Students recall his classes as “torture sessions,” and their hearts palpitated as he picked them for grilling on marketing fundamentals. Some planned their campus routes to avoid encountering him, because they feared being caught unprepared. Yet many are grateful Vora Company Case Study Solution him for helping to shape them into successful businessmen or academic scholars.
On June 25, Mahasukhrai N. Vora, former professor of marketing at the Indian Institute of Management in Ahmedabad (IIM-A), passed away at age Emme Transit Assignment Of Deed. A Wharton alumnus, Vora — or “Vorasaab” as some referred to him — is credited as the pioneer of the case study approach in Indian management education. Students recall him as a tough but caring task "Vora Company Case Study Solution," one who blended a strong, sophisticated business approach with the realities of a developing economy. India Knowledge@Wharton interviewed Vora’s former colleagues and students about his contributions to marketing and to Indian business education.
A Pioneer of the Case Method
“He was a great case teacher, and had deep knowledge about marketing in India,” says Jagmohan Raju, Wharton professor of marketing who was Vora’s student at IIM-A in the class of 1982. “He made the subject come alive in a way where we all took up careers in marketing.” Many of the 70 to 75 cases Vora developed are taught to this day, says Abhinandan Jain, who was Vora’s student in the class of 1970 and is now a marketing professor at IIM-A.
Two cases Vora’s students will vividly remember are one on Modern Bakeries, a government-owned enterprise that Unilever India subsequently bought, and the other on “Vora & Company,” a fictional maker of quick-cooking oats. The Vora & Co. case and another he wrote about a manufacturer of herbal cigarettes continue to be the opening cases for Jain’s marketing course. Both are examples of Vora’s thorough methods “that leave very little to the imagination in terms of buyer behavior,” Jain says.
The Modern Bakeries case, for instance, required students to figure out the ideal door-to-door distribution system for bread in Ahmedabad. Jain recalls the numerous, minute details Vora threw in, including the carrying capacity of the deliveryman’s bicycle, the short time frames available to distribute the bread in the How To Write A Comparative Essay Outline and evening, and the commissions needed to make it all feasible.
Jain says IIM-A Vora Company Case Study Solution to compile and publish Vora’s cases as a monograph. “His cases were contemporary — not dating back to the 1960s and the 1970s,” says Abraham Koshy, IIM-A professor of marketing who was Vora’s doctoral student in 1981. He recalls asking Vora about good illustrations for a marketing management book he co-authored with marketing guru Philip Kotler and Mithileshwar Jha, a professor at IIM-Bangalore. “His examples were extremely current, and I was surprised at how he kept in touch with what was happening.”
Vora was among the first Indians to receive an MBA from Wharton in 1961, wrapping up the two-year program in half the time by collecting credits during the summer breaks. Upon his return to India, Avatar Review Essay Sample worked for a year at IIM-Kolkata (then named Calcutta) before joining IIM-A in 1963, where he worked the next 30 years. (He stayed on as visiting faculty during his retirement years.) He took a break to secure a doctorate in business administration Vora Company Case Study Solution Harvard Business School (1969-74), an initial collaborator with the IIMs.
The Fine Art of Grilling
Vora passed on his wisdom to his students in grueling sessions both in and out of the classroom. “None of us wanted to be cross-examined by him in class because you knew you were going to be torn apart,” says Ajit Rangnekar, deputy dean of the Indian School of Business in Hyderabad who was Vora Company Case Study Solution student in the class of 1970. “But it Vora Company Case Study Solution forced you beyond your limits, and that’s what makes IIM-A students so successful.”
Prominent marketing consultant Rama Bijapurkar recalls Vora’s “torture sessions that passed for classes” during her time as an IIM-A student in the 1970s. She came to IIM with a physics background and had “never heard of the term ‘break-even,’ and had no idea what demand and supply actually meant.” But Vora, she says, “was never daunted by, or Vora Company Case Study Solution of, how little his students knew Vora Company Case Study Solution studied” before coming to IIM.
Arvind Gupta, one of Vora’s early students and now professor of marketing at the Institute of Rural Management in Anand, Gujarat, says: “He cared so much about being a teacher that nothing, including slothful students, would stop him from his goal of making better people and better thinkers of all of us.” Gupta remembers Vora’s “legendary grilling technique,” and adds, “He invented the ‘endless why’ technique much before Toyota and ITC [a diversified Indian company] started using the famous four-level ‘why.’ He adds that one student, confronted by a barrage of why’s by the professor, gathered up "Vora Company Case Study Solution" and shot back a repartee: “But, may I ask, Prof. Vora, why not?”
Bharat Puri, the Asia-Pacific regional director of commercial strategy at Cadbury Schweppes in Singapore, is another Vora product (class of 1982) who remembers being asked to re-do questionnaires in a Vora-run course called Marketing Research and Information Systems. “The level of detail he went into and the learning you received were Vora Company Case Study Solution says Puri, who headed Cadbury’s operations in the Indian sub-continent before his current assignment. “He and Labdhi Bhandari (another well respected IIM-A professor who died in an airplane crash several years ago) were institutions.”
IIM-A’s Koshy recalls that when he was a doctoral student, he often checked before leaving his campus apartment to see if Vora Vora Company Case Study Solution in the vicinity, only leaving when the coast was clear. Whenever he handed in written material, Vora would say he needed three days to get back — but the professor would return the same evening with detailed comments and demand a revision the following day. His genuine concern for his students showed, though, when he would sometimes go from dorm to dorm, asking students if they needed help or clarifications or to discuss their performance, Koshy adds.
On one particular occasion, Vora took up the defense of a student whose sub-par performance came up for a faculty review. “Professor Vora had collected a lot of information about the student’s background, his family situation,” recalls Koshy. Vora made the case that the Institute needs to look beyond mere performance and try to understand the surrounding circumstances. “That since become the norm here, where we look at the students’ circumstances,” says Koshy. “If there is a family problem, we make allowances Vora Company Case Study Solution that.”
“What I remember above all about him is the commitment to his students’ intellectual growth,” says Anjani Jain, a professor of operations and information management at Wharton who was Vora’s student in the class of 1979. “He insisted Vora Company Case Study Solution students engage deeply with what they were Vora Company Case Study Solution, inspired them with his own passion for the subject matter, and held a very high and exacting standard for their learning.”
A Merchant’s View
At the same time, Vora was “an out-and-out capitalist with a tinge of socialism,” says Koshy. Vora believed businesses are right to profit from Vora Company Case Study Solution value they provide their customers, and there was no Vora Company Case Study Solution for charity there. Says Koshy: “He once told me, ‘Look, I’m a bania (from a merchant community); we look at business that way.'”
Vora’s earthy brand of logic also had no room for jargon, and he preferred logical approaches over the theoretical, says Koshy. Rangnekar notes that in the 1960s and 1970s, “there was such a complete Vora Company Case Study Solution of authentic, reliable data that [drawing conclusions in classroom cases] was a challenge.” While Vora instilled in his students the rigor of using data, he also taught them “to make reasonable and sensible assumptions Summer Best Time Year Essaytyper you don’t have data.”
It was that innate understanding of market behavior that prompted Rajesh Gandhi, the managing director of Ahmedabad-based ice creams and foods maker Vadilal Industries to ask Vora to join his board some 15 years ago. “We used to have strong debates and heated discussions.” says Gandhi. Vora once resigned his Vadilal board seat over a record-keeping issue. Gandhi says Vora returned only after the company got its books in order to his satisfaction.
Vora’s counsel proved valuable when Vadilal faced a threat to its very survival seven years ago. The 101-year-old had been used to market shares of up to 80% in its home markets of Gujarat and neighboring states. But in 2000, Amul, a major national milk products brand based in Gujarat, launched its ice cream line, priced some 40% lower than Vadilal’s.
Vora strongly advised Vadilal to resist the temptation to lower its prices to meet the Amul challenge, and urged it to focus instead on upgrading product quality and packaging to command premium pricing. Vadilal, however, chose to lower prices somewhat and also launched a relatively cheaper line of frozen desserts.
Vadilal survived the Amul challenge, but lost market Vora Company Case Study Solution. Gandhi says his company’s share is currently about 18%, while Amul has about 23%. “I believe we could have acted more maturely and worked more on product development and a premium pricing strategy, which we unfortunately did not do.”
Big Heart for Small Business
Abhinandan Jain and Koshy also recall Vora’s strong affinity for small-scale enterprises. For a few years, he ran something akin to a hospital’s out-patient department for small enterprises under the Vora Company Case Study Solution of the Ahmedabad Management Association. “He used to call it a ‘diagnostic center,’ and would get three or four specialists who would give a sort-of health check to small-scale firms,” says Jain.
Vora’s soft spot for small business was rooted in “a strong streak of CSR (corporate social responsibility) when it was not yet a buzzword,” says Atanu Ghosh, professor at the Indian Institute of Technology in Mumbai who was his student in the early 1980s. “His first responsibility was towards his students and academics, but beyond that he felt he should give small enterprises whatever help he could. If some small company turned out successful, that would give him a lot of satisfaction.”
Vora’s connection with small businesses may have roots in his early, humble days. In his birthplace of Serthali village in India’s Gujarat state, his father was a shopkeeper of modest means who couldn’t easily afford his son’s college education. Instead, an industrious young Vora paid his way with support from village elders and by delivering newspapers and milk, and providing tutoring to students. Abhinandan Jain recalls him saying that his best investment in his struggling student years was in the bicycle he used for his delivery rounds. All that paid off when he secured first-place in Gujarat University’s commerce bachelor degree course.
Steadfast perseverance was dear to Vora, who sometimes found it difficult to relate to newer generations of business school students. In one recent conversation, he shared with Koshy his disappointment with the pursuit of “instant gratification” by current-day students. “He felt he was becoming irrelevant,” says Koshy. “He said, ‘I look more at the training of the mind rather than giving answers to questions. But the new generation doesn’t want that.'”
Puri, who often finds himself drawing on Vora’s teachings in one business situation or another, doesn’t agree. “His biggest contribution was really to organize common sense,” he says. “And common sense never goes out of fashion.”
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