YEAR 2021 | ISSUE 112

MESSAGE FROM THE DIRECTOR

Prof. Dr. Uday SalunkheGroup Director

Dear Readers,

It gives me great pride to introduceSAMVAD’s edition every month. OurSAMVAD team’s efforts seem to be payingoff and our readers seem to be hookedonto our magazine. At WeSchool we try toacquire as much knowledge as we can andwe try and share it with everyone.

As we begin a new journey with 2021, I sincerely hope that SAMVAD willreach new heights with the unmatched enthusiasm and talent of theentire team. Here at WeSchool, we believe in the concept of AAA: Acquire Apply andAssimilate. The knowledge that you have acquired over the last couple ofmonths will be applied somewhere down the line. When you carry out aprocess repeatedly it becomes ingrained in you and eventually tends tocome out effortlessly. This is when you have really assimilated all theknowledge that you have gathered. At WeSchool, we aspire to be the best and to be unique, and we expectnothing but the extraordinary from all those who join our college. Fromthe point of view of our magazine, we look forward to having morereaders and having more contributions from our new readers. SAMVAD is a platform to share and acquire knowledge and developourselves into integrative managers. It is our earnest desire todisseminate our knowledge and experience with not only WeSchoolstudents but also the society at large.

Prof. Dr. Uday Salunkhe, Group Director

ABOUT US

OUR VISION “To nurture thought leaders and practitioners through inventiveeducation”

CORE VALUES Breakthrough Thinking and Breakthrough ExecutionResult Oriented, Process Driven Work EthicWe Link and CarePassion “The illiterate of this century will not be those who cannot read andwrite, but those who cannot learn, unlearn and relearn.” -Alvin Toffler

At WeSchool, we are deeply inspired by the words of this greatAmerican writer and futurist. Undoubtedly, being convinced of the needfor a radical change in management education, we decided to tread thepath that leads to corporate revolution.Emerging unarticulated needs and realities require a new approachboth in terms of thought as well as action. Cross-disciplinary learning,discovering, scrutinizing, prototyping, learning to create and destroy themind’s eye needs to be nurtured and differently so.WeSchool has chosen the ‘design thinking’ approach towardsmanagement education. All our efforts and manifestations, as a result,stem from the integration of design thinking into managementeducation. We dream to create an environment conducive toexperiential learning.

ABOUT US

Dear Readers,

Welcome to the 112th Issue of SAMVAD!

SAMVAD is a platform for “Inspiring Futuristic Ideas” and we constantly strive toprovide articles that are thought-provoking and that add value to yourmanagement education.

We have an audacious goal of becoming one of the most coveted businessmagazines for B-school students across the country. To help this dream become areality we invite articles from all the domains of management giving a holisticview and bridge the gap between industry veterans and students through ourWeChat section.

In this issue of SAMVAD, we bring to you half a dozen articles focusing on"Business Analytics" with a new section of "WeAchievers" highlighting the topperformers of WeSchool in various top B-School Competitions and "Talk of thetown", which will give you crisp insights about the current happenings in theworld.

In the corporate world, there isn't one who is unaware of Business Analytics orData Science. Business analytics, in simple words, is the combination of variousskills to uncover business information based on data and statistics and drivebusiness planning accordingly. Lots of data is being generated each day in everybusiness sector, such as - Social Media, E-Commerce, Banking, etc. Analytics isthus required to allow companies and organizations to make better businessdecisions. Today, almost every company uses business intelligence (BI) andbusiness analytics (BA) to interpret information and create effective data-drivenaction plans. This Edition describes how companies are channeling this trend andearning profits

Hope you have a great time reading SAMVAD! Let's read, share and grow with us!

Best Wishes,Team SAMVAD.

FROM THE EDITOR’S DESK

Saurabh Pramanick

TECHNICAL ARCHITECTHEXAWARE TECHNOLOGIES

I have seen a lot of phases in my careersince completing the Post GraduateDiploma in Business Design fromWeSchool in 2014. The course gave me anentrepreneurial mindset to viewtasks and my activities from a non-traditional way, incorporating aninnovative and design-thinkingapproach to problem-solving. As acorporate individual, you need tohave these skills to differentiateyourself from your peers and carve aniche for your further success.

I have been part of several successfulcampaigns and programs for myorganizations taking them to newhighs. While in the industry workingwith professionals from other MBAcolleges, I can clearly see thedifference in analytical capability andproblem-solving ability betweenmyself and graduates from othercolleges. I have worked as FinancialConsultant, Regulatory ReportingConsultant, Data Analytics Lead, DataGovernance Lead, and Data ScienceLead for large corporates like TCS,

Data Science and Analytics have seena large transition across the lastdecade with each organizationunderstanding its importance andsignificance. Traditionally, DataScience and Analytics were considereda part of the IT team which later gotsegregated under BusinessIntelligence and MIS. However, withthe increase in use, organizations arenow creating a separate business unitfor Data Science and Analytics, with aseparate role for the Head of DataScience and Analytics with a specialfocus on this practice. Institutions havestarted seeing the benefits of keepingit as a separate practice as it avoidsambiguity, hierarchical issues, andclear separation of roles andresponsibilities,

2. How is analytics helping in shapingthe decisions for managers in anygiven field?

Wolters Kluwer Financial Services,PwC, Hexaware Technologies, andtheir various clients acrossgeographies. Data is my bread andbutter, and

I would like to say that you need tofall in love with data if you want tosucceed in the Data analytics space.

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1. Could you please take us throughyour journey from being aWelingkarite to date?

At the same time, they canincorporate advancements andchanges in the data ecosystem quitesmoothly, ensuring regulatory andlegal compliance. This is helpingorganizations define specific use casesand then focus on these specific usecases for their implementation andsuccess.

Analytics has been wrongly perceivedas related to reporting andvisualization over these years. Severalcomponents get covered under DataAnalytics that include, but are not

limited to, Business Intelligence, MIS,Data Visualization, single andconsolidated view of data, DataGovernance, Data life cyclemanagement, machine learning,artificial intelligence, cognitiveintelligence, etc. A Data Analyticsindividual and leader should have acomplete understanding of theseconcepts and areas as well as theinteraction of these areas with eachother. It will give them an overallunderstanding of the interactions anddependencies of the components. Itwill also help them understand thevalue of data and how data can beleveraged for achieving their goals. Italso gives them a competitiveadvantage as compared to their peers.

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3. What according to you, are thecompetitive advantages of beingskilled in analytics in thecontemporary world?

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The latest Gartner magic quadrant ofservice providers in the Data andAnalytics space: (Fig. 1)Each of these service providers useseither in-house built applications orofferings from leading productcompanies such as Microsoft, Amazon,SAP, SAS, Salesforce, Informatica,Talend, TIBCO, Tableau. Qlikview, etc.,for their offerings. There are a lot ofopen-source technologies andproducts in this space. A properevaluation of these products andservices needs to be done for finalizingthe technology stack.

The core offerings in the space ofData and Analytics are:· D&A strategy and operating modeldesign· Data management· Analytics and business intelligence(ABI)· Data science and machine learning(aka AI)· D&A governance· Program management· Enterprise metadata

Data Analytics, though related to data,has a lot of dependency on otherteams and departments as they arethe owners of their data. Some of the

4. What are some major tools andtechnologies that are currently usedfor analytical purposes byorganizations?

5. According to you, what are somemajor challenges in the field ofBusiness and Data Analytics?

key challenges faced by clients andorganizations in Business and DataAnalytics include:Data Ownership and Access. Itbecomes essential to have a correctand clear understanding and mappingof the data owners for each dataattribute. A proper data access matrixhelps in such scenarios.Secondly,

Data attributes have multiple sourcesof origin and residence. Organizationsstruggle to understand the completetraceability of the data and itsjourney across the technology.

They also do not have a clearunderstanding of the lifecycle of thisdata from its collection or generationto its deletion or archiving. It becomesmeaningful to have a single version oftruth for each data attribute withappropriate data traceability in place.Since organizations are focused oncollecting as much data as possible, alot of times they fail to understandwhich of the data is actuallymeaningful and useful, ultimatelycreating data swamps. This hasaccessibility, performance issues andmay lead to filtering out of usefulinformation.

Data Quality issues, this is one of themost critical components of DataAnalytics as most of the time the dataresiding within the organizationsystems are least matured. A properdata quality policy, framework with adata quality maturity model needs tobe adopted by the organization.

Lastly, Insights from data are achallenge. Though the collection ofdata is one aspect of the datalifecycle, gaining meaningfulinsights is another facet of thejourney. The core responsibility of thedata analytics team is to gathermeaningful insights from the datawithin the organization systems butchallenges due to meaningful dataand data quality often cause a hurdle.

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6. How are companies taking care ofcustomers' information given recentincidents of a data breach ofcompanies like Dominos and AirIndia, which could pose a potentialthreat to the customers?

Organizations are nowunderstanding the importance ofgathering Personal IdentifiableInformation (PII) of customers andways to handle them. Withregulations getting stringent andnew regulations getting enforced,organizations are setting up specificdata privacy teams and data officesto handle these regulations.

They are firstly trying to perform adata impact assessment to identifythe critical data elements, identifythe data owners and business ownersfor these elements, understand thecomplete end-to-end traceability of

these elements, correspondingregulations, compliance, legalrequirement, and clauses for these dataelements, maturity level and as-is stateto define the required to-be state. Adetailed report is shared with all thestakeholders on a continuous basis tohelp everyone align to the analysisdone and take the necessary stepsgoing ahead. Some organizationsmight take a proactive while some maytake a reactive approach in this butultimately sooner or later, they arerealizing the benefits andrepercussions and are actingaccordingly.

Data analytics and its adoption andacceptance by all will be widely seenin the coming days with moreinnovative solutions and processesbeing used by organizations. This willbe coupled with the advances incorresponding areas of artificialintelligence, machine learning, anddata science.Typical challenges will be faced byorganizations such as finding perfectlyskilled individuals with domain andbusiness expertise,

investments in appropriate technicalsolutions and capabilities, acceptanceand adoption by business and seniormanagement, dependency onnetworks and hardware advancements,and efficient performance evolution,useful v/s non-useful data identificationand usage. Organizations able tounderstand, identify, mitigate andovercome these challenges in data andbusiness analytics will be able to have acompetitive edge over theircompetitors and will be able to surviveand advance further.

There are ample opportunities foryoung professionals to pursue theircareer in Data and business analyticsand its affiliated areas of machinelearning, artificial intelligence, datamanagement, data science, datavisualization, quantum computing,neural networks, and data governance.They should understand each or any ofthese areas and understand thedomain, target results, theirinteractions with other componentsthat will help them have a holisticunderstanding of these areas.Most of the time, professionals focusonly on either tools or technology, ordomain thereby failing to understandboth sides of the story and theirinteraction. Also, it will be useful totake active live projects and test theirknowledge and understanding thathelps them to solve their queries andhave a business understanding of thepractical usage of their knowledge.

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7. What is the future of data andbusiness analytics?

8. What are your suggestions to youngprofessionals, who would be startingtheir careers soon?

'India expects to add 95

new tech unicorns to its 56-strong unicorn pool by

2025' says, “Turning Ideas to

Gold,” report by 256Network and Praxis Global

Alliance

Indian ultra-HNIs likely to invest$30 bn in tech start-ups by2025

Indian ultra-high net worthindividuals (UHNI)

are likely to invest upto $30 billion in techstart-ups in India by

2025.

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Druid-Backer Imply Lands$70M to Drive Analytics inMotion

Imply is building a cloud platform that

simplifies management of the distributed analyticproduct, thereby enabling

customers to focus on usingDruid to crunch the fast-flowing data to benefit

their businesses.

Imply, the startupfounded to productize

the Apache Druiddatabase in pursuit of

analytics in motion, thisweek announced that

the completion of a $70-million Series C round

of funding.

Imply was founded in 2015 by some of the creators ofApache Druid, a column-oriented in-memory data storethat was originally developed at Metamarkets, an ad techanalytics firm. The goal with Druid, which was created in2011, was to serve OLAP-style analytic queries on high-dimensional data at low latencies, something that theHadoop-based distributed processing projects (Hive,Impala, and later Presto) of the day struggled to do.

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Business Intelligence as the namesuggests, helps in deriving intelligentinsights about a business. BusinessIntelligence, often termed as BI, helps indriving decisions based on historical,current and potential future data.

The BI process starts with organizationscollecting data from sources such asinternal IT systems and externalresources. After collection, the data isprepared for analysis and queries arerun through the data.

The end product is received in the formof creative data visualizations like BIdashboards, charts, graphs and reportsto make the analytics results availableto business users.

These insights are presented in a verycrisp and clear way making the datamore readable and easilyunderstandable to derive insights from.This helps decision makers at every levelunderstand their business and makebids

Role of Business Intelligence Tools in Decision Making

decisions that aren't just supported bygut instincts, but actual statisticalreasoning and data.

Business Intelligence has been in thelimelight in recent years when it comesto making data driven decisions. Inorder to have advantage overcompetitors, BI tools can give firms anedge by providing insights to predictmarket trends, disclose opportunitiesand develop breakthrough strategies.

BI tools use OLAP (Online AnalyticalProcessing) to aid enterprises inperforming data analysis, monitoringKPIs, and generating reports.

The intricate analysis performed by BItools helps firms to identify businesstrends, trace gaps in performance,communicate the findings tostakeholders and gain insights on datawhich ultimately leads to making timelyand data-driven business decisions.

Disha BirjePGDM Research & Business Analytics 2020-22, Welingkar Institute of Management & Research

General Management

8

source: mauriziopittau.it

Economic Impact of COVID-19 on MSME sector

According to Dresner, Post COVID-19, it’sexpected that 95% or more of enterprisesoftware vendors will consider Cloud BIas a must-have, as every organization isnow a distributed one.

BI APPLICATIONS IN DECISION MAKING

To understand in what ways BIcontributes in upscaling the decision-making process, let us have a look at theapproach followed by different teamsand departments when it comes toimplementing BI supported decisions inbusiness:

DATA SCIENTISTS AND ANALYSTS

Analysts make excellent use of BI; theyuse data in powerful analytics tools toinspect where opportunities forimprovement and growth exist and alsowhat strategic recommendationsshould be suggested to leverage acompany. They can gain intricatebusiness insights from complex datausing various BI tools which providedifferent outlooks for the decisionmaker.

These are the popular BI tools

FINANCE

The financial experts integrate financialdata with other departments and deriveinsights from which decisions can bemade and understand factors thatimpact the profitability. The insightsprovided by BI onto the past andcurrent outgoing and incoming financesof the company can enable the financialexecutives to make accurate decisions.

For example, American Expressidentified up to 24% of the Australianusers who were likely to close theiraccounts within four months. Using thatinformation, American Express tookeffective steps to retain those customerswho would otherwise be lost.

They also detected credit card fraudsmore accurately (in case of unusualpatterns) and thereby protectedcustomer’s accounts that may havebeen compromised.

OPERATIONS

Operational BI enables business users toquickly spot an emerged opportunity ora problem and act accordingly.

This can be done with operationalreports and dashboards using BI tools(where the information is updatedwithin a set time interval), as well asalerts or messages.

For instance, line supervisors can gethourly production reports that will helpthem in achieving their daily productiontargets. Business intelligence can alsohelp in improving the distributionroutes to a great extent. Also, gaining anidea of the ordering pattern of a productwould allow managers to set thedistribution cycle and witness efficientsupply of products.

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Economic Impact of COVID-19 on MSME sector

HUMAN RESOURCES

An HR professional needs an overview ofthe different aspects of a company’sbiggest asset: employees. BI tools helpin keeping track of the workforceperformance and activity, the retentionrate, overall labour effectiveness, theabsenteeism rate. One can then analysewhat works and what does not, in orderto implement fast-response decisionsand bring out the best from youremployees.

SALES AND MARKETING

Sales managers use BI dashboards andkey performance indicators (KPIs) foreasy access to complex information likecustomer profitability, discount analysisand customer lifetime value.

Managers monitor sales and revenuetargets, sales performance along withthe status of the sales across times usingdashboards with reports, charts andother data visualizations. BI systemsprovide real-time campaign tracking,measure the performance and plan forthe future accordingly.

For instance, Starbucks has been verywise in its use of data in determiningoptimal store location with the help ofBI tools. Starbucks leverages data usingAtlas, an in-house mapping andbusiness intelligence platform. Atlasprovides Starbucks with data onpopulation density, consumerdemographics, income levels, publictransport stops and the types of storesin the location. By carefully analysingthis data, Starbucks can interpret foottraffic and average customer spend of achosen location, this helps Starbucks toanalyse the economic viability ofopening a store in that location. Notonly finding the right location, but alsoserving tailored menus was madepossible using BI. Atlas found areas that have the highestalcohol consumption and Starbucksselected stores that would servealcohol as part of a special menu calledas ‘Starbucks Evenings’ in Seattle; thistailored menu strategy has beenexpanded to a growing number ofstores.

In a data-driven company, everydepartment can take advantage of BItools by focusing on why and how theyare using data. These insights generatedby BI tools are going to be critical forbusinesses in the future, owing to theever-increasing amount of dataproduced. As more and morecompanies are heading towardsadopting Business Intelligence fordecision making, the global BusinessIntelligence market is expected to touch$33.3 billion by 2025.

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source: datapine.com

Roshni Panda, Jyotika RayMBA - BM (2020-2022)Xavier Institute of Management, Bhubaneswar

Let’s begin by justifying the need forbusiness analytics, consumer behaviourand the crucial link between them. It isno surprise that the firms thrive in adigital environment where customer-centricity, personalization, andcustomer experience distinguish thewinners from the losers.

According to Forbes, the quantity ofdata produced, stored and absorbed inthe world increased from 1.2 trilliongigabytes to 59 trillion, from 2010 to2020.

It will not be long until those that aretoo tardy to follow in their customer-. Roadmap:

centric, behavioural data-drivenfootsteps find it increasingly impossibleto compete in any business. BusinessAnalytics is the process by whichbusinesses use technologies to collectand analyse data in order to gainvaluable insights. In marketing, analyticscan be used to learn how customers actacross each channel & interaction pointand this can greatly help understandconsumer behaviour. Therefore, it isimportant to understand therelationship between business analytics& consumer behaviour and to simplify itfurther, we present you a roadmapdiscussing the steps involved in theprocess.

How Can Business Analytics Help UnderstandConsumer Behaviour?

Marketing

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demand planning, financial operations, production capacity, marketing initiatives.

1. Data Aggregation and Mining: DataAggregation is a technique that enablesorganizations to achieve specificbusiness objectives or performprocess/human analysis at practicallyany scale by searching, gathering, andpresenting data in a summarized,report-based format. Data aggregationin marketing is generally extracted frommarketing campaigns and the variouschannels through which a businessengages with its clients. It shows howthe product is doing across channels,audiences, and cohorts. Data Mining aids in the prediction ofpotential risks, the growth of sales, thereduction of costs, and theimprovement of customer experience. Italso helps with market segmentation,competitor analysis, audience targeting,and customer acquisition.2. Forecasting: It is a strategy forpredicting the future value for databased on its particular trends. Past data is gathered and evaluatedusing quantitative or qualitative modelsto identify trends that can be used toguide the following:

Corporations can predict consumerbehaviour by using forecastingtechniques in sales and businessstrategies.

consumer sentiment,credit availability, economic conditions,salaries.

Data assists in the formulation ofyour target segment(s) and thedetermination of the optimumpositioning for each. Predictive analytics can also enablethe identification of the mostprofitable categories based onhistorical customer behaviour withineach category.

One can use data that focuses on issuesaffecting the retail industry such as:

3. Predictive Analytics: In the digitalage, predicting consumer behaviourpatterns based on customerinteractions and transactions is vital. Customer experience analytics,consumption-based, expenditureanalytics, multichannel analytics, anddigital footprints left by a user's onlinebrowsing can all be useful predictivedata for driving insightful retailinteractions. Few benefits of predictiveanalytics are:

4. Association and SequenceIdentification: To discover whichproducts are frequently purchasedtogether, association rules may bederived from a database of suchtransactions. Purchases of flashlights, forexample, may usually coincide withpurchases of batteries in the samebasket.

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How to deliver model output in auser-friendly manner?How to integrate it?How to correctly check the analyticalmodel's monitoring?

Recognize patterns, trends, andoutliers.Support a point of view of anargument.Make well-informed choices.Improve information engagementlike blog entries, social mediapostings, eBooks, reports, andpresentations.

Sequence analysis is concerned withpurchasing a product or items after aprior purchase of a product or service.Purchasing an extended warranty, forexample, is more likely to follow (in thatprecise sequence) the purchase of atelevision or other electrical goods. Onthe other hand, sequence rules are notalways evident, and sequence analysiscould help you extract such regulationsregardless of how hidden they may bein your market basket data.5. Optimization of the best solution:After the analytical model has beenvalidated and authorized, the analystwill use the prediction modelcoefficients and findings to drive "what-if" scenarios, utilizing the specifics tofind the optimum answer within theconstraints. The following concerns arenecessary:

The best solution is determined by thelowest error, management objectives,and the identification of modelcoefficients linked to the company'sgoals.6. Data Visualization: As marketers, datavisualization can help communicateand interpret data more effectively. Itmakes information more exciting andaccessible by using visual componentsto tell a story inside it. Marketers mayuse data visualization to:

Choosing a data visualization type thatwill assist you in communicating theinformation in the most effective waypossible.

A marketing funnel will be the suitabletool to define the link between BusinessAnalytics and Consumer Behaviour.Figure 5 shows a simpler illustration ofthe funnel which distinctly shows thesteps of the customer journey.7. Awareness and Consideration:The essential thing at this point is toensure that you are targetingappropriate people to drive traffic toyour website that is likely to purchaseinto your offer. If your stage one leadgeneration tactics bring in traffic that isnot interested in conducting business,you're squandering money, time, andother critical resources. Businessawareness can be generated from theuse of SEOs, advertising, social media,targeted keywords and more.The potential customer is familiar withthe product or service at this point and

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Fig.5 Marketing Funnel

What sort of solutions are buyerslooking for?What is the best way for purchasersto learn about these solutions?

is assessing the problem – how it can besolved and whether it has to be solvedright now. The goal is to show them allof the possible solutions to theirproblem and how advantageous it willbe for them, and how the product mayassist them. There is also a requirementto demonstrate how you are superior toyour competition.

At the stage of awareness andconsideration, 60% of consumers wantto speak with a sales representative.

Making sure sales staff are prepared toaddress any queries clients may have,such as:

8. Decision and Retention:Analysts would then make judgmentsand act based on the model's results inlight of the predetermined businesschallenges. To meet business demands,the period is accounted for in theassessment of conclusion; all favourableand adverse outcomes are calculated inthis time frame.

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If businesses are clever enough to paycareful attention by gathering,evaluating, and acting on customerbehaviour data with the help ofbusiness analytics, it can reveal valuableinformation about customers, business,and the link between the two thatcannot be found anywhere else.

Conclusion:Business analytics may provide solidand valuable visions that would not bepossible otherwise in the absence ofdata. Any firm may improve itsoperational efficiency across severalactivities by using analytics. BusinessAnalytics for marketing has consistentlyhelped businesses to adapt to customerneeds through increased availability ofmerchandise or improved sales reps. It ishere to stay, and companies areinvesting heavily in the training of end-users on business intelligence tools toencourage fact-based decision-making.

1..Introduction:Taxation is the process through which agovernment or taxation authorityimposes or levies a tax on the income ofits citizens and businesses.

2. Structure of Taxation:In India, the tax structure is classifiedunder two main categories:

2.1. Direct Tax:A tax that we pay directly to the taxingbody. For example, the Governmentimposes income tax and corporate tax,which we must pay directly to theGovernment. These taxes are non-transferable to any other company orindividual.

2.2. Indirect Tax: While income and profits are subject todirect taxes, goods and services aresubject to indirect taxes. Direct tax ispaid directly to the Government, butindirect tax is collected through anintermediary from the end-consumer, asignificant distinction between directand indirect tax. It is then theintermediary's job to remit the collectedtax to the Government. E.g., GST, VAT,and Customs duty.

3. Challenges faced by variousstakeholders in the conventionaltaxation method

3.1 Tax authorities: ✔ Authorities are having difficultyanalyzing structured and unstructureddata to identify non-filers and under-reporters of income. ✔ New business models based ondigital technologies and transactionsin virtual marketplaces wouldnecessitate a new tax administrationsystem. As a result, governments aresearching for digital ways tocommunicate with businesses tomake their tax, financial, andoperations data entirely transparent.They rely on consumption taxes andincreased tax transparency frommultinational corporations.

3.2 Business Organizations:✔ Managing and locating finalversions of critical documents isdifficult.✔ There is inadequate information-sharing across tax functions andgeographic locations. Because of theconsiderable repetitional risk thatfirms may suffer due to tax litigation orsocial media-initiated concerns,effective communication of the taxfunction to C-suite executives iscritical.✔ Methods of data collection that areredundant and email-intensive

How Tax Data Analytics is transforming theTax Planning and Compliance Process

Finance

15

Mrityunjay Dass, Gayatri RepalaMBA 2020-22,Indian Institute of Management, Indore

✔ The ability to factor in precise taxcost estimates in business decision-making is a competitive advantage,which is not available in traditionalspreadsheets.

4. How can Data Analytics beimplemented in Taxation?4.1 Requirements:✔ An integrated Tax Data sourceprovides a seamless, integrated view oftax-related data across the organization(from operations to marketing tofinance departments).✔ A robust ERP system captures tax-related data from various departmentsand collates it at a single source usingautomated tools.✔ Use of cloud-based applications,data can be stored and accessedanytime, anywhere.✔ Adopt analytics solutions for real-time informed decision making andembrace predictive analytics to gainactionable insights from data generatedthrough internal business processes aswell as external market sources✔ Appropriate dashboards to enablemeaningful communication from theirtax functions.

4.2 Structure

5. Advantages of Tax Analytics: ✔ Using Data Analytics can increasethe collection of indirect taxes.✔ Government can now know if acitizen owes any tax to the country ifhe/she lives in any other part of theworld.✔ Data Analytics can help automatecustomer due diligence and decreasethe risk of fraud by a significantpercentage.✔ By using predictive analysis, taxauthorities can identify the tax yieldsaccurately.✔ Having data automized makes iteasy to visualize, and one can quicklydraw inferences that help makeinformed decisions. Allows tax expertsto focus their resources on analyzingdata and developing revenue-generating and cost-cutting initiativesrather than spending time obtainingdata.✔ The expenditure pattern of thecitizens can be identified.

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Image source: https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/digital/ey-tax-technology-transformation.pdf

7.1 Example: The use of thecombination of Prediction andClustering Analysis to find thelikelihood of Tax audits

In this case, the model predicts thathigh-income taxpayers who declare ahigher value of charity donations,concentrated in a few charities, willhave their tax returns audited morefrequently.Using precise algorithms, tax analyticswill use clustering, identify groups withsimilar behaviors, and cluster it intomultiple categories. As a result, it will bedone faster, with higher accuracy, andvast quantities of transactional anddetailed data.

8. Recent Developments8.1 Project Insight:India introduced "Project Insight" totrack the people who are more likely notto pay the tax and follow the rules. Theanalytics tool will collect data not onlyfrom traditional sources like banks andfinancial institutions but also socialnetworking sites to correlate spendingpatterns with income declarations. Now,if an individual is traveling to a foreigncountry and posting pictures on socialmedia or buying a luxury car beyond thereturns filed, the I-T Department can useBig Data to analyze them and check themismatch between their earnings andexpenses. Analytics helps to track downthese people and send them messages,emails, and phone calls to remind themabout the tax payment.

Taxable Income > $450k?

NO YES

NO YES

6. Tax Analytics Opportunities in anOrganisation✔ Making Comparison of units overtime✔ Considering the ramifications ofdecisions like buying or selling of assets✔ Tax items are sampled to identifypotential problems and audit risk✔ Tax law interpretation

7. Example of a Tax AnalyticsApplication

7.1 Example: The use of the combinationof Prediction and Clustering Analysis tofind the likelihood of Tax audits:A decision tree may, for example, beused to assess the likelihood of a futuretax audit for a high-net-worth individualbased on historical results.Organizational decision trees can becreated in the same way.

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AuditProbability

= 6%?

Donations >$45k?

AuditProbability

= 18%? No. of Donations < 4

NO

YES

Audit Profitability = 70%

Audit Probability= 30%?

8.2 Exposure to Data post-GSTImplementation: A large amount of data has beencollected from the citizens, especiallyafter the implementation of GST. TheGovernment also got to know thespending of the Indian citizens onforeign products and tried to analyzethe purchase pattern to evaluate the taxevasion. Before Data Analytics,employees had to ask so manyquestions and record the data indocuments, which cannot be kept trackof due to the increased number. Taxdepartments have become smart withthe improved system. It has alsoimproved the tax to GDP ratio.Information is being collected from thepublic forums without invading thecitizen's privacy, making the systemeven more efficient. Sectors such as realestate, mining, pan masala, etc., whichare uncounted wealth, can be identified,and more tax can be collected, andthere is less of taking advantage.

8.3 Extracting advantage by linkingGovt. ID cards:✔ The Government has made itmandatory for all taxpayers to link theirAadhaar numbers to their PANnumbers. While an individual's ability toescape declaring high-value purchaseswas previously limited to using onlytheir PAN to pay taxes, this link of twovital documents has considerablydecreased their capacity to do so.✔ Additionally, taxpayers must utilizeForm 61A to disclose cash receipts, stockpurchases, mutual fund purchases,immovable property purchases, termdeposits, and foreign currency sales.Softwares such as Avalara, TaxCompliance Software Trust map, DrakeTax, Tax Jar, Canopy, Sovas, etc., are theoptions. These softwares can becompared based on user-friendliness,scope, and cost.

updating the administration'swebsite with new information andinstructions making use of generalcommunications tools likeadvertising and social media;contacting individual taxpayersdirectly, such as through SMS orphone.

9. How Covid 19 has changed the taxcompliance process and role of DataAnalytics.✔ Remote WorkingThe actual percentage of employeeswho work remotely climbed by 60%.Two-thirds of administrations acquiredor rented additional IT equipment fortheir employees to help with this. Goingforward, administrations intend tocontinue moving field audit work to avirtual/digital environment.✔ IT system developmentMany tax administrations wererequested to build or improve existing ITsolutions during the crisis, regardinginternal processes or taxpayer servicesand take on additional obligations to aidthe Government with COVID-19 support. For example, over half ofadministrations said they had to createnew processes to provide financialassistance to citizens and enterprises.✔ Taxpayer servicesThere remain many taxpayers thatcontinue to make use of non-digitalcommunication and service offerings,such as paper-based inquiries or in-person visits.

On a positive note, administrationsnoted that they were able to shift asignificant percentage ofcommunications from paper to digitalthrough:

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Anyone who has tried hoarding foodproducts during the lockdown phaseand faced sanitizer shortage hasexperienced the taste of thecomplexities that the supply-chainleaders have faced during thepandemic. These changing conditionshave made it very crucial for all thecompanies to tackle the crisis by beingresilient towards the aftershocks. Insuch a scenario, analytics offers agreater capability to know rather thanspeculate about the future and helps toincorporate risks and resilience as anintegral part of supply chainmanagement.

Over the years, companies havebroadened their supply chainintelligence and analytics has disrupted

every level of the supply chainmanagement process by helpingcompanies to accelerate their journeytowards supply chain analytics. Variousfirms have adopted AI and Analytics inlogistics-network optimization,inventory and parts optimization,improvement in business processes, andincreased visibility in the supply chainprocess through collaboration withsuppliers. With supply chain analyticsgetting more complicated, there havebeen independent software solutionproviders that enable the supply chainanalytics at every level of the businessesmaking it easier for the companies toincorporate AI and supply chainanalytics in their business processes.Consider the case in Minneapolis in 2012when a Target store was able to predictthat a teenage customer was pregnantbefore her father. The girl had had achange in her shopping patterns andwas making a few purchases that theinternal algorithm of the target hadflagged as her being a potential mother.So, the company had sent her certaincoupons and targeted offers for babycribs and clothes. This outraged herfather who only, later on, found out thetruth. All this happened in 2012 and theprediction algorithms have come a longway since then.

Gunjan AhujaPost Graduate Diploma in Management(2020-22)Great Lakes Institute of Management, Gurgaon

The Importance of Big Data Analytics inSupply Chain Management

Operations

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The evolution that Big Data Analyticsbrought to supply chain managementhas evolved over the years fromstatistical analysis to a more integratedanalysis where the companies startedadopting Enterprise Resource Planning(ERP) to easily access data for analysis,forecasting, and planning.

Over the years, businesses began tomake the best use of businessintelligence as well as predictiveanalytics software solutions to providea more detailed understanding of theintricacies of the working of supplychain networks and how to make moreinformed decisions to optimize costand enhance the performance.

Today companies are using AI andcognitive technologies to incorporatedata-driven intelligence into thebusiness and to optimize the businessprocesses by incorporating bothstructured as well as unstructured datathat helps to identify all the availableopportunities in the supply chaininitiative which fosters growth as well ascontrols the revenue losses which arebound to occur due to inefficiencies inthe supply chain. AI capabilities helpsupply chain platforms to automate andself-learn which provides them withintelligence in real-time.

Covid 19 is undoubtedly the biggest oneand there have been unprecedentedshocks that supply chains have had toexperience since the advent ofglobalization. It has highlighted thevulnerabilities in the businesses andnow, more than ever, organizations haveseen the opportunities of acting quicklyand adapting to the changing needs,innovating their business models, andproactively forecasting and predictingevents to be better equipped to dealwith uncertainties and build a moresustainable business process.Consider the case of large supply chainnetworks like Amazon who rely heavilyon their algorithms for them to workout their daily operations. This waythey had relied on some basic form ofBig data analytics to make predictions.

But after the great disruption of theCOVID pandemic, they have had to re-evaluate their algorithms and establishnew working patterns to better suitthem. The Amazon web services is ashining example of how a well-designedsystem can face any uncertainty andreap rich rewards for the client.Role of Big Data in Supply chain in thepost-pandemic worldThe pandemic has exposed vulnerabilityand inflexibility built into many businessmodels and has posed significantquestions to businesses.

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Now, more than ever businesses wish fora system of supply chain analytics that iscapable of predicting the ever-increasing externally created supplychain variables that has an impact onthe overall business performance. In thecovid era, companies have failedmiserably by relying on the steady-statemodels which are seen at the heart ofthe planning systems, and studyinghistorical data alone is no longer reliableto create a baseline. The crisis hasshown the interdependence of differentsegments and the impact of externalvariables on the businesses which hasforced companies to make decisionswhich are based on the informationavailable in real-time which becameparamount for continuity of businessoperations and leading to theintroduction of new capabilities such asorder monitoring being done real-time,end to end visibility of the inventory,enhancing the reverse logisticsexperience and making the supplychains more resilient to futuredisruptions.

Post covid, companies are increasinglyusing analytics to model the potentialcosts and are looking for technologiesthat would provide greater intelligencein evaluating the potential risks byidentifying the macroeconomicopportunities. To succeed in the longterm, it is becoming extremelyimportant to incorporate risk-responseas an integral part of the businessprotocols.Now, companies have recognized theneed for diversifying supplier bases andplan for multiple future scenarios toenhance the ability to navigate newrestrictions. AI can deliver quick resultstranscending regions, languages, andbiases and so success in the future willincreasingly be driven by resilient supplychains and the progressive,collaborative professionals who managethem. The crisis has increased thenumber of variables to be accounted forto better reflect the macroeconomicenvironment and models with highergranularity are likely to be more robust.

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COVID-19 has highlighted the increasedload on legacy systems and has madebusinesses reassess the need forupdates and overhauls. It has evolvedthe importance of big data in supplychains around the world and has testedthe flexibility and resilience of supplychains around the globe. More thanever, enterprises are realizing the needto embrace data and analytics torespond to the changes and break the

existing silos in supply chains byunderstanding the supply chains inmore dimensions and ensuring real-time transparency across. Goingforward, a more comprehensiveoverview of the supply chain andproactive modeling is most likely tobuild resilience in the business, andbalancing of Big-data with empathy willbe more important than ever forcompetitive differentiation.

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BUSINESS ANALYTICS IN HR

Progress and innovation over the past 10years alone have changed the world incountless ways, we realize that humancapital perhaps became the mostsustainable source of competitive edgeand value creation for any company. Therole of HR is critical and is not an easytask, as HR teams have to manage aseries of tools and resources designed todrive real insights and opportunities.

These involve an approach to formdecisions that are supported by factsand numbers, instead of intuition andguesswork. Analytics thus takes the eyewithin the HR monarchy today. BusinessAnalytics Software automates theprocess of gathering, organizing, andanalyzing the data to help HRprofessionals efficiently perform variousfunctions like recruitment, talentmanagement, employee engagement,performance analysis, productivityanalysis, and engagement/ attrition/budget prediction.

Business analytics in HR can helpforesee the employment needs of anorganization that might be required inthe organization’s future and also, figureout the skills which are desirable toimprove business performance.

Moreover, organizations are inclinedtowards data, and explicitly insightsemerge from data, to explore anotherway ahead.

Business Analytics usually employsthree different types of analytics tohelp HR make decisions:

Predictive Analytics

By applying predictive analysis to data,HR can become a strategic partner thatrelies on proven and data-drivenpredictive models, rather than countingon gut feeling and soft science.

People Analytics Maturity Model ofDeloitte’s 2018, only 17% oforganizations worldwide had accessedand utilized HR data. Out of this 17% in2018, 2% of companies have business-integrated data, meaning they use real-time, advanced AI-aided tools togather, integrate, and analyze data.

Deep Arora, Shristhi KumariMBA 2021-23 Symbiosis Institute of Management Studies, Pune

Role of HR in Maximizing EmployeeProductivity in Different MSME Sectors

Human Resource

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Prescriptive Analytics

Prescriptive analytics refers to analyticsthat seek to supply optimalrecommendations during a choicemaking process.Prescriptive analytical approaches canbe profoundly useful for organizationswith peak or hectic seasons. A companywill need to know the number of staffwho can work during the holidays.

Prescriptive analytics can assist todecide how to properly onboard a newhire based on their skills & strengths.

Descriptive Analytics

Descriptive analytics is the basic type ofanalytics, it’s taking historical data andsummarizing it into something that'sunderstandable like a headcount reportof all employees within an organizationis descriptive analytics.

Recruitment

When it comes to hiring, you have hugedata to track down the ideal candidatefor the role. Yet, even before that, youneed to recognize the vital traits of that

optimal candidate, and that is the placewhere Business Analytics comes in.

Business analytics can break downcomparable positions and recognize keyskills and characteristics for the role.This BA-driven methodology assists withenhancing the pursuit and lettingmanagers center around the interviewstage instead.

Measuring Performance, Promotionand Salary

As we know, performance is everything.Business Analytics can assist you withanalyzing the performance of your freshrecruit and perceive how fit they are forthe job. The applicant’s daily reports canbe updated on day one, day 10, day 30,etc. on various analysis tools which notonly help in analyzing their performancebut also indicate success or a failure ofthe onboarding process.

For long-term employees, instead oftying analysis to the employees’ reports,you may focus on other key indicators,such as comparing the metrics withsimilar positions at competingcompanies or career growth rates. Byanalyzing this data, we have a betteroverall picture of an employee’s success,and areas where HR can help––throughproviding training, motivation, or a goodold-fashioned chat. One of Google’sanalysis reports, those who don't get apromotion within four years aresubstantially more prone to leave theorganization.

Business Analytics (BA) can be utilizedto recommend trends, for example,expanded staff turnover in a particularoffice, dips in efficiency, and so on,which may indicate areas for furtherconsideration.

The data gathered can be utilized toanticipate the turnover, pay increment,and workers' requirements as far aspreparing, expertise, improvementmeetings, evaluation, pay, and reward.This might be anything from analyzingthe aftereffects of employee fulfillmentsurveys and comparing them withproductivity levels to uncover areas ofconcern.

Training and Development

This may be used to uncover lowproductivity rates within departments,indicate a need for either more staff tohire or need for further analysis, orperhaps identify training needs bylooking at which department hasn'tupdated their skills yet. We can observeareas of the experience that were failingemployees who left according toengagement survey responses, and thereasons employees gave for leaving byexit survey, and load all that informationinto the system to inform the model.

Predicting Attrition

The Percept research database containsa set of nearly 100,000 employees withboth employee engagement surveyresults and exit data. This provides ahuge, globally diverse, and statisticallyrelevant dataset for conducting researchspecific to attrition.

In analyzing the pre-exit response datafrom these respondents to four standardengagement items (intent to stay,referral behavior, intrinsic motivation,and pride in company), employees whowere mostly engaged had an attritionrate of 5.7% in the next six months afterthe survey, less than one-third of the20.6% attrition rate for employees whowere actively disengaged.

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The data also shows a strong correlationbetween the quality of theemployee/manager relationship andattrition in the next six months after theengagement survey. Relationship ofemployee-manager getting a tag of“poor”, 17.8% left the organization -almost double the 9.6% rate of attritionfor relationships tagged “good”. Because top performers are always indemand, an efficient employeeretention model is so important.Predictive analytics is the key to thedevelopment of this model.

Critical Evaluation

With technological advancements, thebusiness has developed the use of HRanalytics that improves organizationaleffectiveness. HR analytics quantifiesand provides data-driven decision-making by using statistical models andtechniques.

It is analyzed that implementation andusage of HR analytics in business havebeen challenging as the HRprofessionals may lack the requiredskills and knowledge of using the HRanalytics tool or there may be dataquality or data governance issues. Dueto such an issue organization may notget the support of top management.

Despite such challenges, HR analyticshelped businesses in gainingcompetitive advantage, solving HR-related problems, improvingorganizational performance, and theHR function.

Data can be used and stored ethicallyand legally for best use if theorganization has relevant rules andpolicies.

Conclusion

The study explains that HR analyticsusage and implementation have bothpros and cons but if analyzed on abroader concept then opportunities ofusing HR analytics diminishes thechallenges and lead to the tremendousgrowth of the organization. It isanalyzed that if an organizationunderstands the right purpose ofimplementing HR analytics, then theycan get a better return on investmentand businesses will accept and startinvolving HR analytics in HRdepartments. Soon HR analytics usagewill rise and help the organization ingetting evidence-based results and willtransform the working of the HRdepartment from traditional tostatistical decision making.

The right use of HR analytics in theright business can lead to thetremendous growth of HR analytics inan organization providing them togrow faster.

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WeAchievers

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Disha Patil

Disha PatilPGDM HCM(2019-21)

Best B-school Project Award 2020

I won the 3rd prize in ‘Best B-School Project Award2020’ by Business Standard. This competition

highlighted the top 5 summer internship projectsacross B-Schools in India with the choice of subject

topics presented ranging from public health toemployee attrition to therapeutic platforms and

many more.

Santosh Chintakindi

Santosh ChintakindiPGDM HCM(2020-22)

Medical Device Hackathon

I won the ‘Novel Design Award’ at the MedicalDevice Hackathon organized by IIT Bombay, for

innovation of a Medical Device - Oral Appliance fortackling the blockage of airflow to lungs inObstructive Sleep Apnea (OSA) patients.

Top 5 Nationalist | We were among the top 5 teams on a national levelin SC Quest, DRISHTI 2021, a competition by Symbiosis Institute ofOperations Management. It aimed at testing the ability of students in

finding a supply chain strategy that suits your company best and also actsas a differentiating factor.

Three of a Kind

WeAchievers

Vaibhav MurudkarPGDM

(2020-22)

Vinit HulePGDM RM (2020-22)

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Tanya MahajanPGDM

(2020-22)

Word limit: 800 - 1200 words Cover page should include your name, institute name, course details &contact no. The references for the images used in the article should be mentionedclearly and explicitly below the images. Send in your article in .doc or .docx format, Font size: 12, Font:Constantia, Line spacing: 1.05’ to samvad.we@gmail.com. Please name your file as: <Your Name>_<title>_<section name e.g.Marketing/Finance>Subject line: <Your Name>_<Course>_<Year>_<Institute Name>Ensure that there is no plagiarism and all references are clearlymentioned.Clearly provide source credit for any images used in the article.

We invite articles for the 113th Issue of 2021 of SAMVAD.

The Theme for the edition - “Social Innovations and Entrepreneurship”

The articles can be from Finance, Marketing, Human Resources, Operationsor General Management domains.

You may also refer to sub-themes on Dare2Compete.

Submission Guidelines:

Call forArticles

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Parag JoshiChief Editor

Sivapriya JayaprakashCo-Editor

Sanjyot MahajanCo-Editor

EDITORS GUILD

Harshita SharmaHead

CREATIVE MINDS

Aakash RaiMember

Nikita BansalMember

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Srija Jha Head

Aayushi SachdevHead

Mandar BhagdikarDeputy Head

Ayushi ChoudharyMember

Parita LimbadMember

Akshata GunjanMember

PUBLIC RELATIONS PROS

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Mitali SatwilkarMember Member

Sohan Soni

CONTENT CURATORS

Harshita AjwaniHead &

Content Curator - HR

Aditi Pandey

Shubham Wagh

Twesha DharDeputy Head &

Content Curator - Marketing

Animesh Pandey Content Curator - Ops Content Curator - Fin Content Curator - GM

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