Data Con LA 2019 - Innovating with Data by Joey Beitdashtoo
•
0 gefällt mir•190 views
There are three classes of business models for leveraging data:1) Data as a Competitive Advantage (use of Data, advanced analytics and data science capabilities create competitive advantage.)2) Data as Improvement of Existing products or services 9Use of data into exiting offerings, effectively differentiating the value in the market.)3) Data as the Product (this class of business is a step beyond utilizing data for competitive advantage or plugging data into existing products.) Data becomes the asset or product to be monetized.)
Empfohlen
Weitere ähnliche Inhalte
Was ist angesagt?
Was ist angesagt? (20)
Ähnlich wie Data Con LA 2019 - Innovating with Data by Joey Beitdashtoo
Ähnlich wie Data Con LA 2019 - Innovating with Data by Joey Beitdashtoo (20)
Mehr von Data Con LA
Mehr von Data Con LA (20)
Kürzlich hochgeladen
Kürzlich hochgeladen (20)
Data Con LA 2019 - Innovating with Data by Joey Beitdashtoo
- 1. © Systech Solutions, Inc. By Systech Solutions Inc. Joey Beitdashtoo EVP, Corporate Business Development Innovating with Data Acknowledgment: Rob Thomas, GM, IBM Data Analytics & Ai Kaplan & Norton, The Balanced Scorecard Yusuf Gulamhussain, CTO Systech
- 2. © Systech Solutions, Inc. Distinct Waves of Innovation WAVE 1 INDUSTRIAL REVOLUTION The emergence of machines, equipment, and factories automating many tasks that were previously done by humans. It brought scale to the production of many materials and products Lasted over 150 years! WAVE 2 INTERNET REVOLUTION The rise of information networks, driven by connectivity to networks for people and business and a similar rise in computational power. In the the last 2 decades, internet connectivity has transformed many businesses. WAVE 3 INDUSTRIAL INTERNET A new era is dawning, in which machine learning and analytics will automate many tasks that require human decision making today Machines will be intelligent enough to do this themselves Age of Digital Enterprise and Big Data Revolution
- 3. © Systech Solutions, Inc. Three Classes of Business Models for Leveraging Data Data as a Competitive Advantage Use of Data, advanced analytics and data science capabilities create competitive advantage. Example: In banking, mitigate risk, and create market advantage Data as Improvement to Existing Products or Services Use of data into existing offerings, effectively differentiating the value in the market. Example: A real-estate firm that utilizes local data to better target potential customers and match Data as the Product This class of business is a step beyond utilizing data for competitive advantage or plugging data into existing products. Data becomes the asset or product to be monetized. Example D&B, Nielsen
- 4. © Systech Solutions, Inc. Digital Transformation is driven by 4 Key Questions How to build the digital front-end for better customer experience and new customers? How to transact faster in supplier network, sharing smart data securely and in real-time? How to connect digital assets & products real-time to create the live enterprise? How to excite workforce in a hyper-connected world? DIGITAL ENTERPRISE
- 5. © Systech Solutions, Inc. DIGITAL CONTENT 3RD PARTY DATA SOCIAL MEDIA ENTERPRISE CLOUD APPS ENTERPRISE DATA SMART MACHINES Data is the New Oil
- 6. © Systech Solutions, Inc. What Oil Teaches us about Data 4 | Distillation Consuming poor quality data can an 2 | Drilling Use of right tools and approach 3 | Recovery Strategy to recover and extract the data and movement to right users 5 | Refining This is where data is turned into action 6 | Additives Data can be enriched, with 3rd party data or simply through human aided curation 7 | Transporting Data must be in the right place, at the moment of a decision for high impact 1 | Exploration Data can be anywhere - internal or external to the organization
- 7. © Systech Solutions, Inc. Using a Data-Driven Business Decision Cycle 8 Key Functions to Successful Business Performance Finance Product Development Operations Human Resources IT & Business Systems Customer Service Marketing Sales What should we be doing about it? How are we doing? Why?
- 8. © Systech Solutions, Inc. Understanding evolving maturity in the ability to execute analytics has grown more complex The Adaptive Analytics Model is capability based, not a timeline.. Different analytical capabilities and maturity can be collaborative but also independent of each other Business value and use-case driven demand, drive execution rather than technical capability that drive enablement Adaptive Analytics Model !
- 9. © Systech Solutions, Inc. “New” Blue Print
- 10. © Systech Solutions, Inc. Adaptive Advantage is the ability to learn to do new things quickly . In today’s digital age, companies need to instantly adapt to market changes in order to stay relevant. Analytics & Data Management is at the core of building that adaptive capability and fuel Digital Transformation, the ability to sense, experiment, collaborate and act fast. Adaptive Advantage: Be Competitive in Digital Age Reference: Adaptive Advantage: Winning Strategies for Uncertain Times – Boston Consulting Group
- 11. © Systech Solutions, Inc. Data Management Strategy
- 12. © Systech Solutions, Inc. Analytics Strategy
- 13. © Systech Solutions, Inc. Adaptive Analytics – An Approach for Context-Driven Business Decisions “InfoStream” Data-driven business decisions, driving business value AnalyticalApps Analytics & Insights Advanced Analytics (ML | AI) Cloud Implementation Managed Analytics Program Managed Cloud Analytics Platform Data Management Industry | Domain Expertise Social Media Digital Content Enterprise Cloud Apps Smart Machines (IoT) 3rd Party Data ENTERPRISE DATA
- 14. © Systech Solutions, Inc. User Interface, Applications, Business Processes The Business View for Modern Digital Architecture Data Governance Management Data Engines Data Virtualization Answer Fabric
- 15. © Systech Solutions, Inc. Data Innovation Across Industry Verticals INTELLIGENT MACHINES (IoT) MEDICAL GOVERNMENT & SOCIETY WEATHER & ENERGY FARMING & AGRICULTURE RETAIL/CPGCORPORATE SUSTAINABILIT Y INSURANCE FINANCIAL SERVICES CUSTOMER SERVICE
- 16. © Systech Solutions, Inc. The evolution of Farming Transforming Farms with Data Subsistence Farming 1700s Farming for Profit 1800s Power Farming EARLY 1900s The ability to monitor, control, and if necessary, alert the processes Machine Farming MID - LATE 1900s Application of Data Geospatial Information and Beyond… NOW New advantage driven by intangibles: Knowledge, insight, decision making. Ultimately, data is the fertilizer for each of these intangibles.
- 17. © Systech Solutions, Inc. Why Doctors will Have Math Degrees Achieving reduced costs, regulatory compliance, and evidence-based care requires integration of data points across the patient experience • Historical approaches to Medicine, treatments, and wellness are not relevant in Data Era • Decisions based on opinions instead of facts, leads to suboptimal outcomes • Leaders in medicine use data • Today’s medical industry starting with the collection of data and ending with science- based analytics of that data is very different than the past. Transition to Outcomes- Based Care Affects Every Aspect of the Healthcare Industry
- 18. © Systech Solutions, Inc. Data Science Transforms Insurance DATA COLLECTION • Optimal pricing of premiums • Reduced customer churn OUTPUT Fundamental shift based on better collection, access, and use of data New business models are emerging, which is disrupting the traditional skills and tools needed to win in insurance TRENDS: • Better collection, access anduse of data
- 19. © Systech Solutions, Inc. Personalizing Retail and Fashion Transform traditional segment-based retailing into a more personal approach. Transformation in retail is more than just using data to better target clients, it’s about using data to transform the role of a retailer and truly serve a customer of one! one! Household Size Marriage Status Household Size Income Household Size Household Size Household Size Gender Household Size Parenthood Household Size Age Household Size Spend Household Size Customer Lifetime Value Household Size Departments & Categories Household Size Visits Household Size Customer Satisfaction Household Size Brand vs. Generic Preference Household Size Online Shopping Interest Household Size Urbanicity Household Size Number of Children Household Size Marketing Vehicle Engagement Household Size CUSTOMER PROFILE Primary Demographics Secondary Demographics Psychographics Behaviors
- 20. © Systech Solutions, Inc. Transforming Customer Relationships with Data • Increase intimacy between firm and customer • Improve and maximize customer satisfaction, by processing data about the individual in real-time Data about customer behaviors and preferences will allow organizations to offer more tailored services & solutions - to improve customer satisfaction and experiences, and identify challenges ahead of time.
- 21. © Systech Solutions, Inc. Intelligent Machines Predictive Maintenance: Oil Rigs Potentials of drones Exploration of GE Power and Energy business Tesla’s Vehicle Management System The network of data will revolutionize our world
- 22. © Systech Solutions, Inc. Government and Society Whereas election, referendum, and opinion surveys cost substantial amounts of money, social media, offers a means of monitoring public opinion, assessing perceptions, and testing and fine-tuning public policy. Egypt, 2011 Revolution instigated by Social Media • Cities and Crime prevention • Use of public-private partnership for delivering socio- economic benefits • 8 Millennium Development Goals monitored with data driven indicators • Impact bonds (Social Impact, and Development Bonds) Closing the loop between people and government Trending Hashtag Volume
- 23. © Systech Solutions, Inc. Weather and Energy • The application of data for insight, could have better prepared the country or perhaps even prevented the blackout! • Accurate weather forecasting serves to illustrate how human behavior relates to the task of generating and responding to future scenarios • The relationship between weather and energy shows how big data will be used to operate power systems when substantial amounts of variable renewable energy are integrated • The combination of better data and technology innovation will help to balance supply and demand, and keep the lights on. • Renewable energy – solar, Hydro, andWind Power • Smart meters India in 2012 3rd largest consumer and producer of electricity in the world after US and China. The summer of 2012 was hot and demand hit record highs in New Delhi.
- 24. © Systech Solutions, Inc. The Method for Applying Big Data Patterns to Decision-Making 1. Understanding Data Assets 2. Explore the Data 3. Design for Future 4. Design a Data-driven Business Model 5. Transform Business Processes for the Data era 6. Design for Governance and Security 7. Share Metrics and Incentives
- 25. © Systech Solutions, Inc. A Pragmatic and Realizable Vision for Digital Strategy Process Technology People Analytics Address Business Challenges Evaluate Industry Opportunities Identify Corporate Objectives Leverage Data AssetsTo Enable Business Value
- 26. © Systech Solutions, Inc. Making it Happen Within Your Organization People ProcessTechnology Project Sponsors, Stakeholders, IT, Suppliers, Partners, Executive Management Data ingestion, Modern BI/Analytics infrastructure, data quality, data science, integration, MDM, IoT, data warehouse, operational intelligence Efficiencies, data governance, integration of process improvements into solution management
- 27. © Systech Solutions, Inc. Framework for Translating Strategy into Action Financial Growth and Margins Customer Loyalty and Complete Offerings Internal Business Process Brand, Quality, Experience Learning and Growth Strategic Skills THE BALANCED SCORECARD Measurement and Management in the Information Age
- 28. © Systech Solutions, Inc. Consider Mix of Innovative Methods, Products and Services • Alignment of Business Strategy to Operational Innovation • Adoption of Cloud, Analytics, Mobile, Social (C.A.M.S.) to maximize impact • Adoption of Data Science capabilities for predictive intelligence and insights • Continuous knowledge transfer – Instructor-led, On-Demand, and others
- 29. © Systech Solutions, Inc. Next Steps? Questions?
- 30. © Systech Solutions, Inc. www.systechusa.comCONTACT:LOS ANGELES, USA SAN FRANCISCO, USA OUR LOCATIONS: CHENNAI, INDIA DUBAI, UAE Joey Beitdashtoo (714) 322 - 6422 joeyb @systechusa.com
Hinweis der Redaktion
- Big Data Revolution: The ability to suspend disbelief of what is possible, and create own definition of possible An inherent knowledge of pattern recognition and the insight to apply patterns from one industry or dimension to another that may be seemingly unrelated Commitment to one-percent improvement in every aspect related to DATA Combining these seemingly different characteristics and applying them creates possibilities previously undetected. By empowering ourselves with data and believing we can discover the undiscovered, we can launch businesses and industries to new levels.
- Industrial Internet: Pushing the boundaries of Minds and Machines! Thinking, small gains in performance can have a huge impact on overall results. This phenomenon where a simple 1 percent in fuel savings, for example , could drive $30 billion of value over 15-year period! Software being the primary enabler of Wave 3. The software not only will analyze the data gathered from the machines, but also will provide the tools to manage the machines themselves! This is why GE is making a huge bet in software when many people believed it was perhaps non-core to their business.
- Data has the power to create new businesses and even new industries. The challenge is that there are many biases about the use of data in a business. There is a view that data is just about analytics or reporting. In this scenario, it’s relegated to providing insight about the business. There is another view, that data is simply an input into existing products. In this case, data would be used to enrich a current business process, but not necessarily change the process. While these cases are both valid, the power of the Data era enables much greater innovation than simply these incremental approaches!
- Digital Transformation is driven by 4 key questions about Digital reality revolving around answers to these questions:
- Technology & Innovation is presenting organizations with a whole new treasure trove of data that wasn’t either available or accessible before. Characterized by the 3Vs, this new data set is enabling real-time actionable insights across the the spectrum of industry verticals, coining the phrase “Data is the New Oil” The Method for Applying Big Data Patterns to Decision-Making Understanding Data Assets - Locate, catalog, and assess the potential of, all relevant data inside and outside the organization Explore the Data - Applying a rigorous approach of searching for statistical significance Design for Future - Use the implications of data exploration to either make better decisions, design a new business model, or redesign current business processes Design a Data-driven Business Model - If appropriate, design a business model to take advantage of the new data discovery Transform Business Processes for the Data era – If appropriate, redesign existing business processes to capitalize on the new Insights from steps 1 and 2 Design for Governance and Security – Understand the impact of leveraging new insights and data assets, comprehending the implications of privacy and data usage Share Metrics and Incentives – Develop a system to ensure KPIs are measured
- About the Oil: Exploration: Without finding oil sands, or another source of crude., and hence petroleum, the process can never begin Drilling: While exploration requires tools such as geospatial maps and visualizations, drilling requires a rotary drill and insertion of a pipe Recovery: Pipes and valves are installed into the rock to ensure the proper extraction of the crude oil. The pipes are connected to a recovery system, which separates the oil & gas Distillation: Fractional distillation is the processes of removing gasoline from other compounds in the crude oil. The process of heating crude oil, letting it vaporize, and then condensing the vapor, prior to the refining Refining: The most important processes in the manufacturing of oil. Catalysts are added to the crude oil to ensure that the oil is useable Additives: Chemical are added to ensure performance of the finished product Transportation: The last step in the process is about ensuring that the finished product is delivered to a location for consuming About the Data: Exploration - Data can be anywhere internal to organization and external Drilling - Use of right tools and approach Recovery - Strategy to recover and extract the data and movement to right users Distillation - consuming poor quality data can cripple an organization Refining - This is where data is turned into action Additives - Data can be enriched, with 3rd party data or simply through human aided curation Transporting - Data must be in the right place, at the moment of a decision for high impact
- Business Decision Cycle Depends on Answers to Questions that Drive Business Performance Established reports, scorecards and dashboards monitor the business metrics to find answer to how are we doing? Reporting and analysis provides the ability to look at historic static data and understand trends, to look at anomalies and understand why? Planning and forecasting help establish a reliable view of the future and answer what should we be doing? Integrating these capabilities allows to respond to changes happening in your business.
- Desired Outcomes Recommendation Engines Rule-Based Optimization In-Stream Operational Intelligence Real-Time Offers Dynamic Pricing Models
- Data Management and Advanced Analytics is at the core of building adaptive capabilities into business competitive strategy and the four key aspects of Digital Transformation will determine your success.. Signal Advantage: Can we receive and interpret what our customers, partners, employees, infrastructure and other key stakeholders in our ecosystem are sending? Experimentation advantage: Do all facets of the organization have the ability to “experiment” from a cultural, systems and organizational point of view? Organizational Advantage: Can the company respond quickly with nimble and teams that support “variation” in products and business processes that enable adaptation? Systems advantage: Has the organization established a comprehensive and integrated systems infrastructure that support the flow of information, experimentation and adaptive learning?
- Modern Information Management Architectures address a wide range of data inputs. More importantly effective organizations know how to go beyond reporting and structure information output along different information streams that enable data-driven decisions and drive business value. Customers should “re-think” the Analytics & Data Management strategy to deliver context-driven information to the relevant stakeholders, via its modern execution framework ( Key Business Vectors), enabling data-driven business decisions Industry Domain Expertise Data Management Analytics & Insights Advanced Analytics w/ML Cloud Implementation Solutions Managed Analytics Program Managed Cloud Analytics Platform Enterprise Analytical Apps Understanding the Logical View and Technical Capabilities to Support the Business View Data Ingest - Provides the technology to collect, ingest, process, and pre-analyze data Analytics - This is where the heavy lifting is done to extract value from data assets. Analytics requires three distinct capabilities around Discovery, Landing, and Operational Warehouse Information Insight - This layer is the interface to users, business sponsors, and the primary consumption vehicle Operational Data - The traditional data repositories, augmented with new capabilities for entity resolution and data matching Governance - Incorporating security, along with risk management, ensures the stability, continuity, and sustainability of the data architecture
- Understanding The Business View Components as Organizations Evolve to the Data Area: User Interface, Applications, and Business Processes - This is what the business users see as they interact with the big data infrastructure Data Governance - Ensures that data assets are managed like other assets, and must be secured, and managed, over their lifetime, and available for interrogation as required Management - Primary point of operation and orchestration for the IT team. Answer Fabric -This is the brain of the data architecture for analytics capabilities to wow the users and drive business value to the organization Data Virtualization - A requirement to ensure all data assets are utilized and prevents data from having to be moved physically Data Engine - If the answer fabric is the brain, the data engines are the nervous system, delivering the inputs to the brains so that the brain can take action
- Farming and Agriculture - Insurance - Financial Services - Medical - Retail/CPG and Fashion - Customer service - Intelligent Machines - Government and Society - Corporate Sustainability – Weather and Energy
- 1700s (Subsistence Farming) 1800s (Farming for Profit) Early 1900s (Power Farming) Mid – to Late 1900s (Machine Farming) Now, the application of Data! Geospatial Information and beyond. The basic idea that a plant needs sunlight, nutrients from the soil, and water to grow into a healthy plant. The ability to monitor, control, and if necessary , alert the processes The advantage driven by intangibles: Knowledge, insight, decision making. Ultimately, data is the fertilizer for each of these intangibles.
- Historical approaches to Medicine, treatments, and wellness are not relevant in Data Era Decisions based on opinions instead of facts, leads to suboptimal outcomes Leaders in medicine use data Today’s medical industry that starts with the collection of data and end with science-based analytics of that data is very different than the past. The transformation impacting every aspect of healthcare; Biotech, Pharma, Payors, Providers, Patients Scientific method: Formulation of a question Hypothesis Prediction Testing Analysis Enhanced curriculum from anatomy, Biochemistry, Genetics, Microbiology, Pathology, Pharmacology to include; Mathematics, Statistics, Probability, Data analysis and Tools!
- Fundamental shift based on better collection, access, and use of data New business models are emerging, which is disrupting the traditional skills and tools needed to win in insurance Dynamic Risk Management i.e. Pay as you Drive (PAYD) and Pay How you Drive (PHYD) changes from Actuarial insurance practice to Dynamic Risk Management model Opportunities in development sophisticated risk models that are focused on individuals, extremely accurate, and capable of being updated in real-time
- Transform traditional segment-based retailing into a more personal approach - i.e. Thousands of individual customers, instead of thousands of customers Transformation in retail is more than just using data to better target clients, it’s about using data to transform the role of a retailer and truly serve a customer of one! The Shift 1995 The launch of Amazon.com and the collapse of Circuit City, Borders, CompUSA, Blockbusters, Tower Records, and countless others! A number of factors contributed to the decline in traditional retails: Financial Model Price Transparency Social Engagement New distribution Models Price of Innovation Experience
- Increase intimacy between the firm and customer Improving and maximizing customer satisfaction, by processing data about the individual customer in real-time Data about the locations and preferences of individuals will allow organizations to offer services and solutions to improve their personal experiences and identify challenges ahead of time Data transforming Customer service: Data is key ingredient in each of aspects of the successful customer service. The lack of data or lack of use of data is preventing the personalization of customer service, which is the reason that it is not meeting expectations.
- Exploration of GE Power and turbine business Potentials of drones Tesla’s Vehicle Management System The network of data will revolutionize our world Predictive Maintenance Machine Data; Database logs Application logs Application server logs Call detail records Sensor data GPS data IP Router data Clickstream data Transactional data
- Graphics (Police Car, City (Smart Cities) , Government) Cities and Crime prevention Closing the loop between people and government using data has considerable potential Whereas election, referendum, and opinion surveys cost substantial amounts of money, social media, offers a means of monitoring public opinion, assessing perceptions, and testing and fine-tuning public policy. Use of public-private partnership for delivering socio-economic benefits Egypt, 2011 example Social Media* find photo of this 8 Millennium Development Goals monitored with data driven indicators Impact bonds (Social Impact, and Development Bonds)
- Power Crisis in North India occurred due to over withdrawal of power by some states. Better Smart Grid/Metering systems, balancing loads would help prevent these crises in the future, by preventing overutilization. Power failure cascaded through the grid, leaving more than 300 million people without electricity! The next day power failure, left 620 million without electricity!
- Understanding Data Assets - Locate, catalog, and assess the potential of, all relevant data inside and outside the organization Explore the Data - Applying a rigorous approach of searching for statistical significance Design for Future - Use the implications of the of data exploration to either make better decisions, design a new business model, or redesign current business processes Design a Data-driven Business Model - If appropriate, design a business model to take advantage of the new data discovery Transform Business Processes for the Data era – If appropriate, redesign existing business processes to capitalize on the new Insights from steps 1 and 2 Design for Governance and Security – Understand the impact of leveraging new insights and data assets, comprehending the implications of privacy and data usage Share Metrics and Incentives – Develop a system to ensure KPIs are measured A Method for recognizing Patterns in Data: Data Acquisition and sensing Pre-processing Feature Extraction Classification Post-processing
- Framework for Turning Data Assets into valuable information insights and higher business performance Information age organizations are built on a new set of operating assumptions. Cross-functions Links to customers and suppliers Customer segmentation Global scale INNOVATION! Knowledge workers
- Alignment of Business Strategy to Operational Innovation Bridge data strategy, design, implementation and operations Digital transformation advisory on organization (people), processes and technology Adoption of Cloud, Analytics, Mobile, Social (C.A.M.S.) to maximize impact Adoption of modern platform to smartly integrate Adoption of data science capabilities for predictive intelligence and insights Use proven approaches (Adaptive Analytics), innovative software tools, open source, proven IPs, outcome based services for speed and specific outcomes Continuous knowledge transfer - Instructor led, On-Demand, and others Adoption of Self-Service Modern BI, Data Preparation, Advanced Analytics (ML & AI)