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Operational Analytics & Data and Implementation Sciences IISE Annual Conference Orlando 2019 Industry Practitioner Track 12 Nov 2019 The New Industrial and Systems Engineering: Operational Analytics & Data and Implementation Sciences Scott Sink, Senior Advisor, The Poirier Group Ben Amaba, Global CTO, Data Science and AI, IBM Industrial Mftg. ISE and IISE for Life—how IISE supports you for your entire Career….. CISE (seasoned executives, CISEISE IAB thought (Highly leaders) successful midIAB-career ISE’s) Young Young Professionals Professionals (early career) IISE Student Chapter Professional Chapters are: Alumni Affinity Groups, Local/State/Regional Affinity CareerGroups, Industry Path and and Practitioner Timeline Focused You can get involved in Societies, Divisions and also ‘Affinity Groups’ like Young Professionals, Industry Advisory Board and the Council on Industrial and Systems Engineering Performance Excellence Track—New Orleans 2020 The Performance Excellence Track is focused on: Technology (e.g. AI), Strategy (e.g. shaping Cultures to Support Lean), Process (e.g. Agile), People (e.g. how to successfully navigate politics). How to Improve Culture Expand and Successfully Extend my Navigating Network of Politics Accelerate Peers Voice of Member and Customer Career Progress led us to this example of our and Success Altitude on my life and Operational job and Programming for the Annual Analytics career and have some Conference in New Orleans. Fun Agile Webinar Line-up 13 June—Chapter #1 Annual Virtual Meeting 9 July—Operational Analytics: ideas on how to sustain visible measurement systems and the process improvement benefits you’ve worked to achieve (Scott Sink) 13 Aug—Virtual Mentoring: Career Choicepoint learnings, lessons, tips from Senior ISE Leaders (David Poirier, President, The Poirier Group; Ron Romano, Sr. Mgr. Business Process Reengineering, Walmart, Canada; Yves Belanger, VP Supply Chain, Wolseley Canada) 27 Aug—The next 7 Habits of Highly Effective Young (ISE) Professionals (Allen Drown, United Airlines; Michael Beardsley, Law Student, Case Western Reserve; Jagjit Singh, Discover) 10 Sept—Winners Presentations from the IISE Outstanding Capstone Sr. Design Projects from 2018-19 (Georgia Tech/Cisco; Ohio State/Abbott Nutrition; Virginia Tech/Eastman Chemical) 1 Oct—Being Successful as a “Covert” ISE (Sean Gionvese, IE Manager, Lockeed Martin) 12 Nov—ISE and Data and Implementation Sciences (Scott Sink and Ben Amaba, CTO, IBM Manufacturing) 3 Dec—The Art and Science of Selling your Ideas to various stakeholder groups in different situations (e.g. Private Equity supported firms) (Brent Miller, West Monroe Partners & David Poirier, CEO, The Poirier Group and President-Elect IISE) https://www.iise.org/details.aspx?id=49715 AGENDA 12:00 Scott Kick-off—Framing Up The New ISE and Operational Analytics and Data & Implementation Sciences 12:20 Ben Data Sciences and AI 12:40 Q&A with Participants, Dialogue between Scott and Ben 12:55 Close-out Review upcoming Line-up--Scott 6 This was a “Seminal” piece of work back in 1990. Clear vision of what has transpired and evolved the past 30 years, and also still relevant for what is ahead. 7 Story Line Key Points for our Webinar today….. 1. Defining Operational Analytics, Data Sciences, Implementation Sciences 2. Frameworks for thinking about it and doing it; 3. Example of this—Digital Transformation in Healthcare 4. Accelerating Benefits Realization—Reducing the Latencies 5. Dialogue/Q&A Operational Analytics ▪ This is a useful visual that conveys much of what we mean by Operational Analytics. How to build Visible Measurement/Management Systems in a way that Decreases Latencies ▪ “Above the line” analyst role • Extract features based on questions you have to answer by ‘torturing’ the data until it speaks to you and others. Pick right metrics of interest!! • Apply curiosity & business acumen to data & analyses – create new knowledge, insights, ‘aha’s’ • Apply data visualization techniques to aid in telling the right story – as in life, so in business: the best story wins …Develop the Art of Great Story Lines and Powerful Visualizations and stay focused on driving the ‘end game’ Goal!!! Story Line Key Points for our Webinar today….. 1. Good analytics come from good problem statements, access to the right data, and applying the right techniques 2. Some people have every skill – business acumen, data, technique – to perform a good analysis – but it tends to result in a slow ‘craft’ process 3. Investment in the right data foundation has a positive ROI, as analysts move faster when they trust the data – results in faster results 4. Good data visualizations can tell the right story quickly, because people are predisposed to believe what they see in a chart … 5. There is very positive ROI in getting these decisions right – small analytics teams can wield disproportionate influence on the bottom line 6. Good analytics drive positive action – indeed, in Intel’s supply chain environment, simple/influential beats complex/impotent every time S. Cunningham; Intel Corporation; Adapted from 2013 Management Systems Model— depicting latencies Leadership & Information perception/ management team Information Data management understanding portrayal / insights and Operational (wisdom application, Analytics data/facts to information conversion process) Data Organization Data Analytics Decisions Latencies Data Actions entry Data capture Data Capture Latencies Decision-Making and Action- Upstream Taking Latencies Systems The Business Downstream and Inputs: Processes/Value Systems and Suppliers & Outputs: customer Streams Orders orders Fulfilled The ISE role in Service Systems Engineering: Digital Transformation in Healthcare Michael Caesar, MBA Executive Director, Data & Implementation Science University Health Network November 2018 Data & Implementation Science University Health Network - Not for Distribution (Used with Permission-DSS) Knowing, Understanding, Changing in a Digital World DATA-DRIVEN HEALTH ORGANIZATION Data Supply Drivers Data Demand Drivers Rich New Data Sources Personalized healthcare • Electronic Health Records • Health Information Exchange (HIE) • • Shared decision making • Genomic Information Systems • Personal ownership of health BioRepositories • Data lakes • record • Engagement & Natural language processing • A Healthcare persuasion hub • Benchmarking • organization that is Continuous Data Streams data-driven Non-traditional care • Wearable body sensors • environments Implantable systems • Point of care Leading in evidence- • Reduced hospitalization • testing • smart sensors/bandages • based practice Video/tele health • Virtual nanotechnology • and augmented reality • Enables evidence Patient Generated generating medicine Predictive medicine • Personal health applications AI enabled care (apps) • Patient portals • CRM • Resulting in value- • Shift from restrictive Patient engagement portfolios • based healthcare gatekeeper to coordinator • Rapid diagnosis and treatment • Web and Social media Predictive modelling • Learning • Online communities • health system • Public forums • Population health Smart Machines • Patient stratification • • Internet of things • Disease prevention and health Intelligent processors • promotion • Chronic diseases Machine to machine • PEOPLE, PROCESS, & • Value-based care delivery Robotics • TECHNOLOGY models • Integration of all clinical, research, education data and Performance Operations workflows (quality, standards & Efficiency & Optimization • Workflow • Time stamps contribution) • Patient flow • Delivery • Effort • Investment • • Efficiency • Cost • Data & Implementation Science Caesar, M (2017) University Health Network - Not for Distribution Knowing, Understanding, Changing in a Digital World It is not about adopting digital technologies, it is about changing the way we work in response to the nature of a digital world University Health Network - Not for Distribution DATA & IMPLEMENTATION SCIENCE DATA STRUCTURE GOVERNANCE INSIGHT CHANGE VALUE DATA SCIENCE ANALYTICS Our Data & Implementation Science approach will… • Create a deliberate, bi-directional connection between data and value • Link statistical analysis, computer science and business process understanding to drive insight and change • Enable deep learning across the organization • Develop data-driven capacity and capabilities • Reflect our corporate purpose by providing insight into care, discovery and learning Caesar, M (2017) Data & Implementation Science University Health Network - Not for Distribution Knowing, Understanding, Changing in a Digital World TEAM: CAPABILITIES Identifying and building the skillsets to unlock the value of data benefiting the delivery of care Data Mining Experimentation DATA SCIENCE Explore and Collect and curate experiment with new value data while Develop insights & builds ways of using improving data models through machine learning & statistical algorithms, machine accessibility within a methods learning and AI to community and support, enhance and ecosystem of creators automate decisions and users of data DATA IMPLEMENTATION ENGINEERING SCIENCE Design, build and Inform decision- manage data making and drive infrastructure process and behavioral change Change the way we provide care, discover Insight-enabled and learn Caesar, M (2017) Data & Implementation Science University Health Network - Not for Distribution Knowing, Understanding, Changing in a Digital World DATA SCIENCE: CAPABILITIES Capability and capacity in Data Science enabling personalized medicine, predictive modelling and operational efficiency
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