Posts in Supply Chain Innovation

New Research by MIT Uncovers the Behavioral and Network Features for “Follow Back” on Twitter

 

Interesting insights and exploration from Dylan Walsh, who tells the tale of Taumid Zaman, MIT professor, who tries to tries to get a follow from Taylor Swift and ends up with a new tool for information warfare. To influence someone on social media, first you need them to follow you. New research uncovers the behavioral and network features that make that happen.

Reference: http://mitsloan.mit.edu/newsroom/articles/solving-twitters-follow-back-problem/?utm_source=mitsloantwitter&utm_medium=social&utm_campaign=followback

It was 2014. Taylor Swift had recently released her single “Shake It Off.” She was now a certifiable pop star and Tauhid Zaman, associate professor of operations at MIT Sloan, wondered if he could get her to follow him on Twitter. Swift had about 60 million followers; he had fewer than 1,000. She represented a global empire; he was an academic. A long shot, yes, but these odds were precisely what motivated the question. “I wanted to know what makes people follow you back,” Zaman said. “Celebrities have a wall around them, but their weaknesses on social media are the people they follow.”

Could he somehow use a celebrity’s friends on Twitter — Swift’s hair stylist or sound engineer — to open the gates to her inner circle? He dubbed this the “follow-back problem,” and he solved it with his students at MIT. The first step of this process was to understand the underlying dynamics of follows on Twitter. For instance, what kinds of Twitter interactions matter the most when trying to get followers? And do overlapping social networks actually help build connections? If they do, then to what degree do they help?

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Zaman tested these questions using a group of Twitter bots posing as artists. Each bot was designed to promote a real artist’s work through Twitter’s three main interactions: following, retweeting, and replying. By tracking these interactions and the responses, Zaman was able to methodically probe and quantify the behavior of users on Twitter.

Two basic principles emerged: first, intuitively, those who don’t follow many other people are unlikely to follow you back, while those who follow a lot of people are likely to follow you if you follow and retweet them. Second, social overlap matters. If Swift follows somebody who, in turn, follows Zaman, then Zaman has a greater chance that Swift will follow him. This boost follows a predictable pattern where the friend of my friend is my friend.

But simply understanding these relationships wasn’t Zaman’s goal.

“We’re engineers, and so we wanted to design a system around this insight,” he said.

By the time he and his team got to work on this, though, “Shake it Off” had become much less interesting than the world’s most famous Twitter user, President Donald Trump. What, he wondered, would be the most promising path to get a follow from @realDonaldTrump?

Zaman ran a model to find the optimal sequence of interactions to garner a follow from Trump, assuming you could only interact with 10 or 20 of his connections. (As the number of interactions gets larger, Zaman said, a Twitter account becomes increasingly suspect, looking more like a bot than a real person.)

He found that targeting the right people in the right order made a follow from the president four to five times likelier than a random approach; and if the follow-back campaign expanded to include friends of friends, then the likelihood jumped even higher. In the end, by targeting a network of 200 individuals on Twitter associated with Trump and the people he follows, Zaman found that he could increase the chance that the president would follow him back by an order of magnitude compared to an uncoordinated campaign. The chance was still small, about 2 percent in his calculations, but it still showed the impact of following people in a smart way.

What does this have to do with democracy and counterterrorism? 
As frivolous as this result may seem, Zaman’s work is both timely and relevant to core questions of democracy and counterterrorism, and more generally information warfare. Consider the involvement of Russian bots on Twitter and Facebook now understood as a concerted effort to sway results of the 2016 election.

Or consider the social media accounts created by organizations like the Islamic State group, which has very effectively expanded membership through these channels. Given this social media landscape, cracking the follow-back problem is the first, essential step for infiltrating an adversary’s network. By targeting certain Twitter accounts, for instance, Zaman believes it may be possible to spread information that dampens the effect of foreign actors in domestic elections, or that counters the recruitment propaganda spread by IS.

This prospect, he admits, is equal parts exciting and scary. While there is plenty of good that can come out of these tools — getting people to exercise, eat their vegetables, stop joining IS — there is an obvious dark side.

“In my opinion, this can be far more dangerous than conventional weapons which have a fixed blast radius,” Zaman said.

While social media tools don’t present direct physical threats, they can powerfully influence the opinions of a whole country; they can, in Zaman’s analogy, have a tremendous blast radius.

“These are weapons, and I’m building efficient ways to use the weapons, so this has to be handled with care,” he said.

Zaman hasn’t yet used the modeling results from this work to pursue a Twitter follow from Swift and Trump, but he is considering giving it a try. And as for the follow-back problem, he is planning on incorporating it into a full-fledged social network counter-measure for influence campaigns by hostile state and non-state actors.

Or, as he puts it, he is “developing the tools for the next generation of information warfare.”

This is the first in a three-part series examining new work about Twitter, influence, and bots by MIT Sloan associate professor Tauhid Zaman.

 

 

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Is Circular Progress in Fashion Moving Forward or Far Away?

Introduction

The fashion industry fuels a linear economy with waste greater than $460B of value each year through unsustainable disposal of clothing (Ellen MacArthur Foundation, 2017). Characterized as one of the most polluting and wasteful industries, it consumes 98 million tonnes in non-renewable resources, 93 billion cubic metres of water, and 53 metric tons of fibre to produce clothes used for a short time, after which 13% of the total material input is recycled and 73% of the materials are sent to a grave via landfill or incineration (Ellen MacArthur Foundation, 2017). One estimate suggests that as global population grows to 16% by 2030, the mass-consumption of clothing will grow 65% as 3 billion people move into the middle class (Rosa, 2016).

Reimagining the current take-make-dispose linear process, a circular economy (CE) model demonstrates an opportunity to prevent value leakage by decoupling economic activity from the consumption of finite resources, including shrinking or decreasing use, slowing, and closing material loops as depicted in Figure 1 (Ellen MacArthur Foundation, 2015). This analysis will explore circular approaches that collectively address system-level waste in the textile and clothing system, and the effectiveness of each approach in the acquisition of materials, production of goods, consumption, and disposal.

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Figure 1: Outline of a Circular Economy (Ellen MacArthur Foundation, 2017)

Circular Economy Approaches

According to the Ellen MacArthur Foundation (2017), “A circular economy is restorative and regenerative by design and aims to keep products, components and materials at their highest utility and value at all times, distinguishing between technical and biological cycles.” It represents a paradigm shift in the way products are designed, manufactured, used, and recovered, beyond reducing the negative impacts of the linear economy (Lacy & Rutqvist, 2015). The following CE approaches, particularly when used together, can reduce waste and impact to natural systems throughout the entire textile and clothing system.

Product Design

CE starts with designing products with zero waste, understanding material inputs and dynamics, planning for asset recovery, and considering the total cost of ownership in a product’s lifecycle (Rydberg, 2016). Design also includes development of product lines that meet demand without deteriorating assets. CE design must source material from within regenerative loops, rather than from linear flows and enable businesses to develop a revenue model that generates value across the supply chain as depicted in Figure 2 (PWC, 2017). This may include designing products to last longer, with higher quality specs, and that are easily repairable by the customer.

Figure 2: Value Leakage in Linear v. Circular Economy Model (PWC, 2017)

Recovery and Recycling

CE views recovery and recycling waste as a resource holistically integrated into the business model, not as an external problem (Rydberg, 2016). Upcycling converts an old product or material into something of higher valuable, while downcycling deconstructs the properties of a material for reuse (Lacy & Rutqvist, 2015). Conceptually, reuse enables the mining of resources from current products, repurposing material inputs previously funded (PWC, 2017). One variation includes recovering end-of-life products that recapture value in an actor’s own closed loops or any actor’s open loops as depicted in Figure 2 (PWC, 2017). A second variation recovers waste and by-products from a company`s own production process and operations to recapture value (Marino & Pariso, 2016). Therefore, the CE model can generate a revenue stream from large amounts of inefficiency in waste and disposal that are valuable to the broader supply chain or another actor (Marino & Pariso, 2016).

Raw Materials and Innovation

Disassembling a garment for reuse and recycling can be labor intensive and ineffective (Rosa, 2016). Current linear business models rely on large quantities of natural resources. Little or no control over price and supply of commodities forces companies to accept the risk of fluctuations affecting raw material acquisition and production, and mitigate risk or remove it from the supply chain (PWC, 2017). Integrating CE in sourcing and procurement risk management strategy provides, “a more predictable, long-term, cost-effective source for the energy or materials” (Lacy & Rutqvist, 2015, p. 36). Additionally, advances in raw material innovation fuel eco-design and feed CE loops across the supply chain. Examples of innovation include: a dissolving thread called Smart Stitch that aids in recycling, Crop-A-Porter that makes fabric out of crop waste, a compostable clothing called Algae Apparel, and a design that uses mycelium to grow clothing (Sandvik, 2017).

Product Life Extension

Product Life Extension (PLE) lengthens a product’s useful lifecycle by generating revenue through longevity instead of volume; an example is selling a product second hand, or repurposing it until worn out. Manufacturers leverage human behavior and consumerism in the form of trade-in or buy back models. Additionally, companies help customers extend PLE with repairs, maintenance services, care guidelines, and DIY repair alternatives.

Policy and Regulations

Governments and regulators, particularly in Europe, are rallying to enable the CE. Broad changes include eco-design directives, green public procurement, extended producer responsibility, and taxation mechanisms. Promoting longer product lifetimes, defining sustainable performance criteria, a standard of labeling, metrics to define circularity, and avoiding hazardous substances progress the CE model through legislation and compliance.

Sustainable thought leader Walter Stahel suggests leveraging policy and taxation, “That legal considerations, especially taxing systems have to be reconsidered. If we had ‘sustainable taxation’, a tax on non-renewable resources and no tax on renewable resources, where human labor is a renewable resource, it would give activities of the circular economy an immediate incentive” (Sustainable Taxation, n.d.). As depicted in Figure 1, the smallest loops create the highest social benefits because they are labor intensive (Ellen MacArthur Foundation, 2017). Another key component of sustainable taxation is value added tax (VAT). Since all the activities of a circular economy inherently maintain value, actors who adapt CE approaches should not have to pay VAT. “This concept has been accepted in principle by the UK treasury and several other European countries, such as in Scandinavia, where there is 25% VAT. By not levying VAT on repairs, re-marketing or re-manufacturing of goods, you would create a clear signal to business that it’s beneficial to get involved in the sustainable activities of the circular economy” (Stahel, 2013, p. 2).

Certifications play a major role in CE because they validate the quality and sustainability in the complex, multi-tier process of a fabric (Sandvik, 2017). Although a single commodity is certified, there are factors that influence the total life cycle assessment of feedstock. Several organizations including the Global Organic Textile Standard, Oeko-Tex, Made in Green, and the Better Cotton Initiative define high-level requirements in environmental criteria, technical quality, and minimal social criteria in the supply chain of organic textiles’ to be certified. Standardizing disclosures and labels for eco-compliant products facilitate trust between actors upstream in raw material acquisition through production, and downstream to distributors, retailers, and consumers (Rosa, 2016). Alignment of power and incentives between actors is critical to improve cross-cycle and cross-sector performance.

Sharing Platform and Product as a Service

The sharing platform business model simplifies ownership through channels of renting, sharing, swapping, lending, gifting, or bartering of resources and allows businesses to expand into new markets (Lacy & Rutqvist, 2015). Consumers choose sharing platforms for convenience, diversity, lower price, and better product or service quality (Lacy & Rutqvist, 2015). The product-as-a-service (PaaS) model offers an alternative for products with high costs and high operating costs where consumers are users not owners. PaaS user adoption influences include infrequent use, lack of capacity, and unaffordability. Product design and quality are critical to performance because “quality degradation, short lifespan, low utilization rate and low recycling or return can directly impact a company`s bottom line” (Lacy & Rutqvist, 2015, p. 103).

 Changes in Human Behavior

Customer behavior is evolving and demand is increasing for sustainable and responsible products. Manufacturing quality products coupled with access to new CE business models transforms the perception of clothing as a disposable item to being a durable product as described in Figure 3, ‘Customer Personas and Access Model Types in a New Textiles Economy’ (Ellen MacArthur Foundation, 2017). Shifting the consumption of fast fashion to purchasing green garments, while increasing garment lifecycle and the number of wears, could be the most powerful way to capture value, reduce pressure on resources, and decrease negative impacts. For example, if the number of times a garment is worn is doubled, on average GHG emissions would be 44% lower (Ellen MacArthur Foundation, 2017).

Figure 3: Customer Personas and Access Model Types in a New Textiles Economy (Ellen MacArthur Foundation, 2017)

Collaborative Supply Chains

Adopting a circular model is gaining momentum as actors across the supply chain agree to share the cost and benefits of innovation and product design (Lacy & Rutqvist, 2015). To optimize material flows, supply chain actors must improve how they trace material flows, which includes in-depth information sharing, often times with competitive overlap that includes design, pricing, costs, volumes, lead times, and supplier terms. The Higg Index is a “self-assessment tool that empowers brands, retailers and facilities of all sizes, at every stage in their sustainability journey, to measure their environmental and social and labor impacts and identify areas for improvement” (Sustainable Apparel Coalition, 2018). “Using the Higg Index is the most adapted and reliable way to measure textile value chains, manage their impact and to finally create a common language on sustainability practice” (Sustainable Apparel Coalition, 2018).

Circular Approaches: Moving Forward or Far Away?

The Ellen MacArthur foundation estimates that “CE could deliver $1.8 trillion for Europe by 2030” (2017) with “savings in materials alone could exceed $1 trillion a year by 2025”. Although the CE approaches outlined herein are beneficial, when applied separately in a global trading environment, they are insufficient to move forward because they address only certain parts of the transition, products, process, policy, or actor in the supply chain. Largely, the textile and clothing system is directed by compliance rather than innovation, with exceptions like Levi’s, Nike, and Patagonia to name a few. Many companies try to be “less bad” by optimizing the wrong system, using less input, less energy, and less hazardous materials, striving for eco-efficiency (Braungart & McDonough, 2002).

Consumerism and mass-production create bad demand and economic signal inputs that do not encourage efficient resource use, pollution mitigation, or space for CE innovation. In developing countries, mass production of cheap, fast fashion creates Gross Domestic Product and influences the quality of life for citizens. Globalization and cost competitiveness force production economies of scale, while unethical labor conditions and unsustainable business practices are necessary to compete. Developing countries lack strict standards, environmental laws, and institutions to reinforce sustainable measures. So, the traditional linear economy still has many economic advantages for actors because businesses can still externalize the cost of risk, non-compliance, and waste (Lacy & Rutqvist, 2015).

There are two key challenges: maintaining the quality of resources and keeping ownership rights to high-quality resources (Franco, 2017). Secondly, controlling the return flow and maximizing the quality of recovered resources through improving waste separation, inspection, processing and refining. For example in downcycling, fibres are recovered into materials of lower quality. At some point, fibres cannot be further cascaded and retire to a landfill (Franco, 2017). Downcycling is therefore only a mitigating factor. Product design, raw material innovation, and cooperation across the supply chain is critical for progress.

Other challenges that delay the scale and adoption of CE include insufficient skills and investment in circular product design and production that could facilitate greater re-use, remanufacture, repair and recycling (Anderson, 2016). There is an insufficient investment in the CE recycling and recovery infrastructure, which further propagates a lock-in linear mindset. Scale economies for PaaS, sharing platforms, production and recovery technologies are still comparatively immature to alternatives (Lacy & Rutqvist, 2015).

Current policies do not promote widespread end-to-end adoption of CE, slowing and closing resource flows. There are weaknesses in policy compliance in bioenergy and waste management. Potential policy actions include economic incentives, targeted and increased funding, efforts to engage and link actors across the supply chain. Collaborative supply chains have limited information, and lack no-brainer economic incentives to encourage repair and reuse (Gam, Cao, Farr, & Heine, 2008). Other policy improvements include taxes on aggregates of unsustainable materials and products, CO2 and waste disposal taxes, and landfill taxes.

Conclusion

To disrupt the current linear process for clothing, new models to access and maintain clothes are essential. Economic opportunities already exist for these approaches, and are achievable through refocused marketing, scaling sharing models, making higher quality and durability more attractive, and increasing clothing utilization further through brand commitments and policy (Sandvik, 2017).

References

Anderson, R. (2016). The Firms Planning on Making Less and Recycling More. Retrieved March 18, 2018, from http://www.bbc.com/news/business-35755492

Braungart, M., & McDonough, W. (2002). Cradle to Cradle. New York: New Point Press.

Cardoso, A. (2013). Life Cycle Assessment of Two Textile Products: Wool and Cotton. Universidade Do Porto, Environmental Engineering. U.Porto.

De Vries, B. (2013). Sustainability Science. Cambridge: Cambridge University Press.

Ellen MacArthur Foundation. (2015, December 9). Towards a Circular Economy: Business Rationale for an Accelerated Transition. Retrieved March 19, 2018, from https://www.ellenmacarthurfoundation.org/assets/downloads/TCE_Ellen-MacArthur-Foundation_9-Dec-2015.pdf

Ellen MacArthur Foundation. (2017, January 12). A New Textiles Economy: Redesigning Fashion’s Future. Retrieved March 20, 2018, from https://www.ellenmacarthurfoundation.org/publications/a-new-textiles-economy-redesigning-fashions-future

Franco, M. (2017). Circular Economy at the Micro Level: Dynamic View of Incumbents’ Struggles and Challenges in the Textile Industry. Journal of Cleaner Production, 168, 833-845.

Gam, H., Cao, H., Farr, C., & Heine, L. (2008). C2CAD: A Sustainable Apparel Design and Production Model. International Journal of Clothing Science and Technology, 21(4), 166-179.

Harrington, L. (2013, September). Fashion Unleashed: The Agile Fashion Supply Chain. DHL Supply Chain.

Lacy, P., & Rutqvist, J. (2015). Waste to Wealth: The Circular Economy Advantage . New York: Palgrave Macmillan. Retrieved 2018, from https://www.forbes.com/sites/tomiogeron/2013/01/23/airbnb-and-the-unstoppable-rise-of-the-share-economy/#729b2ccfaae3

Maia, L., Alves, A., & Leao, C. (2013). Sustainable Work Environment with Lean Production in Textile and Clothing Industry. International Journal of Industrial Engineering and Management , 4(3), 183-190.

Marino, A., & Pariso, P. (2016, May). From Linear Economy to Circular Economy: Research Agenda. International Journal of Research in Economics and Social Sciences , 6(5), 270-281.

PWC. (2017). Spinning Around: Taking Control in a Circular Economy. Retrieved March 22, 2018, from https://www.pwc.com/gx/en/sustainability/assets/taking-control-in-a-circular-economy.pdf

Rosa, A. (2016). Circular Economy in the Clothing Industry: Challenges and Strategies. KTH Industrial Engineering and Management.

Rydberg, A. (2016). Circular Economy Business Models in the Clothing Industry. Uppsala University, Department of Earth Sciences.

Sandvik, I. (2017). Applying Circular Economy to the Fashion Industry in Scandinavia Through Textile-to-Textile Recycling. Monash University, School of Social Science.

Stahel, W. (2013, July). The Circular Economy. Retrieved from http://www.makingitmagazine.net/?p=6793

Stahel, W. (n.d.). Sustainable Taxation. Retrieved March 27, 2018, from http://www.progressiveeconomy.eu/content/sustainable-taxation

Sustainable Apparel Coalition. (2018, March 27). Retrieved from The Higg Index: https://apparelcoalition.org/the-higg-index/

Sustainable Brands. (2015, September 25). NIKE Commits to 100% Renewables, Partners With MIT Climate CoLab on Materials Innovation. Retrieved from http://www.sustainablebrands.com/news_and_views/products_design/sustainable_brands/nike_commits_100_renewables_partners_mit_climate_

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Cradle-to-Cradle System Design: reflections by Dr. Michael Braungart

 

Wanted to share insights from Dr. Michael Braungart on circular economy. My focus this Spring in post-graduate work is centered on application of circular economy theory in supply chain optimization.

The passage below is from ICR (2007) 7:152–156 – DOI 10.1007/s12146-007-0020-2 – © ICR 2007 Published online: 28 November 2007.

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“Our current ‘eco-efficient’ view of sustainability sees materials flowing through the system in one direction only – from input to an output that is either consumed or disposed of in the form of waste. Eco-efficient techniques may be able to minimize the volume, velocity and toxicity of these material flows, but they cannot alter its linear progression ‘from cradle to grave’. While some materials are recycled, this recycling is difficult and brings added costs. The result of such recycling is actually downcycling: a downgrade in material quality which limits its future usability. We need an ‘eco-effective’ perspective to replace this limited and limiting agenda. In eco-effective industrial systems, the material intensity per service unit or ‘waste’ produced by each individual element is irrelevant as long as the materials entering the system are perpetually maintained as usable resources. For example, if the trimmings from the production of textile garments are composed in such a way that they become nutrients for ecological systems, then it doesn’t matter that they are not included in the saleable product. They are not ‘waste’. Even if the material intensity per service unit of the textile mill is astronomically high, it could still be highly eco-effective if its trimmings become productive resources for natural systems. The goal is not to minimize the cradle-to-grave flow of materials, but to generate cyclical cradle-to-cradle ‘metabolic cycles’ that enable materials to maintain their status as resources and accumulate intelligence over time.

Instead of downcycling this approach is all about upcycling. It doesn’t seek to eliminate waste or produce zero emissions. Instead it focuses on maintaining (or upgrading) resource quality and productivity through many cycles of use (and in doing so, it achieves ‘zero waste’ along the way). The difference between the two strategies of cradle-to-grave and cradle-to-cradle are very important. Strategies focused on achieving ‘zero waste’ do not create sustainable cradle-to-cradle cycles. But eco-efficient cradle-to-cradle cycles do achieve zero waste. How they achieve their goals is also different. ‘Zero waste’ cradle-to-grave strategies emphasize volume minimization, reduced consumption, design for repair and durability and design for recycling and reduced toxicity. On the other hand cradle-tocradle strategies design products and industrial processes so that every single one of their ‘outputs’ becomes a nutrient for another system – designed to be re-used – to create a perpetual cycle where resources are either maintained or ‘upcycled’.”.

Blockchain: Revolutionizing the Global Supply Chain by Building Trust and Transparency

Introduction

The history of Supply Chain Management has evolved since its’ roots in the early 1900s. From improving labor processes of basic material handling and freight transportation, to more sophisticated approaches of balancing cost and efficiency trade-offs, the concept of a supply chain is no longer siloed. It requires integration of supplier-customer relationships, process synchronization, and data harmonization in a complex, dynamic network that is susceptible to vulnerabilities in a global environment. Critical processes to this relationship include real-time communication, collaboration, trust, and transparency that yield mutually beneficial outcomes and competitive advantage. In today’s world, there is a growing prevalence in leading firms advancing toward the adoption, development and implementation of Blockchain technology as a backbone of business operations. This case dives a bit deeper into Blockchain, a novel technology with the strong potential to revolutionize the Global Supply Chain. The goal of this analysis is to discuss: 1) the key technical and economic aspects of Blockchain, 2) the current Blockchain innovators, barriers, and obstacles to Marketplace acceptance, 3) the business case for Blockchain, and 4) future applications and implications of Blockchain technology.

Click here to read the research: Blockchain_Revolutionizing the Global Supply Chain by Building Trust and Transparency

Operations or Supply Chain Excellence?

I’m sharing great insights from Innovation Enterprise via Micha Veen who explains simple tips to master supply chain excellence pinned Operational Innovation.

Source: A Refreshing Innovative Approach To Supply Chain Excellence | Articles | Chief Supply Chain Officer | Innovation Enterprise 

Operational or Supply Chain Excellence has been one of the buzzwords that is often heard around senior Supply Chain Execs. However, is excellence the right terminology, or do we need to rename ‘excellence’? Due to globalization, continuous creation of new small ‘global’ businesses that can compete with established organizations, leading supply chain organizations have started to look beyond ‘operational excellence’, best-in-class, benchmark data and industry metrics, towards using a combination of their own internal and tailored external relevant data to continuously review, assess, and adopt evolving leading-edge processes, technologies and behaviors to stay ahead in this ever increasing competitive business landscape. This new approach, named Operational Innovation, has become an effective methodology to deliver transformational impact through the following elements…

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Innovative solution design

Instead of spending a lot of time and effort in designing the optimal operational and supply chain solutions, successful organizations focus on creating a solid solution foundation, which is constantly reviewed and improved with cross functional teams to deliver cross-divisional, fit-for-purpose solutions.

Close collaboration

Instead of phased hand-offs between subject matter experts, technology specialists, operational teams, sales, finance, etc., leading innovative supply chain solutions should be created through continuous close collaboration with all impacted process participants at every stage of the supply chain journey.

Use of Robotics and Blockchain Technologies

A recent article (How will manufacturing robotics change in 2017) describes how robotics will change the industry as early as 2017. The article describes how by 2019, 35% of leading companies in logistics, health, utilities, and resources will start implementing robotics to automate their operations. Additionally, supply chain blockchain technology has started to be utilized in supply chain organizations to deliver additional benefits. A recent article describes clearly the impact that Blockchain has on Supply Chain.

End-to-end Solution integration

The key to delivering true Supply Chain Innovation is the manner in which organizations integrate end-to-end processes, technologies, data, and internal vs. external organizational units. Due to the external focus on innovative technologies, many organizations are still only focused on technology integration, but leading businesses have started to explore how different cloud solutions can be integrated across their partners and customers, creating hybrid learning organizational models which go beyond the traditional joint venture organization models.

Continuously generate value

In supply chains it’s crucial to continuously generate value. Through the use of innovative technologies, solution partnerships, operational models, etc. leading supply chain organizations are known to continuously review, adapt and improve their supply chain environment to deliver operational innovation. It allows supply chains to continuously deliver ‘new and improved’ excellence.

In today’s world, Supply Chain Excellence is not enough. There is no ‘end-station’. It’s critical for supply chain organizations to adopt an ongoing innovation journey, which requires people with the right mindset, experience levels, attitude and curiosity to deliver supply chain innovation….

 

Blockchain: The Best Way to Decentralize Supply Chains

 

This is a recent article written by a brilliant colleague Harry Goodnight. Great insights and perspectives on blockchain technology and why decentralization is a good thing for modern supply chains.

Source: http://www.supplychaindive.com/news/blockchain-Sweetbridge-decentralization-supply-chain-management/504362/

In business and economics, decentralization often refers to the ability to participate in a market and exchange value between peers without the interference of a third-party intermediary who most likely controls and restricts barriers of entry. As Ethereum co-founder Vitalik Buterin explains in his blog post “The Meaning of Decentralization,” blockchain is politically and architecturally decentralized, meaning no entity one controls it and there’s no central point of failure in its infrastructure. In this way, a decentralized supply chain would allow for a frictionless vehicle of business-to-business value exchange amongst even the smallest players in the industry.

Decentralization is defined as the transfer of power away from a central location or authority. As a concept, it is not new; as a business model, however, it is a powerful idea. Some sociologists claim that decentralization and centralization theories have actually been occurring in cycles for the last 4,000 years, causing the rise and subsequent fall of ruling states and empires. Throughout history, the core theory behind decentralization has remained the same: dispersing power from authorities and empowering smaller, individual entities with the ability to act in their own self-interest.

Why decentralization is necessary for modern supply chains

This is especially necessary in the supply chain industry, which has historically suffered from a number of issues that hinder its efficiency. Its main roadblock is that current supply chains are unable to become agile, which poses a significant problem in a market in which they must be able to change their configurations quickly and continually to meet the constantly-changing dynamics of supply and demand. Another major disadvantage is that methods of communication tend to vary greatly, with some companies still relying on manual paperwork. As a result, data storage becomes locked away in in proprietary systems that don’t allow for collaboration.

Supply chain companies also tend to face cultural and organizational issues, such as executing operating plans due to corporate goals, board restrictions and the competitive nature of the market. Consequently, companies have revoked social contracts, mistreated skilled laborers and underutilized their professional talent assets.

This mismanagement has serious financial consequences: for instance, $4.2 trillion is locked up in net working capital in today’s supply chains. By allowing today’s virtual supply chains to break from the company-centric, server-based environments in which they currently find themselves, they will become less brittle, more scalable and fully leverage the underutilized skills and assets available in modern-day business networks. Even a 1% improvement in Invoice-to-Cash cycle times would immediately return about $42 billion in cash to operations.

How can blockchain remedy the issues of centralization in supply chains?

When looking at its positive implications, blockchain is the most logical next step for supply chain managers and logistics providers. Blockchain was brought to the mainstream through cryptocurrencies like bitcoin and Ethereum. It creates an unchangeable digital ledger that provides a record of financial transactions in chronological order. This technology has been increasingly adapted to address gaping deficiencies in other fields, from education to voting to real estate. Through blockchain, massive networks of decentralized autonomous individuals and organizations can grow and operate seamlessly within a decentralized, distributed operating platform.

Blockchain also provides an efficient and viable solutions to the aforementioned hurdles that are restricting today’s supply chain. Specifically, it offers opportunities to synchronize processes that occur within supply networks, resulting in reduced Cost-of-Goods-Sold (COGS) and more cash freed from working capital.

The solution to many of these recurring issues in supply chain primarily involves people. By creating networks of skilled individuals and decentralized autonomous organizations, immense value can be brought to companies, supply chains, and customers. These networks align economic incentives so that everyone prospers, based on their contributions of time, skill, and intellectual property. These contributions are monitored and administered through outcome-based smart contracts on the blockchain. This new vision of decentralization has the potential to radically transform the supply chain space.

The world’s most valuable resource is DATA

 

Source: The world’s most valuable resource is no longer oil, but data

A NEW commodity spawns a lucrative, fast-growing industry, prompting antitrust regulators to step in to restrain those who control its flow. A century ago, the resource in question was oil. Now similar concerns are being raised by the giants that deal in data, the oil of the digital era. These titans—Alphabet (Google’s parent company), Amazon, Apple, Facebook and Microsoft—look unstoppable. They are the five most valuable listed firms in the world. Their profits are surging: they collectively racked up over $25bn in net profit in the first quarter of 2017. Amazon captures half of all dollars spent online in America. Google and Facebook accounted for almost all the revenue growth in digital advertising in America last year.

Such dominance has prompted calls for the tech giants to be broken up, as Standard Oil was in the early 20th century. This newspaper has argued against such drastic action in the past. Size alone is not a crime. The giants’ success has benefited consumers. Few want to live without Google’s search engine, Amazon’s one-day delivery or Facebook’s newsfeed. Nor do these firms raise the alarm when standard antitrust tests are applied. Far from gouging consumers, many of their services are free (users pay, in effect, by handing over yet more data). Take account of offline rivals, and their market shares look less worrying. And the emergence of upstarts like Snapchat suggests that new entrants can still make waves.

But there is cause for concern. Internet companies’ control of data gives them enormous power. Old ways of thinking about competition, devised in the era of oil, look outdated in what has come to be called the “data economy”. A new approach is needed.

Quantity has a quality all its own

What has changed? Smartphones and the internet have made data abundant, ubiquitous and far more valuable. Whether you are going for a run, watching TV or even just sitting in traffic, virtually every activity creates a digital trace—more raw material for the data distilleries. As devices from watches to cars connect to the internet, the volume is increasing: some estimate that a self-driving car will generate 100 gigabytes per second. Meanwhile, artificial-intelligence (AI) techniques such as machine learning extract more value from data. Algorithms can predict when a customer is ready to buy, a jet-engine needs servicing or a person is at risk of a disease. Industrial giants such as GE and Siemens now sell themselves as data firms.

This abundance of data changes the nature of competition. Technology giants have always benefited from network effects: the more users Facebook signs up, the more attractive signing up becomes for others. With data there are extra network effects. By collecting more data, a firm has more scope to improve its products, which attracts more users, generating even more data, and so on. The more data Tesla gathers from its self-driving cars, the better it can make them at driving themselves—part of the reason the firm, which sold only 25,000 cars in the first quarter, is now worth more than GM, which sold 2.3m. Vast pools of data can thus act as protective moats.

Access to data also protects companies from rivals in another way. The case for being sanguine about competition in the tech industry rests on the potential for incumbents to be blindsided by a startup in a garage or an unexpected technological shift. But both are less likely in the data age. The giants’ surveillance systems span the entire economy: Google can see what people search for, Facebook what they share, Amazon what they buy. They own app stores and operating systems, and rent out computing power to startups. They have a “God’s eye view” of activities in their own markets and beyond. They can see when a new product or service gains traction, allowing them to copy it or simply buy the upstart before it becomes too great a threat. Many think Facebook’s $22bn purchase in 2014 of WhatsApp, a messaging app with fewer than 60 employees, falls into this category of “shoot-out acquisitions” that eliminate potential rivals. By providing barriers to entry and early-warning systems, data can stifle competition.

Who ya gonna call, trustbusters?

The nature of data makes the antitrust remedies of the past less useful. Breaking up a firm like Google into five Googlets would not stop network effects from reasserting themselves: in time, one of them would become dominant again. A radical rethink is required—and as the outlines of a new approach start to become apparent, two ideas stand out.

The first is that antitrust authorities need to move from the industrial era into the 21st century. When considering a merger, for example, they have traditionally used size to determine when to intervene. They now need to take into account the extent of firms’ data assets when assessing the impact of deals. The purchase price could also be a signal that an incumbent is buying a nascent threat. On these measures, Facebook’s willingness to pay so much for WhatsApp, which had no revenue to speak of, would have raised red flags. Trustbusters must also become more data-savvy in their analysis of market dynamics, for example by using simulations to hunt for algorithms colluding over prices or to determine how best to promote competition.

The second principle is to loosen the grip that providers of online services have over data and give more control to those who supply them. More transparency would help: companies could be forced to reveal to consumers what information they hold and how much money they make from it. Governments could encourage the emergence of new services by opening up more of their own data vaults or managing crucial parts of the data economy as public infrastructure, as India does with its digital-identity system, Aadhaar. They could also mandate the sharing of certain kinds of data, with users’ consent—an approach Europe is taking in financial services by requiring banks to make customers’ data accessible to third parties.

Rebooting antitrust for the information age will not be easy. It will entail new risks: more data sharing, for instance, could threaten privacy. But if governments don’t want a data economy dominated by a few giants, they will need to act soon.

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Blockchain Will Do to the Financial System What the Internet Did to Media

 

Source: The Blockchain Will Do to the Financial System What the Internet Did to Media

Even years into the deployment of the internet, many believed that it was still a fad. Of course, the internet has since become a major influence on our lives, from how we buy goods and services, to the ways we socialize with friends, to the Arab Spring, to the 2016 U.S. presidential election. Yet, in the 1990s, the mainstream press scoffed when Nicholas Negroponte predicted that most of us would soon be reading our news online rather than from a newspaper.

Fast forward two decades: Will we soon be seeing a similar impact from cryptocurrencies and blockchains? There are certainly many parallels. Like the internet, cryptocurrencies such as Bitcoin are driven by advances in core technologies along with a new, open architecture — the Bitcoin blockchain. Like the internet, this technology is designed to be decentralized, with “layers,” where each layer is defined by an interoperable open protocol on top of which companies, as well as individuals, can build products and services.

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Like the internet, in the early stages of development there are many competing technologies, so it’s important to specify which blockchain you’re talking about. And, like the internet, blockchain technology is strongest when everyone is using the same network, so in the future we might all be talking about “the” blockchain.

The internet and its layers took decades to develop, with each technical layer unlocking an explosion of creative and entrepreneurial activity. Early on, Ethernet standardized the way in which computers transmitted bits over wires, and companies such as 3Com were able to build empires on their network switching products. The TCP/IP protocol was used to address and control how packets of data were routed between computers. Cisco built products like network routers, capitalizing on that protocol, and by March 2000 Cisco was the most valuable company in the world. In 1989 Tim Berners-Lee developed HTTP, another open, permissionless protocol, and the web enabled businesses such as eBay, Google, and Amazon.

The Killer App for Blockchains

But here’s one major difference: The early internet was noncommercial, developed initially through defense funding and used primarily to connect research institutions and universities. It wasn’t designed to make money, but rather to develop the most robust and effective way to build a network. This initial lack of commercial players and interests was critical — it allowed the formation of a network architecture that shared resources in a way that would not have occurred in a market-driven system.

The “killer app” for the early internet was email; it’s what drove adoption and strengthened the network. Bitcoin is the killer app for the blockchain. Bitcoin drives adoption of its underlying blockchain, and its strong technical community and robust code review process make it the most secure and reliable of the various blockchains. Like email, it’s likely that some form of Bitcoin will persist. But the blockchain will also support a variety of other applications, including smart contracts, asset registries, and many new types of transactions that will go beyond financial and legal uses.

We might best understand Bitcoin as a microcosm of how a new, decentralized, and automated financial system could work. While its current capabilities are still limited (for example, there’s a low transaction volume when compared to conventional payment systems), it offers a compelling vision of a possible future because the code describes both a regulatory and an economic system. For example, transactions must satisfy certain rules before they can be accepted into the Bitcoin blockchain. Instead of writing rules and appointing a regulator to monitor for breaches, which is how the current financial system works, Bitcoin’s code sets the rules and the network checks for compliance. If a transaction breaks the rules (for example, if the digital signatures don’t tally), it is rejected by the network. Even Bitcoin’s “monetary policy” is written into its code: New money is issued every 10 minutes, and the supply is limited so there will only ever be 21 million Bitcoins, a hard money rule similar to the gold standard (i.e., a system in which the money supply is fixed to a commodity and not determined by government).

This is not to say the choices Bitcoin currently offers are perfect. In fact, many economists disagree with Bitcoin’s hard money rule, and lawyers argue that regulation through code alone is inflexible and doesn’t permit any role for useful discretion. What cannot be disputed, however, is that Bitcoin is real, and it works. People ascribe real economic value to Bitcoins. “Miners,” who maintain the Bitcoin blockchain, and “wallet providers,” who write the software people use to transact in Bitcoin, follow the rules without exception. Its blockchain has remained resilient to attack, and it supports a robust, if basic, payment system. This opportunity to extend the use of the blockchain to remake the financial system unnerves and enthralls in equal measure.

Too Much Too Soon?

Unfortunately, the exuberance of fintech investors is way ahead of the development of the technology. We’re often seeing so-called blockchains that are not really innovative, but instead are merely databases, which have existed for decades, calling themselves blockchains to jump on the buzzword bandwagon.

There were many “pre-internet” players, for example telecom operators and cable companies trying to provide interactive multimedia over their networks, but none could generate enough traction to create names that you would remember. We may be seeing a similar trend for blockchain technology. Currently, the landscape is a combination of incumbent financial institutions making incremental improvements and new startups building on top of rapidly changing infrastructure, hoping that the quicksand will harden before they run out of runway.

In the case of cryptocurrencies, we’re seeing far more aggressive investments of venture capital than we did for the internet during similar early stages of development. This excessive interest by investors and businesses makes cryptocurrencies fundamentally different from the internet because they haven’t had several decades of relative obscurity where noncommercial researchers could fiddle, experiment, iterate on, and rethink the architecture. This is one reason why the work that we’re doing at the Digital Currency Initiative at the MIT Media Lab is so important: It is one of the few places a substantial effort is being made to work on the technology and infrastructure clear of financial interests and motivations. This is critical.

The existing financial system is very complex at the moment, and that complexity creates risk. A new decentralized financial system made possible with cryptocurrencies could be much simpler by removing layers of intermediation. It could help insure against risk, and by moving money in different ways could open up the possibility for different types of financial products. Cryptocurrencies could open up the financial system to people who are currently excluded, lower barriers to entry, and enable greater competition. Regulators could remake the financial system by rethinking the best way to achieve policy goals, without diluting standards. We could also have an opportunity to reduce systemic risk: Like users, regulators suffer from opacity. Research shows that making the system more transparent reduces intermediation chains and costs to users of the financial system.

The Takeaway

The primary use and even the values of the people using new technologies and infrastructure tend to change drastically as these technologies mature. This will certainly be true for blockchain technology.

Bitcoin was first created as a response to the 2008 financial crisis. The originating community had a strong libertarian and antiestablishment spin that, in many ways, was similar to the free-software culture, with its strong anticommercial values. However, it is likely that, just as Linux is now embedded in almost every kind of commercial application or service, many of the ultimate use cases of the blockchain could become standard fare for established players like large companies, governments, and central banks.

Similarly, many view blockchain technology and fintech as merely a new technology for delivery — maybe something akin to CD-ROMs. In fact, it is more likely to do to the financial system and regulation what the internet has done to media companies and advertising firms. Such a fundamental restructuring of a core part of the economy is a big challenge to incumbent firms that make their living from it. Preparing for these changes means investing in research and experimentation. Those who do so will be well placed to thrive in the new, emerging financial system.