1、400 Bn EBITDA opportunity with Advanced analytics and AI in Retail45Opportunity landscapeMeet the AuthorsArpit AgarwalProject LeaderBoston Consulting GroupAbheek SinghiManaging Director&Senior PartnerBoston Consulting GroupNamit PuriManaging Director&PartnerBoston Consulting GroupBharat MimaniManagi

2、ng Director&PartnerBoston Consulting GroupRajat MathurPartnerBoston Consulting GroupShivam JainPrincipalBoston Consulting GroupAbout BCGAbout RAIBoston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities.BC

3、G was the pioneer in business strategy when it was founded in 1963.Today,we work closely with clients to embrace a transformational approach aimed at benefiting all stakeholdersempowering organizations to grow,build sustainable competitive advantage,and drive positive societal impact.Our diverse,glo

4、bal teams bring deep industry and functional expertise and a range of perspectives that question the status quo and spark change.BCG delivers solutions through leading-edge management consulting,technology and design,and corporate and digital ventures.We work in a uniquely collaborative model across

5、 the firm and throughout all levels of the client organization,fueled by the goal of helping our clients thrive and enabling them to make the world a better place.Retailers Association of India(RAI)is the unified voice of retailers in India.A not for profit organization,RAI,works with various stakeh

6、olders to create the right environment for the growth of modern retail in India.It represents an entire gamut of retailers,from chain store retailers and department stores to independent emerging retailers.RAI encourages,develops,facilitates and supports retailers to modernize and adopt best practic

7、es.It works with all levels of the government and stakeholders to drive employment opportunities,promote retail investments,drive thought leadership,enhance customer choice and build industry competitiveness.ForewordIn todays fast-paced environment,businesses are constantly looking for ways to stay

8、ahead of the competition and meet the evolving needs of consumers.Leading retailers across the globe are aggressively leveraging advanced analytics and AI solutions driven by its potential to significantly enhance customer value proposition,streamline operations,bring in efficiency and establish dif

9、ferentiation.By leveraging these technologies,retailers can gain valuable insights and make smarter decisions that drive overall growth and profitability.This report on 400 Bn EBITDA opportunity with Advanced analytics and AI in Retail,jointly developed by Boston Consulting Group(BCG)and Retailers A

10、ssociation of India(RAI),takes a comprehensive look at the potential opportunity in Indian context,and sheds light on innovative ways in which retailers globally are leveraging advanced analytics and AI across the value-chain to unlock value.The report also shares overview of the maturity level and

11、extent of current adoption of advanced analytics and AI by Indian retailers,various approaches taken and challenges faced.Further,the report also covers a roadmap for Indian retailers including how to get started,the right approach,capabilities and type of partnerships needed to ensure successful ad

12、option and value realization.We believe,with a deep understanding of the potential benefits and limitations of advanced analytics and AI,retailers can chart a clear path forward and take advantage of the numerous opportunities these technologies present.Overall,this report serves as a guiding frame

13、for retailers looking to leverage AI and advanced analytics to boost their business priorities.Whether you are already deep into your AI and advanced analytics journey or just starting out,this report will provide you with the learnings and perspective that might help you succeed in the rapidly evol

14、ving world of retail.Abheek SinghiManaging Director&Senior PartnerBoston Consulting GroupKumar RajagopalanChief Executive OfficerRetailers Association of India(RAI)400 Bn EBITDA opportunity with Advanced analytics and AI in Retail89Opportunity landscapeExecutive SummaryAdvanced Analytics and Artific

15、ial Intelligence(AI)are rapidly transforming the retail industry,revolutionizing the way retailers operate and interact with customers.These technologies are helping retailers to gather,analyze,and interpret vast amounts of data,enabling them to make more informed decisions and improve the overall c

16、ustomer experience.Globally,the Advanced Analytics and AI Champions have gained substantial market share with significant revenue growth and margin unlock.In India,if done well and at scale,retail industry has potential to unlock 400 Bn incremental EBITDA over next 5 years.Indian retailers recognize

17、 the opportunity and are bullish on the power and relevance of AI and advanced analytics and many leading retail players have already set off on their journey.Advanced analytics and AI use-cases span across the value chain and can unlock 200-300 bps of profitability and provide 8-10%incremental grow

18、th over next 5 years.Relative importance of the use-cases vary across sub-sectors basis characteristics of the sub-sectors.Globally,retail leaders have successfully leveraged AI and advanced analytics to solve for critical business challenges and have achieved significant impact.While larger&digital

19、-first retailers such as Alibaba have deployed use-cases across the value chain,others have deployed specific use-cases and scaled them first.Multiple learnings from global retailers:Solve critical&high-value business problems first,demonstrate value and kick-start flywheel of sustained value creati

20、on for analytics scale-upFocus on fast adoption of use-cases instead of perfecting the algorithm,build iteratively and scale-up in an agile manner Build strong in-house dedicated team to manage internal complexity and gain competitive advantage,and complement them with right partnerships wherever ne

21、ededEstablish robust data governance to ensure availability of high-quality and structured data with a single source of truthBuild top-down conviction and right positive and receptive environment for change solve in an integrated manner with business processesThere has been a rapid increase in spend

22、ing on analytics&demand for talent in India,but significant headroom exists when compared to other Asian markets.However,Indian retailers have created a large impact already with analytics and AI in driving growth and profit objectives through various use cases like pricing,sourcing,last-mile and tr

23、end analytics amongst others.Large-size brick-and-mortar players and digital-first retailers have deployed analytics use-cases across the value chain,while mid-size retailers have taken a pragmatic approach with a few high-impact ones.Retailers have found their own balance of in-house and outsourced

24、 capabilities.This has been driven by the trade-offs between cost of operations and their ability to retain talent.While retail organizations are increasingly targeting massive value creation opportunity through adoption of advanced analytics and AI,they must build necessary capabilities to realize

25、its full potential.Change management is the most critical component of this journey and needs way more attention from leadership than algorithms and technology.A strong foundation to the transformation journey requires a cohesive approach towards Data,Tech and People&processes with change management

26、 embedded in the ways of working to deliver sustained value creation.Strong data governance to ensure the availability and the quality of data for AI modelsRobust tech back-bone to ensure scalability and flexibility to build-vs-buy solutionsRight people and process enablers with re-skilling,bridging

27、 capability gaps,agile ways of workingAs retailers think of the journey on analytics,they should start small and scale with demonstrated positive business impact.This is a journey that-if executed thoughtfully yields sufficient benefits during its ignition phase to fund the next acceleration level.4

28、00 Bn EBITDA opportunity with Advanced analytics and AI in Retail1011Opportunity landscapeContentsPage 4859Page 3447Page 2433Page 1223Building capability&managing changeStarting position for retailers in IndiaLearnings from exemplarsOpportunitylandscape01020304400 Bn EBITDA opportunity with Advanced

29、 analytics and AI in Retail1213Opportunity landscapeOpportunity landscape01400 Bn EBITDA opportunity with Advanced analytics and AI in Retail1213Opportunity landscape400 Bn EBITDA opportunity with Advanced analytics and AI in Retail1415Opportunity landscapeSource:EuromonitorGlobal retail had recover

30、ed from COVID-19 in 2021 but has been challenged recently given consumption slow-downRetail Market Size($Tn)15.916.316.716.717.617.3+2%0%+5%-2%201720182019202020212022400 Bn EBITDA opportunity with Advanced analytics and AI in Retail14countries have seen a decline in retail market size in 2022 vs 20

31、2128/Top 50 However,India is in a shining spot and well on path to hit$1.1 Tn by 2027Source:Euromonitor,Quarterly reports of top listed companies650-700610-630740-7601,100-1,200-7%10%8-10%2019202020222027(P)Retail Market Size($Bn)Increase in share of e-commerce channel in last 3 yearspoints2%+CAGR f

32、or top offline retail chains in 9M FY23 vs 9M FY2015%+400 Bn EBITDA opportunity with Advanced analytics and AI in Retail1617Opportunity landscapeExplosion of data and ability to monetize a game changer90%4x10 xOf all data existing today was generated in last 2 yearsIncrease in computing and network

33、speed in last 5 yearsIncrease in data storage on cloud in last 5 yearsSource:Secondary research,Press searchAnalytics is moving towards being prescriptive&automatedMachineManEvolution of analytics in RetailDATAINFORMATION DISPLAYINSIGHTDECISIONACTION ANDEVALUATIONWhat did happen?DESCRIPTIVEStatistic

34、s/visualizationsWhy/how did it happen?DETECTIVEHypothesis testingWhat will happen?PREDICTIVEMachine learning and simulation What should I do?PRESCRIPTIVERecommendation/Decision support systemsDecision Automation400 Bn EBITDA opportunity with Advanced analytics and AI in Retail1819Opportunity landsca

35、pe7 of 10 game changing retail trends are heavily enabled by Advanced analytics and AICustomer centricity and digital marketing The store of the futureOptimized execution Omni-channel 2.0:Consumers expect seamless,omni-channel experiencesCustomization boosts customer engagement and reachData and tec

36、hnology unlocks personalization at scaleAdvocacy marketing fuels exposure and engagement Showrooming:Online retailers are getting physicalMobile payment is making spending seamlessSmall is beautiful:Retailers focus on smaller and inspiring store formatsExperiential retail:Creating unique and interac

37、tive experiences(AR/VR)for customers Instant supply chain is becoming a realityService automation improves customer experience while lowering costs400 Bn EBITDA opportunity with Advanced analytics and AI in Retail18Advanced analytics and AI enabledAdvanced analytics and AI re-shaping the retail valu

38、e chain globallySource:Secondary researchAutomation in warehouse operationsCHINESE ONLINE RETAILERAI-based demand forecasting&inventory trackingGLOBAL FASHION RETAILERStore network optimizationAFRICAN GROCERY RETAILERAI-based image recognition eliminates checkout linesAMERICAN ONLINE RETAILERCollect

39、s feedback from social community for design innovationsAMERICAN WOMEN FASHION RETAILERTrend detection to design collectionGLOBAL APPAREL RETAILERDynamic shelf prices based on store traffic analyticsAMERICAN DEPARTMENTAL STORE CHAINPrecision marketing for micro-targetingFURNITURERETAILERAI driven ind

40、ividual,personalized offersGLOBAL COFFEE CHAINIn-store experience and service via videoEU ELECTRONICS RETAILERProduction andlogisticsCategorymanagementStore layoutand build upCRM and loyaltyMarketing,Sales and Pricing400 Bn EBITDA opportunity with Advanced analytics and AI in Retail2021Opportunity l

41、andscapeAdvanced analytics and AI champions have gained market share at expense of laggardsMarket share evolution of champions,mid-tier and laggards1 over 10 years Market share indexed to 100100201220132014201520162017201820192020202111110189ChampionsMid tierLaggards1.Advanced analytics and AI Champ

42、ions,Mid-tier and Laggards are the top quartile,mid 50%and bottom quartile of retailers in terms of overall maturity score respectivelySource:BCG Digital and AI maturity study with 100+retailers globally to estimate their digital and AI maturityChampions starting to break awayStable YoY MS capture b

43、y the largest retailers that have been investing in Advanced analytics and AI since 2012Significant opportunity for unlocking value:8-10%revenue growth and 2-3%EBITDA upliftProduction andlogisticsCategorymanagementStore layoutand buildCRM and LoyaltyMarketing,Sales and PricingStore location optimiza

44、tionStore work-force planningOn-shelf availabilityTalent managementPersonalization and CLM approachSmart retentionProspect targetingAI+Digital experienceCategory pricingMarkdown/Promo optimizationMarketing mix managementLocalized pricing&promosDemand forecastingPlan,buy and allocateOmni-channel fulf

45、illmentWarehouse&route optimizationTrend detectionAssortment localizationSpace optimizationCategory negotiation400 Bn EBITDA opportunity with Advanced analytics and AI in Retail2223Opportunity landscapeAdvanced analytics and AI can unlock 400 Bn incremental EBITDAImpact from Advanced analytics and A

46、I1Value at stake2LaggardsChampions1.BCG Digital Acceleration Index(DAI)-Global Study 20222.BCG analysis:Size of organized retail(e-commerce and chain stores)is around 8-9 Tn in 2022,expected to grow by 16-18%to 19-20 Tn in 2027;Potential EBITDA impact of 2%points and 8-10%revenue growth over 5 years

47、 due to adoption of Advanced analytics and AIEBITDA ImpactRevenue Impact(over 5 years)+1pp+2pp6%2%8%10%3%400 Bnincremental EBITDA by 2027Strong conviction among Indian retailers that Advanced analytics and AI can unlock profitable growthThere was a famous quote that came about 10-15 years back-Data

48、is the new oil.We are at the beginning of the next cycle of innovation-where AI represents the broad basket of techniques thatll mark the creation of revolutionary new engines that will consume the new oil and churn out insights at a pace and scale never seen before.Rakshit Daga CTO,Big Basket“Our p

49、roactive approach to AI and analytics has enabled us to reap numerous benefits across various use cases-from Pricing and Personalization to Warehouse management and Margin optimization.There is no set playbook when it comes to Advanced Analytics and AI the use cases and their applicability is bespok

50、e for every business.We realized this early and have evolved in this journey by building a massive data engine and institutionalizing a strong A/B testing process on this data for every initiative we undertakeGaurav AgarwalCo-founder&CTO,1MGSource:BCG interviews with Indian retail CXOs;NASSCOM AI Ad

51、option Index(2022);Press search;BCG Analysisorganizations have Advanced analytics and AI strategy defined at functional or enterprise level 65%CXOs considering Advanced analytics and AI within top 3 priorities for their organizations8/10organizations have set up a dedicated Advanced analytics and AI

52、 team44%2425Learnings from Exemplars400 Bn EBITDA opportunity with Advanced analytics and AI in RetailLearnings from exemplars0225Learnings from Exemplars24400 Bn EBITDA opportunity with Advanced analytics and AI in Retail2627Learnings from Exemplars400 Bn EBITDA opportunity with Advanced analytics

53、and AI in RetailGroceryDurables&specialtyFood ServiceGroceryIndustry characteristics vary across the various retail sub-sectorsPURCHASEFREQUENCYLowerHigherDurables&specialtyFashionFood ServiceGroceryWIDTH OF SELECTION LowerHigherFashionASSORTMENTREFRESH FREQUENCYPerennialSeasonalDurables&specialtyFa

54、shionFood ServiceGroceryEASE OF PRICE COMPARISON VS PEERSLowerHigherDurables&specialtyGroceryFashionFood ServiceSHELF LIFE AND RISK OF SHRINKAGELowerHigherDurables&specialtyFashionFood Service which determines the relative importance of various use-casesDurables&specialtyFashionFood ServiceIntegrate

55、d Online PlatformGroceryCategory pricingTrend detectionMarkdown/Promo optimizationDemand ForecastingAssortment localizationPersonalization&CLM approachLocation optimizationMarkdown/Promo optimizationSmartretentionPersonalization&CLM approachDemand ForecastingLocationoptimizationWarehouse&route optim

56、izationPersonalization&CLM approachMarkdown/Promo optimizationTOP 3 USE CASESLocalized pricing&promosWarehouse&route optimization Personalization&CLM approachCategory pricingCategory pricingTrenddetectionMarkdown/Promo optimization Smartretention CategorypricingSmartretention NEXT SET OF IMPORTANT U

57、SE CASES2829Learnings from Exemplars400 Bn EBITDA opportunity with Advanced analytics and AI in Retail KEY LEARNINGSGlobal Coffee Chain|Strong data and tech back-bone core to becoming the most personalized brand globallyEstablish robust data governance practices to ensure availability of accurate&st

58、ructured dataACTIONIncorporated strong data governance practices to ensure data collected is accurate and well-structured.Created an advanced personalization algorithm focusing on 3 elements:Customer DNA,Offer DNA and Occasion contextMoved from segmentationto individualization enabling tailored comm

59、unicationIMPACTIncremental revenue per redeemer3xIncrease in consumer engagement150%Source:BCG analysis and case experienceCONTEXTGlobal Coffee Chain wanted to enhance customer experience through hyper-personalization leveraging their vast customer database(100Mn+weekly transactions).30 variants400k

60、 people per variantHi Phil!You are near Oxford st.Currently 50%off on your favorite drink:Vanilla Latte!380k variants32 people per variant28400 Bn EBITDA opportunity with Advanced analytics and AI in RetailGlobal Fast-fashion retailer|Agile approach for test and scale-up was key to perfect assortmen

61、tIMPACTSKUs rationalized but still achieved significant sales growth(impact for select store)40%KEY LEARNINGSFollow value-lens approach for prioritizing use-cases to create a fly-wheel of sustained value creation Quickly develop a use-case,test it in few markets and then swiftly scale it across the

62、organizationACTIONRetailer implemented Assortment localization use-case leveraging advanced analytics taking a test-and-learn approach eventually leading to large-scale roll-out.Standardized approach to allocate merchandizeRelying on fashion shows/magazinesMinor tweaks based on staff inputsAnalytica

63、l approach to customize assortment leveraging expansive data repositoryPurchase and return transactionsLoyalty card holder details and preferencesSearch engine trendsSocial media and blog post listeningCONTEXTRetailer had been facing a slump in same store sales leading to unsold inventory accumulati

64、on primarily driven by store assortment not being in line with local customer preferences.Source:Secondary research&press search29Learnings from exemplars3031Learnings from Exemplars400 Bn EBITDA opportunity with Advanced analytics and AI in Retail 30400 Bn EBITDA opportunity with Advanced analytics

65、 and AI in RetailChinese E-commerce Platform|Pioneered AI adoption driven by strong top-down conviction and focusReduction in travel distance via route optimization30%Customer queries handled by chatbots95%Higher conversion for merchants20%Implemented multiple advanced analytics and AI use-cases acr

66、oss the retail value chain with the objective of building differentiation,enhancing customer value proposition,and streamlining operations.Trend forecasting based on customer browsing and social media activityOptimized logistics and warehouse operations leveraging robotic automationZero-staff store

67、powered by AI technologyPersonalized storefronts&landing pages for merchants with individualized offersAI-based chatbot for merchants to handle customer service requestsCONTEXTChinese online retail platform,pioneers in adoption of advanced analytics and AI,with strong top-down conviction and organiz

68、ational focus on building competitive advantage and differentiation in core business leveraging technology.ACTION KEY LEARNINGSStrong top-down conviction of having advanced analytics and AI at the core of business processes is essential to drive sustainable transformation.IMPACTSource:Secondary rese

69、arch&press search31Learnings from exemplarsEuropean Grocer|Partnered with external vendors to deploy next-gen pricingPartnered with external vendors to develop a tailored and dynamic pricing methodology for 500+SKUs across multiple storesACTION KEY LEARNINGSLarge European grocer facing stiff competi

70、tion due to aggressive discounting levels from incumbent retail chains and discounter retailers.CONTEXTPartnered with external vendors for accelerated adoptionRevenue upliftMargin uplift2%5%IMPACTDefine Key Value Items(KVIs)Conduct Geospatial Competitor Analyticsbased on consumer value perception:Se

71、asonality in volumesPrice elasticityBasket penetrationCustomer price recallbased on geographical proximity of different grocers and discounters to consumerSource:BCG analysis and case experiencePricing Optimization Engine3233Learnings from Exemplars400 Bn EBITDA opportunity with Advanced analytics a

72、nd AI in RetailLearnings from global analytics&AI championsIdentify core business problems to kick-start flywheel of sustained value creationBuild strong in-house team for competitive advantage&complement with partnershipsAdopt a test-and-learn approach instead of perfecting the algorithm,and scale

73、iterativelyRobust data governance crucial for high-quality structured data with a single source of truthTop-down conviction and receptive environment critical to drive change3435Starting position for retailers in India400 Bn EBITDA opportunity with Advanced analytics and AI in Retail3440,000 Cr EBIT

74、DA opportunity with Advanced analytics and AI in RetailStarting position for retailers in India0335Starting position for retailers in India34400 Bn EBITDA opportunity with Advanced analytics and AI in Retail3637Starting position for retailers in India400 Bn EBITDA opportunity with Advanced analytics

75、 and AI in RetailRetailers are investing behind Advanced analytics and AI in India1.IDCs Worldwide AI Spending Guide(2022),2.Internet&Mobile Association of India(IAMAI),3.NASSCOM AI Adoption Index(2022)Advanced analytics and AI Spend in India increased by 3X over last 3 years1 India upcoming as a gl

76、obal hub for Advanced analytics and AI talent.However,demand still growing faster than supplyof the worlds Advanced analytics and AI talent is produced in India2 16%demand-supply gap for the right talent in 2021,widened from 14%in 20183 33%20182411%12%3-3.5%20217602025(F)2,266India Investment as%of

77、globalAdvanced Analytics and AI spending in India($Mn)3x3x5 key emerging themes from Advanced analytics and AI journey of Indian retailers37Starting position for retailers in IndiaIndia lagging Asian peers on Advanced analytics and AI maturity especially on technology,people&skills,and data governan

78、ceMid-sized Indian retailers have taken a pragmatic approach with focused use-cases Balancing in-house and outsourced resources crucial to manage cost and talent retentionIndian retailers have started creating huge impact through use of advanced analyticsLarge physical and digital retailers have ado

79、pted multiple use-cases across the value chain3839Starting position for retailers in India400 Bn EBITDA opportunity with Advanced analytics and AI in RetailAdvanced analytics and AI Maturity|India has a tremendous opportunity to scale-up capability1.Excluded India from Asia&Rest of the World(RoW)Sou

80、rce:BCG Digital Acceleration Index(DAI)-Global Study 2022TechnologyStrategyUse CasesPeopleData GovernanceOverallINDIAASIA1CHINAJAPANRoW15361685859Average Advanced analytics and AI maturity score65626571586246524549485074666361647261605654657259624041Starting position for retailers in India400 Bn EBI

81、TDA opportunity with Advanced analytics and AI in RetailAdoption|Indian retailers have started leveraging Advanced analytics and AI for higher growth and profitRetail CategoryUse CaseImpactSource:Press search;expert interviews;BCG analysisIntegrated Online PlatformOnline marketplace for unbranded pr

82、oducts using analytical engine for price recommendationsFashion&BeautyRetail CategoryUse CaseImpactE-commerce grocery player ensuring quick last-mile delivery via route optimizationGrocery/Departmentalon-time deliveries of groceries vs 70%earlier99%adoption by sellers to sell products at the recomme

83、nded prices90%E-commerce fashion giant using AI-driven trend prediction to design clothingOnline fashion brand using for accurate ETA commitment,lowest SLAs and costaccurate ETA prediction97%reduction in no.of packages20%Mens fashion brand enabled 1:1 automated customer engagement and dynamic offers

84、75%DND customers activated 3x better hit rate 100Cr+revenue brand with no human involvement120+designsgenerated per dayMobile retailer analyzes 20+parameters to suggest store-level pricing for accessories like insuranceElectronicsFurniture&Home furnishingsFurniture rental company performing last-mil

85、e route optimization Sleep&home solutions company leveraging advanced analytics for precision targetingSource:Press search;expert interviews;BCG analysisQSR chain expanding the food delivery business through target marketing during COVID-19FoodServicesRetail CategoryUse CaseImpactIndian online pharm

86、acy retailer using differential discounting e.g.,by time of dayPharmacyincrease in the bottom line for insurance20%+30-40%growth driven by targeted communicationsincreased average order value33%increase inProfit/SKU7%reduction in logistic cost17%9xincrease in home delivery orders in 6 monthson-time

87、deliveries vs 57%earlier85%4243Starting position for retailers in India400 Bn EBITDA opportunity with Advanced analytics and AI in RetailLarge B&M&digital retailers|Wider spread of use-cases adopted across the value chainIllustration|Vertical e-grocery player,enabling Advanced analytics and AI into

88、its operations across the value chain Food wastage minimized,ensuring high quality standardsIOT BASED FOOD QUALITY CONTROL 90%of final orders already recommended by the AI toolPERSONALIZED PRODUCT RECOMMENDATIONS TOOL99.9%on-time deliveries;Clubbed deliveries and optimum routes minimize costsROUTE O

89、PTIMIZATIONVisibility on customers,business activities&market trendsINVENTORY MANAGEMENTSuggests best market price as compared to competitorsDIGITAL PRICINGTo improve customer delight through quick support;reduce manpower costAI CHATBOTSEnsures right segregation&clubbing of various food items basis

90、temperature,quality,etc.AUTOMATIC SORTING&GRADINGSource:Press search;expert interviews;BCG analysis Procurement&ManufacturingPricing&PromotionSales&After-salesMid-sized retailers|Sharp and pragmatic approach with priority use cases Select IllustrationsSource:Press search;expert interviews;BCG analys

91、is Indian electronics retailer uses AI to enhance customer serviceMobile retailer using AI to increase in-store emp productivityWritten reviews/feedback crawl to gauge issue and propose solution and next steps to service teamVideo-based analytics to determine optimal customer-to-staff ratio on varyi

92、ng days and timesAI based real time sentiment analysis for assisted response through speech/voice recognitionAI enabled monitoring of CCTV footage created automatic alerts in case of any anomaliesPoor NPS(40),High complaint resolution TATContext Low labour productivity in stores,high absenteeism Con

93、text Impactpoints increase in the NPS score8-10fall in customer complaint TAT20%of staff costs saved by mix of full-time&part-time staff model21%Improved efficiency&flexibility with better in-store time and fewer long breaks4445Starting position for retailers in India400 Bn EBITDA opportunity with A

94、dvanced analytics and AI in RetailCapability|Crucial to balance in-house and external resourcing for effective long-term transformationSource:NASSCOM AI Adoption Index(2022);Expert interviews;BCG analysisAdvanced analytics and AI leaders/mature firms have developed in-house capabilities across 3 key

95、 dimensionsof firms have designated cross functional Advanced analytics and AI teams34%of firms outsource their Advanced analytics and AI capabilities 25%Mid-sized companies typically outsource data engineering and solution design,but keep data governance and maintenance in-house.while larger compan

96、ies have full-scale in-house analytics teamsValue realization team to improve data driven systems,cross functional team to create strong feedback loopPROCESS AND OPERATING MODEL Advanced analytics and AI tools and automation capabilities significantly crashing period of streamlining of modelsTECHNOL

97、OGYThriving R&D community of domain experts,data scientistsPEOPLE4647Starting position for retailers in India400 Bn EBITDA opportunity with Advanced analytics and AI in Retail CEO speakAvijit MitraManaging director&Chief Executive OfficerCroma-Infiniti RetailIn a tight margin business like retail,AI

98、 can be a disruptive competitive advantage or a severe drain on profitability,depending on how smartly retailers choose areas of investment in AI.Nilesh GuptaDirectorVijay SalesWe,at Vijay Sales,believe that data analytics is core to our business.Our Advanced analytics and AI journey has been use ca

99、se specific and not a full scale transformation e,g.,we started by analytically driving inventory/stock management in a big way and are looking at sales enablement as the next area to unlock value.Given nature of our business and ability to nurture the right talent in-house,we have outsourced our AI

100、/AA requirements which has worked well for us.4640,000 Cr EBITDA opportunity with Advanced analytics and AI in RetailSagar DaryaniChief Executive OfficerWow!Momo FoodsData has always been a crucial aspect of our business.From production to sales,we have embraced advanced analytics and have implement

101、ed multiple use cases across the value chain e.g.precision targeting,store opening algo,operations efficiency improvement and many more to unlock profitable growth for the business.47Starting position for retailers in IndiaV.Noushad Managing Director Walkaroo InternationalAdvanced Data Analytics has

102、 immensely helped Walkaroo to define inventory levels across outbound supply chain and has resulted in significant improvement in availability across all sizes and colours.We are looking to extend the data analytics for predicting the design and quantity of new launches based on SKU level data recei

103、ved from markets.Gulshan BakhtianiFounder DirectorWellness ForeverAI and use of advanced data analytics is the future and the future is now.However,we need to choose the use-cases carefully to reap the right benefits.Creating an algorithm is not the biggest part,it is the behavioral&cultural change

104、in the organization about acceptance of digitization&AI.Moreover,data hygiene and correct data recording is a most important starting point to build any AI solution,else that reduces belief in the analytics solution4849Building capability and managing change400 Bn EBITDA opportunity with Advanced an

105、alytics and AI in RetailBuilding capability and managing change0448400 Bn EBITDA opportunity with Advanced analytics and AI in Retail49Building capability and managing change5051Building capability and managing change400 Bn EBITDA opportunity with Advanced analytics and AI in RetailKey to start smal

106、l and scaling with demonstrated business impact 1234TRANSFORM ORGANIZATIONNew ways of workingAnalytics and business strategy in lock-stepRight organization and processes43SCALE TO SOLUTIONIterative tech scale upPurpose fit tools 2BUILD,TEST,ITERATERight designPractical applicationSTART WITH THE BUSI

107、NESS OPPORTUNITYBusiness firstValue focusLean technology13 key enabling capabilities to deliver sustained value creationDATA GOVERNANCETECH BACK-BONEPEOPLE CAPABILITYData structureData policiesData toolsData org.participantsData platform and cloud architectureAnalytics toolingRoles&structureTalent&c

108、apabilitiesAgile ways of workingCHANGE MANAGEMENT5253Building capability and managing change400 Bn EBITDA opportunity with Advanced analytics and AI in RetailData Governance:Critical due to fragmented data landscape and de-centralized management in IndiaTo ensure complete,accurate and compliant use

109、of dataDATA POLICIESDefine rulebooks,documentation and master data managementTo build a common understanding of dataDATA STRUCTURESDefine consistent data glossaries,models,flow mapsTo make data a shared company assetDATA ORGANIZATION PARTICIPANTSDefine key stakeholders,roles and decision-matrixTo es

110、tablish single source of truthDATA TOOLSLeverage the right hygiene tools for easier data tracing and managementTech back-bone:Indian retailers should focus on building the right data architecture vs changing core systemsAvailable and secure for cyber-security and access controlModular architecture f

111、or easier adaptation across use casesOpen architecture for flexible access to build new use casesAuditable&compliant data platform to provide value-adding capabilitiesLean core systems for stable back-end processesCloud services and automated provisioning for scalable infrastructureINTEGRATION MANAG

112、EMENTSECURITY AND ACCESS5455Building capability and managing change400 Bn EBITDA opportunity with Advanced analytics and AI in RetailTalent&Capabilities:Upskilling key to complement hiring given talent demand-supply gap in India86%firms believe existing workforce will need to change skill set59%of c

113、ompanies actively reskilling their workforce see an impact from AI and advanced analytics effortsPerform strategic workforce planning,regularly reassessComplement hiring with upskillingDevelop flexible employee pool for people with Advanced analytics and AI skillsSources:BCGs The Future of Jobs in t

114、he Era of AI,2021;BCG-MIT Sloan Research report Winning with AI Pioneers Combine Strategy,Organizational Behavior,and Technology,Oct 2019;BCGs How to Win with Artificial Intelligence;BCG experienceSuccessful transformation is less about algo&tech,but about changing current practices&beliefsPeople&Pr

115、ocessesTechnologyAnalytics/Algorithms10%20%70%5657Building capability and managing change400 Bn EBITDA opportunity with Advanced analytics and AI in RetailScopingPrototypeValidateScale-upWe propose a balanced approach between use-cases&capability build to re-ignite your AI transformation journey123S

116、et the ambition&Build the roadmapCapability assessment Capability buildingValueIdentificationEnvisionActivateSustainAccelerate time to impactMake solutions sustainable for the long runStrategic assessment of business opportunitiesPrioritize from a value-lens approachAssess make or buy optionsMobiliz

117、e stakeholdersDecide Go vs No Go for use-casesAssess gaps in AI/Analytics,Data and Tech capabilitiesDefine target organization to support new solutionsStabilize operating model and ways of workingDefine talent management model upskilling/recruitmentBuild/Buy prototypeDefine incubation protocolTest a

118、nd iterate MVPReshape work processesTech at scale/Tech partners selectionTrain users59Learnings from Exemplars58400 Bn EBITDA opportunity with Advanced analytics and AI in RetailWill Indian retail capture the 400 Bn EBITDA opportunity with Advanced analytics and AI?61Building capability and managing

119、 change400 Bn EBITDA opportunity with Advanced analytics and AI in Retail60For Further ReadingBoston Consulting Group publishes reports on related topics that may be of interest to senior executives.Recent examples include:Digital is not just tech,its biz transformationAn article by Boston Consultin

120、g Group,December 2022Riding Indias Digital Super-cycleA report by Boston Consulting Group,November 2022Racing towards the next wave of Retail in IndiaA report by Boston Consulting Group,April 2022Digital Payments in India:A US$10 Trillion OpportunityA report by Boston Consulting Group,June 2022Ten T

121、hings You Should Know About E-Commerce in IndiaA report by Boston Consulting Group,June 2022Retail Resurgence in India:Leading in the New RealityA report by Boston Consulting Group,February 2021Retail 4.0:Winning the 20sA report by Boston Consulting Group,February 2020How India Spends,Shops and Save

122、s in the New RealityA report by Boston Consulting Group,December 2020Note to the ReaderAbout the AuthorsAcknowledgementsAbheek Singhi is a Managing Director and Senior Partner,in the Mumbai office of Boston Consulting Group and leads BCGs Consumer and Retail practice in Asia PacificNamit Puri is a M

123、anaging Director and Partner,in the New Delhi office of Boston Consulting Group and leads BCGs Consumer and Retail practice in IndiaThis study was undertaken by Boston Consulting Group(BCG)with support from the Retailers Association of India(RAI).We would like to thank Kumar Rajagopalan,Dr.Hitesh Bh

124、att,and Palak Taneja Sapra from the Retailers Association of India for their support and guidance while developing this report.We would like to thank Namrata Panwar,Rishav Mehta,Vishal Parwani and Shreya Nagpal for their assistance in writing this report.Bharat Mimani is a Managing Director and Part

125、ner,in the Mumbai office of Boston Consulting Group Rajat Mathur is a Partner,in the New Delhioffice of Boston Consulting Group Shivam Jain is a Principal,in the Mumbai office of Boston Consulting GroupWe are thankful to Jasmin Pithawala and Sucheta Desai for managing the marketing process as well a

126、s Jamshed Daruwalla,Saroj Singh,Sujatha Moraes,Subhradeep Basu,Isha Sheth,Nanakdeep Singh,Saanchi Chatwal,and Jahnvi Chauhan for their contribution to the editing,design and production of this report.Arpit Agarwal is a Project Leader,in the New Delhi office of Boston Consulting GroupFor Further Cont

127、actAbheek SinghiNamit PuriBharat MimaniRajat MathurShivam JainArpit AgarwalManaging Director&Senior PartnerBCG,Mumbai+91 2267497017Singhi.AManaging Director&PartnerBCG,New Delhi+91 1244597339Puri.NManaging Director&PartnerBCG,Mumbai+91 2267497466Mimani.BPartnerBCG,New Delhi+91 1244575684Mathur.RPrincipalBCG,Mumbai+91 2267497005Jain.SProject LeaderBCG,New Delhi+91 2267497077Agarwal.A