Posts tagged innovation

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.

“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’.”

The Social Dilemma of Human Behavior & Sustainable Choices in the Fashion Supply Chain

Introduction

Although the premise of clothing characterizes a rudimentary need (Yawson, Armah, & Pappoe, 2009), the intricacies and system dynamics specific to the fashion industry’s supply chain are far from basic (Amed, Berg, Brantberg, & Hedrich, 2016). The current state of the fashion industry is challenging because factors contributing to its complexities are uncertain and constantly changing (Amed, Berg, Brantberg, & Hedrich, 2016). From the acquisition of raw materials, to manufacturing and distribution for purchase by the consumer, the fashion industry can influence sustainable practices across the global supply chain (Strahle & Muller, 2017).

Sustainability involves changing environmental dynamics that affect dimensions of ecology, economy, socio-politics, and human behavior (Joy, Sherry, Venkatesh, Wang, & Chan, 2012). Research shows an inherent dissension among some fashion consumers (McNeill & Moore, 2015), who “often share a concern for environmental issues even as they indulge in consumer patterns antithetical to ecological best practices” (Joy, Sherry, Venkatesh, Wang, & Chan, 2012). An emerging concept in industry is fast fashion, which refers to “low-cost clothing collections that mimic current luxury fashion trends and helps sate deeply held desires among young consumers in the industrialized world for luxury fashion, even as it embodies unsustainability” (Joy, Sherry, Venkatesh, Wang, & Chan, 2012).

Globalization and competition create increased financial and operational pressures in industry to reduce costs (Christopher, Lowson, & Peck, 2004). When paired with growth in human population (Strahle & Muller, 2017), scarcity of natural resources (De Vries, 2013), growth in industry (Amed, Berg, Brantberg, & Hedrich, 2016), advances in technology, consumer trends (Education Bureau, 2017), and human behavior in social dilemmas, the participants in a fashion supply chain may partake in unsustainable business practices (Chan & Wong, 2012). At the intersection of globalization, market competition, fast fashion (Joy, Sherry, Venkatesh, Wang, & Chan, 2012) and sustainability is the social dilemma of fashionable versus durable clothing. This analysis will explore the social dilemma of human behavior and sustainable choices in the fashion supply chain using the context of a pay-off matrix (De Vries, 2013).

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Social Dilemma Assessment

A social dilemma is where interdependent participants face a conflict between the maximizing personal gain and/or a collective interest (Dawes, 1980). As noted by Dr. Robyn Dawes (1980), leading psychologist and researcher, “public goods dilemmas occur when individuals can choose whether to contribute to a common pool that benefits both contributors and non-contributors alike, as long as enough choose to contribute”. Resource dilemmas are slightly different because individuals can decide how much to withdraw for personal use from a common pool that will only be maintained if withdrawals are kept to a minimum (Dawes, 1980). Public goods and resource dilemmas encompass “many of the most critical problems facing humanity, most notably those regarding resource shortages caused by overuse and failures to contribute to the common good” (Shankar & Pavitt, 2002). Moreover, research demonstrates that communication between participants has a significant effect on cooperation rates in these two types of social dilemmas (Shankar & Pavitt, 2002).

Overview of the Pay-Off Matrix

The pay-off matrix offers a way to analyze human behavior in situations of interdependence and conflict (Yawson, Armah, & Pappoe, 2009). As depicted in Figure 1, interdependent positions can range from virtuously cooperative, wherein a gain for one is a gain for the others, to a win-lose competitive position (Dawes, 1980). A decision to maximize individual gain is known as a defecting choice (Dawes, 1980), depicted as “you are the free rider” in Figure 1 (De Vries, 2013). Conversely, a win-win decision (De Vries, 2013) to maximize the gain of the collective is known as a cooperative choice (Dawes, 1980). Furthermore, “at any given decision point individuals receive higher payoffs for making selfish choices than they do making cooperative choices regardless of the choices made by those with whom they interact” (Weber, Kopelman, & Messick, 2004). The cost of the dilemma is that everyone involved receives a lower payoff by making a selfish choice (Dawes, 1980).

 

Figure 1: Pay-Off Matrix in a Social Dilemma (De Vries, 2013)

Pay-Off Matrix Participants in a Fashion Supply Chain

While enduring substantial growth over the past two decades (Strahle & Muller, 2017), the fashion industry has drastically evolved due to retail consolidation, globalization and e-commerce (Amed, Berg, Brantberg, & Hedrich, 2016). It is considered to be one of the most polluting industries in the world (Strahle & Muller, 2017). Industry and trading partners often request for participants to act sustainably (Strahle & Muller, 2017). Participants in a fashion supply chain include suppliers, manufacturers, distributors, retailers, and consumers (Strahle & Muller, 2017).

Theory and Influence in Consumer Fashion Decisions

Martin Christopher, thought leader in supply chain theory and best practice, defines fashion markets as typically exhibiting the following characteristics: short life cycles, high volatility, low predictability and high impulse purchasing (Christopher, Lowson, & Peck, 2004). A key concept in understanding the impulses of consumer purchasing is Maslow’s theory of human motivation (Chan & Wong, 2012). The theory classifies all human efforts as an attempt to fulfill one of five needs (Yawson, Armah, & Pappoe, 2009, p. 951). Figure 2 shows the hierarchical order in which these needs are connected, specifically in decisions that involve buying clothes.

Figure 2: Adaption of Maslow’s Motivational Theory in Fashion-Based Decisions (Yawson, Armah, & Pappoe, 2009, pp. 952-953)

Consumer decisions to purchase fashionable or durable clothing are also influenced by body type, age, family, lifestyle, peers, society, and consumer socialization (Yang, Song, & Song, 2017), or amount of disposable income that allows for considerations of quality and durability (Education Bureau, 2017). Other influences include values from one’s culture, environment, and value orientation (Education Bureau, 2017, p. 16). Lastly, frequency of wear and care instruction (McNeill & Moore, 2015) may influence the need for fashionable, inexpensive, and of lesser quality clothing versus durable clothing (Education Bureau, 2017, pp. 47-51).

Perspectives in the Pay-Off Matrix

Using the interdependent participants in a fashion supply chain, the over-arching perspectives and the decision to cooperate or defect in sustainable practices are shown below in Figure 3.

Figure 3: Pay-Off Matrix in a Fashion Supply Chain (De Vries, 2013)

Cooperate, Cooperate: A Win-Win Solution

When all participants cooperate, all are aligned in sustainable practices (Yang, Song, & Song, 2017). Because all parties benefit from this scenario, resolutions to the conflict are likely to be accepted voluntarily (Joy, Sherry, Venkatesh, Wang, & Chan, 2012). In this scenario, the supplier uses ethical growing conditions, labor practices, and pricing mechanisms that are passed onto the manufacturer (McNeill & Moore, 2015). The product is manufactured with considerations in sustainable design, efficient use of water and energy in textile process, chemical-free treatments, and lean waste reduction (Shankar & Pavitt, 2002). Distributors and retailers respect considerations of packaging waste, energy use in transportation and logistics (Christopher, Lowson, & Peck, 2004) and the ethical treatment of trading partners. Most importantly, the consumer uses sustainable participation across the supply chain to guide purchasing decisions. After purchase, the consumer limits the use of chemical detergents, water and energy use in care, early disposal and landfill waste, and shares the experience with others in his or her circle of influence (Yang, Song, & Song, 2017). The costs of quality and sustainable considerations are shared and accepted by each participant (Jung & Jin, 2014).

Cooperate, Defect

In this scenario, the consumer adheres to sustainable practices while the supplier, manufacturer, distributor, and retailer defect. The consumer receives a small positive individual outcome that is immediate and a large negative collective outcome (the depletion of future resources) is delayed (Shankar & Pavitt, 2002). The defectors receive a higher payoff in the short run no matter what decisions all other individuals make (Dawes, 1980). The result is that the consumers suffers or loses (Dawes, 1980). The defecting choice is known as the “dominant strategy” (Dawes, 1980). Because the dominant strategy produces less preferred outcomes, it is known to be a deficient outcome (Dawes, 1980). The costs of sustainable considerations are born by the consumer and common resource pools (Jung & Jin, 2014).

Defect, Cooperate

In this scenario, the consumer defects and is “a free-rider” (De Vries, 2013), while the supplier, manufacturer, distributor, and retailer adhere to sustainable practices. The consumer pursues individual short-term interest regardless of the impact to common resource pools in the long run (Chan & Wong, 2012). Common pool resources are available to all participants such as air, water, energy, and are increasingly in short supply (Shankar & Pavitt, 2002). When the consumer defects, resources are still available without any personal cost borne. The collective actively participates in aforesaid sustainable practices across the supply chain.

Defect, Defect: The Commons Tragedy

In this scenario called the commons tragedy (De Vries, 2013), all participants in the supply chain defect causing unsustainable outcomes in decision making as depicted in Figure 4. The concept echoes that “open-access common resource pools are exploited until the very last unit as long as someone else pays for it” (De Vries, 2013, p. 390). In a widely cited paper entitled The Tragedy of Commons (1968), the biologist Hardin suggested there is an inherent tendency amongst humans to overexploit such a shared, common, or collective resource” (De Vries, 2013, p. 390). Research related to the commons tragedy “emphasizes the role of factors that may predispose people to take risks in social dilemmas” including aforementioned theory and influence in consumer fashion decisions (Weber, Kopelman, & Messick, 2004). As Figure 4 suggests, participants may differ systematically in the way each arrives at the same decision to defect.

 

Figure 4: Unsustainable Outcomes of Decisions Made by Participants in the Fashion Supply Chain (Strahle & Muller, 2017)

Conclusion

Sustainability and ethical conduct has gained increasing importance in the fashion industry (Joy, Sherry, Venkatesh, Wang, & Chan, 2012). Many fashion companies are focusing on tactical efficiencies, implementing changes to their core operations “from shortening the length of the fashion cycle to integrating sustainable inno­vation into their core product design and manu­facturing processes (Amed, Berg, Brantberg, & Hedrich, 2016). However, although companies realize that trendy, affordable fashion raises sustainable concerns, the pressure to meet consumers demands is still influencing industry behavior (Amed, Berg, Brantberg, & Hedrich, 2016).  As demonstrated in this analysis, sustainable decisions in the textile and fashion industry can be controlled along the supply chain (Strahle & Muller, 2017). Specifically, “retailers are the link between the supplier and the consumers. They could be the ecological gatekeepers and help the relevant partners along the supply chains incorporate sustainability into the business” (Yang, Song, & Song, 2017). While the fashion supply chain and consumers continue to evolve in the progression of whether to make and/or consume fashionable or green products, the challenge to connect and meet “deeper elements of value, such as high ethical standards in sourcing, efficient use of materials, low-impact manufacturing, assembly, and distribution,” (Joy, Sherry, Venkatesh, Wang, & Chan, 2012) will remain challenging for decades to come.

References

Amed, I., Berg, A., Brantberg, L., & Hedrich, S. (2016, December). The State of Fashion. Retrieved October 29, 2017, from McKinsey & Company: https://www.mckinsey.com/industries/retail/our-insights/the-state-of-fashion

Chan, T., & Wong, C. (2012). The Consumption Side of Sustainable Fashion Supply Chain: Understanding Fashion Consumer Eco‐fashion Consumption Decision. Journal of Fashion Marketing and Management: An International Journal, 16(2), 193-212. doi:10.1108/13612021211222824

Christopher, M., Lowson, R., & Peck, H. (2004). Creating Agile Supply Chains in the Fashion Industry. International Journal of Retail Distribution Management, 32(8), 367-376. doi:10.1108/09590550410546188

Dawes, R. M. (1980). Social Dilemmas. Annual Review of Psychology, 31, 169-193.

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

Education Bureau. (2017, November 13). Consumer Behavior in Clothing Choices and Implications. Retrieved from www.hkedcity.net/res_data/edbltr-te/1-1000/…/2_Consumer_eng_Oct_2011.pdf

Joy, A., Sherry, J., Venkatesh, A., Wang, J., & Chan, R. (2012). Fast Fashion, Sustainability, and the Ethical Appeal of Luxury Brands. Fashion Theory, 16(3), 273-296. doi:10.2752/175174112X13340749707123

Jung, S., & Jin, B. (2014). A Theoretical Investigation of Slow Fashion: Sustainable Future of the Apparel Industry. (D. E. Kempen, Ed.) International Journal of Consumer Studies, 38(5), 510-519. doi:10.1111/ijcs.12127

McNeill, L., & Moore, R. (2015, May). Sustainable Fashion Consumption and the Fast Fashion Conundrum: Fashionable Consumers and Attitudes to Sustainability in Clothing Choice. International Journal of Consumer Studies, 39(3), 212-222. doi:10.1111/ijcs.12169

Shankar, A., & Pavitt, C. (2002, July). Resource and Public Goods Dilemmas: A New Issue for Communication Research. The Review of Communication, 251-272.

Social Dilemma. (n.d.). Retrieved November 7, 2017, from Wikipedia: https://en.wikipedia.org/wiki/Social_dilemma

Strahle, J., & Muller, V. (2017, October 30). Key Aspects of Sustainability in Fashion Retail. Retrieved from Springer Link: https://link.springer.com/chapter/10.1007/978-981-10-2440-5_2

Sustainable Apparel Coalition. (2017, November 7). The Higg Index. Retrieved from Sustainable Apparel Coalition: https://apparelcoalition.org/the-higg-index/

Weber, J. M., Kopelman, S., & Messick, D. M. (2004). A Conceptual Review of Decision Making in Social Dilemmas: Applying a Logic of Appropriateness. 8(3), pp. 281-307.

Yang, S., Song, Y., & Song, S. (2017). Sustainable Retailing in the Fashion Industry: A Systematic Literature Review. Sustainability, 9(7), 1266. doi:10.3390/su9071266

Yawson, D., Armah, F., & Pappoe, A. (2009, November). Enabling Sustainability: Hierarchical Need-Based Framework for Promoting Sustainable Data Infrastructure in Developing Countries. Sustainability, 946-959.

Moving Towards a Circular Economy

When you think about accelerating impacts and long-term solutions to current supply chain challenges that impact the 3P’s (people, planet and profit), we need to adopt and develop sustainable frameworks with a holistic life-cycle perspective. There is a ton of innovation happening in the CPG space (Levi’s, Unilever, PepsiCo, etc.)

Shifting from the current ‘take-make-waste’ linear model to the circular economy is critical for businesses to continue to thrive and meet society’s needs. Waste volumes are projected to increase from 1.3 to 2.2 billion tons by 2025, and with nearly 9 billion consumers on the planet including 3 billion new middle class consumers by 2030. The challenges of addressing waste and meeting increasing demand are unprecedented. Therefore it is imperative businesses continue to re-evaluate raw materials, design, manufacturing, consumption, and end of life to keep materials and products continuously flowing through closed loop systems.

How is your company innovating in product life cycle management from design and inception to sustainable product packaging? How are you personally adopting a sustainable mindset in your home, the daily choices you make as a consumer to move toward a circular economy? The bigger question is how are YOU INFLUENCING this change?

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

Going Green or Greenwashing?

 

Sustainable, much like organic, is used loosely as a marketing ploy. More often than not, countless companies use a concept called “green-washing.”Green washing is when a company, government or other group promotes green-based environmental initiatives or images but actually operates in a way that is damaging to the environment or in an opposite manner to the goal of the announced initiatives. This can also include misleading customers about the environmental benefits of a product through misleading advertising and unsubstantiated claims.

I use this greenwashing index greenwashingindex.com/about. There are more robust reporting initiatives, but this site is simple and give tips to the basic consumer on how to spot greenwashing and outlines the methodology behind the index. I highly recommend EcoVadis for larger organizations looking to integrate a desktop, cloud-based sustainable compliance solution. EcoVadis operates the first collaborative platform providing Supplier Sustainability Ratings for global supply chains. With a focus on maintaining quality and integrity, EcoVadis has managed to also grown quickly to meet this increasing need. Since its founding in 2007, EcoVadis has become a trusted partner for procurement organizations in more than 150 leading multinationals worldwide including Verizon, Nestlé, Johnson & Johnson, Heineken, Coca-Cola Enterprises, Nokia, L’Oréal, Bayer, Alcatel-Lucent, ING Bank, Air France-KLM, Centrica/British Gas, BASF, and Merck. Combining People, Process and Platform, EcoVadis has developed the industry-leading team, innovative technology, and a unique CSR assessment methodology that covers 150 purchasing categories, 110 countries, and 21 CSR indicators. More than 30,000 companies use EcoVadis to reduce risk, drive innovation and foster transparency and trust between trading partners. EcoVadis is driven by a diverse team of over 300 talented professionals from 40 nationalities committed to a real impact on the environmental and social practices of companies around the world.

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…

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….

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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.

8 Fundamentals for Achieving AI Success in the Supply Chain

Sharing point of view from  Greg Brady is the CEO and founder of One Network Enterprises, a global provider of a secure and scalable multi-party business network. For more information, contact the author at gbrady@onenetwork.com or visit http://www.onenetwork.com. Enjoy!

Source: 8 Fundamentals for Achieving AI Success in the Supply Chain – Supply Chain Management Review

There’s a lot of buzz and hype about artificial intelligence (AI) in supply chain management (SCM). That’s understandable given its potential. AI can offer a huge benefit to supply chain managers, but only if it is based on solid fundamentals that take into account the diverse and dynamic nature of today’s modern supply chains. More importantly, it needs to consider the availability of the timely and accurate data needed to make smart decisions.

Before addressing what AI can do, it is critical to first understand what it is. In the simplest terms, AI is intelligence exhibited by machines, or when machines mimic or can replace intelligent human behavior, such as problem solving or learning. In essence, AI is machines making decisions whether that is deciding which chess piece to move where, or how to adjust an order forecast based on changing demand.

Despite its benefits, when looked at through the lens of a supply chain executive, AI is relatively useless unless it’s able to add value to support better decision-making.

Why AI Hasn’t Delivered in SCM

In the race to use AI, many companies have made attempts to implement it, but the results have been disappointing. This is because typical SCM systems today:

  • Require armies of expensive planners
  • Run complex engines at each step in the process and at each node in the supply network
  • Are usually in conflict with other functions and/or partners
  • Miss huge opportunities hidden in the network because they are locally sub optimized
  • Work on stale data and thus promote bad decisions
  • Use dumbed-down, over-simplified problem models that do not relate to the real world

These SCM limitations have severely suppressed return on AI investments. For example, typical Retail/CPG supply chains still carry 60-75 days of inventory. The average service level in the store is about 96 percent, with promoted item service levels much lower at the 80 percent range. The Casual Dining segment on the other hand, carries around 12 – 15 days of inventory with relatively high waste and high cost-of-goods-sold. So, unless AI can make a significant impact on these metrics, it’s simply not delivering.

Key Requirements for AI in Supply Chain Management

Having worked with hundreds of supply chain executives, on dozens of software implementations, I’ve studied the AI issue a lot. What I have found is there are eight criteria that are required for a successful AI implementation. Miss one of these and you’ll be lucky to achieve mediocre outcomes, but when you meet them all, you can indeed achieve world class results. For the AI solution to offer optimal value in supply chain, it important to ensure the following:

1. Access to Real-Time Data 
To improve on traditional enterprise systems with older batch planning systems, new AI systems must eliminate the stale data problem. Most supply chains today attempt to execute plans using data that is days old, but this results in poor decision-making that sub-optimizes the supply chain, or requires manual user intervention to address. Without real-time information, an AI tool is just making bad decisions faster.

2. Access to Community (Multi-Party) Data 
The ability to access data outside of the enterprise or, more importantly, receive permission to see the data that is relevant to your trading community, must be made available to any type of AI, Deep Learning or Machine Learning algorithms.

Unless the AI tool can see the forward-most demand and downstream supply, and all relevant constraints and capacities in the supply chain, the results will be no better than that of a traditional planning system. Unfortunately, this lack of visibility and access to real-time, community data is the norm in over 99 percent of all supply chains. Needless to say, this must change for an AI tool to be successful.

3. Support for Network-Wide Objective Functions
The objective function, or primary goal, of the AI engine must be consumer service level at lowest possible cost. This is because the end-consumer is the only consumer of true finished goods products. If we ignore this fact, trading partners will not get the full value that comes from optimizing service levels and cost to serve, which is obviously important as increased consumer sell-through drives value for everyone.
A further enrichment of the decision algorithm should support enterprise level cross-customer allocation to address product scarcity issues and individual enterprise business policies. Thus, AI solutions must support global consumer-driven objectives even when faced with constraints within the supply chain.

4. Decision Process Must Be Incremental and Consider the Cost of Change
Re-planning and changing execution plans across a networked community in real time can create nervousness in the community. Constant change without weighing the cost of the change creates more costs than savings and reduces the ability to effectively execute. An AI tool must consider trade-offs in terms of cost of change against incremental benefits when making decisions.

5. Decision Process Must Be Continuous, Self-Learning and Self-Monitoring
Data in a multi-party, real-time network is always changing. Variability and latency is a recurring problem, and execution efficiency varies constantly. The AI system must be looking at the problem continuously, not just periodically, and should learn as it goes on how to best set its own policies to fine tune its abilities. Part of the learning process is to measure the effectiveness “analytics,” then apply what it has learned.

6. AI Engines Must Be Autonomous Decision-Making Engines
Significant value can only be achieved if the algorithm can not only make intelligent decisions but can also execute them. Furthermore, they need to execute not just within the enterprise but where appropriate, across trading partners. This requires your AI system and the underlying execution system to support multi-party execution workflows.

7. AI Engines Must Be Highly Scalable
For the supply chain to be optimized across an entire networked community of consumers to suppliers, the system must be able to process huge volumes of data very quickly. Large community supply chains can have millions if not hundreds of millions of stocking locations. AI solutions must be able to make smart decisions, fast, and on a massive scale.

8. Must Have a Way for Users to Engage with the System
AI should not operate in a “black box.” The UI must give users visibility to decision criteria, propagation impact, and enable them to understand issues that the AI system cannot solve. The users, regardless of type, must to be able to monitor and provide additional input to override AI decisions when necessary. However, the AI system must drive the system itself and only engage the user on an exception basis, or allow the user to add new information the AI may not know at the request of the user.

AI in the Real World Today

Sounds good in theory, but how does it work out in practice? Now that we have addressed the key fundamentals, let’s look at how some actual companies have achieved applying these criteria.

For instance, one of the major problems in Casual Dining is anticipating and meeting demand for the restaurants, corporate owned or franchised. This is especially important during Limited Time Offers (LTOs). Using the eight criteria outlined above, a global, casual dining company connected to a real-time, multi-party network, and was able to rapidly achieve their objective function – excellent customer service at the lowest cost.

The company constantly monitors Point-of-Sale (POS) data, and is using AI agents to recognize and predict consumption patterns of consumers. In addition, intelligent AI agents create the demand forecast and then compare it to the actual demand in real-time. When there is significant deviation, the agents make the decision to adjust the forecast, and additional agents adjust replenishments. They then propagate those adjustments across the supply chain to trading partners in real time at all times considering the cost of change and the propagation impact.

This drove a remarkable improvement in forecast accuracy. During promotions, the company achieved over 85 percent forecast accuracy at the store level and even higher at the DC level. This represents at least a 25 percent improvement over traditional approaches.

Intelligent agents also optimize restaurant orders autonomously by recognizing the impact of projected restaurant traffic trends and impact on LTOs and therefore the orders. The system runs on an exception basis but allows the managers to review the decision criteria and override orders where the managers may have local information such as inventory issues or local store traffic issues. This has resulted in much faster order placement and order accuracy of over 82 percent, which reduces both inventory and waste dramatically while increasing service levels to the consumer. This is a significant improvement to all other known implementations in the marketplace.

Because the algorithms are highly scalable, they are processing over 15 million stocking locations continuously throughout the day.

Prior to the AI-based, multi-party execution system, restaurant managers had to interact with nine different ordering systems and manually create their own orders based on general guidelines, rules of thumb, and spreadsheet-based or manual calculations.

With AI implemented on a sound foundation, this company can now anticipate, manage, and serve demand at the lowest possible cost. During LTO’s, when demand fluctuations would overwhelm a restaurant manager, intelligent agents monitor demand in real time, and autonomously orchestrate the supply chain to align supply with demand. Thus, the company can meet its goal and maintain high service levels while reducing cost to serve.

These are not isolated results. Also in the food marketplace, another CPG-Retail implementation achieved 99 percent in-stock, in-store, with 25 days of supply (DOS) across the supply chain.  The inventory results are less than half the standard DOS in this marketplace and 3 percent points higher in in-store in-stocks
AI-based solutions are being deployed at two large automotive tier one suppliers with results ranging from 16 – 40 percent reductions in inventory as well as significant reductions in expedited freight costs.

AI Delivers Value in SCM Today

As you can see, laying the proper groundwork for AI pays huge dividends. There’s no doubt that AI offers even greater promise in the future, but, as these results show, there are significant benefits and dramatic results waiting for companies that focus on the fundamentals and put AI to use today.

The beauty of AI-based solutions is that they learn and drive continuous improvement over time. They get more precise and sophisticated as they gather more data and more experience. The sooner you start, the better the results you’ll see in future, and the further ahead you will be. With the right AI solution in place, you can outpace your competitors today, and be well positioned for reaping even bigger rewards of AI’s promise tomorrow. ~Greg Brady

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