The digital transformation of CPG and manufacturing
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Both CPG (Consumer Packaged Goods) and manufacturing industries face similar challenges: in order to differentiate and innovate, they need to draw insight from the one thing they both have in abundance - data. The source of the data may be different; the opportunity is always innovation and differentiation. For CPG, forever changing buyer expectations must flow into product development and sales. For both CPG and manufacturing, Industry 4.0 promises improved efficiency, lower costs, and higher revenues. Becoming data-driven is the key for both industries and requires clever combination of machine learning, analytics and cloud for success. In this webinar, business strategist Frank Vullers will discuss how Cloudera's platform is central to this century’s industrial revolution: the digital transformation of the CPG and manufacturing industries.
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The digital transformation of CPG and manufacturing
- 1. 1© Cloudera, Inc. All rights reserved. The digital transformation of manufacturing / consumer packaged goods (CPG) industry Frank Vullers Business Strategist
- 2. 2© Cloudera, Inc. All rights reserved. Agenda • Manufacturing / CPG industries • Trends • Industry 4.0 • The digital consumer / changing customer demand & behaviour • How can data / Cloudera help ? • Customer examples
- 3. 3© Cloudera, Inc. All rights reserved. Value chain manufacturing/ CPG Marketing / consumer management Product development Procurement Production & operations Sales & distribution ManufacturingCPG Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 4. 4© Cloudera, Inc. All rights reserved. Industry 4.0* * Aberdeen group http://www.aberdeenessentials.com/opspro-essentials/industry-4-0-industrial-iot-manufacturing-sneak-peek/ Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 5. 5© Cloudera, Inc. All rights reserved. Trends in manufacturing* * Aberdeen Group , December 2016 http://v1.aberdeen.com/launch/report/research_report/15203-RR-digitalization-manufacturing.asp Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Top pressure on operations Top challenges
- 6. 6© Cloudera, Inc. All rights reserved. Digital innovation in manufacturing • Connected factories for condition based asset monitoring and predictive maintenance • Connected value networks for supply and consumption • Improved product quality with sensor derived data and contextual data • Connected products enabling new business models, better customer experience, and better product design Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 7. 7© Cloudera, Inc. All rights reserved. Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Benefits of Industry 4.0 10-40% reduction of Maintenance costs Productivity increase by 3 -5 % 30 -50 % reduction of total machine downtime 45-55 % increase of productivity Costs for inventory holding down by 20-50 % 3 Costs for quality reduced by 10-20 %6 Forecast accuracy increased to 85+ % 20-50 % reduction in time to market1
- 8. 8© Cloudera, Inc. All rights reserved. A revolution in shopping behavior 1950- 2000 2018 Customer can shop and interact with the retailer / brand anytime, anywhere, and expects seamless experience Retailer controls the shelves Brands control the message Consumer is in control Teradata User Group Moscow Nov 20, 2014Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 9. 9© Cloudera, Inc. All rights reserved. Consumer experience will evolve further* Path to purchase: web of interactions Planned shopping at regular times (weekly stock up) Research by specific channels Basket assembled by adding products at the shelf Shopper decides what to buy and when * BCG Analysis https://www.bcgperspectives.com/content/articles/digital_economy_consumer_products_digital_future_game_plan_consumer_packaged_goods/?chapter=2#chapter2 An even more complex web of interactions Shopping blended into everyday routine anytime, anywhere Subtle influence through customer engagement Stream of purchases in real time, basket ceases to exist Shopping service provides recommendations and makes decisions for consumers Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Today Potential future disruption
- 10. 10© Cloudera, Inc. All rights reserved. Digital maturity* Digital presence Consumer interaction Insight generation Integrated operations Leading edge Basic Innovative • Digital advertising • Social media • Interactions • Communities • Digital listening • Analyzing consumer data • Limited e- commerce • Digital touchpoints • Significant e- commerce • Offering tailored to digital • New partnerships *BCG analysis https://www.bcgperspectives.com/content/articles/digital_economy_consumer_products_digital_future_game_plan_consumer_packaged_goods/?chapter=4 What is your starting position by country or region? • Maturity of the digital offering • Benchmark to industry How far do you want to go and how fast? • Be a leader or a follower • Endgame How much are you willing to invest? • Support companies ambition • Endgame Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 11. 11© Cloudera, Inc. All rights reserved. Devices & Sensors • Device Readings • Device Performance • Device Diagnostics • Battery / Power Consumption • Software Logs • Environmental Interactions • R&D • Quality / Testing Plant & Operations • MES • Sensors • Video / Surveillance • Line Productivity • Machines • Staffing / Scheduling • Quality data Supply Chain & Inventory • ERP • Supplier / Manufacturer • Orders / Receivables • Commodity Supplies / Prices • Chargebacks • Scorecards • Delivery Metrics Marketing & CRM • Transactions • Accounts • Warranties / Aftermarket • Customer Service Logs • Campaigns / Promotions • Website / SEO • Affiliates / Merchants • Surveys • Competitive Intelligence Public & Trade • Market Intelligence • Policy / Regulation • Demographic / Census • Psychographic • Inflation / Macroeconomic • Gas Prices • Labor Statistics • Social / Search • Public Health Data • Clinical Studies • Store Schematics • Journals / Editorial • Seismic / Speculation Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Where is the data? Mapping and consolidation are the tip of the iceberg for Big Data
- 12. 12© Cloudera, Inc. All rights reserved. Managing data from connected products / data sources
- 13. 13© Cloudera, Inc. All rights reserved. Handle real-time data ingest from diverse sources Fundamentally secure Data Streams Machine learning capabilities Diverse analytical options Combine Data from Different Sources Cloudera Enterprise Scale easily & cost effectively Batch or Real- time Data Streams Data Sources Connected Machines/ Data Sources Security, Governance & Easy Management Data Ingest Process, Refine & Prep Data Discovery Advanced Analytics Deployment Flexibility Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples A comprehensive data management platform to drive business insights from data Managing data from connected products / data sources EXTENSIBLE SERVICES CORE SERVICES DATA ENGINEERING OPERATIONAL DATABASE ANALYTIC DATABASE DATA CATALOG INGEST & REPLICATION SECURITY GOVERNANCE WORKLOAD MANAGEMENT DATA SCIENCE
- 14. 14© Cloudera, Inc. All rights reserved. EXTENSIBLE SERVICES CORE SERVICES DATA ENGINEERING OPERATIONAL DATABASE ANALYTIC DATABASE DATA CATALOG INGEST & REPLICATION SECURITY GOVERNANCE WORKLOAD MANAGEMENT DATA SCIENCE Cloudera Enterprise The modern platform for machine learning and analytics optimized for the cloud S3 | ADLS | HDFS | KUDU SHARED STORAGE Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 15. 15© Cloudera, Inc. All rights reserved. Enabling unprecedented business agility 1: Hybrid (Hot on HANA, rest on Cloudera) 2: Central datalake • HANA Offload • NLS BW Data • Active Archive • Customer Insight • IoT • Advanced Machine Learning • Reducing (storage) Costs • Data longer available • Extending Customer Insight • Connect products & services • Power & speed Open source ML Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Data Sources Analytic Database Operational Database Data Science & Engineering Business AnalystData scientist SAP HANA EXTENSIBLE SERVICES CORE SERVICES DATA ENGINEERING OPERATIONAL DATABASE ANALYTIC DATABASE DATACATALOG INGEST& REPLICATION SECURITY GOVERNANCE WORKLOAD MANAGEMENT DATA SCIENCE SHAREDDATA EXPERIENCE Cloudera Enterprise Augmenting SAP EXTENSIBLE SERVICES CORE SERVICES DATA ENGINEERING OPERATIONAL DATABASE ANALYTIC DATABASE DATA CATALOG INGEST & REPLICATION SECURITY GOVERNANCE WORKLOAD MANAGEMENT DATA SCIENCE
- 16. 16© Cloudera, Inc. All rights reserved. Data is Transforming Business DRIVE CUSTOMER INSIGHTS CONNECT PRODUCT & SERVICES LOWER BUSINESS RISKS MODERNIZE ARCHITECTURE Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 17. 17© Cloudera, Inc. All rights reserved. Use Case Library Manufacturing/CPG Drive customer insights Connect products & services (IoT) Protect business Customer Satisfaction Customer Segmentation Product Development Recipe Development R/T Asset Monitoring HCM Sales Forecasting Cross Selling Quote Optimization Support Optimization Invoicing & Settlement Churn Management Demand Planning SC Optimization SC Planning Inventory Optimization Modernize Architecture Storage Costs Scalable Architecture EDW Optimization Active Archive Real-Time Data Ingestion Real-Time Analytics 360 Degree View Product / Service Improvement Commercial Risks Social Engagement Warrantee & Claims Waste Reduction R/T Reporting & Viz A/R Risk Sales & Marketing Social Monitoring Log Analytics Competitive Intelligence Product Risk Vendor Risk (T1/2/3) Commodities Risk SC Compliance Logistics Compliance Production Predictive Maintenance Production Planning Proactive Quality Production Forecasting Energy Optimization Operations Optimization Risk / Fraud Cyber Security Fraud Prevention Logistics Storage Architecture ETL ETL Offload & Optimization R/T Offers / NBO / NBA Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Digital Marketing
- 18. 18© Cloudera, Inc. All rights reserved. Drive customer insights Connect products & services (IoT) Protect business Customer Satisfaction Customer Segmentation Product Development Recipe Development R/T Asset Monitoring Sales Forecasting Support Optimization SC Optimization Inventory Optimization Modernize Architecture EDW Optimization Active Archive Real-Time Data Ingestion Real-Time Analytics 360 Degree View Product / Service Improvement Commercial Risks Warrantee & Claims Waste Reduction A/R Risk Sales & Marketing Product Risk Vendor Risk (T1/2/3)Production Predictive Maintenance Proactive Quality Risk / Fraud Fraud Prevention Logistics Storage Architecture ETL ETL Offload & Optimization Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Digital Marketing Modernize architecture
- 19. 19© Cloudera, Inc. All rights reserved. The case for big data: Why we started the big data journey Business Challenges / Opportunities • Business access to more granular data • Challenges delivering better insight – “why is this happening”. • Quickly acquire and integrate multiple / unstructured data sources • Integrate a variety of NEW data types. • Growing data volumes = growing storage costs. • Time to insight challenged Original Big Data Use Cases • Category Management / Proof of Platform • Initiative Launch: Sense and Respond for live new product launches • Customer Facing Operations – high value questions • Other Hard questions - “Why is THIS happening” • Ability to quickly load and integrate structured, unstructured, and semi-structured data Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer ExamplesGlobal CPG company
- 20. 20© Cloudera, Inc. All rights reserved. Big Data complements enterprise data warehouse (EDW) Global CPG company Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Big Data Analytics Enterprise Data Warehouse (EDW) Highly variable and volatile, unpredictable Predictable reporting needs Accuracy not as critical, insights Highly accurate, data standards critical New, complementary option Legacy Structured and Unstructured data Structured data Power analysts, data scientists Mass users, analysts New, open source tools Well-established tools
- 21. 21© Cloudera, Inc. All rights reserved. Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Big Data Analytics Enterprise Data Warehouse (EDW) Highly variable and volatile, unpredictable Predictable reporting needs Accuracy not as critical, insights Highly accurate, data standards critical New, complementary option Legacy Structured and Unstructured data Structured data Power analysts, data scientists Mass users, analysts New, open source tools Well-established tools Big Data Traditional BI (EDW) Category Analytics WHY Analysis WHAT AnalysisHOW Analysis Customer Sufficiency Wall Street Reporting Shipment Reporting Official Share Reporting Digital Marketing optimization Data Exploration Business Pulse MGRC / Top 40 Influencer marketing Fraud detection IDF This line may shift over time Historical archiving Global CPG company Big Data complements enterprise datawarehouse (EDW)
- 22. 22© Cloudera, Inc. All rights reserved. • Complex calculations customer behaviour takes too long • Business not launching new products on time. • The nutritional calculation from 6 days to minutes • Platform scalable for 25 identified use cases • Budget is a strong criteria in first scope CPG » CUSTOMER BEHAVIOUR PRODUCT INTRODUCTION Faster insight in customer behavior Challenge Solution Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer ExamplesEuropean CPG company
- 23. 23© Cloudera, Inc. All rights reserved. Improving customer experience using ERP data, digital interaction, CRM, factory machine, and external causal data. • Predictive modeling create product recommendations and reduce customer churn • Extraordinary Customer Experience (ECE) drives improvements in safety, productivity, and financial performance • Created environment for advanced analytics and integrating data from manufacturing facilities. TRANSPORTATION » CUSTOMER 360 » IMPROVED SERVICE » DATA DRIVEN PRODUCTS Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 24. 24© Cloudera, Inc. All rights reserved. Automating data-driven R&D decisions • Provides single view of all R&D data, with photos from each growing stage indexed • Optimizes production process, reducing time-to-market from years to months • Improves collaboration among researchers CUSTOMER 360 AGRIBUSINESS » PROCESS IMPROVEMENT » PRODUCT INNOVATION » SCALABLE PROCESSING Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 25. 25© Cloudera, Inc. All rights reserved. Predictive Maintenance on Thousands of industrial machinery in real-time Challenge: • Collect and analyze data from thousands of diverse manufacturing systems in real-time Solution: • iTrak application using Cloudera on public cloud to monitor the performance of individual manufacturing systems in real-time • Predictive Maintenance - proactively identifying & fixing issues before they break MANUFACTURING » INDUSTRIAL IoT » PREDICTIVE MAINTENANCE » IMPROVED EFFICIENCIES DATA-DRIVEN PROCESS Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Connected Factories
- 26. 26© Cloudera, Inc. All rights reserved. Performance Monitoring & Predictive Maintenance of heavy equipment Challenge: • Continuously monitor performance of heavy machinery and perform predictive maintenance Solution: • Use Cloudera to parse large volume and high velocity sensor data from equipment • Process and analyze data for performance analysis, advanced defect detection HEAVY MACHINERY » INDUSTRIAL IoT » PREDICTIVE MAINTENANCE » LOWERED COSTS Change Image Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Industrial IoT – heavy machinery
- 27. 27© Cloudera, Inc. All rights reserved. Ensuring zero down time & lowered energy costs on industrial-grade robots Challenge: • Gather, store and analyze sensor data from 10,000 robots in order to minimize downtime Solution: • Cloudera platform used to gather and analyze sensor data coming from robots in real-time • Diagnostic solution predicts potential failures and alerts the operators in advance ZERO DOWN TIME » INDUSTRIAL IoT » LOWERED DOWNTIME » LOWERED COSTS Zero down time – industrial robotics DATA-DRIVEN PROCESS Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 28. 28© Cloudera, Inc. All rights reserved. Predictive Maintenance on industrial- grade turbines for hydro power stations Challenge: • Gather, store and analyze noise levels from turbines for anomaly detection Solution: • Cloudera platform used to gather and analyze acoustic data/audio files coming from the turbines in real-time • Using diagnostic solution to monitor the health of turbines and predict failures in advance PREDICTIVE MAINTENANCE » INDUSTRIAL IoT » LOWERED DOWNTIME » LOWERED COSTS Predictive Maintenance - turbines DATA-DRIVEN PROCESS Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 29. 29© Cloudera, Inc. All rights reserved. Maximizing production quality with machine learning and analytics • Reducing drive errors, predicting failures, and ensuring superior reliability, quality, and performance of its products • Ensuring real-time data encryption, fine-grained authorization policies, and role-based access controls to protect SanDisk’s intellectual property. • Leading, driving, and enabling net new capabilities TECHNOLOGY/MANUFACTURING » MACHINE LEARNING » OPERATIONAL ANALYTICS » PRODUCT INNOVATION Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 30. 30© Cloudera, Inc. All rights reserved. Siemens Omneo drives $15-25M in annual savings by identifying and addressing supply chain issues in near real time. Challenge: • No single view of the supply chain - Manufacturing millions of devices globally with 100s of components Solution: • Enterprise data hub empowering 360- degree view of product quality and performance across the supply chain • Savings: $25M/ year MANUFACTURING » SUPPLY CHAIN OPTIMIZATION » IMPROVED PRODUCTIVITY » COST REDUCTION Supply chain optimization DATA-DRIVEN PROCESS Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 31. 31© Cloudera, Inc. All rights reserved. • A leading CPG company uses overlapping forecasts and algorithms to identify critical demand signal exceptions, • The combination of trade and market data with execution data improves channel performance for meeting customer and consumer service levels. • Used both for retail execution and supply chain optimization. MANUFACTURING/ CPG » SUPPLY CHAIN OPTIMIZATION » LESS OUT-OF-STOCK (OOS) » IMPROVED PRODUCTIVITY » COST REDUCTION Channel in-stock & promotion execution DATA-DRIVEN PROCESS Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 32. 32© Cloudera, Inc. All rights reserved. Measure user interaction across the ecosystem, help direct R&D and development spend • Virtuous cycle: Identify features that facilitate sharing of content that drive new customers • Analyze utilization of new community attributes that drive adoption • Real-time streaming and batch data from product logs, web analytics, channel data and ERP MANUFACTURING » CUSTOMER 360 » DATA DRIVEN PRODUCTS » DATA DRIVEN SERVICES Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 33. 33© Cloudera, Inc. All rights reserved. HiPer (High Performance Computing Platform) processes over 200,000 files and 12.5 million unstructured documents monthly • Significantly enhancing productivity with 9-10x improvement in delivery speed • Procure-to-pay audit services across order, invoice, shipment, and sales using machine learning and search frameworks • Ability to re-run and experiment on large volumes of data • 25% decrease in storage costs RETAIL / CPG Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 34. 34© Cloudera, Inc. All rights reserved. Using Predictive Maintenance to improve performance and reduce fleet downtime • Real-time visibility of 300,000+ trucks in order to improve uptime and vehicle performance • OnCommand Connection is collecting telematics and geolocation data across the fleet • Reduced maintenance costs to $.03 per mile from $.12-$.15 per mile • Centralizing data from 13 systems with varying frequency and semantic definitions TRANSPORTATION » PREDICTIVE MAINTENANCE » IMPROVED SERVICE » DATA DRIVEN PRODUCTS IOT & Connected Products Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples
- 35. 35© Cloudera, Inc. All rights reserved. Visibility across multiple ERPs Consumer manufacturer has 10 manufacturing sites in EMEA and 5 ERP systems from a variety of vendors, including SAP, creating a fragmented and inconsistent view of the Supply Chain. With a consolidated view… • Sourcing monitors procurement across 10 manufacturing sites daily covering 800+ suppliers & 12K+ item codes • Finance analyzes quarterly purchase price variance across all sites • Plan users optimize inventory worth ~$400M daily across 20K+ finished materials Solution plugged $2M of value leakage in very first quarter of operation Manufacturing/ CPG Industry 4.0 Digital Consumer Cloudera Solution Customer Examples Modernize architecture
- 36. 36© Cloudera, Inc. All rights reserved. Thank you Frank Vullers Business Strategist fvullers@cloudera.com @FrankVullers
Hinweis der Redaktion
- We’ve entered a new era for manufacturing, dubbed Industry 4.0, and characterized by widespread digitalization. Prior to this fourth major transformation in modern manufacturing, there was the lean revolution of the 1970s, the outsourcing trend of the 1990s, and the automation boom that began in the 2000s. Even at this early stage, manufacturer commitment to digital transformation is strong. Preliminary findings from Aberdeen Group’s analysis found that 35% of manufacturers plan to achieve digital transformation (industrial IoT, Industry 4.0, smart manufacturing). A key part of digital transformation is the Internet of Things, which is positioned to revolutionize the entire manufacturing value chain by providing an unprecedented level of connectedness and functionality. For consumers, this change comes in the form of small, highly connected devices (smartphones, tablets, GPS devices) and sophisticated electronics embedded into our transport means, living spaces, and workplaces. For manufacturing firms, this change empowers them with new ways to develop, innovate, and manufacture due to the endless connections that can take place. Indeed, Industrial IoT (IIoT) is the subset of IoT that concerns itself with connected manufacturing operations to develop products and services.
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- As more users find more ways to employ advancing technologies, new disruptions on the purchasing pathway are not only possible but likely. (See Exhibit 4.) The technology already exists, for example, that would enable consumers to do away with the regular (say, weekly) shopping basket in favor of a continuous stream of purchases transacted in real time. Amazon Dash, for example, a combination digital recorder and barcode scanner, connects to a home Wi-Fi network and works directly with the customer’s AmazonFresh account. The user speaks or scans items into the device, then uses his or her PC or mobile device to make the purchase and schedule delivery. Amazon has embedded quick-shopping capabilities in its Fire smartphone as well. In time, the active participation of the individual consumer may no longer be necessary. Marketplaces or delivery services, such as Google Shopping Express, could receive information from “smart” storage devices or refrigerators that provide recommendations and make decisions, replacing the shopper’s own decisions about what to buy and when. The one thing that’s certain is that the consumer experience will continue to evolve as more users find more ways to use advancing technologies to improve their daily lives.
- A clear and integrated strategy requires a comprehensive assessment of the role of digital and e-commerce for the company. This means determining how large a digital presence to build for each brand based on the circumstances of its category and market. The strategy must be driven from the top of the organization and requires an objective assessment of the starting point. It should define a sustainable position for each brand or product (profitable margins, steady share) and the capabilities required to get there. An integrated strategy lays out a company’s digital ambition and level of investment commitment. The key question is how far does a company want to try to go—and how fast. Is it a player in the new game, a fast follower, or does it have aspirations to be a leader? What does it see as its own digital endgame—a competitive capability or a unique, fully integrated omnichannel offering? Part of the answer may lie in the amount the company is willing (or able) to invest to support its ambition and desired pace of growth. Investments need to be calculated by category, brand, and market. The strategy will determine how far and how fast the company moves through the phases of digital maturity. (See Exhibit 10.) The importance of strategy, commitment from the top, and building the right capabilities can be seen in the example of a leading international fashion company. Almost a decade ago, the company was in a bind: its brand was outdated and it was losing relevancy with consumers. The company determined that its most attractive future rested in establishing a strong digital relationship with its customers, especially younger customers who had grown up online; to do that, it needed to become a digital leader. The CEO oversaw development of a multiyear digital strategy, including a series of no-regret moves and a few capital-heavy bets, that has led its organization and investment decisions ever since. The choices weren’t easy, requiring top management to have the courage of its conviction and make hard trade-offs, such as pulling budget dollars from traditional print advertising to fund digital investments. The strategy unified the company around the goal of becoming the first fully digital brand in its industry. The company made early, low-risk investments in online brand building and social media. It used Facebook to connect with customers and created its own photo-sharing site featuring its fashions, with content provided by users. As it progressed, it updated its organizational structure and talent, including appointment of a chief creative officer to run digital. (It’s often necessary to have someone highly placed in the organization who “owns” the digital agenda in order to sustain momentum.) The company has invested 60 percent of its marketing budget in digital channels, three times the industry average, underscoring its commitment. Having determined that its principal sales channels would be its own online and brick-and-mortar stores, with other retail outlets playing a supplementary role, the company rethought its product distribution and made the heavy capital investments necessary to build a best-in-class e-commerce operation and digitize its real-world stores to create a seamless online-offline experience for consumers. Today the company is one of the most successful in its industry and is looked to as a model for tailoring online content to enhance brand awareness and drive sales.
- No individual record is particularly valuable, but having every record opens the door to extreme value. This sector generates data from a multitude of sources, from instrumented production machinery (process control), to supply chain management systems, to systems that monitor the performance of products that have already been sold (e.g., during a single cross-country flight, a Boeing 737 generates 240 terabytes of data). And the amount of data generated will continue to grow exponentially. The number of RFID tags sold globally is projected to rise from 12 million in 2011 to 209 billion in 2021. IT systems installed along the value chain to monitor the extended enterprise are creating additional stores of increasingly complex data, which currently tends to reside only in the IT system where it is generated. Manufacturers will also begin to combine data from different systems including, for example, computer-aided design, computer-aided engineering, computer-aided manufacturing, collaborative product development management, and digital manufacturing, and across organizational boundaries in, for instance, end-to-end supply chain data.
- But obviously it takes more than good people and processes. You need the right technology. Let’s get down to brass tacks on what the software is about We’re based on an open source core. A complete, integrated enterprise platform leveraging open source HOSS business model - core set of platform capabilities – we contribute actively into that community. and we layer value added software on top - that’s how we run our business. But what’s truly differentiating about our platform is the enterprise experience you get. It’s why we’re able to claim 7 of the top ten banks and 9 of the top ten telcos are our customers. For regulated industries, the enterprise experience is critical. Multi-cloud – No vendor lock in. Work in the environment of your choice. Better pricing leverage Managed TCO – Multiple pricing and deployment options Integrated – Integrated components with shared metadata, security and operations Secure - Protect sensitive data from unauthorized access – encryption, key management Compliance – Full auditing and visibility Governance – Ensure data veracity
- IoT and predictive analytics. Company Background: TE Connectivity (NYSE: TEL) is a $12 billion global technology leader. Our connectivity and sensor solutions are essential in today's increasingly connected world. We collaborate with engineers to transform their concepts into creations – redefining what's possible using intelligent, efficient and high-performing TE products and solutions proven in harsh environments. Our 72,000 people, including over 7,000 engineers, partner with customers in close to 150 countries across a wide range of industries. TE’s connectivity and sensor solutions are key enablers in our increasingly connected world. Smarter factories, connected vehicles, safer and more advanced medical devices, and data everywhere are underlying market trends creating significant opportunities for TE. Use Case: Hadoop is being used to bring together data from multiple sources including ERP data (SAP), Digital Interaction (Omniture), CRM (Saleforce) & (eloquoa), Factory machine data, and external data (Weather, Social).
- Note: The content of this slide is based on the Monsanto slide. The slide was created in February 2014. Company Background: Monsanto is a major agricultural company that sells seeds and genetic traits developed through biotechnology and crop protection chemicals. Their mission is to attack hunger while our world population grows from 7 billion to 9 billion people, helping farmers produce as much food in the next few decades as they have in the last 10,000 years combined. Use Case: It takes 5-10 years to bring one new product to market because of the intensive research, testing, and evaluation that needs to be done during the R&D process. Meanwhile, Monsanto’s data from labs, the field, literature, and so on are all stored separately and it seemed impossible to combine those data sources. Their researchers were working in special purpose analytical systems that made it difficult to share their results and combine information. The biotech company has deployed Cloudera Enterprise with Cloudera Search to knock down data silos and help researchers share their data. With Cloudera Search, they are indexing images of plants at various stages in their lifecycles to optimize the production processes. Their Cloudera system is integrated with the Oracle Exadata data warehouse, which delivers spatial awareness and visualization. Cloudera Enterprise with Search helps researchers work together so they can automate many data-driven decisions in the R&D pipeline, answering questions like: What traits do we want to integrate into this germ plasm? Which germ plasms do we integrate -- which male and female plants should be brought together to create a child plant? Once that child plant is created, where should it be tested -- in the northern or southern part of the country? This ultimately helps them reduce the time to market of new products. The company is giving scientists direct access to Hadoop so everyone has a single view of their R&D data. Cloudera Navigator will help them increase user adoption of the Cloudera platform even further by offering auditing and access control. Data sources: R&D data Solution Modern Data Platform: Cloudera Enterprise Workloads: Analytic Database Components: Apache HBase, Apache Hive, Apache Oozie, Apache Pig, Apache Sqoop, Apache ZooKeeper, Cloudera Navigator, Cloudera Search Industry Use Case: Product Innovation
- IoT and predictive maintenance. Company Background: Rockwell Automation Millions of sensors wired to controllers in machinery measuring everything from Speed, Force, Temperature, Pressure, RPM Typical Data volumes of 1 PB/ factory/ month; Potentially going up to 30 - 40 Petabytes of data per month iTrak Analytics application built on top of Cloudera on Azure to monitor the performance of individual manufacturing systems in real-time Key Use cases: IoT Enabled ‘Predictive Maintenance’ Predict failures before they happen Reduce or eliminate downtime Real time animation dashboards using Itrak Improved ‘Triaging & Support’ Brokering the right resource with a problem Improved SLAs Optimize the use of skilled resources
- The first one is a Predictive Maintenance case study within the heavy machinery domain. Our client is one of the leading heavy equipment fleet manufacturers and they are using Cloudera in an IoT setting to – a) Continuously monitor performance of their fleet and b) do predictive maintenance. So, their fleet has a number of sensors that are embedded; and it continuously monitors the performance and health of each of the equipment in various locations and sends data back to the data hub– including temp, pressure, force, torque etc. They are using Cloudera to parse this large volume of high velocity sensor data that is coming in from each of their fleet -- every second. They are able to then process and analyze all of this data in our platform, combine this with other data sources from both within and outside of their organization; in order to do things like - performance analysis, advanced defect detection & predictive maintenance.
- [FANUC] Our customer is one of the world’s leading supplier of robotics and factory automation systems. They supply robotics equipment to industries as diverse as aerospace, agriculture, food and beverage, medical devices, and textile industries, to name a few. They also provides engineering, service support, analysis, and system maintenance. Our customer has built a ZDT robotics monitoring solution, that sits on top of the Hadoop platform. Zero Down Time (ZDT) Application – a software platform which analyzes data from GM’s robots throughout its factories to detect potential problems that could lead to failures in the production line. They are using Hadoop platform to gather, store and analyze sensor data files from the thousands of robots across manufacturing plants If a potential failure is identified, ZDT alerts GM and FANUC’s Service Center. Parts and support can then be delivered to tackle the issue before any downtime occurs. Apart from lowering down time, using ZDT, they can can collect data generated from their robots to determine how to optimize their Customer’s manufacturing environment by reducing energy consumption, extending equipment life and improving cycle time and product quality.
- [VOITH] Our customer is one of the global leaders in manufacturing turbines, generators and automation solutions for hydro-electric power stations. They have built and Acoustic monitoring solution built on top of Hadoop to monitor the performance of these massive and expensive turbines. It is similar to what a mechanic does while assessing your car. About 50 % of what a mechanic finds out about your car comes from listening for potential problems. HyGuard applies this principle to hydropower plants.” HyGuard technology works through a series of sensors installed at strategic locations around a remote, unmanned power plant. They are using Hadoop/ Cloudera to gather and analyze acoustic data/audio files coming from the turbines in the power plants, in real-time They are then able to detect anomalies/ variations in the sound waves coming from these machines to detect potential wear and tear And if, for example, one of the sensors detects an anomaly, it sends out an alert and an operator, who is perhaps, based hundreds of kilometers away – can make a quick assessment, and immediately send the recording to an expert for analysis anywhere in the world. They are able to continually monitor ‘’health’’ status of the turbine in order to detect issues before they occur, predict when the turbine will fail & do predictive maintenance
- Note: The content of this slide is based on 2016 Press Release. The slide was created in Jan, 2017. Company Background: SanDisk is an American manufacturer of flash memory products, including memory cards and readers, USB flash drives, and solid state drives. SanDisk is one of the world’s leading producers of data storage products based on flash memory. The inherent nature of the technology manufacturing industry in tandem with its market growth translates into constantly increasing volumes of manufacturing data that SanDisk must write, cleanse, process, and log at every stage of the manufacturing process. Use Case: By implementing an enterprise data hub with Cloudera, SanDisk can collect, analyze, and test all data generated throughout the manufacturing pipeline -- from design to product assembly, and from groups spanning the company whose data traditionally resided in relational databases, NoSQL databases, Microsoft Excel spreadsheets and more, in a single, secure location. The Cloudera platform, including components like Impala, Apache Spark, and Apache Hive, allows users to search, query, and analyze their data, while also enabling machine learning across the vast dataset. Cloudera Navigator and Apache Sentry are critical components of the platform, ensuring real-time data encryption, fine-grained authorization policies, and role-based access controls to protect SanDisk’s intellectual property. “With the creation and adoption of the Hadoop data platform and an Enterprise Data Centric Architecture, SanDisk and Cloudera are leading, driving, and enabling net new capabilities, to perform advanced analytics, machine learning, and pattern matching at scale on SanDisk data at different stages of the manufacturing process,” said Janet George, fellow/chief data scientist at SanDisk. Solution Modern Data Platform: Cloudera Enterprise; Cloudera Navigator Workloads: Analytic Database Components: Impala, Apache Spark, and Apache Hive; Apache Sentry Industry Use Case: Product innovation Quality assurance Read more with the published press release: http://www.cloudera.com/about-cloudera/press-center/press-releases/2016-01-26-SanDisk-Maximizes-Production-Quality-with-Machine-Learning-and-Analytics-Powered-by-Cloudera-Enterprise.html
- Link to account record in SFDC: https://na6.salesforce.com/0018000000y2EIt?srPos=0&srKp=001 Omneo, a Division of Camstar, drives $15 to $25 million in annual savings for electronics manufacturers based on its ability to address supply chain issues in near real time. Background: Today’s consumers have high expectations for the products we use everyday, particularly when it comes to our devices. We want new products to come out faster, at lower prices, with more capabilities than before. But we also demand increased reliability. Camstar, a 30-year veteran in the enterprise manufacturing and supply chain space, saw this trend and identified an opportunity. Challenge: Electronic device manufacturers are responsible for delivering millions of products, each comprised of hundreds of components that are sourced from all over the globe, put together, and pushed through distribution channels to customers. There’s a large margin for error. Camstar set out to address this by spinning off a division called Omneo, who set out to build 360-degree view into supply chain and product quality. Solution: After evaluating IBM Netezza, Infobright, Cassandra, MongoDB, and Hadoop, Omneo decided to try out Hadoop based on 3 main factors: Scalability to grow with customers’ needs over time Flexibility to meet the needs of diverse customers and data sets in a multi-tenant environment Low TCO for an efficient big data solution The team downloaded Cloudera Express since it was easy and no one had any prior experience with the technology. After a few months of demonstrating promising results, Omneo decided to perform a TCO analysis of Cloudera vs. IBM Netezza and their legacy (Oracle) data warehouse. Cloudera’s costs came in 75% lower per TB than IBM Netezza and 90% lower per TB than the incumbent. But before moving forward with a Cloudera Enterprise subscription, the team compared the different Hadoop vendors. They ultimately decided to move forward with Cloudera due to 4 main factors: Long-term company strategy and viability Ease of use and maturity of Cloudera Manager Enterprise-grade support Dedication to open source Omneo has deployed a multi-tenant enterprise data hub from Cloudera as the platform behind its supply chain cloud solution, which ingests machine data and existing system data from throughout the manufacturing process, including from clients’ factory data, supplier data, field services, after-market repairs, and re-manufacturing data. The company uses MapReduce to transform and manipulate data into any structure needed; HBase to access specific records in real time; and Cloudera Search to rapidly index all raw data in a way that makes sense for customers. Results: Omneo’s supply chain SaaS delivers a 360-degree view of the supply chain process in seconds, allowing manufacturers to access their data in different ways, on the fly. If something happens at any supplier that drives a sudden increase in quality issues, they can figure out where the issue stems from and why in minutes or hours. In traditional environments, these investigations would take weeks or months. Instead of spending time trying to pinpoint challenges, manufacturers can spend their time resolving them. Omneo’s clients report total annual savings between $15-25 million each, conservatively.
- Webinar with Josh Byrd (Manager Data Architecture & Operations) and David Winters (Principal Engineer, Data Science & Engineering) Company Background: GoPro helps people capture and share their lives’ most meaningful experiences with others—to celebrate them together. Like how a day on the mountain with friends is more meaningful than one spent alone, the sharing of our collective experiences makes our lives more fun. The world’s most versatile cameras are what we make. Enabling you to share your life through incredible photos and videos is what we do. Use Case: Platform is called “The Philosopher's Stone” (TPS) -- Processing logs: Raw, gzip, binary, cSV, JSON (Streaming and Batch). Data Sources: IoT play Logs from devices, applications (desktop and mobile), external 3rd party systems and services, internal ERP, web/email marketing, etc. – very diverse data Some Raw and Gzip, Some Binary and JSON – processing lots of logs Some streaming single messages and some batch Using data from equipment's to understand better how customers are using their cameras, how often and how can they instrument the devices better. Recently (March 2016) used in launch of GoPro Desktop application to measure usage patterns and popularity of features. “What kind of customer is using the app, what cameras do they use, what resolution”? Virtuous cycle – if GoPro can facilitate the sharing of content, then more customer are likely to buy a camera.
- Company Background: PRGX Global, Inc. is the world's leading provider of accounts payable recovery audit services. With over 1,400 employees, PRGX operates and serves clients in more than 30 countries and provides its services to over 75 percent of the top 20 global retailers. The company’s goal is to help its clients detect, find, and fix leakage in their procurement and payment processes. To do so, PRGX auditors must analyze purchasing, receiving, and payment transactions, along with buyer/supplier contracts, agreements, and emails, to find and recover overpayments. Use Case: Working with Cloudera and Talend, PRGX created a high-performance computing platform for data analytics and discovery that could more rapidly process, discover, model, and serve this massive amount of structured and unstructured data. This new platform delivers on average 9-10x performance improvements—with a 45x performance improvement in one case. Faster performance translates into more auditing time. The more auditing time PRGX staff has, the more payment errors they can identify. The result is greater profitability for both PRGX’s clients and the company itself. Additionally, greater scalability and flexibility to incorporate new data types is expected to help PRGX innovate and offer new products and services. PRGX receives over 2 million client files annually, 2.3 petabytes of data “live” for auditing on average. Data includes purchasing, payment, receiving, deals, point of sale, and emails. Document types processed include: EDI, XML, Flat file csv, Flat file delimited, database backups, spreadsheets, Pdfs, Tiff, Jpeg, Png, Prns, Emails, Microfiche, Proprietary formats Go through the emails etc to find vendor agreements (search etc) and get % of recovery of that (dave shuman)
- IoT and predictive analytics. Company Background: Navistar is a leading manufacturer of commercial trucks, buses, defense vehicles and engines. Navistar International Corporation (NYSE:NAV) is comprised of four segments: North America Truck, North America Parts, Global Operations, and Financial Services. The company’s portfolio includes International® brand commercial and military trucks, proprietary diesel engines, and IC Bus™ brand school and commercial buses. Use Case: Hadoop is being used to bring together data from multiple telematics sources to synthesize a fleet-wide view and enable predictive analytics. http://www.cio.com/article/3009011/analytics/navistar-cio-looks-to-big-data-analytics-to-fuel-turnaround.html