Category: Digital Industry

Industry Reborn: How Tech Is Changing The Way We Make Things

1

As information technology remakes the modern factory, forward-looking companies are creating virtual worlds to optimize real-world manufacturing. The rewards include improvements in business value and sustainability that would have been almost unimaginable just a few years ago.

Among the most important domains in which data-driven approaches are helping manufacturers boost innovation and performance are:

A digital twin is a computer-based replica of a physical object or system.

More specifically, it’s a digital representation of the information embedded within the system. And it’s something that industrial managers can easily study and comprehend—in a way that they can’t, say, a functioning container ship or sprawling manufacturing plant. Managers can use digital twins to predict problems before they occur or to run experiments, exposing the twin to stresses and different inputs without disrupting the real-world system.

The use of duplicates to manage systems dates back to NASA’s Apollo program—more precisely, to 1970’s ill-starred Apollo 13 mission, which almost ended in disaster. The space agency deployed mirrored systems to diagnose the imperiled spacecraft’s problems and devise a plan to get its astronauts back to Earth.

The combination of model-based systems that represent the attributes and behavior of business processes in manufacturing with the recent ascendancy of the Industrial Internet of Things (IIoT) is letting digital twin technology come into its own. The IIoT uses sensors and smart components embedded in machines to allow those machines to communicate with other systems—and to feed data back to managers for analysis. That data and the model, together, constitute the material from which the digital twin takes shape.

Digital twins can also guide sustainable manufacturing, letting companies test out different approaches in a virtual environment. That lets them see how they can best eliminate potential waste, whether in inventory, energy use, equipment efficiency or anywhere else.

A digital twin’s most powerful application, however, may be in the design and planning of manufacturing processes and even entire factories. Eric Green, vice president at Dassault Systèmes, cites the case of a company that Dassault Systèmes helped to create a digital model as a starting point for a new plant.

The company realized that it could improve quality and reduce costs by self-manufacturing parts that it had long outsourced. Working with the digital simulacrum, the company simulated different production volumes and flow rates for the parts it wanted to make in-house.

The state-of-the-art plant worked efficiently from day one—the digital twin eliminated the need for a shakedown period. As a bonus, the company now has nearly identical virtual and real environments. This allows managers to more efficiently shift production around various lines.

“They can simulate and optimize for production rates as they grow their business and understand what they need to do before they actually make changes on the factory floor,” says Green. “They’ve now saved a lot of money and become very efficient.”

Dassault Systèmes’ 3DEXPERIENCE tech goes further. A 3DEXPERIENCE twin is a virtual model of business processes, with digital continuity from engineering to manufacturing. It’s generated from a single data model on a unified platform—an advantage no other twin can claim. A 3DEXPERIENCE twin also ensures unmatched accuracy and fidelity. When these powerful simulated environments are used for analysis in real time, the result is an unparalleled ability to experiment in the digital world. That in turn creates a flawless experience in the real world.

Organizations are also putting twin-based IT platforms to work to create more value within their supplier networks. A supplier may notice, for example, that a different material is more suitable for a component and suggest its use. The twin can then confirm whether that alternative will meet expectations.

The drive to squeeze more value from networks often starts with a market opportunity. A company might detect a shift in the marketplace, and want to capitalize on it. By mapping a network’s complexities in the virtual realm first, managers can model the entire value network—determining how best to acquire and distribute resources before taking real-world steps.

Ultimately, Green says, a company wants to “maximize the profit mix and the product portfolio mix on a global level, and in a sustainable way.”

“Suppliers in certain parts of the world might be more efficient or better than others,” he says. Impacts will vary “based on total landed costs, which include product costs, transportation costs, labor costs, environmental costs, taxes and tariffs.”

Companies are also using collaborative platforms to create sustainability throughout the value network. A platform such as 3DEXPERIENCE lets firms capture, standardize and analyze data to evaluate a business activity’s environmental and social effects and communicate what’s been learned. Beyond their own operations, companies can collaborate through the value network to reduce waste and increase efficiency—from upfront product and packaging design and raw-material sourcing, to end-stage disposal and recovery of materials.

Designing work environments using virtual twins can make them safer, more efficient and more collaborative. Digital twins can help identify workflow bottlenecks or other process flaws.

Augmented reality and virtual reality systems are proving their utility as part of the worker-training process. Dassault Systèmes designed a system for one manufacturer that uses computer-aided design to create an immersive and interactive environment in which trainees manipulate holographic 3D images. New employees can more quickly grasp complex concepts and gain new insights into processes.

The system also improves safety outcomes and efficiency as workers arrive ready to handle the tools, technologies and procedures the factory will throw at them. The risk of human error falls dramatically. And with less need for shop-floor training and shadowing, the arrival of a new employee can have little or no negative impact on production rates.

Needless to say, when life is easier for shop-floor employees, the whole company benefits. In the United States, an aerospace firm was looking for ways to decrease the two full years it was investing in training incoming engineering graduates. With assistance from Dassault Systèmes, the company created a learning program that gave new hires experience with 3D design and digital transformation software. The new employees became productive team members at the company’s aircraft manufacturing sites that much faster.

Collaborative platforms and augmented or virtual reality systems are also providing a mechanism through which experienced workers can share knowledge and know-how—or what Green calls their “DNA”—with younger colleagues.

Then too, collaborative platforms are easing the ability of existing employees to share knowledge across teams or groups.

Green asks us to imagine a worker helping assemble an aircraft. If the engineering team modifies the assembly process and the worker notices that a key procedural step is lacking, that worker needs the ability to raise a red flag and make sure the appropriate people notice it.

Incorporating digital twin technology into these platforms lets companies test out changes that workers have suggested and identify whether it might make sense to formalize some of their on-the-spot work-process improvisations. The result might be more efficient and improved business processes, fewer wasteful steps and less risk of injury. That, in turn, will boost productivity, empower employees and promote wellness—things crucial to leading companies.

By Tom Clynes

Dassault Systèmes

Dassault Systèmes

Dassault Systèmes, the 3DEXPERIENCE® Company, provides business and people with virtual universes to imagine sustainable innovations.

Source: Industry Reborn: How Tech Is Changing The Way We Make Things

.

More contents:

How Low-Code Creates Agility In a Turbulent Business Environment

The pandemic taught us that change is real. It taught us that sometimes a business has to change in order to survive. Sometimes the customers demand change. Sometimes not just revenue, but human health depends on being able to change fast enough. And if you can’t change, you are going to let your customers down. You’ll let your employees down.

These are the reflections of Matt Calkins, co-founder and CEO of Appian, a low-code automation platform that has for almost 20 years helped companies undergo digital transformations. Calkins believes that while many companies have been talking about digital transformation for a decade, the COVID-19 pandemic demonstrated that talk is not enough; using technology to create agility in an organization is now a business imperative.

He admits that his industry is responsible for much of the confusion around terms like digital transformation, visual transformation, hyper automation, low-code, and digital automation. “Those terms basically mean the same thing,” he explains. “They refer to using technology to allow a business to change faster because the world is changing faster, and the business has to keep up.”

Low-code gives you the fastest possible way to build and run a new application. It allows a business to specify a new pattern of behaviour by drawing a flow chart instead of writing lines of code.

“When you make a new application, the thing that slows you down the most is you’ve got to write the code, debug it, test it, and change it,” he explains. “Low-code allows companies to create processes by dragging and dropping, by drawing a picture, a logical flow chart. And this is much more intuitive and mirrors the way humans think about processes and procedures and applications. It’s a very human way to communicate.”

Because low-code is highly flexible and allows you to build and modify unique software for a unique situation, companies using it responded quickly when the pandemic hit.

“They were able to change their processes and the way they work with their customers. They were able to coordinate their employees better and deal with the dispersion of people and assets,” Calkins says.

The pandemic made coordination at a distance across separation a vital skill. Companies had to rally their teams and resources, create new workflows, and delegate decision making to the right person. Businesses that had already embarked on a digital transformation journey were better placed to do this than those that hadn’t.

“Big businesses are very slow to move sometimes,” Calkins says. “A small business sometimes doesn’t even need a procedure. They can just delegate it to a person. But a big organization that needs to do something a hundred thousand times can’t delegate that to a person. They absolutely need a system. The bigger an organization gets, the more scale it requires. And the more scale, the more you must systematize. And so, your agility, your ability to change as a big organization is absolutely a function of software. Software has locked us into patterns because it’s a formula and hard to alter.”

So, are there any barriers for companies considering using low-code?   “In the last few years, they have become exceptionally low,” he explains. “It’s now much, much easier to start a new project in low-code than it ever has been. At this point, products are free to use on the internet. Training is probably free. Thousands of people have certifications around the world. The total cost of ownership has come down, and it’s now very affordable. For these reasons, Forrester says that 75 per cent of organizations will be using low code by the end of 2021.”

Calkins says that because low-code empowers people to communicate with computers in a very human way, it delights them.

“It empowers two [groups of] people specifically. It empowers developers because studies show they can develop 10 to 20 times as much on a low-code platform than if they weren’t using one. It also empowers users because it allows them to participate as members of a dispersed team with great cohesion. It allows them to be connected to key data at the moment of decision, which they wouldn’t otherwise have been. It’s also super empowering as a user because we’re coordinating the assets across the dispersed enterprise so that you can make the decisions at the moment you need to make them.”

How does the Appian platform operate?

“We see our industry is comprised of three core functions. The first one is to discover your processes: to learn what’s actually going on inside your business, so you can figure out what you want to build software around. The second part is to design a new process, and the third is to automate that process to execute it. You have to do the work by delegating it to people, artificial intelligence, robotic process automation, or even business rules.

“Our platform allows you to discover, design and automate your new process. And so that’s what digital transformation or, we like to say, low-code is all about. And by bringing these three things together, we’ve also made this industry far more accessible than it was recently.”

Recent research conducted by Appian, in conjunction with the Economist Intelligence Unit, reveals that 89 per cent of Australian executives believe their organisation encountered operational difficulties in addressing the challenges posed by the pandemic, and 41 per cent described them as significant.

Calkins says that the study focused on the obligations of the modern CIO and the expectations on them. It revealed that 83 per cent of respondents said that their current applications weren’t good enough. They needed them to be more agile, scalable, and flexible to deal with future challenges. But IT departments are also experiencing a serious backlog, so they need to clear the backlog and create better applications.

“The survey says there’s a lot of pressure on the CIO, but I also say there’s a spotlight, there’s an opportunity, and there is respect for the IT function like there’s never been.”

Beyond COVID-19

Calkins predicts that our world will continue to change at high speed. And businesses will have to respond by meeting the needs of all their constituencies: customers, regulators, employees, and even the new boss whose plan disrupts existing patterns. He says the next challenge businesses will face is adopting a hybrid work model.

“It’s going to be different,” he says. We’re going to have customers demanding different services from different places, through different media, and workers working from different places in different modes. We’re entering a new world.

“Businesses are always looking for an edge, and once they find one, they stick with it. They’re going to use agility as their differentiator. So, if you thought it was scary a few years ago to be a slow business, it’s going to be scarier next year because now we’ve emboldened a set of competitors who are all gaining on you because they are fast. And so, everybody’s got to raise their game.”

Clare Loewenthal

By: Clare Loewenthal

Source: How low-code creates agility in a turbulent business environment – Dynamic Business

.

Related Contents:

Schmarzo, Bill (31 May 2017). “What is Digital Transformation?”. http://www.cio.com. Retrieved 9 July 2021.

“Digital Transformation 101: The Only Guide You’ll Ever Need”. http://www.digitaladoption.com. 3 November 2019. Retrieved 9 July 2021.

“What is digital transformation? Definition, Examples, Main Areas”. http://www.zendesk.com. Retrieved 9 July 2021.

“E-commerce to Account for Half the Growth in Global Retail by 2025”. 25 March 2021.

Aleksej Heinze; Marie Griffiths; Alex Fenton; Gordon Fletcher (2018). “Knowledge exchange partnership leads to digital transformation at Hydro-X Water Treatment, Ltd”. Global Business and Organizational Excellence. 37 (4): 6–13. doi:10.1002/JOE.21859. ISSN 1932-2054. Wikidata Q56622208.

Westerman, G; Bonnet, D; McAfee, A (2014). Leading Digital: Turning technology into business transformation. Harvard Business Press.

Imschloss, M. “The impact of digital transformation on the retailing value chain”. International Journal of Research in Marketing.

“La Transformación digital desde la arquitectura empresarial”. Retrieved 22 August 2021.

“The Company Cultures That Help (or Hinder) Digital Transformation”. Harvard Business Review. Retrieved 12 January 2017.

“Strategy, not Technology, Drives Digital Transformation”. http://www.mit.edu. 2015-07-14. Retrieved 2016-01-18.

“The case for digital reinvention”. Retrieved 2021-09-01.

Groover, Mikell (2014). Fundamentals of Modern Manufacturing: Materials, Processes, and Systems.

Rifkin, Jeremy (1995). The End of Work: The Decline of the Global Labor Force and the Dawn of the Post-Market Era. Putnam Publishing Group. pp. 66, 75. ISBN 978-0-87477-779-6.

Lyshevski, S.E. Electromechanical Systems and Devices 1st Edition. CRC Press, 2008. ISBN 1420069721.

Lamb, Frank. Industrial Automation: Hands On (English Edition). NC, McGraw-Hill Education, 2013. ISBN 978-0071816458

The Changing Nature of Work (Report). The World Bank. 2019.

Dashevsky, Evan (8 November 2017). “How Robots Caused Brexit and the Rise of Donald Trump”. PC Magazine. Archived from the original on 8 November 2017.

Torrance, Jack (25 July 2017). “Robots for Trump: Did automation swing the US election?”. Management Today.

Harris, John (29 December 2016). “The lesson of Trump and Brexit: a society too complex for its people risks everything | John Harris”. The Guardian. ISSN 0261-3077.

Darrell West (18 April 2018). “Will robots and AI take your job? The economic and political consequences of automation”. Brookings Institution.

Clare Byrne (7 December 2016). “‘People are lost’: Voters in France’s ‘Trumplands’ look to far right”. The Local.fr.

Bennett 1993.

“Feedback and control systems” – JJ Di Steffano, AR Stubberud, IJ Williams. Schaums outline series, McGraw-Hill 1967

Mayr, Otto (1970). The Origins of Feedback Control. Clinton, MA USA: The Colonial Press, Inc.

Bennett, Stuart (1992). A history of control engineering, 1930–1955. IET. p. 48. ISBN 978-0-86341-299-8.

The elevator example is commonly used in programming texts, such as Unified modeling language

“MOTOR STARTERS START STOPS HAND OFF AUTO”. Exman.com. Archived from the original on 13 April 2014. Retrieved 14 September 2013.

Guarnieri, M. (2010). “The Roots of Automation Before Mechatronics”. IEEE Ind. Electron. M. 4 (2): 42–43. doi:10.1109/MIE.2010.936772. S2CID 24885437.

Ahmad Y Hassan, Transfer Of Islamic Technology To The West, Part II: Transmission Of Islamic Engineering Archived 18 February 2008 at the Wayback Machine

J. Adamy & A. Flemming (November 2004), “Soft variable-structure controls: a survey” (PDF), Automatica, 40 (11): 1821–1844, doi:10.1016/j.automatica.2004.05.017

Otto Mayr (1970). The Origins of Feedback Control, MIT Press.

Donald Routledge Hill, “Mechanical Engineering in the Medieval Near East”, Scientific American, May 1991, p. 64-69.

“Charting the Globe and Tracking the Heavens”. Princeton.edu.

Bellman, Richard E. (8 December 2015). Adaptive Control Processes: A Guided Tour. Princeton University Press. ISBN 9781400874668.

Bennett, S. (1979). A History of Control Engineering 1800–1930. London: Peter Peregrinus Ltd. pp. 47, 266. ISBN 978-0-86341-047-5.

Bennett 1979

Bronowski, Jacob (1990) [1973]. The Ascent of Man. London: BBC Books. p. 265. ISBN 978-0-563-20900-3.

Liu, Tessie P. (1994). The Weaver’s Knot: The Contradictions of Class Struggle and Family Solidarity in Western France, 1750–1914. Cornell University Press. p. 91. ISBN 978-0-8014-8019-5.

Jacobson, Howard B.; Joseph S. Roueek (1959). Automation and Society. New York, NY: Philosophical Library. p. 8.

Hounshell, David A. (1984), From the American System to Mass Production, 1800–1932: The Development of Manufacturing Technology in the United States, Baltimore, Maryland: Johns Hopkins University Press, ISBN 978-0-8018-2975-8, LCCN 83016269, OCLC 1104810110

Partington, Charles Frederick (1 January 1826). “A course of lectures on the Steam Engine, delivered before the Members of the London Mechanics’ Institution … To which is subjoined, a copy of the rare … work on Steam Navigation, originally published by J. Hulls in 1737. Illustrated by … engravings”.

Britain), Society for the Encouragement of Arts, Manufactures, and Commerce (Great (1 January 1814). “Transactions of the Society Instituted at London for the Encouragement of Arts, Manufactures, and Commerce”.

Bennett 1993, pp. 31

Field, Alexander J. (2011). A Great Leap Forward: 1930s Depression and U.S. Economic Growth. New Haven, London: Yale University Press. ISBN 978-0-300-15109-1.

“INTERKAMA 1960 – Dusseldorf Exhibition of Automation and Instruments” (PDF). Wireless World. 66 (12): 588–589. December 1960. […] Another point noticed was the widespread use of small-package solid-state logic (such as “and,” “or,” “not“) and instrumentation (timers, amplifiers, etc.) units. There would seem to be a good case here for the various manufacturers to standardise practical details such as mounting, connections and power supplies so that a Siemens “Simatic,” say, is directly interchangeable with an Ateliers des Constructions Electronique de Charleroi “Logacec,” a Telefunken “Logistat,” or a Mullard “Norbit” or “Combi-element.” […]

“les relais statiques Norbit”. Revue MBLE (in French). September 1962. Archived from the original on 18 June 2018. [1] [2] [3] [4] [5] [6] [7]

Estacord – Das universelle Bausteinsystem für kontaktlose Steuerungen (Catalog) (in German). Herxheim/Pfalz, Germany: Akkord-Radio GmbH [de].

Klingelnberg, W. Ferdinand (2013) [1967, 1960, 1939]. Pohl, Fritz; Reindl, Rudolf (eds.). Technisches Hilfsbuch (in German) (softcover reprint of 15th hardcover ed.). Springer-Verlag. p. 135. doi:10.1007/978-3-642-88367-5. ISBN 978-3-64288368-2. LCCN 67-23459. 0512.

Parr, E. Andrew (1993) [1984]. Logic Designer’s Handbook: Circuits and Systems (revised 2nd ed.). B.H. Newnes / Butterworth-Heinemann Ltd. / Reed International Books. pp. 45–46. ISBN 978-0-7506-0535-9.

Weißel, Ralph; Schubert, Franz (7 March 2013) [1995, 1990]. “4.1. Grundschaltungen mit Bipolar- und Feldeffekttransistoren”. Digitale Schaltungstechnik. Springer-Lehrbuch (in German) (reprint of 2nd ed.). Springer-Verlag. p. 116. doi:10.1007/978-3-642-78387-6. ISBN 978-3-540-57012-7.

Walker, Mark John (8 September 2012). The Programmable Logic Controller: its prehistory, emergence and application (PDF) (PhD thesis). Department of Communication and Systems Faculty of Mathematics, Computing and Technology: The Open University. pp. 223, 269, 308. Archived (PDF) from the original on 20 June 2018.

Rifkin 1995

Jerome, Harry (1934). Mechanization in Industry, National Bureau of Economic Research (PDF).

Constable, George; Somerville, Bob (1964). A Century of Innovation: Twenty Engineering Achievements That Transformed Our Lives. Joseph Henry Press. ISBN 978-0309089081.

“The American Society of Mechanical Engineers Designates the Owens “AR” Bottle Machine as an International Historic Engineering Landmark”. 1983. Archived from the original on 18 October 2017.

Bennett 1993, pp. 7

Landes, David. S. (1969). The Unbound Prometheus: Technological Change and Industrial Development in Western Europe from 1750 to the Present. Cambridge, New York: Press Syndicate of the University of Cambridge. p. 475. ISBN 978-0-521-09418-4.

Bennett 1993, pp. 65Note 1

Musson; Robinson (1969). Science and Technology in the Industrial Revolution. University of Toronto Press.

Lamb, Frank (2013). Industrial Automation: Hands on. pp. 1–4.

Arnzt, Melanie (14 May 2016). “The Risk of Automation for Jobs in OECD Countries: A COMPARATIVE ANALYSIS”. ProQuest 1790436902.

“Process automation, retrieved on 20.02.2010”. Archived from the original on 17 May 2013.

Bartelt, Terry. Industrial Automated Systems: Instrumentation and Motion Control. Cengage Learning, 2010.

Bainbridge, Lisanne (November 1983). “Ironies of automation”. Automatica. 19 (6): 775–779. doi:10.1016/0005-1098(83)90046-8.

Kaufman, Josh. “Paradox of Automation – The Personal MBA”. Personalmba.com.

“Children of the Magenta (Automation Paradox, pt. 1) – 99% Invisible”. 99percentinvisible.org.

Artificial Intelligence and Robotics and Their Impact on the Workplace.

To Reimagine The Student Experience, Think Like A Tech Company

With these five mindset shifts, higher-ed institutions can immerse digital learning into their strategies and operations, reveals Tij Nerurkar, Business Leader for Cognizant’s Education practice.

The news that online learning platform 2U is acquiring edX, a nonprofit platform run by Harvard and MIT, is yet another sign of the momentum of digital learning.

Among the deal’s synergies is 2U’s access to edX’s global learner base of 39 million registered users and 120 million annual website visitors. This increases 2U’s reach and stands to lower student acquisition costs, which typically account for as much as 20% of online program managers’ revenues.

Often overlooked amid the headlines, however, is the reality that technology is only part of the change that digital learning is inflicting on higher education. Equally important is the change in mindset among colleges and universities as they shape the direct-to-consumer (DTC) learning experiences that will engage today’s students.

How to make the higher-ed shift

To reimagine the college experience and make the transition to digital learning, higher-education leaders need to think like a tech company would. The following mindset shifts will propel them forward to immersing digital learning into their strategies and operations:

  • Out with the old culture, in with the new.

This change is among the toughest for colleges and universities to execute. Many university leaders we talk with focus exclusively on the technology that the DTC model requires. But the reality is that DTC is an outside-in approach that puts the student experience first, ahead of any administrative and departmental priorities. It brings changes that ripple across campuses, especially the institutional mindset.

Thriving in today’s higher-education environment requires all campus functions — from recruitment and admissions to financial aid and academics — to move quickly and in seamless, connected ways. Reimagining the student experience will require organizational changes that break down siloes and emphasize collaboration.

  • Be willing to take risks.

While bold moves don’t come naturally to higher-ed institutions, they can be an important differentiator. For example, when the pandemic halted college entrance exams, a nonprofit testing organization used the hiatus to overhaul the paper-based exams that millions of students took annually at its 7,000 centers. Our team built a new-generation platform that digitized the entire testing workflow, including online and mobile apps designed to appeal to Gen Z learners accustomed to multitasking and virtually interacting with their peers. As higher ed begins to emerge from the pandemic, the company is ready with a business model fit for today’s students.

  • View the CIO’s role as strategic.

In our recent research, higher-ed leaders said they believe industry disruption will only accelerate; however, we see too many higher-ed institutions that still limit their CIOs to overseeing back-office operations. A talented CIO can help institutions think out of the box by spotting new business models and investment opportunities to drive enrollments and revenue.

For example, Arizona State University’s widely admired CIO helped ASU break ahead early in online learning with innovative programs like its Global Freshman Academy. By providing CIOs with a seat at the table, higher-ed institutions and their governing boards open themselves to emerging ideas such as adopting blockchain for digital credentials or applying mixed-reality simulations to learning.

  • Reassess your marketing strategies.

Glossy direct-mail brochures are a common and costly rite of passage. The median public university spends 14% of its marketing and recruiting budget on student lists purchased to identify prospects, with one public university’s student data costs topping $2 million from 2010 to 2018. Building predictive analytics capabilities can help organizations reach targeted student populations more intelligently and fill seats more effectively than the basic demographics of lists.

For example, St. Mary’s College credits predictive analytics with increasing its applicant pool. When data showed that prospective students who visited the Maryland campus were more likely to enroll, St. Mary’s doubled down on personalized campus tours that deliver a more on-brand experience. Investing in data modernization, automation and robust platforms requires greater capital investments upfront, but it also creates better and long-lasting pull as universities seek to attract lifelong learners.

  • It takes a platform.

The single biggest lesson to learn from educational technology players is the ability to respond to market conditions with agility, and platforms are at the heart of that flexibility. Ed-tech companies are able to pivot quickly and scale their business models in new directions.

For instance, 2U built momentum and scale by positioning itself not just as a provider of online degree classes for individual students but also as a provider of cloud-based software as-a-service (SaaS) platforms to colleges and universities. The strategy elevates 2U from a services-only business model to the SaaS model.

Now colleges and universities are beginning to take steps in the same direction: Last fall, ASU launched the University Design Institute, through which it scales the innovative approaches and solutions it has developed for its own campus to help other universities create online offerings and is even partnering on community-based projects such as supply chain improvements in Ghana and across Africa. Thinking like a tech company means investing in the right platforms and building the ability to scale.

Capitalize on higher-ed strengths

The most successful tech companies also know and relentlessly develop their strengths, which is why you don’t see Apple rolling out a social network or Netflix designing smartphones. It’s no secret that education’s disruptors offer curriculum options that are fast, dirt-cheap and job-ready. Coursera estimates students can complete a Google Professional Certificates program by studying five to 10 hours per week for eight months or less.

Ed-tech clearly knows its market strengths. At the same time, two-thirds of students between the ages of 19 and 30 still think a college degree is a good investment, whether in-person or virtually. Higher ed’s brand value remains strong in the wake of COVID-19: In another survey, 93% of students polled — both enrolled in fully online programs and studying remotely due to COVID-19 — expect a positive return on their online education investment.

The scalability enabled through digital can help colleges and universities press their pedagogic advantages and compete with online competitors’ lean operations. For example, at a time when applications to full-time MBA programs have declined, enrollment in the University of Illinois’ online MBA program has reached 4,000 — up from 114 since the program’s 2016 launch.

The key to capitalizing on the momentum of digital learning is to reimagine a student experience that taps into today’s youth by reshaping your institution’s mindset and approach to education.

Download our latest research report “The Work Ahead in Higher Ed: Repaving the Road for the Employees of Tomorrow.”

Kshitij Nerurkar

Kshitij Nerurkar

Kshitij (Tij) Nerurkar is the North America leader for Education Business at Cognizant. For over 25 years, Tij has advised and implemented digital learning solutions across private and public sector clients on a global basis. In his current role, he helps educational institutions and ed-tech companies develop and implement digital strategies to transform their business model, reimagine learner experience and drive skill enablement. Previously, Tij was the Head of Cognizant Academy in North America. In this role, he was responsible for developing industry partnerships for the Academy and worked as a core member of the talent team to help bridge the reskilling gap through innovative synergistic business models. Tij has a bachelor’s degree in mechanical engineering and a master’s degree in management studies from the University of Bombay, India, and he has completed a sales and leadership program at Harvard University. Tij is also on the executive learning council of the Association for Talent Development (ATD). He can be reached at Kshitij.Nerurkar@cognizant.com

Source: To Reimagine The Student Experience, Think Like A Tech Company

.

Related Contents:

Teaching with Digital Technologies

Digital Learning: Data, Trends, and Strategies You Need to Know

Digital Transformation 101: The Only Guide You’ll Ever Need

The case for digital reinvention

The Company Cultures That Help (or Hinder) Digital Transformation

La Transformación digital desde la arquitectura empresarial

The impact of digital transformation on the retailing value chain

E-commerce to Account for Half the Growth in Global Retail by 2025

Evolution Is not enough: Revolutionizing Current Learning Environments to Smart Learning Environments

ECE Technology: 10 Trending Tools for Teachers

Confusing terminologies: #e-learning, learning technologist, educational technologist

Zero to six: Electronic media in the lives of infants, toddlers, and preschoolers

Technology in the Preschool Classroom

Technology Education for High-Ability Students

An efficient, portable authoring language for microcomputers

Computer-based Mathematics and Physics for Gifted Remote Students

Computer-based Education Research Laboratory

History of Manhattan Virtual Classroom

 

How Digital Makes Banks Flexible, Responsive And Intimate

While making digital the main channel of customer engagement, banks are also looking to move beyond business as usual, says Amit Anand, a Vice President in Cognizant Consulting’s Banking and Financial Services.

COVID-19 made online channels indispensable for bank customers, including those who preferred in-person banking. This accelerated their digital strategies and created an opportunity to go beyond the basics and become partners in their customers’ pursuit of financial wellness.

As banks bet big on digital, they are looking at technologies such as AI, advanced analytics, and automation to provide personalization, prediction and speed in creating powerful customer experiences. Banks are also increasingly relying on machines to automate repetitive tasks and make complex decisions, creating demand for human skillsets that complement intelligent machines.

Cognizant’s Center for the Future of Work (CFoW), working with Oxford Economics, recently surveyed 4,000 C-level executives globally, including 287 senior banking and financial services executives to understand how banks are adapting to fast and dramatic changes.

The earliest forms of digital banking trace back to the advent of ATMs and cards launched in the 1960s. As the internet emerged in the 1980s with early broadband, digital networks began to connect retailers with suppliers and consumers to develop needs for early online catalogues and inventory software systems.

By the 1990s the Internet became widely available and online banking started becoming the norm. The improvement of broadband and ecommerce systems in the early 2000s led to what resembled the modern digital banking world today. The proliferation of smartphones through the next decade opened the door for transactions on the go beyond ATM machines. Over 60% of consumers now use their smartphones as the preferred method for digital banking.

The challenge for banks is now to facilitate demands that connect vendors with money through channels determined by the consumer. This dynamic shapes the basis of customer satisfaction, which can be nurtured with Customer Relationship Management (CRM) software. Therefore, CRM must be integrated into a digital banking system, since it provides means for banks to directly communicate with their customers.

There is a demand for end-to-end consistency and for services, optimized on convenience and user experience. The market provides cross platform front ends, enabling purchase decisions based on available technology such as mobile devices, with a desktop or Smart TV at home. In order for banks to meet consumer demands, they need to keep focusing on improving digital technology that provides agility, scalability and efficiency.

Seven Ways to Capitalize on Digital

  1. Institute front-to-back digitization. Banks can effectively compete with fintech competitors by becoming digital institutions.
  2. Explore new customer segments and business paradigms. Digital makes it easier than ever for banks to explore small business segments, even as they pursue existing markets.
  3. Emphasize platform centricity and smart aggregation. Open banking standards can help banks to provide personalized products to customers in collaboration with third-party providers and fintechs.
  4. Invest in personalizing the customer relationship. Banks should use personalized experiences to make customers’ lives as frictionless as possible.
  5. Focus on re-building trust and resiliency. Banks need to eliminate any biases in decisions made by machines.
  6. Enshrine inclusivity into your digital strategy. Banks should use digital to reach customers who are left out by being physically and cognitively challenged.
  7. Balance machine-driven and human-centric work. Create sturdy human-machine collaboration by reevaluating jobs for a shared environment.

For more, read our paper “The Work Ahead in Banking: The Digital Road to Financial Wellness”.

Amit Anand

Amit Anand

Amit Anand is Vice President and North American Practice Leader for Cognizant Consulting’s Banking and Financial Services. Amit has 20 years of experience with firms such as Accenture, Infosys and Cognizant. He has successfully led and managed large business transformation, digital and IT transformation, and associated organizational change management for several financial services clients. Amit is a recognized thought leader with more than 15 publications on topics such as Open Banking, Digital 2.0 and new-age operating models. He can be reached at Amit.Anand@cognizant.com

Manish Bahl

Manish Bahl

Manish Bahl leads the Cognizant Center for the Future of Work in Asia-Pacific and the Middle East. A respected speaker and thinker, Manish has guided many Fortune 500 companies into the future of their business with his thought-provoking research and advisory skills. Within Cognizant’s Center for the Future of Work, he helps ensure that the unit’s original research and analysis jibes with emerging business-technology trends and dynamics in APAC, and collaborates with a wide range of leading thinkers to understand and predict how the future of work will take shape. He most recently served as Vice President, Country Manager with Forrester Research in India. He can be reached at Manish.Bahl@cognizant.com

Source: How Digital Makes Banks Flexible, Responsive And Intimate

.

Related Contents:

The irresistible rise of digital banking

What really is “digital banking”? Consensus on this oft-used term’s meaning eludes

Will cash disappear? Many technology cheerleaders believe so, but as Rose Eveleth discovers, the truth is more complicated

Computer Giants Giving a Major Boost to Increased Use of Corporate Videotex

Is Your Digital Banking Vendor Hurting Adoption Rates

New banking services for personal customers

China’s First Online Bank Finally Launches

Online banking fraud has doubled since 2011

Security Flaws in Online Banking Sites Found to be Widespread

Australia’s Newest Digital Bank Goes Live on Temenos to Champion Fairer, More Human Banking Experiences

Hamilton Reserve Bank Completes Temenos End-to-End Digital Transformation

Global Fintech Investment Growth Continues in 2016

Investment in fintech booms as upstarts go mainstream

Beyond Banks and Money: A Guide to Banking Services in the Twenty-First Century

Criminalizing Free Enterprise: The Bank Secrecy Act and the Cryptocurrency Revolution

The Most Innovative Fintech Companies In 2021

Vietnam closes in on Singapore as fintech funding booms

Stockholm FinTech: An overview of the FinTech sector in the greater Stockholm Region

Ensuring Cybersecurity In Fintech: Key Trends And Solutions

Data Security Considerations for FinTech Companies

How Hackers Make Money from DDoS Attacks

OCC Begins Accepting National Bank Charter Applications From Financial Technology Companies

How FutureAdvisor plans to shake up wealth management

 

Open Source Brings Collective Creativity To The Intelligent Edge

The idea of open source is not new. Ideas around the power of collectives to share, iterate, and effectively innovate together in near virtual space arose in the mid-eighteenth century, during the heyday of the age of enlightenment, with groups like the Lunar Society in the UK. The Lunar Society met roughly once a month in Birmingham, at the epicenter of the industrial revolution, as a collective of great minds, including both of Charles Darwin’s grandfathers.

They explored, shared, and broke barriers across disciplines together because they had the space in which to do it, and as a byproduct they gained great energy from discovering the possibilities of the world around them. For anyone who has attended an open source event, this description may sound familiar.

The Lunar Society of the 1790s is in many ways the very essence of open source community. Getting the very best ideas, working together, reacting and sharing together in real time. One major difference, though, is that the Lunar Society was very exclusive by nature, while today’s open source community is not. It is truly open. We live in a vastly more complex and expansive world than Birmingham in the 1790s; the power of the opportunities today is global, and mostly still forming.

With billions of devices running autonomously, computing, sensing, and predicting zettabytes of data, there are endless possibilities for what business ideas and technologies will thrive on the intelligent edge. Only an open source strategy can work in this environment: millions of people, ten of millions of ideas, maybe billions of combinations of code.

Open source for the intelligent edge

An effective intelligent edge will require a robust infrastructure that can handle low latency, high availability, and bandwidth demands. This infrastructure will include three key components: a cloud platform for running applications, analytics to monitor the health of the platform and services, and an orchestration layer to deploy and manage services across a distributed network.

There are five basic ways for companies to obtain this infrastructure: build it themselves from scratch, buy a proprietary solution from a vendor, build it starting with open source, buy a vendor-supported open source solution, or use infrastructure as a service (IaaS).

In a recent survey we administered across 500 respondents in France, Germany, Spain, the UK, and the U.S., a relatively small percentage selected “build your own from scratch,” and a few more selected “vendor proprietary.” The majority selected an option where open source plays a role, whether in IaaS, do-it-yourself (DIY), or vendor-supported options. IaaS was the #1 choice for all three elements (cloud platform, analytics, and orchestration). The rest were split between one of the other flavors of open source (DIY or vendor-supported).

It seems most people aren’t interested in building and/or managing their infrastructure themselves. 34% of business in the U.S. cite “lack of internal skills or knowledge” and “bandwidth constraints on people’s time” as the biggest barriers to adopting intelligent edge technologies, followed closely by “additional investments in associated technologies are unclear” and “lack of internal business support or request.” Open source options give these companies the benefits of the solution without having to shoulder the burden all on their own.

If building and supporting your own infrastructure is core to your business, then building from scratch might make sense — but even then, chances are you may still use open source components. With 180,000 open source projects available with 1,400 unique licenses, it just doesn’t make sense not to use open source to some degree.

Two key reasons why open source is so pervasive

The popularity of open source is not surprising. For one thing, you get to tap into a technological hive mind. There is some debate, and many variables, but estimates put the number of open source developers worldwide somewhere north of 20 million. Open source communities attract a wide variety of people who are interested in participating in a particular piece of technology, with communities and projects running the gamut in terms of size and scope, depending on the focus and maturity of the project.

The common thread is the community of people who are contributing and reviewing code in an effort to make the project better. Generally speaking, the more applicable the code is to a variety of use cases and needs, the more participation you might see in the community. So with open source projects you get to leverage some of the smartest people on the planet, and they don’t have to be on your company payroll.

The second reason for such widespread usage of open source — related to the first — is the fact that you don’t have to do it all yourself. It’s a pretty common scenario for a development organization to use open source code as a component of a larger solution. By leveraging that open source component they can save hundreds if not thousands of work hours by not having to develop or be the sole maintainer of that piece of code. It also allows the organization to focus on their value-add.

Not just a groovy codefest

Open source derives its success from community, and just like in any community, some boundaries and agreed-upon rules to play by are necessary in order to thrive. It’s one thing to download a piece of open source code for use in a personal project. It’s another to use open source code as a critical component of your company’s operations or as a product you provide to your customers. Just because you can get open source code “for free” doesn’t mean you won’t make an investment.

Open source projects need focus, attention, and nurturing. In order to get the full value from the community one must be an active member of that community — or pay someone to be an active member of the community on your behalf. Being active requires an investment of time and resources to give a voice and listen to other voices on a steering committee, discuss priority features to work on next, participate in marketing activities designed to encourage more participants, contribute quality code, review code from others, and more. Leaning in is strongly encouraged.

Open source technology offers a tremendous opportunity for collective creativity and innovation. When like-minded people gather together for a focused intellectual purpose, it’s energizing to the individual and can be hugely beneficial to the organization. Whether the open source code is part of an IaaS, a component of something you build, or part of a vendor-supported solution, it is a tremendous asset you can use to push your company’s value-add forward to better meet your customer’s needs.

Matt Jones

Matt Jones VICE PRESIDENT, GLOBAL ENGINEERING

Matt Jones is responsible for the global R&D team at Wind River. In this role, he leads the delivery of innovative products that are enabling and accelerating the digital transformation of our customers across market segments, ranging from aerospace to industrial, defense to medical, and networking to automotive. With nearly 20 years of experience in the technology industry, he oversees the development of the Wind River portfolio to expand the company’s reach in both new and existing markets.

He was previously at Virgin Hyperloop One, where as Senior Vice President he led the Software Engineering teams; tasked with providing all the software needed to manage, control, and operate an autonomous hyperloop system. This included embedded software and electronics, networking, cloud data and services, as well as customer-facing applications. Prior to Virgin Hyperloop One, he was chief product officer at moovel Group, Daimler’s mobility solutions company. Before moovel, he was director of future technology at Jaguar Land Rover. He also serves as Chairman at GENIVI Alliance, and was a member of the Board of Directors at The Linux Foundation.

He holds a Master of Engineering, Electronic and Electrical with Management, from the University of Birmingham.

Source: Open Source Brings Collective Creativity To The Intelligent Edge

.

Critics:

Open source is source code that is made freely available for possible modification and redistribution. Products include permission to use the source code, design documents, or content of the product. It most commonly refers to the open-source model, in which open-source software or other products are released under an open-source license as part of the open-source-software movement. Use of the term originated with software, but has expanded beyond the software sector to cover other open content and forms of open collaboration.

Generally, open source refers to a computer program in which the source code is available to the general public for use for any (including commercial) purpose, or modification from its original design. Open-source code is meant to be a collaborative effort, where programmers improve upon the source code and share the changes within the community. Code is released under the terms of a software license. Depending on the license terms, others may then download, modify, and publish their version (fork) back to the community.

Open source promotes universal access via an open-source or free license to a product’s design or blueprint, and universal redistribution of that design or blueprint. Before the phrase open source became widely adopted, developers and producers used a variety of other terms. Open source gained hold in part due to the rise of the Internet. The open-source software movement arose to clarify copyright, licensing, domain, and consumer issues. 

Agriculture, economy, manufacturing and production

%d bloggers like this: