business rules that can suggest new products and recommendations on the ratings or behavior of other users in the system. A distinct advantage of the based on customer data of transaction and collaborative filtering approach is that it does not rely relationship history. For example, someone who on machine analyzable content and therefore it is has taken a student loan should be sold a vehicle able to accurately recommend complex items such loan in five years, based on event based business as movies without requiring an \"understanding\" of rules. the item itself.  continued...

TRENDING 08This article focuses on highlighting the applicability of 4 Information is available for user (customer) andcollaborative filtering across multiple industries bycustomizing it according to the needs and constraints item (products or services) preferencesof specific industries. 4 Business need for analytical insight is beyondCOLLABORATIVE FILTERING-BASEDRECOMMENDATION SYSTEMS FOR standard apriori based deliverablesNEXT BEST OFFERCollaborative filtering works on a basic assumption 4 Handling of customer life cycle behavioralthat users with similar preferences will respond in asimilar manner to items available where: attributes like disconnection, downgrade etc. for better ROI from next best recommendation4 Users are existing customers for a business4 Items are products or services offered like online Hence, even though the use of collaborative filtering for next best offer started with e-commerce and groceries items, online subscription based online businesses, due to the above points, it has content, Direct-To-Home (DTH) entertainment found its relevance in multiple industries by packages, voice and non-voice based customizing the response function and similarity telecommunication services function as per their business needs. Some industries where standard collaborative filtering algorithm have4 Preference or attitude of users towards items is been successfully customized and implemented include media, entertainment and the captured in different ways like purchase history, telecommunication industry. rating history, subscription history etc. APPROACH AND METHODOLOGY RECOMMENDATION CONSIDERATIONS There are multiple approaches to collaborative SIMILAR filtering which primarily include user-based collaborative filtering and item-based collaborativeCollaborative filtering techniques use these available filtering. Some key considerations while building auser-item response points to predict missing user- collaborative filtering based analytical next bestitem responses. So, in any collaborative filtering recommendation solution include:model, the two most critical components are: MODEL SELECTION: Applicability of specific Preference function Similarity function (f2) collaborative filtering technique depends on multiple(f1) which acts as input which is used to predict factors including user-item data richness, ease of deployment, accuracy, scalability and computation for machine learning responses for missing performance. Due diligence should be done while combinations selecting the appropriate model based on the factors mentioned as per business need and preferences.APPLICATION AND PREFERENCECollaborative filtering is a preferred approach over PREFERENCE FUNCTION GENERATION: Thestandard business rule based approaches and generation of preference function is dependent onclassification techniques under the following the dynamic of customer lifecycle analysis in acircumstances: specific business environment. A customer response may be:4 Customer demographic information which 4 Time-independent static preference or indicates taste and preferences is not readily 4 Time dependent dynamic preference available or accuracy of captured information is not certain for the majority of the customer base For example, in a sales based e-commerce model, a product purchase is an absolute preference for a user-item combination, where once a product is purchased, it is purchased forever. continued...

TRENDING 09However, in a subscription driven business model, a COMPUTATION COMPLEXITY: Computationalsubscription which is purchased at a specific month complexity is a key factor in terms of overall approachcan be discarded next month and can again be since collaborative filtering algorithms can bepurchased in subsequent months. Hence, customer computationally exhaustive based on the user andpreference is a time dependent dynamic function. It is product base.also important to identify the preference mechanismwhich will predict customer propensity—that is, This becomes more relevant for real time businesswhether it is a probabilistic function highlighting deployment versus an offline deployment withprobability of purchase or a hold score function periodic updates. There are multiple approaches tohighlighting product subscription interest as holding deal with computation complexity. Some of themperiod or something else. include:SIMILARITY FUNCTION CONSIDERATIONS: 4 Selection of lesser computationally intensiveSimilarity function should ensure that all the relevantand critical dimensions of user similarity have been collaborative filtering techniquesconsidered. For example, in a telecommunicationbusiness, three customers may have an inclination to 4 Improvement of computational performancebuy the same product or service. However, the firstcustomer may be a loyal customer without any through accuracy trade-offfrequent product or service downgrades, whereasthe second customer may have a tendency to 4 Improvement of computational power throughfrequently downgrade offered products, while thethird customer may have a frequent disconnection additional hardware resourcesbehavior. So, in such a scenario, the similarityfunction should be good enough to take care of not 4 Use of domain knowledge and business rules toonly product type consumption similarity but alsodisconnection, reconnection, product upgrade and simplify computational complexitydowngrade behavior similarities. OPERATIONALIZING ANALYTICS RECOMMENDER SYSTEMS OUTPUT INTO ACTIONABLE INSIGHTS REPRESENT A POWERFUL There are two ways in which collaborative filtering METHOD FOR ENABLING based analytical output can be deployed. Based onUSERS TO FILTER THROUGH industry and product offerings, deployments can be LARGE INFORMATION AND either customer based or product based. PRODUCT SPACES, AND Customer Driven Analytical Deployment THEREBY CONVERT BROWSERS INTO BUYERS. In a customer based deployment, a top-n recommendation methodology is followed where each customer is offered 1st best or 2nd best or nth best product for consumption. continued...

TRENDING 10 Product Driven Analytical Deployment CONCLUSION In a product based deployment methodology, for We are at a juncture where the each product, customers are categorized into hardware maturity can support the high, medium and low propensity buckets for aspirations of algorithms and respective product consumption. frameworks. With companies such asHowever, irrespective of marketing deployment Google open sourcing their machinemethodology, a collaborative filtering based learning systems, it is certainly theanalytical output can be deployed for right time to start thinking aboutoperationalizing analytics. embedding analytics in business processes for decision making. Productization of Analytics is the Holy Grail that will help us reach the last mile! BUSINESSES BENEFIT FROM REVENUE UPLIFT,REDUCTION IN MARKETING COST THROUGH TARGETEDCAMPAIGNS AND OPTIMUM UTILIZATION OF RESOURCES LEADING TO HIGHER ROI

WHAT’S BREWING? 11ONLINE AT IMARTICUSImarticus Learning offers short-term, online programmes thatprovide your employees with a thorough understanding ofproducts, processes and operations as applicable to theAnalytics industry.These programmes provide you with valuable training optionsto add to your calendar for diverse training requirements, suchas supplementing your classroom trainings, onboarding newemployees or as periodic ready refreshers.KEY FEATURES HIGHLIGHTS INDUSTRY RELEVANT COMPLEMENTARY OFFERINGS DELIVERY CURRICULUM 4 Free webinars by imminent industry 4 Self paced videos INSTRUCTOR LED 4 Live instructor-led virtual classes DELIVERY experts on topics of current interest 4 Case study methodology 4 Accessible on multiple platforms 4 Free introductory modules of our online programmes CERTIFICATION PREPARATION Prepare your employees to clear prestigious national and international certifications by SAS Institute, etc PROGRAM OFFERINGSEXPERIENTIAL LEARNING SAS Programs and Writing Functions Statistics using Need for Data Visualization Functions Python FLEXIBLE AND Macros Data Manipulation Predictive, Text Data Visualization MODULAR and Multivariate Best Practices SQL Tables, Views, Statistical AnalyticsINTEGRATED LEARNING Joins Concepts Types of VisualMANAGEMENT SYSTEM Optimization Tools Program Efficiency Predictive, Text (LMS) and Optimization and Multivariate Forecasting Visual Storytelling Analytics with Data Basics of Statistics DURATION DURATION DURATION DURATION 50 Hours 46 Hours 40 Hours 40 Hours

WHAT’S BREWING? 12 NEWMANAGEMENT DEVELOPMENTPROGRAMMES AT IMARTICUSCreating Future Business LeadersThe sweeping changes in the corporate Our Management Development world consequent to liberalization, Programmes prepare your employees privatization and globalization, the to become better leaders as well asconvergence of technologies and the growth of more valuable contributors to yourthe Internet have unleashed competition both in broader institutional goals. They act asthe domestic and international markets. catalysts for fresh thinking, re-training, knowledge enhancement and strategicWith an ever-changing, increasingly connected development.and competitive world, business managers needto constantly update their knowledge andprofessional capabilities in all areas affectingtheir business and career. WHO ARE THEY FOR? LEARNING AREAS METHODOLOGY OF EXPERTISE These workshops are ideal stepping stones for Mid to Senior Level The workshops focus 4 Big Data Management and your high potential on the practical realities employees. of the market, rather 4 Customer than taking an Engagement Using OUR OFFERINGS excessively academic or Analytics theoretical approach,CORPORATE WORKSHOPS and will blend 4 Analytics in Financial discussions with case Services4 Bespoke programmes that are customized to your studies and assignments. 4 Fraud Analytics requirements 4 HR Analytics4 Open only to members of a particular 4 Social Media organization Analytics4 Duration: 1-5 Days 4 Supply Chain ManagementOPEN WORKSHOPS4 Expert faculties identify topics of contemporary interest4 Open to participation across different industries4 Duration: 2 Days

WHAT’S BREWING? 13UPCOMING MDP NEWOPERATIONAL RISKMANAGEMENTBLOCK THE DATES21st & 22nd Jan, 2016This 2-day workshop is designed to deliver a LEARNING OUTCOMES deep, practical understanding of operational risk management frameworks 4 Design and implement an effective operational and measurement methodologies in financial institutions. risk management platform Participants will be better prepared to implement 4 Execute an operational risk assessment and meaningful risk assessment initiatives, produce useful risk management information and measurement program understand basic modeling techniques for operational risk measurement. 4 Understand how to capture, report andWHO SHOULD ATTEND? investigate operational risk events, how to produce meaningful Risk MI including KRI data Senior Managers in organizations, in and trend analysis, and how to implement particular Operational Risk, Financial operational risk appetite Control, Operations, Technology, Compliance, Audit and Legal Officers 4 Apply the best practice models and methodologies for operational risk management EXPERT PROFILE Ops risk in context Performing the Ops DR. RANJAN CHAKRAVARTY risk function 4 22 years of global experience in riskBest practices and wrap up managementManaging COVERAGE Metrics & technology 4 Ex–Managing Director at Hypovereinsbank,reputation Regulatory DBS Bank, Singapore, and Head of Risk, risk environment Research and Products for MCX-SXMeasurement & reporting 4 A specialist in risk management at Bankers Identification techniques Trust New York (now Deutsche Bank), BankBoston (now Bank of America Merrill Lynch)and GE Capital in the US 4 Pioneer in Basel II and III implementation 4 An alumni of Columbia Business SchoolLOGISTICS WHEN: 21st and 22nd January, 2016; 9 AM to 6 PM WHERE: JW Marriot Sahar, Andheri East, Mumbai EMAIL: mdp@imarticus.com

UNWIND 14 GOOD READS Disrupt Yourself: Putting the Power of Disruptive Innovation to Work - Whitney Johnson Johnson, a Merrill Lynch equity analyst turned entrepreneur, shows how and why to upend a career in this practical, concise book. Savvy and often counter-intuitive, this book offers the tools, mind-set guidance, and rationale for avoiding complacency and embracing a new career path. Consider this your playbook for personal and professional innovation. Are you ready to jump? Social Media ROI: Managing and Measuring Social Media Efforts in Your Organization - Olivier Blanchard The social media code has officially been cracked! In Social Media ROI, Blanchard reveals how companies can apply the massive power of social media to achieve equally massive results. Incredibly practical, yet very enjoyable, this book offers a clear roadmap to growing your revenue in the dizzying world of tweets and retweets, likes and shares, connections and comments by measuring your FRY (Frequency, Reach, and Yield). Big Data Revolution: What Farmers, Doctors And Insurance Agents Teach Us About Discovering Big Data Patterns - Rob Thomas and Patrick McSharry In this collaborative work by IBM Vice President of Big Data Products and an Oxford Research Fellow, this book describes the major trends emerging in the field, the pitfalls and triumphs being experienced, and the many considerations surrounding Big Data, all while guiding readers toward better decision making from the perspective of a data scientist. Good to Great: Why Some Companies Make the Leap... And Others Don't - Jim Collins Good to Great introduces readers to the concept of an enduring great company, one that sustains tremendous growth for at least 15 years from the so called \"turning point\". Published in 2001, the book offers a well-reasoned road map to excellence for any organization and gives a great opportunity to analyze how much endurance there is in a great enduring company. The Book of Awakening: Having the Life You Want By Being Present in the Life You Have - Mark Nepo A daily guide for authentic living in hard times, The Book of Awakening is a beautiful and poetic book to keep your head high, your heart open and your feet on the ground. A year's supply of wise and shining thoughts to be taken, one a day, like vitamins for the soul. Highly recommended by Oprah Winfrey and one of her Ultimate Favourite Things.

CORPORATE SOLUTIONS 15Imarticus Learning is formed to bridge the gap between Academia and the industry. The firm provides a rangeof Corporate Solutions designed to assist firms in meeting their skillset requirements.Headquartered in Mumbai, Imarticus has delivery capabilities across India with dedicated centres at Mumbai,Bangalore, Chennai, and satellite centres at Pune and Jaipur. HIGHLIGHTS Training and content delivery Preferred sourcing and Range of customized delivery capability, across the areas of corporate training delivery methods such as instructor ledInvestment Banking, Finance & partner for leading Global training, e-learning, workshops Treasury, Capital Markets Banks, Consulting, KPO, and seminars for optimal Operations, Business Technology and Analytics training effectiveness. Analytics, Technology and firms. Consulting. CONTACT US AGILE HIRINGWe have recently revamped our Ready Placementswebsite to cater better to your at No Cost requirements. SOURCING TO Please visit us at: PLACEMENTwww.imarticus.org/corporate 2-3 month programs targeted towards onboarding TEMPING 6-9 month resource staffing in Investment Banking Operations CORPORATE TRAINING 2-10 day programs targeted towards employee skill developmentEMAIL US: corporaterelations@imarticus.com

Every morning in Africa, a Gazelle wakes up. It knows it must run faster than the fastest Lion or it will get killed. Every morning, a Lion wakes up. It knows it must outrun the slowest Gazelle or it will starve to death.“When the sun comes up, You’d better be running.