Tag Archives: Productivity

Takers and Makers: Who are the Real Value Creators?

By Mariana Mazzucato – We often hear businesses, entrepreneurs or sectors talking about themselves as ‘wealth-creating’. The contexts may differ – finance, big pharma or small start-ups – but the self-descriptions are similar: I am a particularly productive member of the economy, my activities create wealth, I take big ‘risks’, and so I deserve a higher income than people who simply benefit from the spillovers of this activity. But what if, in the end, these descriptions are simply just stories? Narratives created in order to justify inequalities of wealth and income, massively rewarding the few who are able to convince governments and society that they deserve high rewards, while the rest of us make do with the leftovers.

If value is defined by price – set by the supposed forces of supply and demand – then as long as an activity fetches a price (legally), it is seen as creating value. So if you earn a lot you must be a value creator.

I will argue that the way the word ‘value’ is used in modern economics has made it easier for value-extracting activities to masquerade as value-creating activities. And in the process rents (unearned income) get confused with profits (earned income); inequality rises, and investment in the real economy falls.

What’s more, if we cannot differentiate value creation from value extraction, it becomes nearly impossible to reward the former over the latter. If the goal is to produce growth that is more innovation-led (smart growth), more inclusive and more sustainable, we need a better understanding of value to steer us.

This is not an abstract debate.

It has far-reaching consequences – social and political as well as economic – for everyone. How we discuss value affects the way all of us, from giant corporations to the most modest shopper, behave as actors in the economy and in turn feeds back into the economy, and how we measure its performance. This is what philosophers call ‘performativity’: how we talk about things affects behavior, and in turn how we theorize things. In other words, it is a self-fulfilling prophecy.

If we cannot define what we mean by value, we cannot be sure to produce it, nor to share it fairly, nor to sustain economic growth. The understanding of value, then, is critical to all the other conversations we need to have about where our economy is going and how to change its course. more>

Updates from Siemens

Gruppo Campari: Brand spirits leader digitizes its business operations with the SIMATIC IT suite
Using Siemens technology, Gruppo Campari has created a unified repository for all product specifications and increased the efficiency of product development and manufacturing processes
Siemens – With so much talk about securing the Italian control of key businesses, a few companies play offense and take the Italian lifestyle and “Made in Italy” all over the world. Among them is Gruppo Campari, which closed 26 acquisitions in the spirits industry in the past two decades to become the world’s sixth player, with over 50 premium and super-premium brands. Besides aperitifs of international renown (Campari, Aperol), the portfolio includes bitter liqueurs (Averna, Cynar, Braulio) and spirits (Skyy, Grand Marnier, GlenGrant, Wild Turkey, Appleton). In 2016 the group exceeded €1.7 billion in consolidated revenues, with most sales in Americas and the Southern Europe, Middle East and Africa (SEMEA) region.

With each acquisition, Gruppo Campari needs to integrate new products, plants and assets into its operations management systems. Recent examples include J. Wray & Nephew, a company with more than 2,000 employees producing Jamaica’s 225-yearold top rum Appleton Estate, Grand Marnier in France acquired in 2016 and Bulldog London Dry Gin in 2017. Currently, the group operates 58 sites: 18 owned factories, 22 co-packers and 18 distribution centers, counting up to thousands of materials and specifications.

The turning point for the management of such a complex and constantly evolving organization came in 2012. Until then, Gruppo Campari had maintained an unstructured approach to the management of product specifications, which were created locally using Microsoft Word documents or Microsoft Excel® spreadsheets. Besides creating documents in different formats and languages, there was no standard workflow for document authoring and validation, and information was shared via email or phone.

In 2012, the Group launched an extensive digitalization of operation processes, selecting SIMATIC IT Interspec from Siemens PLM Software, a configurable solution for product specification management in process industries, and embracing the Siemens “digitalization” philosophy.

SIMATIC IT Interspec allows the company to develop, configure and manage all product specifications (raw materials, intermediate and finished products and packaging materials), storing all specifications in a single, controlled data repository. more>

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Updates from Siemens

Revolutionizing Plant Performance with the Digital Twin and IIoT eBook
By Jim Brown – How can manufacturers use the digital twin and industrial IoT to dramatically improve manufacturing and product performance?

The manufacturing industries are getting more challenging. Manufacturers must evolve as new technologies remove barriers to entry and enable new, digital players to challenge market share. Operational efficiency is no longer enough to compete in today’s era of digitalization and Industry 4.0.

To remain competitive, companies have to maintain high productivity while offering unprecedented levels of flexibility and responsiveness. We believe this is a fundamental disruption that will change the status quo. To survive, manufacturers need to digitalize operations in order to improve speed, agility, quality, costs, customer satisfaction, and the ability to tailor to customer and market needs.

One of the most compelling digitalization opportunities is adopting the digital twin. This approach combines a number of digital technologies to significantly improve quality and productivity. It starts with comprehensive, virtual models of physical assets – products and production lines – to help optimize designs. But the value is much greater because the physical and virtual twins are connected and kept in sync with real data from the Internet of Things (IoT) and Industrial IoT (IIoT).

Further, companies can use analytics to analyze digital twin data to develop deep insights and intelligence that allow for real-time intervention and long-term, continuous improvement.

The digital twin holds significant productivity and quality opportunities for the plant. It can be used to understand when the plant isn’t operating as intended. It can identify or predict equipment issues that can result in unplanned downtime or correct process deviations before they result in quality slippage, scrap, and rework. more>

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Updates from Georgia Tech

He Quieted Deafening Jets
By Ben Brumfield – In 1969, the roar of a passing jet airliner broke a bone in Carolyn Brobrek’s inner ear, as she sat in the living room of her East Boston home. Many flights took off too close to rooftops then, but even at a distance, jet engines were a notorious source of permanent hearing loss.

For decades, Krishan Ahuja tamed jet noise, for which the National Academy of Engineering elected him as a new member this year. Today, Ahuja is an esteemed researcher at the Georgia Institute of Technology, but he got his start more than 50 years ago as an engineering apprentice in Rolls Royce’s aero-engine division, eventually landing in its jet noise research department.

Jet-setters had been a rare elite, but early in Ahuja’s career in the 1970s, air travel went mainstream, connecting the globe. The number of flights multiplied over the years, and jet engine thrust grew stronger, but remarkably, human exposure to passenger jet noise in the same time period plummeted to a fraction of what it had once been, according to the Federal Aviation Administration.

Ahuja not only had a major hand in it, he also has felt the transition himself.

“In those days, if jets went over your house and you were outside, you’d feel like you needed to put your hands over your ears. Not today,” said Ahuja, who is a Regents Researcher at the Georgia Tech Research Institute (GTRI) and Regents Professor in Georgia Tech’s Daniel Guggenheim School of Aerospace Engineering. more>

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Updates from Siemens

Why the aerospace industry must adopt condition-based maintenance
By Dave Chan and John Cunneen – When the aerospace industry adopts condition-based maintenance and predictive maintenance methods, the cost of owning and operating aircraft is minimized, downtime is reduced and airworthiness is easier to prove.

Unfortunately, many companies seem to simply go through the motions and use antiquated and increasingly unreliable methods to track reliability and, as a result, spend more downtime than needed conducting unnecessary maintenance. This not only increases costs but, more importantly, can put the safety of the aircraft at risk.

In our previous blogs, we discussed the cost of certification and the increasing burdens placed on aircraft companies to prove, through certification documentation, that their aircraft meet the government safety standards established in countries and regions worldwide. We also discussed some of the digital tools available to help manage this process, lower costs, decrease time-to-market and increase availability/readiness.

Digitalization can ease the burden of designing and manufacturing an aircraft, but it’s also a pivotal strategy to implement these digital tools to increase the efficiency of maintaining, repairing and operating the aircraft.

Major industries such as maritime and oil and gas are using condition-based maintenance to lower costs and reduce downtime. With the maritime industry, just like the aerospace industry, reliability, availability, maintainability, and safety (RAMS) are key in keeping a maritime fleet operational. more>

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The unlikely origins of USB, the port that changed everything

By Joel Johnson – In the olden days, plugging something into your computer—a mouse, a printer, a hard drive—required a zoo of cables.

If you’ve never heard of those things, and if you have, thank USB.

When it was first released in 1996, the idea was right there in the first phrase: Universal Serial Bus. And to be universal, it had to just work. “The technology that we were replacing, like serial ports, parallel ports, the mouse and keyboard ports, they all required a fair amount of software support, and any time you installed a device, it required multiple reboots and sometimes even opening the box,” says Ajay Bhatt, who retired from Intel in 2016. “Our goal was that when you get a device, you plug it in, and it works.”

But it was an initial skeptic that first popularized the standard: in a shock to many geeks in 1998, the Steve Jobs-led Apple released the groundbreaking first iMac as a USB-only machine.

Now a new cable design, Type-C, is creeping in on the typical USB Type-A and Type-B ports on phones, tablets, computers, and other devices—and mercifully, unlike the old USB cable, it’s reversible. The next-generation USB4, coming later this year, will be capable of achieving speeds upwards of 40Gbps, which is over 3,000 times faster than the highest speeds of the very first USB.

Bhatt couldn’t have imagined all of that when, as a young engineer at Intel in the early ’90s, he was simply trying to install a multimedia card. The rest is history, one that Joel Johnson plugged in to with some of the key players. more>

3 Ways AI Projects Get Derailed, and How to Stop Them

The rate of companies implementing AI is continuing to skyrocket. Don’t fall victim to wasted time and a blown budget.
By Don Roedner – In the blink of an eye, AI has gone from novelty to urgency.

Tech leaders are telling companies they need to adopt AI now or be left behind. And a recent Gartner survey shows just that: AI adoption has skyrocketed over the last four years, with a 270 percent increase in the percentage of enterprises implementing AI during that period.

However, the same survey shows that 63 percent of organizations still haven’t implemented AI or machine learning (ML) in some form.

Why are there so many organizations falling behind the curve?

We meet with companies every week that are in some stage of their first ML project. And sadly, most of the conversations go more or less the same way. The project is strategic and highly visible within the organization. The internal proof of concept went off without a hitch. Now, the team is focused on getting the model’s level of confidence to a point where it can be put into production.

It’s at this point – the transition from proof of concept to production software development – that the project typically runs into big trouble. When we first meet with data science teams, their budget is often dwindling, their delivery deadline is imminent, and their model is still underperforming.

Sound familiar? The guidelines below might help your organization get its AI model to production on time without blowing your budget. more>

Optimizing the Digital Transformation Process

By Stuart Carlaw – When looking at optimizing the digital transformation process in industrial and manufacturing verticals, the task is complex, fraught with risk and subject to increasing pressures in abundance. ABI Research has outlined a number of best practices that fall within a two-step process that will help in “de-risking” the transformation process.

Probably the most profound challenges for anyone looking to implement a technology-driven transformation process is clearly understanding where you are currently in terms of solution maturity and what the end vision should be. Once you know where you are, then you can realistically look to where to target for advancement.

The Industry 4.0 Maturity Model by ABI Research has been designed to provide companies with a quick snapshot of their maturity level and should be viewed as a tool to help align corporations objectively about not only where they stand in the spectrum of industrial development but also where their vision should be aligned regarding future projects.

Once an organization has a good perspective of where it sits on the maturity scale, the job of avoiding common mistakes becomes a far easier prospect. The chances of chasing unrealistic technology goals and making poor decisions based on stock price rather than operational viability become far less when leadership is honest and aligned around a clear understanding of state zero represented in today’s modus operandi.

However, any company is not out of the woods until it galvanizes around a few golden rules when it pivots towards making meaningful changes to your future fortunes. >more>

Updates from Ciena

Tomorrow’s cities: evolving from “smart” to Adaptive
Cities are going smart – trying to deal with the proliferation of people, sensors, automobiles and a range of devices that demand network access and generate mind-boggling amounts of data. However, being smart is not an instance in time, and a “smart city” is not static. To be worthy of the name, a smart city must continually evolve and stay ahead of demand. This is only possible if the city’s underlying network is just as smart and can adapt to its constantly changing environment.
By Daniele Loffreda – Cities are constantly in flux. Populations move in; populations move out. Demographics change, economic growth falls and then soars. New leadership steps in and—if you believe all the commercials—technology will make everyone’s life better.

Municipal governments understand the need to consider which smart city applications will best serve the demands of their diverse demographic segments. The City of Austin’s Head of Digital Transformation, Marni White, summed up these challenges stating, “Our problems will continue to change over time, so our solutions also need to change over time.”

The one constant in the smart city is the network running underneath these solutions—and the truly smart city has a network that adapts.

Smart city applications must be aligned with where a city and its citizens want to go. Some municipalities that created model smart-cities early on have had to initiate extensive revamping. For example, the City of Barcelona has long been at the cutting edge of using digital devices and the Internet of Things to improve municipal operations; however, in 2017, Mayor Ada Colau gave Barcelona’s CTO, Francesca Bria, a mandate to “rethink the smart city from the ground up.”

This meant shifting from a “technology-first” approach, centered on interconnected devices, to a “citizen-first” focus that responds to the changing needs that residents themselves help define. more>

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Updates from Siemens

Siemens – In an industry that demands new products at an unprecedented rate, electronics companies are increasingly relying on “smart manufacturing” to address the challenges of complexity, customization, compliance, globalization and customer expectations for near-perfect quality.

Smart manufacturing – employing computer control and high levels of adaptability – takes advantage of powerful information and manufacturing technologies that enable flexibility in physical processes for a dynamic and global market.

The foundation of smart manufacturing is an integrated platform that unites all of the domains required to engineer, manufacture and deliver today’s smart products. Smart manufacturing is a digitalized development strategy that encompasses the entire process, from PCB design and factory floor optimization to incorporating customer feedback in new designs.

This approach can reduce time-to-market by up to 50 percent, shrink development costs by as much as 25 percent and enable electronics companies to deliver near-perfect product quality.

A digitalization strategy is aimed at creating digital twins of products, production, and performance – detailed and accurate replicas that help accelerate the development, manufacturing, delivery, and service of their real-world counterparts. more>

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