A CASE ANALYSIS
VORA AND COMPANY
EN. NO. 10BSP0920
Introduction to the Case:
This case is about Vora and Company, established in December 1963 by M.C. Vora, which manufactures Blossom quick cooking oats. The company was located in Lucknow. The company was suffering with lower sales and losses. This case discuss about various strategies adopted by the company, their strengths and weaknesses and in that way it also discuss about reasons for low sales.
Objective of the case:
The main objective of the case, in general, is to discuss various points which a firm should consider before entering into new market. In terms of Vora and company, the objective is to know whether Blossom should continue in the business or not and to give suggestions on various marketing techniques for increasing the sales of Blossom.
Issues in the case:
* Sales of the product were lower than expected even after taking measures to improve sales.
* The company had suffered considerable losses since the launching of his enterprise.
* Problems were aroused due to insufficient study of market and trends before launching the product
* There were some issues with packaging, distribution and advertising of the product.
In 1994, the government of India stopped the importation of packed cereals which resulted in exit of "Muller and Phipps", the sole seller of packed oats in India. A competitor named Ganesh Flour Milles was already present in the market under the trade mark "Champion".
* Blossom was rated as equal as or better than the competing product by the consumers.
* The company followed required quality standards and used the mark of Indian standards Institution.
* Proper listing of demand in order of quantitative importance by regions
* Product had high nutritive value.
* The packaging was not satisfactory- It was too flashy, bright and copy of competitor, phrase quick cooking oats was written in small.
* The distributors assigned to sell Blossoms were new to the sale of Food Products
Presentation on theme: "Big-Data IoT, VORA = Digital Enterprise"— Presentation transcript:
1 Big-Data IoT, VORA = Digital Enterprise
Hari GuleriaVP Big-Data & SAP HANARoadmap to Digital Monitization
2 Start and End With Business Benefits
The success of any new technology lies in the impact it has on the Company’s operations
3 Agenda The Digital Reality Today
ROIThe Digital Reality TodayBig-Data Explosion Digital DisruptionInverting the PyramidBusiness NeedsBusiness Case 1- O&GBusiness case 2- RetailThe ball is now in your court
4 - BIG-DATA- Digital Disruption
I d e a !- BIG-DATA- Digital DisruptionDigital Disruption Starts with an IdeaWhat Disruption!
5 Accelerating Data Creation
PaperHostSLI SystemsNetSuiteOpSourceJoyentHosting.comTata CommunicationsDatapipePPMAlterianHylandNetDocumentsNetReachOpenTextXeroxGoogleMicrosoftIntraLinksQvidianSageSugarCRMVolusionZohoAdobeAvidCorelSerifYahooCyberShiftSabaSoftscapeSonar6AribaYahoo!QuadremElemicaKinaxisCCCDCCSCMADP VirtualEdgeCornerstone onDemandKenexaWorkscapeExact OnlineFinancialForce.comIntacctPlex SystemsQuickbookseBayYouTubeViberQzoneAmazon Web ServicesGoGridRackspaceLimeLightJive Softwaresalesforce.comXactlyPaint.NETBusinessEducationEntertainmentGamesLifestyleMusicNavigationNewsPhoto & VideoProductivityReferenceSocial NetworkingSportTravelUtilitiesWorkbrainSuccessFactorsTaleoWorkdayFinancebox.netFacebookLinkedInTripItPinterestZyngaBaiduTwitterYammerAtlassianMobilieIronSmugMugAmazoniHandyPingMeAssociatedcontentFlickrSnapfishAnswers.comTumblr.UrbanScribd.PandoraMobileFrame.comMixiCYworldRenrenXingYandexHerokuRightScaleNew RelicAppFogBromiumSplunkCloudSigmacloudabilitykagglenebulaParseScaleXtremeSolidFireZillabytedotCloudBeyondCoreMozyFringTogglMailChimpHootsuiteFoursquarebuzzdDragon DictionSuperCamUPS MobileFed Ex MobileScanner ProDocuSignHP ePrintiScheduleKhan AcademyBrainPOPmyHomeworkCookie DoodleAh! Fasion GirlEvery 60 seconds148,000+ tweetsMRMClaim ProcessingPayrollSales tracking & MarketingCommissionsDatabaseERPCRMSCMHCMPLMHPEMCCost ManagementOrder EntryProduct ConfiguratorBills of MaterialEngineeringInventoryManufacturing ProjectsQuality ControlSAPCash ManagementAccounts ReceivableFixed AssetsCostingBillingTime and ExpenseActivity ManagementTrainingTime & AttendanceRosteringServiceData Warehousing1,245,000 status updatesIBMUnisysBurroughsHitachiNECBullFijitsu22 million instant messagesDIGITAL DISRUPTIONMobile, Social, IoT,Big Data & The CloudERP BUSINESSClient/ServerCONNECTIVITYThe InternetMainframe1,523,216 Google searches368 million+ s sent3,820TB of data created916 new mobile web users Every 7-10 years, technology delivery undergoes a tectonic shift; one that opens up new business and access models. A shift that changes the way technology is consumed and the value that it can bring. A change in what is possible. A removal of inhibitors that unleash the power of innovation.Today, mobility, social, big data, and the advent of cloud computing are representative of such shifts offering a new means for IT to help organizations accelerate progress towards solving their most pressing challenges (including speeding innovation, enhancing agility, improving financial management). These shifts can unleash the power of IT to not only support but help shape the business.Some of it about your products
6 The Digital Data Explosion
A poor fit for the traditional relational databaseAs-IsTo-Be200520182010More than 90% is unstructured dataApprox. 500 quadrillion filesQuantity doubles every 2 yearsMost unstructured data is neither stored nor analyzed!1.8 trillion gigabytes of data was created in 2011:10,000GB of Data(IN BILLIONS)STRUCTURED DATA – MIDSTREAM(Repetitive Data)UNSTRUCTURED DATA UPSTREAM AND DOWNSTREAM (Non-Repetitive Data)90% of the DIGITAL ‘Business Value Attainment’ lies10% / 90%99% of CURRENT Focus lies90% / 10%Source: Cloudera
7 Disruption just needs an idea
Digital connections are changing the definition of an enterpriseImage: The EconomistAttributeOldNewLeadershipInnovationWorld ClassHigher Quality + Lower CostData StoreOn-PremiseCloud’sOperationsAssetsSelf OwnedCrowd Sourced (Uber, airbnb)Customer SurveyAnnualInstant - Real-RimeDecisionsPeriodicReal-TimeTrade-PromotionReal-Time (Gaming)Welcome to the world of ‘IoQ’
8 Customer Centric Decisions Operational Management
Inverting the Pyramid..Legacy OrganizationsOn-Premise ITManager is always rightQuarterly/Annual review of customers100% Focus inside the MidstreamLow connectivity to UpstreamLow connectivity to DownstreamVery Little Predictive AnalysisField Information Flows Down-to-UpMost decision flow Top-to-DownDIGITAL PyramidCustomer Centric DecisionsOperationalUser FeedbackPower Users & CONNECTED Consumers = Customer LoyaltyOperational Management‘C’ levelExecutivesLeadersNeedAuditCustomerExpectationsFlow downReal-Timedeployed toExceedIMPROVEExecutives becomeConductors to theSymphony ofCustomer SatisfactionCustomer Inclusive DIGITAL ConnectivityIdentifying, Prioritizing & Meeting ExpectationsReal-time Customer Satisfaction AdminConnectLeadersInstructionsFlow downLevel-by-LevelOperational RealitySummarized upLevel-by-Level‘C’ LevelExecutivesDisconnectedPeriodicOperational ManagementOperational AssetsOperational Supply ChainsOperational Stocks and ServicesSales persons driven QuotasDisconnectedOperationalUsersCustomer Exclusive MethodologyThe Digital disruption is inverting traditional ‘Command & Control’ organizations existing in ‘Brick & Mortar’ enterprises with a tear tht is totally services and customer focused. In this new world ‘customers’ are the new CIO’sLEGACY Decision PyramidEnterprise Centric Decisions
9 Data-Explosion + Real-time ‘Value-Chain’ Decisions
I d e a !What is THIS CReatingData-Explosion + Real-time ‘Value-Chain’ DecisionsEmerging Pressure of..
10 IoT- The Connected Enterprise
MidstreamThis is our enterpriseOur PlantsOur SystemsOur EmployeesBehind our FirewallOur most familiar placeUpstreamOur Vendors & SuppliersOur Manufacturing UnitsDownstreamOur RetailOur customersOur Buyers
11 The Connected Enterprise = The Digital Enterprise
Disrupt or Be DisruptedThe digital economy is disrupting everything.In every industry, data is being created in places it never has before.Creating hyper-distributed data environments.It is becoming ever increasingly hard to reach that data, secure that data, and much less draw an insight and enable a person or process to take action on the data.But data is not the problem, connected data is the problem.If every single employee is a decision-maker, organizations must focus on enhancing the quality of each decision taken.The ability to secure, aggregate, automate, and draw insights from an organization’s own data – with speed – will define value for that organization.When you connect People, Process, Data and Things, new opportunities emerge:New market opportunitiesNew business modelsNew way to operateNew ways to consume technologyTechnology becomes an enabler
12 The Digital Enterprise Evolution
MIDSTREAMVENDORSSUPPLIERSCOMPANYPLANTSInboundLOGISTICSDRIVERSEMPLOYEESVEHICLESSENSORSDOWNSTREAMCUSTOMERSRETAILWHOLESALECONTRACTMFGSOutboundLOGISTICSSENSORSUPSTREAMCORPHQVP SalesVP ServiceCIOPlannersVP BUVP Supply ChainCustomer Service45,000+CONNECTEDPARTNERS~100FACTORIES4,000+DEALERS100M+VEHICLES AND DRIVERS ON THE ROAD500+APPLICATIONS450,000+ CONNECTEDUSERSWhat do we mean by hyper distributed operations? Let’s take an automobile manufacturers…they may have hundreds of factories, thousands of dealers, tens of thousands of partners, and millions of vehicles on the road…it doesn’t get much more distributed then this…and they want and need to share systems and data across all of these participants in their value chain…
13 Data Processing Must Evolve Too
CENTRALIZEDDECENTRALIZEDFEDERATEDHEADQUARTERSPARTNERSVEHICLESDRIVERSFACTORIESDEALERSFIELD SALESEnterprise ApplicationsDealer AccessMachine AppsCustomer Mobile AppsMobile Workforce ApplicationsOn-board ComputerSupplier ExchangesThis evolution of the network requiring a new approach to computing…Starting with the need to support computing at the edge. Today’s environment requires that you support application development and hosting across fog, cloud and mobile.It requires enabling an Application-centric Infrastructure with application-based policies that decouple application requirements from network configurations to reduce the impact of application changes on performance, security, availability and scaleEnabling Streaming Analytics and Aggregation…streaming analytics across data-in-motion and data-at-rest and rapid logical aggregation of dataIt requires Secure Interaction – the growing ecosystem of partners requires pervasive security policies that support the new B2B and B2C interactions.And last but not least, it requires application integration across hybrid computing environmentsCisco is uniquely positioned to help our clients address these new requirements with:• an intelligent network and IoX that supports network distributed workload and edge computing• new streaming analytics and data virtualization capabilities with our Connected Analytics software• and best in class application integration with our Cisco Integration Platform that allows you to connect disparate applications across hybrid environments.To further support these evolving requirements, we are announcing a number of new software capabilities that serve as the foundation for digital business.across hybrid computing environments
14 Digital Enterprises Will Process Data at the Edge
Widely Distributed, Streaming, Short Shelf Life, Too Big to Move“By 2020 Most Decision-Datawill be processed at the edge”(mobile devices, appliances, routers)86%HYPER FEDERATED(Inter-Cloud)Three years from now, where will most data generated by IoT solutions be processed?
15 What is Changing?New data processing must take the processing to the data and send subsets for Decisions & AnalyticsTraditional data processing moved the data for Decisions & AnalyticsFog NodeEdge NodeIoT DeviceReal-TimeDecisionProcessingHind-SightDecision ProcessingDataAll Select DataOnly Filtered Data
16 A real world example: Sensor data from a Boeing jet flying from New York to SFO
2,600+ sensors per engine30 TB30 TB of Data per engine every hour2twin-engine Boeing 73760TB / Hour5five-hour, flight from New York to San Francisco300 TB / flight28,537# of commercial flights in the sky in the United States on any given day.days in a year36530 GB8.5 TB312.4 TB300 TB /flight8,561,100 TB/day3,124,801,500 TB/yearPredictive Patterns: 99.9% of this data simply states ‘I am OK’
17 Real-Time Decisions & Predictive Analytics
Business NOW!IotInternet of Things & EverythingReal-Time Decisions & Predictive Analytics
18 IoT vs. IoE From Internet of Things to Internet of Everything
EnterpriseUnit 1Unit 2Unit ‘Z’Unit ‘N’Step 1: IoTHub & SpokeStep ‘N’: IoEIntra-ConnectedUnit 1EnterpriseUnit 2Unit ‘Z’Unit ‘N’*Unit= Sensor, Car, component, Person, Patient, ProductMeter, Gauge, Engine, Bearing in an engine= any thing that that can be digitizedCONNECTED TO A HUB*Unit= Sensor, Car, component, Person, Patient, ProductMeter, Gauge, Engine, Bearing in an engine= any thing that that can be digitizedHYPER-CONNECTED
19 Business Needs by Priority – Digital Enterprise
REAL-TIME Decision Feedback LoopWhat is happening in the field Right-NowAutomated Reality Checks and Alerts systemsPredictive AnalyticsLink History to Predict the FuturePrescriptive SolutionsHow do I fix that I can now PredictHighest Quality & Lowest Cost SolutionsDo it Right the First Time, Every Time
20 Deconstructing Predictive Analytics
Those who do not learn History, tend to make the same mistakes againPresentHistorical ConePASTUnlikelyFUTURELikelyAlgorithmsPatternsDataTimePredictableExperiencePatternsData&PatternsAlgorithmsOBSERVERLikelyProbabilityFuture ConeUnlikely
21 Preventive Maintenance & Monitor Condition
Cost to RepairIIoT - Predictive Maintenance and Service Visuals: The P-F Interval CurvePreventive Maintenance & Monitor ConditionRepair or ReplaceEquipment Unusable“Can”Effect of PdMSPotential FailurePEarly Signal 1 – Ultrasonic Energy DetectedMachine Capability / Resistance to FailureEarly Signal 2 – Vibration Analysis FaultEarly Signal 3 - Oil Contamination DetectedAudible NoiseHot to TouchMechanically LooseFFunctional Failure“Want”Total FailureAncillary DamageTime
22 Real-Time Decision Enablement
VORA Business CASE 1O&GReal-Time Decision Enablement
23 What is SAP VORA Real-Time Streaming Data Integrator Between For
Streaming Unstructured Data (Non-Repetitive Data)Streaming Semi-Structured Data (Semi Repetitive Data)Enterprise Structured Data (Predictable+ Repetitive Data)ForReal-TimeAlertsPredictive & Prescriptive AnalyticsOperational Analytics
24 Operational Facts 4 Unplanned Downtime
‘Unplanned Downtime’ Cost per unit InstanceOn-Shore Drilling$3,000-5,000 per hour = $72k to 120k per dayOff-Shore Drilling Rigs$500,000 to $2 million per day or $15,000/hrAverage Unplanned downtime is 1-5 daysDepending on the severity of the damage
25 Asset failure for Predictable Maintenance
Acquisition Start timeAcquisition end timeTool Status ( Temp)Scintillator detector ParametersDataInputsDepthAngle of PenetrationInternal temperatureExternal TemperatureRPMInternal PressureExternal PressureTorqueVideo + Audio
26 Solution Architecture
On Cloud1Scintillator DetectorTemperaturePressureHDFSSAP HANA VORASCALA ProgrammingSPARK SQLSPARK2On- PremiseSAP EAMSAP ERPSAP FISAP HANA Information ModelVORA Virtual TablesVORA Remote Data SourceSAP HANA3Assets Master dataECC operational DataOLAP – SAP LumeraOLAP AnalyticsPredictive AnalyticsPredictive engineAlgorithms4Self-Help AnalyticsHANASPARKAdapter
27 Data Flow Real-time Streaming Data Cloud HANA Modeler HDFS Alerts
For ‘Zero-Unplanned Downtime’ Predictive AnalyticsReal-timeStreaming DataAlertsCloudSPARKVORASAP ECCHDFSHANA ModelerSPARKVORAPredictionsSPARKVORASAP EAMAnalytics
28 Business Benefits Unplanned Downtime reduced by 62%
9 Month Cost savings of $7.6 millionZero Downtime increased from 72% to 93%OSHA 300A scores improved by 13%
29 Real-Time Decision Enablement
VORA Business CASE 2RetailReal-Time Decision Enablement
30 Operational Facts Per Store Indirect Costs Sales Target vs. Actuals
From total 760 stores - ’12 Stores data’ Cost per unit storePer Store Indirect Costs$3,000-$4,000 per daySales Target vs. Actuals$17,000 good day ; $ 5,000 bad dayStore Manager concernsDelighting a customerFinding what customer needsKeeping store employees motivated- Decreasing Employee ChurnTraining / on-boarding costs are around $3,000 to $10,000Store employee concernsNormally a temp job- waiting for a better opportunityUnable to predict earnings from commissionsAverage employee employment is 4-6 months
31 Analytics for Customer Experience
Store ID, + Geo LocLocation Heat Map, Traffic, Locality, etcCustomerLoyalty CardStore Opening timeStore Closing TimeDataInputsLocation&Movement AnalyticsStore ManagerStore Employees + InvoiceEmployee Attendance In/OutStore RacksStore StocksStore Sales, Order Line ItemsPermission based servicesStore POS DataWeatherTemperature
32 Data Flow Real-Time Customer Real-time Feedback Alerts Cloud
For ‘Store Employee Real time’ Retention Analytics – Grew Customer satisfaction by 16% in 3 monthsReal-Time CustomerFeedbackReal-timeAlertsCloudSPARKVORASAP ECCHDFSHANA ModelerSPARKVORAPredictionsSPARKVORAAnalyticsReal-Time POSStreaming DataPOSSAP ECCSAP EAM
33 Business Benefits Employee Retention increased by 43%
Per store sales increased by 17%Customer satisfaction went up by 13%Overall Per Store Sales went up by 21%
34 The ball is now in your Court
Option 1Option 2Stay as you are!Hope for the BestDisrupt – Don’t get DisruptedBecome the competitive DisrupterUndertake a Design thinking workshop (80% Buss/20% IT)Follow the Digital Enterprise Structured FrameworkBuild the Digital Enterprise for the FutureAsk us for ourD-BAS (Digital- Business Assurance Services)B-QAS (ERP selection- Business Quality Assurance Services)
35 Thank YouThe Base for Business Success is a strong foundation of Technology
36 Gartner’s Digital Marketing Hub
37 Actionable Roadmap to Digital Delivery
Proven and RepetitiveScientific approach to digital successStructured Stepping Stones