Top 50 #BigData Twitter Influencers

Jen Cohen Crompton

#BigData – Twitter Influencers

We are aimed at becoming an authority on business innovation and want to help you identify the top influencers so you can follow the latest trends, news and opinions of these influencers in the field of Big Data. We’ll be publishing more lists on cloud computing, analytics and enterprise mobility in the coming weeks. In the meantime, here is the list of Top 50 Big Data Influencers on Twitter.

Note: Big Data Twitter influencers were determined based on tweeted topics, influence as measured by Klout, number of followers, and number of tweets. Below are the “top” influencers at this time based on the combination of factors.

@bigdata – Ben Lorica
Big Data, Analytics, Cloud Computing resources from Ben Lorica, Chief Data Scientist @OReillyMedia – San Francisco, CA · http://www.bglorica.com
Klout – 49

@BigDataAnalysis – John Akred
Big Data R&D Lead at Accenture Technology Labs, Musician, Engineer, Technologist, Analog Audio and Vacuum Tube lover, Provocateur. These thoughts are my own. – Chicago / San Jose · http://www.linkedin.com/pub/john-akred/1/b0a/320
Klout – 44

@imbigdata – Manish Bhatt
News and Updates about BigData, NoSQL, Hadoop, BI and other Big Data related technologies from BigData enthusiast Manish Bhatt
Klout – 24

@ibmbigdata – IBM Big Data
Talking about the challenges and approaches to handling Big Data. Primarily managed by @TheSocialPitt – http://www.ibm.com/bigdata · http://www.smartercomputingblog.com/category/big-data/
Klout – 37

@bobgourley – Bob Gourley
A CTO. Also find me @CTOvision and @CTOlist. National Security, Cyber Security, Enterprise IT and tech fun are key topics of interest.
Washington, DC · http://ctovision.com
Klout – 50

@klintron – Klint Finley
I write for SiliconAngle. I also run Technoccult and build strange soundscapes.
Portland, OR · http://klintfinley.com
Klout – 45

@KristenNicole2 – Kristen Nicole
News editor at SiliconANGLE, writer at Appolicious, recovering social media addict –  http://kristennicole.com
Klout – 40

@dhinchcliffe – Dion Hinchcliffe
Business strategist, enterprise architect, keynote speaker, book author, blogger, & consultant on social business and next-gen enterprises. – Washington, D.C. · http://dachisgroup.com
Klout – 52

@dmkimball05 – Dan Kimball
CMO at Kontagent, helping companies interpret patterns in social & mobile data to optimize their customer economics – San Francisco, CA · http://www.linkedin.com/in/danielkimball
Klout – 18

@HadoopNews – John Ching
Latest news about Hadoop, NoSQL & BigData from John Ching, Big Data Guru, Consultant, and Evangelist for BI, Machine Learning, and Predictive Analytics
Klout – 44

@medriscoll – Michael E. Driscoll
CEO @Metamarkets. I ♥ Big Data, analytics, and visualization. – San Francisco, CA · http://medriscoll.com/
Klout – 48

@peteskomoroch – Pete Skomoroch
My mission is to create intelligent systems that help people make better decisions. Principal Data Scientist @LinkedIn. Machine Learning, Hadoop, Big Data.
Silicon Valley · http://datawrangling.com
Klout – 56

@hmason – Hilary Mason
chief scientist @bitly. Machine learning; I ♥ data and cheeseburgers.
NYC · http://www.hilarymason.com
Klout – 56

@TimGasper – Tim Gasper
@Infochimps product manager, @Keepstream co-founder, techie, app addict, music writer/lover, #BigData, #Cloud – Austin, TX · http://timgasper.com
Klout – 43

@flowingdata – Nathan Yau
Data, visualization, and statistics. Author of ‘Visualize This.’ Background in eating. – California · http://flowingdata.com
Klout – 58

@bradfordcross – Bradford Cross
design and data @prismatic – San Francisco · http://getprismatic.com/
Klout – 44

@CityAge – City Age
We amplify good ideas through unique dialogues and their associated campaigns. We’re now organizing The Data Effect, amid other projects. – Vancouver, BC · http://www.thedataeffect.org
Klout – 32

@BigDataExpo – Big Data Expo
Join 30,000+ Delegates in 2012 at World’s Largest #Cloud Events! New York [June 11-14] Silicon Valley [Nov 5-8] Register & Save! ▸ http://bit.ly/tucY2B – New York/Silicon Valley · http://BigDataExpo.net
Klout – 34

@acmurthy – Arun C Murthy
Founder & Architect, Hortonworks. VP, Apache Hadoop, Apache Software Foundation i.e. Chair, Hadoop PMC. Moving Hadoop forward since day one, since 2006. – online · http://people.apache.org/
Klout – 43

@infoarbitrage – Roger Ehrenberg
Big Data VC at IA Ventures. Data junkie. Quant dude. Baseball coach. – ÜT: 40.76136,-73.980129 · http://www.iaventures.com
Klout – 56

@jeffreyfkelly – Jeff Kelly
I am an Industry Analyst covering Big Data and Business Analytics at The Wikibon Project and SiliconANGLE – Boston · http://wikibon.org
Klout – 45

@timoreilly – Tim O’Reilly
Founder and CEO, O’Reilly Media. Watching the alpha geeks, sharing their stories, helping the future unfold. – Sebastopol, CA · http://radar.oreilly.com
Klout – 69

@digiphile – Alex Howard
Gov 2.0 @Radar Correspondent, @OReillyMedia: alex@oreilly.com. Intrigued by technological change, taken with ideas, cooking, the outdoors, books, dogs and media – Washington, DC · http://radar.oreilly.com/alexh
Klout – 74

@band – William L. Anderson
Sociotechnical systems developer, open access advocate, and editor at CODATA Data Science Journal – austin texas
Klout – N/A

@HenryR – Henry Robinson
Engineer @ Cloudera, Zookeeper committer / PMC member, professional dilettante – San Francisco, CA · http://the-paper-trail.org/
Klout – 43

@furrier – John Furrier
Silicon Valley entrepreneur Founder SiliconANGLE Network. Inventing New Things, Blogging, Tweeting Social Media – Palo Alto, California · http://SiliconAngle.com
Klout – 49

@mikeolson – Mike Olson
Cloudera CEO – Berkeley, California · http://www.cloudera.com/
Klout – 48

@davenielsen – Dave Nielsen
Co-founder of CloudCamp & Silicon Valley Cloud Center – Mountain View, Ca · http://www.platformd.com
Klout – 44

@znmeb – M. Edward Borasky
Media Inactivist, Thought Follower, Sit-Down Comic, Former Boy Genius, Real-Time Data Journalism Researcher, Open Source Appliance Maker And Mathematician – Portland, OR · http://j.mp/compjournoserver
Klout – N/A

@rizzn – Mark ‘Rizzn’ Hopkins
I’m the editor in chief for SiliconANGLE and the purveyor of fine content at rizzn.com. · http://rizzn.com
Klout – N/A

@edd – Edd Dumbill
Telling the story of our future, where technology is headed, and what we need to know now. O’Reilly Strata and OSCON program chair. Incurably curious – California · http://eddology.com/
Klout – 57

@kellan – Kellan E
Technological solutions for social problems. CTO, Etsy. (if you follow me, consider introducing yourself with @kellan message) #47 – Brooklyn, NY · http://laughingmeme.org
Klout – 58

@mikeloukides – Mike Loukides
VP Content Strategy, O’Reilly Media, pianist, ham radio op usually in Connecticut
Klout – 54

@laurelatoreilly – Laurel Ruma
Director of Talent (speaker and author relations) at O’Reilly Media. Homebrewer, foodie, farmer in the city – Cambridge, MA · http://www.oreilly.com
Klout – 45

@neilraden – Neil Raden
VP/Principal Analyst,Constellation Research;Analytics, BigData, DecisionManagement. Author/Writer,Blogger,Speaker.Husband/(Grand)Father
Santa Fe, NM ·http://www.constellationrg.com/search/node/Neil%20Raden
Klout – 53

@greenplum – Greenplum
Greenplum, a division of EMC is driving the future of big data analytics.
San Mateo, California · http://www.greenplum.com/
Klout – 48

@squarecog – Dmitriy Ryaboy
Analytics Tech Lead at Twitter. Apache Pig committer.
San Francisco
Klout – 48

@BigData_paulz – Paul Zikopoulos
Director of Technical Professionals for IBM’s Information Management, BigData, and Competitive Database divisions. Published 15 books and over 350 articles.
Klout – 38

@moorejh – Jason H. Moore
Third century professor, Director of the Institute for Quantitative Biomedical Sciences at Dartmouth College, Editor-in-Chief of BioData Mining – Lebanon, NH, USA · http://www.epistasis.org
Klout – 47

@GilPress – Gil Press
I launched the #BigData conversation; Writing, research, marketing services; http://whatsthebigdata.com/ & http://infostory.wordpress.com/
Boston
Klout – 41

@ToddeNet – Todd E. Johnson PhD
Educational Access and Academic Sustainability • STEM •Data Informed Decisions (DID) • Always Dreaming and Learning(ADL)….Tweets here are my own!!
Olympia, WA · http://www.linkedin.com/in/toddenet
Klout – 27

@digimindci – Orlaith Finnegan
Provider of Competitive Intelligence & Market Intelligence Software. Online Reputation, Real-time Web Monitoring and Analysis, Social Media Monitoring.
Boston, Paris, Singapore · http://www.digimind.com
Klout – 36

@SmartDataCo – Smart Data Collective
Expert writers on analytics, BI and big data brought to you by the folks at Social Media Today.com · http://smartdatacollective.com
Klout – 42

@al3xandru – Alex Popescu
NOSQL Dreamer http://mynosql.tv, Software architect, Founder/CTO InfoQ.com, Web aficionado, Speaker, iPhone: 44.441881,26.139629 · http://mynosql.tv
Klout – 49

@marksmithvr – Mark Smith
CEO & Chief Research Officer at Ventana Research – http://www.ventanaresearch.com & follow

@ventanaresearch – San Ramon, CA · http://marksmith.ventanaresearch.com/
Klout – 51

@BernardMarr – Bernard Marr
Leading global authority and best-selling author on delivering, managing and measuring enterprise performance – London
Klout – 50

@johnlmyers44 – John L Myers
Senior Analyst for EMA Business Intelligence and Data Warehousing practice specializing in telecom analytics and business process management – Boulder, Colorado · http://www.enterprisemanagement.com/about/team/John_Myers.php
Klout – 54

@leenarao – Leena Rao
Tech Writer (tech Crunch), dog-lover, foodie, quirky – Chicago
Klout – 68

@HKotadia – Harish Kotadia Ph.D
Big Data, Predictive Analytics, Social CRM and CRM. Work for Infosys (NASDAQ: INFY). Views and opinion expressed are my own. – Dallas, Texas, USA · http://HKotadia.com/
Klout – 42

@chuckhollis – Chuck Hollis
technologist, marketeer, blogger and musician working for EMC.
Holliston, MA · http://chucksblog.emc.com
Klout – 49

Disclosure: I am being compensated by SAP to produce a series of posts on the innovation topics covered on this site. The opinions reflected here are my own.

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About Jen Cohen Crompton

Jen Cohen Crompton is a SAP Blogging Correspondent reporting on big data, cloud computing, enterprise mobility, analytics, sports and tech, and anything else innovation-related. When she's not blogging, she can be caught marketing, using social media and/or presenting at conferences around the world. Disclosure: Jen is being compensated by SAP to produce a series of articles on the innovation topics covered on this site. The opinions reflected here are her own.

Three Reasons Discrete Manufacturers Must Integrate Digital And Physical Products

David Parrish

Discrete manufacturers in automotive, aerospace and defense, high tech, and industrial machinery and components are facing unprecedented pressures on their ability to innovate, engage with customers and consumers, and maximize return on their assets. By 2018, nearly one-third of discrete manufacturing leaders will be disrupted by competitors that are digitally enabled, reports IDC. In the age of digital disruption and transformation, discrete manufacturers must rethink traditional business models to capitalize on new, digital opportunities. One such opportunity is the sale of digital products.

Digital products offer many benefits over physical products, including frictionless buying, immediate delivery, and no shipping or supply chain management costs. But digital products can be difficult to sell on their own. To address this challenge, companies are pairing digital products with physical ones. For discrete manufacturers, this pairing offers new business models and revenue-stream opportunities.

Valuing digital products: Using physical products to drive digital sales

What is the value of a digital product? Consumers in the B2C world have historically been slow to jump at the purchase of digital products. As Fast Company reports, it takes a companion physical product to give the digital product value. For example, consider the case of Apple’s iPod and digital music downloads. In the age of Napster and free MP3s, digital music downloads were a slow seller. This changed after Apple introduced its iPod in 2001, creating a new physical product to house these digital downloads. More than 5 billion songs were sold through Apple’s iTunes store by 2008.

Learning from Apple, discrete manufacturers can adopt a similar approach by integrating their physical and digital offerings. Digital offerings, such as remote upgrade service and preventive maintenance contracts, are a natural add-on to physical products. IDC estimates that by 2018, 60% of large manufacturers will bring in new revenue from information-based products and services with embedded intelligence driving the highest profitability levels.

Three applications for digital-physical product integration

For discrete manufacturers, integrating digital and physical products offer three key benefits:

  1. Increased aftermarket value. Selling remote monitoring and digital services is perhaps the most obvious application for digital and physical product integration. Offering upgrades, continuous service, and preventive maintenance via remote monitoring is an important new revenue stream for discrete manufacturers. For example, remote monitoring can dramatically extend the shelf life of industrial machinery used in the food and beverage industries, high-tech manufacturing and automotive manufacturing. Typically, an industrial machine has a shelf life of 20+ years. But the rapid pace of technological change means machines constantly need to be retrofitted. Conditioning-monitoring sensors combined with the Internet of Things (IoT), cloud technology, and analytics would enable discrete manufacturers to offer ongoing digital service plans.
  1. Data monetization. IDC estimates that less than 10% of data is effectively used. Discrete manufacturers must treat data as a digital asset and use this data to improve user experiences, provide insight, influence decisions, and set directions. In the automotive space, discrete manufacturers can leverage usage and engagement information to effectively send content, such as software upgrades and infotainment. Like the Apple iPod/digital download model, auto manufacturers could use the physical product (the car entertainment system) to sell the digital product (the infotainment) to drivers. Automobile manufacturers can use analytic data to better understand driving patterns and preferences, location usage, and demographics. Analyzing this data will allow manufacturers to better target their digital infotainment offerings.
  1. Faster design-to-market cycles. Embedding sensors in industrial machines will generate a wealth of digital performance data that is useful not only for predictive maintenance but also for streamlining future production. Industrial machines are incredibly complex. Ideally, these machines are built following a model-based systems engineering approach that allows designs to be reused for a variety of customers. Integrating sensors into these machines will produce a stream of data that discrete manufacturers can use for future production guidelines. This includes using the data to configure new customer orders. This approach accelerates design-to-market cycles and increases customer satisfaction.

For discrete manufacturers to capitalize on new business opportunities, they need a strategic partner to support digital and physical product integration. Manufacturers need a platform that enables the seamless integration of industrial IoT with advanced analytics process to support product development.

Learn how to innovate at scale by incorporating individual innovations back to the core business to drive tangible business value by reading Accelerating Digital Transformation in Industrial Machinery and Components. Explore how to bring Industry 4.0 insights into your business today by reading Industry 4.0: What’s Next?

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David Parrish

About David Parrish

David Parrish is the senior global director of Industrial Machinery & Components Solutions Marketing for SAP. Before joining SAP, he held various product and industry marketing positions with J.D. Edwards, PeopleSoft, and QAD going back to 1999.

Taking Flight With Aerospace: The Power Of Digital

Torsten Welte

Market experts predict the world’s fleet of commercial aircraft will double in size over the next 20 years. This is due to increasing demand from growing markets like China. Industry leaders can secure their market share if they use an integrated approach to innovation and technology.

Faced with growing market demand, aviation companies are under pressure to speed delivery of new aircraft while implementing digital technologies to improve productivity and reduce manufacturing delays. The aerospace firms that are successful in these efforts will be able to stay within schedules and budgets, focus more intently on global expansion, and attract the best industry talent. But the road ahead is full of challenges.

The complexity of aerospace

The global impact of the aerospace industry is quite impressive. Last year alone, it provided the infrastructure to transport over 3.7 billion passengers. Aviation companies also delivered more than 1,800 new commercial aircraft, and launched 85 orbital space missions. Many of today’s innovations depend on technology coming out of the aerospace world. As an example, imagine smartphones without GPS capabilities, a technology developed in aerospace.

The digitalization of aerospace will drive innovation to produce smarter, more efficient aircraft. Already, modern planes can create over 0.5 TB of data for each flight, as input for next-generation services and groundbreaking 3D printing advances – targeting both primary and replacement parts – are enabling equipment manufacturers to better meet service-level agreements and increase uptime. More than ever, success depends on strong engineering to meet the highest quality and safety standards and a strong focus on the integrated approach to innovation.

Challenging traditional paradigms

Aerospace is one of the most regulated and controlled industries in the world and traditionally has not been made up of “rule breakers.” But innovation in this industry does happen when key players challenge their own business processes, then redefine those processes using an array of new technologies.

Two strong examples of this approach come from commercial aerospace manufacturing. Emerging player SpaceX has redefined the rules of space travel and transformed how payloads are sent into space, delivering an operational model with significantly reduced costs. In contrast, the well-established Lockheed Martin is relying heavily on technology, in the form of the Internet of Things (IoT) and machine learning, to protect people and products. The company is also using a blockchain strategy to speed the discovery and solution of cybersecurity problems and has relied on 3D modeling for many years.

The economics of innovation

The aerospace industry has seen tremendous benefits from technological innovation. 3D printing, for example, has helped redefine the process and cost of manufacturing components. Recently, GE produced a 3D-printed 1,300HP advanced turboprop engine. But while 3D printing an entire engine is impressive, aircraft parts will gain the most from this technology.

With fleets always on the go, it’s difficult to anticipate what parts a plane will need and the optimal service location to store them. A grounded airplane can quickly become an expensive problem, with the estimated cost of a typical “B check” maintenance issue near $60,000 USD. 3D printed parts help avoid that scenario and improve fleet uptime and reduce costs.

The industry has also been an early adopter and innovator of IoT technology. Maintenance, repair, and overhaul (MRO) is the daily task of managing the upkeep of aircraft. Checking working systems and how they interconnect requires data gathering and analysis. Technicians, OEM parts manufacturers, and carriers tend to take a more reactive approach to maintenance. This leads to downtime, delayed flights, and aircraft on the ground (AOG) issues during busy airport hours.

IoT enables companies to launch predictive maintenance initiatives. Maintenance technicians gain an understanding of current known issues through available data. They can also see the time remaining until equipment failure. The maintenance techs then have enough information and time to make repairs before major issues arise.

Soaring with a digital core

Technology modernization, including cloud computing, is a top priority for aerospace. Most aviation companies operate in a hybrid environment. In this situation, cloud-based systems interact with on-premises applications, enabling companies to secure intellectual property while enjoying cloud benefits for traditional business applications, HR, and other things.

Aerospace companies that capitalize on the following strategic priorities will succeed in the changing market:

  1. Customer-centricity. Putting the customer’s point of view at the center of every decision is vital for success in the digital age. Providing tailored benefits, improving product performance, and outcome-oriented service models are key.
  1. Digital business networks. Enabling collaboration and leveraging knowledge benefits all business partners. Scalable and secure, many-to-many networks distribute critical, real-time business information across the network.
  1. Innovation. With even more technology embedded, OEMs aim to make products smarter, more reliable, and affordable for customers.
  1. Agile manufacturing. Advanced automation and integration provide data for process improvement and proof of compliance.
  1. New business models. New digital technologies disrupt traditional business models. The results include process evolution, new market opportunities, and new revenue streams.

Learn how to bring new technologies and services together to power digital transformation by downloading The IoT Imperative for Discrete Manufacturers: Automotive, Aerospace and Defense, High Tech, and Industrial Machinery. Explore how to bring Industry 4.0 insights into your business today by reading Industry 4.0: What’s Next?

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Torsten Welte

About Torsten Welte

Torsten Welte, the global vice president and head of aerospace & defense (A&D) at SAP, has over 25 years of experience in consulting, sales, IT, and program management. Under Torsten’s leadership, the A&D Team delivers industry solutions that help customers innovate and grow their businesses, operate safely, and develop their people. Torsten joined SAP Americas in 2004 and has held several key leadership roles within the North American Aerospace & Defense segment. Prior to his tenure with SAP, Torsten spent 12 years with Deloitte Consulting managing several large SAP implementations as well as strategy engagements across different manufacturing industries.

The Blockchain Solution

By Gil Perez, Tom Raftery, Hans Thalbauer, Dan Wellers, and Fawn Fitter

In 2013, several UK supermarket chains discovered that products they were selling as beef were actually made at least partly—and in some cases, entirely—from horsemeat. The resulting uproar led to a series of product recalls, prompted stricter food testing, and spurred the European food industry to take a closer look at how unlabeled or mislabeled ingredients were finding their way into the food chain.

By 2020, a scandal like this will be eminently preventable.

The separation between bovine and equine will become immutable with Internet of Things (IoT) sensors, which will track the provenance and identity of every animal from stall to store, adding the data to a blockchain that anyone can check but no one can alter.

Food processing companies will be able to use that blockchain to confirm and label the contents of their products accordingly—down to the specific farms and animals represented in every individual package. That level of detail may be too much information for shoppers, but they will at least be able to trust that their meatballs come from the appropriate species.

The Spine of Digitalization

Keeping food safer and more traceable is just the beginning, however. Improvements in the supply chain, which have been incremental for decades despite billions of dollars of technology investments, are about to go exponential. Emerging technologies are converging to transform the supply chain from tactical to strategic, from an easily replicable commodity to a new source of competitive differentiation.

You may already be thinking about how to take advantage of blockchain technology, which makes data and transactions immutable, transparent, and verifiable (see “What Is Blockchain and How Does It Work?”). That will be a powerful tool to boost supply chain speed and efficiency—always a worthy goal, but hardly a disruptive one.

However, if you think of blockchain as the spine of digitalization and technologies such as AI, the IoT, 3D printing, autonomous vehicles, and drones as the limbs, you have a powerful supply chain body that can leapfrog ahead of its competition.

What Is Blockchain and How Does It Work?

Here’s why blockchain technology is critical to transforming the supply chain.

Blockchain is essentially a sequential, distributed ledger of transactions that is constantly updated on a global network of computers. The ownership and history of a transaction is embedded in the blockchain at the transaction’s earliest stages and verified at every subsequent stage.

A blockchain network uses vast amounts of computing power to encrypt the ledger as it’s being written. This makes it possible for every computer in the network to verify the transactions safely and transparently. The more organizations that participate in the ledger, the more complex and secure the encryption becomes, making it increasingly tamperproof.

Why does blockchain matter for the supply chain?

  • It enables the safe exchange of value without a central verifying partner, which makes transactions faster and less expensive.
  • It dramatically simplifies recordkeeping by establishing a single, authoritative view of the truth across all parties.
  • It builds a secure, immutable history and chain of custody as different parties handle the items being shipped, and it updates the relevant documentation.
  • By doing these things, blockchain allows companies to create smart contracts based on programmable business logic, which can execute themselves autonomously and thereby save time and money by reducing friction and intermediaries.

Hints of the Future

In the mid-1990s, when the World Wide Web was in its infancy, we had no idea that the internet would become so large and pervasive, nor that we’d find a way to carry it all in our pockets on small slabs of glass.

But we could tell that it had vast potential.

Today, with the combination of emerging technologies that promise to turbocharge digital transformation, we’re just beginning to see how we might turn the supply chain into a source of competitive advantage (see “What’s the Magic Combination?”).

What’s the Magic Combination?

Those who focus on blockchain in isolation will miss out on a much bigger supply chain opportunity.

Many experts believe emerging technologies will work with blockchain to digitalize the supply chain and create new business models:

  • Blockchain will provide the foundation of automated trust for all parties in the supply chain.
  • The IoT will link objects—from tiny devices to large machines—and generate data about status, locations, and transactions that will be recorded on the blockchain.
  • 3D printing will extend the supply chain to the customer’s doorstep with hyperlocal manufacturing of parts and products with IoT sensors built into the items and/or their packaging. Every manufactured object will be smart, connected, and able to communicate so that it can be tracked and traced as needed.
  • Big Data management tools will process all the information streaming in around the clock from IoT sensors.
  • AI and machine learning will analyze this enormous amount of data to reveal patterns and enable true predictability in every area of the supply chain.

Combining these technologies with powerful analytics tools to predict trends will make lack of visibility into the supply chain a thing of the past. Organizations will be able to examine a single machine across its entire lifecycle and identify areas where they can improve performance and increase return on investment. They’ll be able to follow and monitor every component of a product, from design through delivery and service. They’ll be able to trigger and track automated actions between and among partners and customers to provide customized transactions in real time based on real data.

After decades of talk about markets of one, companies will finally have the power to create them—at scale and profitably.

Amazon, for example, is becoming as much a logistics company as a retailer. Its ordering and delivery systems are so streamlined that its customers can launch and complete a same-day transaction with a push of a single IP-enabled button or a word to its ever-attentive AI device, Alexa. And this level of experimentation and innovation is bubbling up across industries.

Consider manufacturing, where the IoT is transforming automation inside already highly automated factories. Machine-to-machine communication is enabling robots to set up, provision, and unload equipment quickly and accurately with minimal human intervention. Meanwhile, sensors across the factory floor are already capable of gathering such information as how often each machine needs maintenance or how much raw material to order given current production trends.

Once they harvest enough data, businesses will be able to feed it through machine learning algorithms to identify trends that forecast future outcomes. At that point, the supply chain will start to become both automated and predictive. We’ll begin to see business models that include proactively scheduling maintenance, replacing parts just before they’re likely to break, and automatically ordering materials and initiating customer shipments.

Italian train operator Trenitalia, for example, has put IoT sensors on its locomotives and passenger cars and is using analytics and in-memory computing to gauge the health of its trains in real time, according to an article in Computer Weekly. “It is now possible to affordably collect huge amounts of data from hundreds of sensors in a single train, analyse that data in real time and detect problems before they actually happen,” Trenitalia’s CIO Danilo Gismondi told Computer Weekly.

Blockchain allows all the critical steps of the supply chain to go electronic and become irrefutably verifiable by all the critical parties within minutes: the seller and buyer, banks, logistics carriers, and import and export officials.

The project, which is scheduled to be completed in 2018, will change Trenitalia’s business model, allowing it to schedule more trips and make each one more profitable. The railway company will be able to better plan parts inventories and determine which lines are consistently performing poorly and need upgrades. The new system will save €100 million a year, according to ARC Advisory Group.

New business models continue to evolve as 3D printers become more sophisticated and affordable, making it possible to move the end of the supply chain closer to the customer. Companies can design parts and products in materials ranging from carbon fiber to chocolate and then print those items in their warehouse, at a conveniently located third-party vendor, or even on the client’s premises.

In addition to minimizing their shipping expenses and reducing fulfillment time, companies will be able to offer more personalized or customized items affordably in small quantities. For example, clothing retailer Ministry of Supply recently installed a 3D printer at its Boston store that enables it to make an article of clothing to a customer’s specifications in under 90 minutes, according to an article in Forbes.

This kind of highly distributed manufacturing has potential across many industries. It could even create a market for secure manufacturing for highly regulated sectors, allowing a manufacturer to transmit encrypted templates to printers in tightly protected locations, for example.

Meanwhile, organizations are investigating ways of using blockchain technology to authenticate, track and trace, automate, and otherwise manage transactions and interactions, both internally and within their vendor and customer networks. The ability to collect data, record it on the blockchain for immediate verification, and make that trustworthy data available for any application delivers indisputable value in any business context. The supply chain will be no exception.

Blockchain Is the Change Driver

The supply chain is configured as we know it today because it’s impossible to create a contract that accounts for every possible contingency. Consider cross-border financial transfers, which are so complex and must meet so many regulations that they require a tremendous number of intermediaries to plug the gaps: lawyers, accountants, customer service reps, warehouse operators, bankers, and more. By reducing that complexity, blockchain technology makes intermediaries less necessary—a transformation that is revolutionary even when measured only in cost savings.

“If you’re selling 100 items a minute, 24 hours a day, reducing the cost of the supply chain by just $1 per item saves you more than $52.5 million a year,” notes Dirk Lonser, SAP go-to-market leader at DXC Technology, an IT services company. “By replacing manual processes and multiple peer-to-peer connections through fax or e-mail with a single medium where everyone can exchange verified information instantaneously, blockchain will boost profit margins exponentially without raising prices or even increasing individual productivity.”

But the potential for blockchain extends far beyond cost cutting and streamlining, says Irfan Khan, CEO of supply chain management consulting and systems integration firm Bristlecone, a Mahindra Group company. It will give companies ways to differentiate.

“Blockchain will let enterprises more accurately trace faulty parts or products from end users back to factories for recalls,” Khan says. “It will streamline supplier onboarding, contracting, and management by creating an integrated platform that the company’s entire network can access in real time. It will give vendors secure, transparent visibility into inventory 24×7. And at a time when counterfeiting is a real concern in multiple industries, it will make it easy for both retailers and customers to check product authenticity.”

Blockchain allows all the critical steps of the supply chain to go electronic and become irrefutably verifiable by all the critical parties within minutes: the seller and buyer, banks, logistics carriers, and import and export officials. Although the key parts of the process remain the same as in today’s analog supply chain, performing them electronically with blockchain technology shortens each stage from hours or days to seconds while eliminating reams of wasteful paperwork. With goods moving that quickly, companies have ample room for designing new business models around manufacturing, service, and delivery.

Challenges on the Path to Adoption

For all this to work, however, the data on the blockchain must be correct from the beginning. The pills, produce, or parts on the delivery truck need to be the same as the items listed on the manifest at the loading dock. Every use case assumes that the data is accurate—and that will only happen when everything that’s manufactured is smart, connected, and able to self-verify automatically with the help of machine learning tuned to detect errors and potential fraud.

Companies are already seeing the possibilities of applying this bundle of emerging technologies to the supply chain. IDC projects that by 2021, at least 25% of Forbes Global 2000 (G2000) companies will use blockchain services as a foundation for digital trust at scale; 30% of top global manufacturers and retailers will do so by 2020. IDC also predicts that by 2020, up to 10% of pilot and production blockchain-distributed ledgers will incorporate data from IoT sensors.

Despite IDC’s optimism, though, the biggest barrier to adoption is the early stage level of enterprise use cases, particularly around blockchain. Currently, the sole significant enterprise blockchain production system is the virtual currency Bitcoin, which has unfortunately been tainted by its associations with speculation, dubious financial transactions, and the so-called dark web.

The technology is still in a sufficiently early stage that there’s significant uncertainty about its ability to handle the massive amounts of data a global enterprise supply chain generates daily. Never mind that it’s completely unregulated, with no global standard. There’s also a critical global shortage of experts who can explain emerging technologies like blockchain, the IoT, and machine learning to nontechnology industries and educate organizations in how the technologies can improve their supply chain processes. Finally, there is concern about how blockchain’s complex algorithms gobble computing power—and electricity (see “Blockchain Blackouts”).

Blockchain Blackouts

Blockchain is a power glutton. Can technology mediate the issue?

A major concern today is the enormous carbon footprint of the networks creating and solving the algorithmic problems that keep blockchains secure. Although virtual currency enthusiasts claim the problem is overstated, Michael Reed, head of blockchain technology for Intel, has been widely quoted as saying that the energy demands of blockchains are a significant drain on the world’s electricity resources.

Indeed, Wired magazine has estimated that by July 2019, the Bitcoin network alone will require more energy than the entire United States currently uses and that by February 2020 it will use as much electricity as the entire world does today.

Still, computing power is becoming more energy efficient by the day and sticking with paperwork will become too slow, so experts—Intel’s Reed among them—consider this a solvable problem.

“We don’t know yet what the market will adopt. In a decade, it might be status quo or best practice, or it could be the next Betamax, a great technology for which there was no demand,” Lonser says. “Even highly regulated industries that need greater transparency in the entire supply chain are moving fairly slowly.”

Blockchain will require acceptance by a critical mass of companies, governments, and other organizations before it displaces paper documentation. It’s a chicken-and-egg issue: multiple companies need to adopt these technologies at the same time so they can build a blockchain to exchange information, yet getting multiple companies to do anything simultaneously is a challenge. Some early initiatives are already underway, though:

  • A London-based startup called Everledger is using blockchain and IoT technology to track the provenance, ownership, and lifecycles of valuable assets. The company began by tracking diamonds from mine to jewelry using roughly 200 different characteristics, with a goal of stopping both the demand for and the supply of “conflict diamonds”—diamonds mined in war zones and sold to finance insurgencies. It has since expanded to cover wine, artwork, and other high-value items to prevent fraud and verify authenticity.
  • In September 2017, SAP announced the creation of its SAP Leonardo Blockchain Co-Innovation program, a group of 27 enterprise customers interested in co-innovating around blockchain and creating business buy-in. The diverse group of participants includes management and technology services companies Capgemini and Deloitte, cosmetics company Natura Cosméticos S.A., and Moog Inc., a manufacturer of precision motion control systems.
  • Two of Europe’s largest shipping ports—Rotterdam and Antwerp—are working on blockchain projects to streamline interaction with port customers. The Antwerp terminal authority says eliminating paperwork could cut the costs of container transport by as much as 50%.
  • The Chinese online shopping behemoth Alibaba is experimenting with blockchain to verify the authenticity of food products and catch counterfeits before they endanger people’s health and lives.
  • Technology and transportation executives have teamed up to create the Blockchain in Transport Alliance (BiTA), a forum for developing blockchain standards and education for the freight industry.

It’s likely that the first blockchain-based enterprise supply chain use case will emerge in the next year among companies that see it as an opportunity to bolster their legal compliance and improve business processes. Once that happens, expect others to follow.

Customers Will Expect Change

It’s only a matter of time before the supply chain becomes a competitive driver. The question for today’s enterprises is how to prepare for the shift. Customers are going to expect constant, granular visibility into their transactions and faster, more customized service every step of the way. Organizations will need to be ready to meet those expectations.

If organizations have manual business processes that could never be automated before, now is the time to see if it’s possible. Organizations that have made initial investments in emerging technologies are looking at how their pilot projects are paying off and where they might extend to the supply chain. They are starting to think creatively about how to combine technologies to offer a product, service, or business model not possible before.

A manufacturer will load a self-driving truck with a 3D printer capable of creating a customer’s ordered item en route to delivering it. A vendor will capture the market for a socially responsible product by allowing its customers to track the product’s production and verify that none of its subcontractors use slave labor. And a supermarket chain will win over customers by persuading them that their choice of supermarket is also a choice between being certain of what’s in their food and simply hoping that what’s on the label matches what’s inside.

At that point, a smart supply chain won’t just be a competitive edge. It will become a competitive necessity. D!


About the Authors

Gil Perez is Senior Vice President, Internet of Things and Digital Supply Chain, at SAP.

Tom Raftery is Global Vice President, Futurist, and Internet of Things Evangelist, at SAP.

Hans Thalbauer is Senior Vice President, Internet of Things and Digital Supply Chain, at SAP.

Dan Wellers is Global Lead, Digital Futures, at SAP.

Fawn Fitter is a freelance writer specializing in business and technology.

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.

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The “Purpose” Of Data

Timo Elliott

I’ve always been passionate about the ability of data and analytics to transform the world.

It has always seemed to me to be the closest thing we have to modern-day magic, with its ability to conjure up benefits from thin air. Over the last quarter century, I’ve had the honor of working with thousands of “wizards” in organizations around the world, turning information into value in every aspect of our daily lives.

The projects have been as simple as Disney using real-time analytics to move staff from one store to another to keep lines to a minimum: shorter lines led to bigger profits (you’re more likely to buy that Winnie-the-Pooh bear if there’s only one person ahead of you), but also higher customer satisfaction and happier children.

Or they’ve been as complex as the Port of Hamburg: constrained by its urban location, it couldn’t expand to meet the growing volume of traffic. But better use of information meant it was able to dramatically increase throughput – while improving the life of city residents with reduced pollution (less truck idling) and fewer traffic jams (smart lighting that automatically adapts to bridge closures).

I’ve seen analytics used to figure out why cheese was curdling in Wisconsin; count the number of bubbles in Champagne; keep track of excessive fouls in Swiss soccer, track bear sightings in Canada; avoid flooding in Argentina; detect chewing-gum-blocked metro machines in Brussels; uncover networks of tax fraud in Australia; stop trains from being stranded in the middle of the Tuscan countryside; find air travelers exposed to radioactive substances; help abused pets find new homes; find the best people to respond to hurricanes and other disasters; and much, much more.

The reality is that there’s a lot of inefficiency in the world. Most of the time it’s invisible, or we take it for granted. But analytics can help us shine a light on what’s going on, expose the problems, and show us what we can do better – in almost every area of human endeavor.

Data is a powerful weapon. Analytics isn’t just an opportunity to reduce costs and increase profits – it’s an opportunity to make the world a better place.

So to paraphrase a famous world leader, next time you embark on a new project:

“Ask not what you can do with your data, ask what your data can do for the world.”

What are your favorite “magical” examples, where analytics helped create win/win/win situations?

Download our free eBook for more insight on How the Port of Hamburg Doubled Capacity with Digitization.

This article originally appeared on Digital Business & Business Analytics.

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Timo Elliott

About Timo Elliott

Timo Elliott is an Innovation Evangelist for SAP and a passionate advocate of innovation, digital business, analytics, and artificial intelligence. He was the eighth employee of BusinessObjects and for the last 25 years he has worked closely with SAP customers around the world on new technology directions and their impact on real-world organizations. His articles have appeared in publications such as Harvard Business Review, Forbes, ZDNet, The Guardian, and Digitalist Magazine. He has worked in the UK, Hong Kong, New Zealand, and Silicon Valley, and currently lives in Paris, France. He has a degree in Econometrics and a patent in mobile analytics.