[AIIM17] Knowledge Management and the Internet of Things - Katrina Pugh
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For the last fifteen years, we knowledge-practitioners have been working with search-related tools to index and combine structured and unstructured data to be pushed or pulled into decisions. With the Internet of Things, intelligence is now everywhere. This is our time to shine. While pundits debate whether robots augment or replace humans, we submit that IoT will be OUR work. IoT will be both more ubiquitous and more chaotic. This session looks at IoT from a knowledge-practitioner perspective, and explores how we can apply 20 years of KM experience to the "Third Wave" of internet disruption. Learn about the current state of Information Management in AIIM’s latest report: http://info.aiim.org/2017-state-of-information-management
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[AIIM17] Knowledge Management and the Internet of Things - Katrina Pugh
- 1. KM and the Internet of Things Katrina Pugh, Columbia University Information and Knowledge Strategy March 16, 2017 Pugh IoT 170316 1
- 2. Today’s Journey • What is IoT? • KM v. IoT • Info mgt & collaboration • What business models lie ahead? Pugh IoT 170316 2
- 3. Cheaper, cleaner, safer, faster • GE Jet Engines: Needs-based maintenance saves $160M/year* • Tesla: Remote “self-fix” recall • NOAA: Satellite, wind, temperature combo forecasts weather, red tide • Norfolk Southern: saves 10.8 million gallons of diesel, 109,500 metric tons of greenhouse gasses* • UC Irvine Hospital: Disposable wearable sensors to Code Blue within 90 sec.* https://www.wired.com/2016/03/meet- teslas-model-3-long-awaited-car-masses/ *Timothy Chou, Precision (2016) http://www.digitalvidya.com/blog/general- electric-ge-built-big-data-software- analytics-for-industrial-internet/ http://www.goes.noaa.gov/dml/east/n hem/eaus/rb.html http://www.nscorp.com/content/n scorp/en.html Pugh IoT 170316 3
- 4. What is IoT? • “Internet of things” is sensor data, big data, machine learning, machine to machine communication, and automation • Big ideas: Needs-based, as opposed to time-based, repair Self-healing analytics Adding external (e.g., benchmark or history) data “Precision action” Smart, connected assets Pugh IoT 170316 4
- 5. IoT by the (big) numbers $14.2T Economic activity by 2030 (Accenture) $4.5T Economic activity by 2025 (McKinsey) 20.7B Devices in 2020, up from 15.4B in 2016 (IHS) 5B Electric grid data points/day in 2020 (Heck) 200M Wearable devices shipped by 2019 WW (IDC) Pugh IoT 170316 5
- 6. Pugh IoT 170316 ~2020 per every man, woman, child on the earth… $556 in economic activity 3 devices 1 Electric grid data point/day 3% have wearable devices 6
- 7. IoT Enablers Equipment Security Battery power System platforms Analytics tools AIIM 2016 …..and we, information practitionersPugh IoT 170316 7
- 8. Collect (alert) Select, integrate analyze, act Collect, select, integrate (alert) Analyze, act KM IoT - event- interaction Pugh IoT 170316 8
- 9. Pugh IoT 1703169 KM Process IoT Process Design Low volumes, flexible design Billions of data points, fixed Sense Sense-making at end of pipe. …throughout the pipe. Route Metadata may be missing Transmissions may leak Snapshot Institutional memory. Last configuration, trends. Interpret Autoclassification/humans Deep learning/devices. Protect Many actors, algorithms. Bi-direct’l, big “surface area” Collabo- rate “Collective intelligence”; emergence. “Crowd sourcing” at each step divergence.
- 10. Columbia Info and Knowledge Strategy Pillars Access, Use/ Innovate Capture Organize, Store Get Feel Act Info Management CollaborationPugh IoT 170316 10
- 11. Sample IoT Info Management Developments • Security • SIM chips • Block chain Pugh IoT 170316 11
- 12. Sample IoT Collaboration Developments • Standards • Open source • Partnerships
- 13. Brave new world! Pugh IoT 170316 13 Static, contained assets Adaptive, inclusive things Product and Syst. Integ’n Cloud apps, Services People ping things Things ping people & things Hierarchies, entities Networks, coalitions
- 15. Kate Pugh, Columbia University kp2462@Columbia.edu www.sps.columbia.edu/ikns www.alignconsultinginc.com Twitter: katrinapugh • KM and the Internet of Things (KMWorld, 2016) • Smarter Innovation (Ark Group) • Designing Effective Knowledge Networks (Sloan Management Review) • Sharing Hidden Know-How (Wiley/Jossey-Bass) Pugh IoT 170316 15
- 16. Pugh IoT 170316 16
Notes de l'éditeur
- With the Internet of Things Intelligence is everywhere, given the right sensors, integration, and analytics. For the last fifteen years, we knowledge-practitioners have been working with search-related tools to index and combine structured and unstructured data to be pushed or pulled into decisions. This is our moment. While pundits debate whether robots augment or replace humans, we submit that IoT will BE our work. IoT will be both more ubiquitous and more chaotic. This session looks at IoT from a knowledge-practitioner perspective, and explores how we can apply 20 years of KM experience to the "Third Wave" of internet disruption.
- Forbes: (11/27/16) “What emerges is a glimpse into where IoT and IIoT can deliver the most value, and that’s in solving complex logistics, manufacturing, services, and supply chain problems.” http://www.forbes.com/sites/louiscolumbus/2016/11/27/roundup-of-internet-of-things-forecasts-and-market-estimates-2016/#57068bed4ba5
- “Internet of things” is sensor data, big data, machine learning, machine to machine communication, and automation -- all in the service of improving efficiency, quality, and environment. Sensor is connected to a transponder (e.g., microchip), which, in turn, is associated with reader/ interrogator(s). Chip-less form (RFID) reflects back a portion of the radio wave, signaling its “state.”
- November 2016 Forbes article http://www.forbes.com/sites/louiscolumbus/2016/11/27/roundup-of-internet-of-things-forecasts-and-market-estimates-2016/#57068bed4ba5 8.4B WW population forecasted by 2030 according to US census (so (Mckinsey calcs ~$1B in 2015) Biggest growth will be in IoT Services, rather than products. Experts don’t agree (Bain is the most conservative – 470B in 2020, McKinsey 4.5T economic activity. GE forecasts $60T in economic activity by 2030 Heck and Rodgers: Heck, Stefan and Matt Rogers, Resource Revolution: How to capture the biggest business opportunity in a century, Melcher media, 2014.
- E.g., GE’s Predix is platform as a service. According to McKinsey, Biggest profit will go to cloud applications, analytics and data services – even more than to Systems integration Equipment (e.g., sensors, chips, machines, NWs) System platforms (e.g., cloud) and standards
- Spiral versus pipe KM example. Can defer selection and integration, analysis. Collections (e.g., AP wire feeds, SME interviews, thought leadership) to action (better sales process) IoT example. Must collect selectively (limited space, battery, transmission). Collections (e.g., data from agricultural sensors, thermometer readings, nitrogen counts)
- Knowledge practitioner: focus on separating signal from noise. Text analytics. Search algorithms. Auto IoT Practitioner: Focus on synthesis. Detail: KM Design/ Strategy - Many unique sources, lower volumes. Flexible design; relatively low barriers to entry and exit Sense - Intelligence more likely to be at the end of the pipe Route - Metadata, assumptions may be missing, requires loop backs. Snapshot - Institutional memory, trends Interpret - Inspires human action. Add new data easily. Protect - Many sources, actors and algorithms Collaborate - Humans collaborate through all of the steps, especially interpretation; much collaboration involves tacit knowledge, people learn. IoT Design/Strategy - Billions of sensors, billions of readings. Ridged design; high barriers to entry, exit Sense - Intelligence throughout the pipe. May entail billions of sensors. Route - Metadata added at each step. Risk of physical transmission stoppages, leakage Snapshot- Last known good configuration, trends Interpret -Kicks off other devices’ actions (escalates exceptions to humans). More rigid, Protect - Many sources, actors and algorithms; bigger device-intercept risks Collaborate - Machines often collaborate autonomously, and “learn,” increasing system-wide intelligence. The collaboration is bigger than one person can comprehend.
- Security Invincia (Fairfax, VA, being acquired by Sophos) discovers Belkin vulnerability http://www.iotjournal.com/articles/view?15178 Invincea comes with Performance-Built-In™, which combines machine learning and behavioral monitoring to eliminate endpoint security blind spots without sacrificing usability. SIM Chips – reprogrammable virtually Callup IoT Engine http://www.iotjournal.com/articles/view?14181/2 http://www.callup.net/ Block Chain Project Microsoft Manifest http://www.coindesk.com/microsoft-unveils-project-manifest-a-plan-for-product-tracking-via-blockchain/
- Google, Facebook, Microsoft, Amazon, and IBM have founded the Partnership on Artificial Intelligence to benefit people, and society. https://www.partnershiponai.org/#s-partners
- New business models Pay as you go could also be for assets – e.g., AGCO sells 87% uptime for farm equipment plus all of the self-healing Also,: Back office to customer facing Note: Contrary to the way that KM developed (biggest returns to the Systems Integrators), McKinsey forecasts the biggest gains will go to the cloud applications, analytics, and data service.