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J2 Innovations

j2innovations

Time

The collection is massive, covering 200 different innovations in categories such as transportation and consumer electronics, but you know the topic we’re most interested in is the food. Lots of interesting foods, appliances, and other culinary marvels ...

The Best Food Innovations of 2023, According to TIME

Yahoo

Canada

Central bank

The Bank of Canada published a staff note on decentralized finance (DeFi) on Oct. 17, assessing the innovations that made it popular and the challenges and risks associated with its use.

Canada central bank assesses innovations and challenges of DeFi

CoinTelegraph

Dubai

The latest innovations and trends in AI (artificial intelligence), the cloud, Web 3.0, cyber security, climate technology, urbanism, and more, are all here at the world's largest technology and ...

Dubai: 6 AI-powered innovations that will make life easier for residents

Khaleej Times

Japan

One of Asia's largest tech exhibitions is set to kick off near Tokyo on Tuesday. CEATEC 2023 will feature products that demonstrate the latest uses for artificial intelligence. About 680 companies ...

CEATEC 2023 to show the latest AI innovations

Offshore wind power

A leading offshore wind developer is calling for innovations in the realm of floating offshore wind that support biodiversity enhancement and help ensure that wind farms co-exist peacefully alongside other sea users. A leading offshore wind developer is ...

Floating offshore wind developer calls for innovations that support biodiversity

carbon-pulse.com

Reuters

Marketscategory Exclusive: Door maker PGT rebuffs $1.9 bln offer from Koch-backed Miter-sources October 10, 2023 Reuters, the news and media division of Thomson Reuters, is the world’s largest ...

PGT Innovations Inc

Technology

Harvard Business School

Faculty

Technological innovations have produced robots capable of jobs that, until recently, only humans could perform. The present research explores the psychology of "botsourcing"—the replacement of human jobs by robots—while examining how understanding ...

Technology & Innovation

Minneapolis

Advanced manufacturing

Keynote

Sutton will explain how innovations in medical technology are saving ever more lives as well as demonstrably improving the quality of life of patients. In particular, he will discuss the evolution of left atrial appendage closure devices in stroke ...

Keynote at Advanced Manufacturing Minneapolis Addresses Transformative Medical Innovations

MD&M East

The Motley Fool

The Motley Fool has a disclosure policy. PGT Innovations, Inc. (PGTI) Q1 2021 Earnings Call Transcript PGT Innovations, Inc. (PGTI) Q3 2020 Earnings Call Transcript PGT Innovations, Inc. (PGTI ...

Why PGT Innovations Stock Rocketed Higher This Week

This cutting-edge AI technology, known for its ability to autonomously generate text, images and other media, is redefining the paradigms of digital innovation. Generative AI holds the potential ...

917Ventures dives into generative AI innovations

cnnphilippines

195 Stories To Learn About Play To Earn

274 Stories To Learn About Software

Blue-collar jobs have already been impacted heavily by robotics and automation, neither of which require artificial intelligence. Now, recent AI innovations like ChatGPT seem poised to make white-collar jobs vulnerable, which were previously considered safe from automation. But will stop at white-collar positions, or will it threaten blue-collar jobs, as well? AI Blue-Collar Jobs Most at Risk From AI Most of the jobs generative AI can eliminate are white-collar roles. However, a few blue-collar fields could also be affected. Jobs that a robot can perform are at an especially high risk of being eliminated with AI integrations. Retail Sales and retail employees are already experiencing the impact of AI and automation in the job market. Over the past several years, more stores have replaced traditional checkout counters with automated self-service kiosks. Additionally, many people have shifted to online shopping, reducing the number of customers visiting physical storefronts. Self-service checkout at brick-and-mortar grocery stores. Some small shops have no employees, only a few associates who come in to restock the shelves. accounts for 55% of all transactions Unfortunately for people working in retail, most customer-facing roles will likely disappear in the near future. Restocking will likely become the only task requiring employees. AI could completely take over most checkout and customer service tasks. Manufacturing Automation has long been a part of the manufacturing industry, but AI could advance automation to the point of eliminating most hands-on jobs. Combining robotics and AI enables manufacturers to automate their assembly processes. Shifting to an employee-free workplace lets manufacturers operate around the clock and significantly reduce payroll, insurance, and injury compensation expenses. Plus, AI and robotics can often deliver higher-quality products since they don’t encounter human error. There are clear financial benefits for a fully automated manufacturing environment. AI will likely take over most assembly line jobs with the help of robotics. Most blue-collar positions in manufacturing will be technician roles, such as robot repair. Agriculture and Food Processing Farming is often not the first thing that comes to mind when people think of AI and robotics. However, there is huge potential for AI-assisted automation in the agriculture industry. Blue-collar jobs like food packaging and crop harvesting are often repetitive manual labor. These tasks are relatively easy to automate, especially now that AI can accurately recognize ripe or bruised fruit. For example, apple orchards in America’s Northwestern states are to pick apples. Some are flying drones that pick them from the air, while others are large robotic arms on a rolling base that drive through orchards. The robots use AI computer vision to identify ripe fruit and pluck apples from the trees with a robotic arm. starting to use AI-powered robots Farmers can completely automate their harvesting process with enough of these robots, eliminating thousands of blue-collar manual labor jobs. The same applies to food processing and packaging tasks, such as cleaning freshly harvested food. AI computer vision enables robots to perform virtually all food processing tasks, even with delicate foods like pastries and fruit. Is AI Replacing Employees or Filling Empty Jobs? It may sound alarming that AI is threatening blue-collar as well as white-collar jobs. However, is AI actually displacing human employees? It’s easy to imagine businesses firing people and replacing them with AI, but that may not be the reality of the situation. Many industries face major labor shortages today, including manufacturing, retail, and agriculture. This hurts productivity and leads to higher rates of stress and injuries among understaffed teams. These shortages are only getting worse, too. For instance, the National Association of Manufacturers estimates that the manufacturing industry by 2030. Additionally, studies show that fully in-person jobs, such as in retail, and lower employee satisfaction. Businesses have a hard time finding and keeping workers in these sectors. will be short 2.1 million employees have higher quit rates There is no lack of open blue-collar jobs. The problem is finding enough people to fill those roles. Employers often turn to AI and automation when labor shortages continue for an extended period. In these cases, integrating AI can improve the employee experience by reducing the workload on understaffed teams. Adapting to AI in the Workforce Is it possible for AI and employees to coexist peacefully in the blue-collar job market? Some may be surprised to hear that AI can be a helpful addition to the workforce in several ways. It may not be replacing employees so much as shifting humans’ jobs. One of the most common challenges in today’s workforce is a lack of skilled labor, specifically in blue-collar roles. Jobs are available, but not enough people have the technical skills to fill them. For example, there is a , which analysts expect to worsen over the next decade. shortage of at least 70,000 skilled HVAC technicians AI can help employers adapt blue-collar roles to close the skills gap. For instance, it can speed training processes to help employees gain the necessary skills in less time. This benefits everyone since more advanced abilities result in higher pay for blue-collar workers. Similarly, AI is creating more opportunities for blue-collar workers to move into higher-level jobs. AI is eliminating low-skill manual labor tasks, but that includes many positions people don’t typically enjoy anyway. The skills gap presents a great opportunity to reskill and upskill manual labor employees so they can graduate to more fulfilling, engaging careers. It’s also worth considering that AI is only good at a narrow niche of tasks. Humans will always : creativity, originality, and the ability to learn. Countless blue-collar jobs require those skills. have the edge in three core areas For instance, auto technicians need creativity to find the best possible solution to vehicles’ mechanical problems. Robotics technicians rely on their ability to learn to help them keep up with advancing technology. Landscapers exercise originality every day to create unique outdoor spaces. AI can’t replicate these skills on a human level. Even with the help of robotics, there will always be blue-collar jobs that require people. While AI automates mundane manual labor, humans get to focus on creativity-centered tasks. The physical nature of blue-collar work also makes it much more resilient to automation than most white-collar jobs. These careers will be more secure as AI’s presence in the workplace grows. Timeline for the Shift to AI in the Job Market How rapidly will AI change the blue-collar job market? It has advanced rapidly over the past few years, but its impact on the workplace is developing a bit slower. Employers need time and money to invest in AI tools and learn how to use them. Therefore, the transition will happen gradually. The first stage in most fields will be integrating AI tools and assistants. This is already occurring in many white-collar jobs. For example, software developers to automate many tasks, like idea generation or debugging. AI may start helping with employee training or managerial processes like shift scheduling in blue-collar fields. now use machine learning This first stage will occur over the next three to five years. Meanwhile, manufacturing specifically will see an increase in physical automation. For example, AI will begin taking over quality control inspections with the help of computer vision. Most of these integrations will fill empty jobs rather than replace employees. The shift to AI will take longer in some blue-collar fields than in others. For instance, manual labor in agriculture is highly threatened by AI, but the technology still needs much more development. As of 2023, agricultural employees are in the United States. among the least exposed to AI Agriculture has very little advanced electronic equipment, so adding AI will take longer than in fields like manufacturing. Engineers must develop outdoor-ready robotics equipment as well as AI models suited for agriculture. It could take another five to 10 years before tasks like harvesting are viable for automation. On the other end of the spectrum, retail jobs could begin seeing a decline due to AI within the next few years. Automation is already rapidly phasing out tasks like employee-serviced checkout lanes. The technology to automate retail is already present in the workplace, so these blue-collar jobs will experience the impact of AI soonest. Working Alongside AI Successfully It’s natural to be concerned about AI eliminating valuable jobs. Most blue-collar careers are at much lower risk of automation than white-collar jobs. However, AI poses a significant threat to manufacturing, retail, and agriculture careers. Luckily, it will mainly fill empty positions in these industries rather than displacing employees. AI can be a valuable assistant in many situations by reducing workloads and stress.

Is There an AI Threat to Blue-Collar Jobs?

FinTech, or financial technology, is a booming industry that uses cutting-edge technologies like artificial intelligence (AI), blockchain, data analytics and cloud computing to transform and improve financial processes and services. FinTech companies offer innovative solutions for various financial needs, such as payments, lending, investing, insurance, wealth management and more. They challenge the traditional financial institutions and create new markets and opportunities. However, FinTech companies also face significant challenges in terms of cost optimization, which is essential for their profitability and sustainability in a highly competitive environment. Cost optimization means strategically controlling and reducing expenses, improving financial efficiency and maximizing the return on investment. Inefficient operations can result in high costs, unhappy customers, low competitiveness and slow economic growth. In this article, we will examine the main types of costs that FinTech companies have to cope with, the strategies they can employ to optimize them and the future trends that will influence the cost optimization landscape. The Cost Structure of FinTech Companies FinTech companies have different types of costs depending on their business model, target market, product portfolio and technology stack. According to Toptal, some of the : main cost categories are These are the costs of running the essential backstage operations that keep the main business functions smooth and secure, such as handling transactions, assisting customers, updating systems, stopping fraudsters and managing risks. These costs are crucial for ensuring cost-effectiveness and customer satisfaction. Operational costs can vary depending on the volume and complexity of transactions, the quality and availability of customer service, the reliability and security of systems and the effectiveness of fraud and risk management. For instance, Revolut, a digital banking platform that delivers banking, payments, investing, budgeting and crypto services, has operational costs associated with handling millions of transactions per day, offering round-the-clock customer support in various languages, sustaining its cloud-based architecture and adhering to anti-money laundering rules. Operational Costs: These are the expenses related to the infrastructure that enables the delivery of FinTech services, such as cloud platforms, software licenses, hardware devices, cybersecurity tools and network connectivity. These costs are often high for FinTech companies as they invest heavily in innovation and security to provide seamless, reliable and secure financial services. Technology costs can vary depending on the type and scale of technology used, the level of customization and integration required, the frequency of updates and maintenance needed and the degree of protection against cyberattacks. For example, Stripe, a global payment platform that enables online businesses to accept and manage payments, has technology costs related to using cloud platforms such as AWS, software licenses such as Ruby on Rails, hardware devices such as card readers, cybersecurity tools such as Stripe Radar and network connectivity such as internet service providers. Technology Costs: These include salaries, benefits, training and recruitment expenses related to hiring and managing skilled talent. This type of costs is a key driver for FinTech companies as they need to attract and retain finance and technology experts who can develop, implement and maintain cutting-edge solutions. Human resource costs can vary depending on the number and quality of employees hired, the level of training and development provided, the turnover rate and retention rate of employees and the compensation structure and incentives offered. For instance, Acorns, an investment app that helps users save and invest their spare change, has human resource costs related to hiring and managing over 200 employees, providing online courses and training programs, offering referral bonuses and stock options and maintaining a low turnover rate. Human Resource Costs: These significant expenses are related to complying with the legal and regulatory requirements of the jurisdictions where FinTech companies operate. Regulatory costs include compliance monitoring systems, legal and regulatory filings, audits, fines and penalties. FinTech companies need to adhere to complex and evolving regulations that aim to protect consumers, ensure financial stability and prevent money laundering and terrorism financing. Regulatory costs can change based on the range and difficulty of regulations, the regularity and rigor of compliance audits performed, the quantity and harshness of fines or sanctions enforced and the assets and proficiency required to comply with regulations. As an example, to obey the insurance laws and regulations in different states, Coalition, an insurance app that provides cyber insurance and security tools for businesses, faces regulatory costs. These costs include using compliance monitoring systems such as Plaid, filing legal and regulatory reports with authorities, undergoing audits by regulators and insurers, adhering to regulations and dodging fines or penalties for non-compliance. Regulatory Costs: These are the less obvious expenses that can accumulate over time and impact the bottom line. Hidden costs include customer acquisition costs, system downtime costs, inefficiency costs, opportunity costs and reputation costs. FinTech companies need to be aware of these hidden costs and take measures to avoid or minimize them. Hidden costs can vary depending on the effectiveness of marketing strategies used to acquire customers, the availability and reliability of systems and services, the level of operational efficiency and productivity, the potential revenue lost due to missed opportunities and the impact of negative feedback or reviews on brand image and customer loyalty. Hidden Costs: For example, ZestFinance, a lending app that uses machine learning to provide fair and transparent credit, has hidden costs related to acquiring customers through online channels such as Google Ads or Facebook Ads, experiencing system downtime due to technical issues or cyberattacks, losing efficiency due to manual processes or errors, missing opportunities due to limited market reach or product range and damaging reputation due to customer complaints or lawsuits. The Cost Optimization Strategies for FinTech Companies FinTech companies have a range of options to fine-tune their costs and boost their bottom line. Some of the popular strategies are: These technologies can help FinTech companies improve their efficiency, enhance their customer experience and reduce their labor costs by automating repetitive tasks, streamlining workflows, providing personalized recommendations, detecting anomalies and optimizing decisions. For instance, FinTech companies can use automation to speed up transaction processing, AI to provide tailored financial advice and machine learning to prevent fraud losses. A recent example of a FinTech company that leverages automation, AI and machine learning is SpdLoad, a FinTech app development company that uses these technologies to create custom FinTech solutions for its clients. SpdLoad uses automation to reduce development time and costs, AI to provide data-driven insights and machine learning to improve user experience and security. Leverage automation, AI and machine learning: Lean principles are a set of practices that aim to streamline processes, eliminate waste, increase efficiency and deliver value to customers. By applying lean principles, FinTech companies can identify and remove non-value-added activities, reduce errors and defects, simplify complexity and increase agility. They can use lean principles to reduce paperwork, minimize rework, standardize procedures and empower employees. A recent example of a FinTech company that implements lean principles is Revolut, a digital banking platform that offers banking, payments, investing, budgeting and crypto services. Revolut applies lean principles to simplify its processes, automate its customer verification, outsource its card issuance, use cloud computing to scale its infrastructure and use data analytics to monitor its performance. Implement lean principles: FinTech startups can reduce expenses by outsourcing non-essential services to external providers. Specialized firms that focus on specific functions can offer accounting, legal, marketing or IT support at lower costs and/or higher quality. Outsourcing allows FinTechs to access top-tier capabilities without having to build in-house teams for non-core activities. This allows them to concentrate resources on their core products and innovations that drive value for customers. A recent example of a FinTech company that outsources non-core support activities is Square, a financial services company that provides payment solutions, point-of-sale systems, e-commerce platforms and business tools for small businesses. Square outsources some of its accounting, legal, marketing and IT services to external providers. For instance, Square uses Stripe as its payment processor, AWS as its cloud provider, Zendesk as its customer service platform and Mailchimp as its email marketing tool. Outsource non-core support activities: RegTech is a subset of FinTech that focuses on using technology to automate compliance processes. FinTech companies can adopt RegTech solutions to reduce their regulatory costs by automating data collection, reporting, validation, analysis and audit. RegTech solutions can also help FinTech companies stay updated with regulatory changes and avoid fines or penalties. FinTech companies can utilize RegTech solutions to monitor transactions for suspicious activity, generate reports for regulators and verify customer identity. An example of a FinTech company that adopts RegTech solutions is Coalition, an insurance app that provides cyber insurance and security tools for businesses. Coalition uses RegTech solutions to automate its compliance processes, such as data collection, reporting, validation, analysis and audit. Coalition also uses RegTech solutions to stay updated with regulatory changes and avoid fines or penalties. For example, the company uses Plaid to verify customer identity, Stripe Radar to monitor transactions for fraud and AWS Config to audit its cloud infrastructure. Adopt RegTech solutions: Using effective HR management practices, FinTech companies can optimize their human resource costs. These practices include remote work arrangements that can save on office space and travel expenses, continuous training programs that can improve employee skills and performance, strategic hiring processes that can find the best talent for the job and performance-based incentives that can motivate and reward employees. These practices can help FinTechs boost their productivity, enhance their employee engagement and retention and reduce their turnover and recruitment costs. A recent example of a FinTech company that implements effective HR management practices is Acorns, an investment app that helps users save and invest their spare change. Acorns adopts various HR management practices that enhance its employees’ productivity and satisfaction. For example, Acorns allows its employees to work remotely from anywhere, saving them time and money on commuting and office space. Acorns also provides its employees with online courses and workshops to improve their skills and performance. Moreover, Acorns uses referrals, assessments and interviews to find and hire the best talent for each job. Furthermore, Acorns rewards its employees with stock options, bonuses and recognition based on their achievements and contributions. Effective HR management: FinTech companies can form partnerships with other entities to share resources, technology, expertise and customer bases, reducing their costs and increasing their reach. They can partner with banks, telecom operators, retailers or other FinTechs to offer complementary services, access new markets or leverage existing infrastructure. ZestFinance, a lending app that leverages machine learning to offer credit that is transparent and fair, is a recent example of a FinTech company that collaborates with other entities. ZestFinance forms partnerships with banks, telecom operators, retailers and other FinTech entities to share resources, technology, expertise and customer bases, reducing its costs and increasing its reach. For example, ZestFinance partners with Baidu to offer credit in China, with Ford Credit to offer car loans in the US, with JD.com to offer e-commerce loans in China and with LendUp to offer payday loans in the US. Partnerships: Cloud computing is a model of delivering IT services over the internet, where users only pay for the resources they use. FinTech companies can use cloud computing to avoid upfront infrastructure investments and reduce their technology costs by scaling up or down their resources according to their demand. Cloud computing also offers benefits such as flexibility, reliability, security and innovation. Finch, a consumer finance app that combines checking and investing in one account, is a recent example of a FinTech company that benefits from cloud computing. Cloud computing helps Finch to host its applications and data on the cloud, access software and hardware resources on demand, protect its systems from cyber attacks and try out new technologies. Finch uses AWS as its cloud provider, which provides it benefits such as scalability, reliability, security and innovation. Use cloud computing: Open-source software provides invaluable benefits to FinTech companies looking to optimize costs. By leveraging freely available open-source applications, startups gain access to innovative tools that can be customized, integrated, and shared. This promotes seamless compatibility across systems and enables transparency and adaptability. By tapping into these resources, FinTechs can focus their efforts on developing their core solutions rather than building foundational platforms from scratch. A recent example of a FinTech company that employs open-source software is Stripe, a global payment platform that enables online businesses to accept and manage payments. Stripe uses open-source software to build its platforms, integrate with other systems, access new features and customize its solutions. Stripe uses open-source software such as Ruby on Rails, React, PostgreSQL, Redis and Kubernetes. Leverage open-source software: Software robots or digital workers can copy human actions and do tasks automatically. This technology is called robotic process automation (RPA). FinTech companies can automate boring, fixed and low-value tasks such as typing data, matching data, checking data and approving data by using RPA. This can help them spend less on labor and work better. For example, paying bills, opening accounts, scoring credit and helping customers are some of the tasks that FinTech companies can automate with RPA. Coalition is one of FinTech companies that uses RPA. Coalition uses RPA to automate invoice processing, account opening, credit scoring and customer service. Coalition uses RPA tools such as UiPath, Automation Anywhere and Blue Prism. Implement RPA: Data analytics transforms raw data into valuable insights that can guide decision making. It involves collecting, processing, analyzing and visualizing data to reveal patterns, trends, opportunities and risks. FinTech companies can leverage data analytics to enhance their performance and profitability by optimizing their resource allocation, minimizing their wasteful spending and maximizing their return on investment. For instance, Acorns, an investment app that helps users save and invest their spare change, uses data analytics to fine-tune its pricing strategies, target its marketing campaigns, improve its customer retention and manage risks. Acorns uses data analytics tools such as Google Analytics, Mixpanel, Amplitude and Segment. Use data analytics: Future Trends The cost optimization landscape for FinTech companies will continue to evolve as new technologies, regulations, customer expectations and competitive forces emerge. Some of the future trends that will shape the cost optimization landscape are: These technologies will enable FinTech companies to further improve their efficiency, enhance their customer experience and reduce their costs by automating more tasks, streamlining more workflows, securing more transactions and enabling more flexible work arrangements. Greater adoption of AI, automation, blockchain and remote work: FinTech companies will need to adopt sustainability practices to reduce their environmental impact, comply with green regulations and meet the growing demand for sustainable finance. Sustainability practices can also help FinTech companies optimize their costs by reducing their energy consumption, waste generation and carbon footprint. Greater focus on sustainability practices: Constant innovation is crucial to create new value propositions, offer new solutions and differentiate themselves from the competition. Innovation can also help FinTech companies optimize their costs by creating new revenue streams, improving customer loyalty and enhancing operational efficiency. Greater innovation and differentiation: Conclusion FinTechs experience fierce competition and need to optimize costs to succeed. They can cut expenses and grow profits by adopting technological innovations, simplifying operations, following regulations, and creating novel business models. They can gain a cost advantage and a profitability surge by innovating quicker than competitors. Cost optimization through operational excellence and forward-thinking strategy is the key to becoming a market leader in FinTech. Sources FinTech App Development in 2023: Cost Breakdown [Examples] - SpdLoad Methodologies for How to Value a Fintech Startup | Toptal® Cost to Develop a FinTech App in 2023 [Major Cost Drivers] - MindK.com Ten Business Cost Optimization Ideas - Gartner What Is Cost Optimization? 8 Best Practices To Use ASAP - CloudZero

How to Cut Costs and Boost Profits in the FinTech Sector

What’s the first lesson of stakeholder management? You can’t please everyone. Trying to please everyone turns great ideas into average ideas. Consensus inevitably drifts to the average, the familiar, the mediocre. Innovative concepts often meet with strong resistance from stakeholder communities directly affected. Ironically, with the benefit of hindsight, those controversial innovations may be embraced subsequently by the very people who once opposed them, and the alien and unfamiliar transformed into beloved landmarks that become part of the community’s living heritage. This phenomenon is no accident. It doesn’t come from having a louder PR microphone. It's the result of better public engagement headphones.. Careful, systematic listening to the fears and concerns of stakeholder groups and being willing  to engage with those concerns can turn initial resistance into collaboration. Key to this transformation is understanding people are suspicious of any external decision-making that directly impacts their backyard and day-to-day life in their community.  To be successful, public decision-making must engage honestly with community concerns and must give those affected a genuine opportunity to influence the outcome. It’s this input that builds a sense of community ownership. The stakeholder troubleshooting framework and guiding principles detailed below demonstrate how  positive momentum can be made in even the most contentious development and planning processes, and how to convert a potential project stakeholder liability and adversarial coalition into a partner-advocate group. 4 Guiding Principles Framing Our Structure Four simple principles serve as pillars for our effective public engagement strategy. : The information that’s been put out in the public domain for community engagement must be true and specific. Accuracy Information must be easily found in press releases, news websites and other news media, online sources, social media Availability: Stakeholder groups must get relevant information promptly or pre-emptively to avoid communication lags that allow misunderstandings to grow. Timeliness: The information must be readily available and easy to find online without barriers. Paywalled articles are reposted with permission and content is optimized for search engines and sharing over social media. Accessibility: Process Clearly Defined Stakeholder Groups We get to know our different stakeholder groups’ hopes, aspirations, emotions, points-of-pain,  and to use these feedback patterns into what marketers call “squeaky wheel personas”. This process involves systematic analysis of feedback from available channels, typically news websites comment sections and blogs, Twitter comment threads, Youtube news channel comments. Since negative emotions prompt more responses, analysis of this commentary normally allows us to dentify 3-5 distinct themes that provide the basis for addressing objections and developing talking points.. This analysis pinpoints where the most frequent misunderstandings and communication breakdowns are happening, and allows us to prioritize communication strategically. So much for the theory; here’s what it looks like in practice Example Situation A high-profile private development in partnership with various levels of government has agreed in principle to a bid to revitalize a local public park and event space. Background The former park previously closed due to dwindling attendance and had been defunct for several years. The site has fallen into disrepair and a microhabitat has grown over a man-made island of contaminated soil that is damaging a nearby local lake. The developer has committed to stewarding local environmental issues, ensuring the public space is desirable and building a new economic driver for tourists and locals to replace the derelict site. Stakeholder Groups Over the stakeholder consultation period, four distinct stakeholder groups emerge. This group is concerned with spending taxpayer money on the project and believes access should be free for everyone. For Free Folks: CCP is chiefly concerned about the public space available for their uses. Concerned Cyclists and Pedestrians (CCP): This group is concerned about the local habitat and how the ecosystem will change to accommodate this new park development. Engaged Environmentalists: a vocal group who feel angry with government because of perceived shortcomings in accountability for public land management, and who believe governments encourage cronyism. Anti-Politicians: Following the initial information campaign, we analyze responses. We identify recurring misunderstandings and misconceptions and develop a Master List of  frequently asked questions (FAQ) to guide the next stage.. Masterlist FAQ This document catalogs thematic lists of stakeholder issues: factual questions, concerns, mis-information that has surfaced in our analysis, providing the foundational material that can be turned into questions and answers. The document appears on the organization’s web page as a Frequently Asked Question (FAQ) page and is used to develop targeted messaging, talking points, and materials for the various different stakeholder communities. Equally importantly, using key terms identified in our feedback analysis, we use recent Search Engine Optimization (SEO) updates to dominate  online search results. News and Editorial Content We now have our stakeholders grouped by primary concerns, and a long list of FAQs that can be found easily. Next, we create content that addresses the frequently asked questions and answers geared for news websites, local blogs and social media content online. Here are a few examples of how this may look. Article Examples: Top 10 Things You Probably Didn’t Know About This Project. 12 Benefits Of the Development Nobody’s Talking About 8 Points The Critics Are Getting Wrong About the Development The points should be an equal mix of stakeholder concerns and the most frequently cited mistaken beliefs for the groups. A company account should repost the original article for those unable to access articles via a website’s paywall. Comment sections will provide the next round of feedback on what objections or misunderstandings should be next to work on. And don’t forget to add it to the living FAQ! Depending on your level of urgency, a way to get feedback quickly would be to promote the article on social media channels. Social Media Content Examples Before-and-after and other side-by-side visual comparison content linking back to the skyscraper FAQ for more information. Visual content can be artist renderings beside the existing location, infographics, side-by-side bullet items and simple charts‌. We should curate social media content and posts for the specific stakeholder group, in contrast to the article approach that would include something for each group in one piece of content. At the bottom of examples 2 and 3, they encouraged readers to continue learning more in the footer call-to-actions (CTA). Our CTA would be to visit the Master list FAQ wherever it is located to learn more. Content marketing that focuses on business self-promotion instead of engaging and showing consultative listening with our troubleshooting stakeholders can be an irritant to them and potentially viewed as tone-deaf to the community’s addressed concerns. It’s almost like waving a red flag at a bull when you’re wanting to calm the bull down. Online Engagement Persona We should create social media and other blog platform accounts to engage online and share appropriate content links related to the mistaken beliefs being shared. These @BrandFAQ accounts assist with delivering accurate information in a reliable, transparent and timely way to appear where, when and how audiences want to engage most on the topic. Wherever the conversations are happening, whether it be news websites comment sections, Twitter threads or elsewhere, these brand FAQ personas need to be there too. It’s important to quickly put out misunderstandings before the negative momentum snowballs. Conclusion Effective public engagement is vital. The stakeholder troubleshooting framework outline provides a structured approach to consult with communities, listen to their fears and concerns, and engage resistant stakeholder groups where they are. By following the four guiding principles of accuracy, availability, timeliness and accessibility, and by clearly defining stakeholder groups based on shared concerns and addressing them, you can turn potential project stakeholder liabilities into partner-advocate groups and assets You can apply this framework to diagnose potential problem communication areas and prioritize actions to have the greatest impact with the least amount of resources. Ultimately, this will help to potentially reduce costly delays related to highly resistant engagement from the community and foster a greater sense of community ownership and pride in the outcome.

Heading Them Off At The Pass: A Guide to Stakeholder Management

The future is now, it's 2020 and Decentralized Autonomous Organizations (DAOs) are experiencing a Cambrian explosion. Typically in an enterprise, you have top-down hierarchies as the mechanism of control. Let's look at a quick example of how a DAO works differently in action. Imagine you’re building a startup, except at this startup, there is a clear sense of organization without humans organizing other humans. It all runs organically, and it's generative in nature, meaning it evolves, innovates and experiences high growth from within. Leaderless leadership! Through active participation from interested parties who share common values, missions and objectives. People-driven autonomous organizations happen mostly through voting on decisions that are proposed by other community members. You can propose, vote and discuss decisions as a team without having to have a singular authority to report to. Resulting in new ideas being seeded and proposed from within the organization to solve mission-critical challenges that the DAO is facing. It's really a synthesis of innovation and ambition, it's great! With that said there are certainly some balanced benefits and drawbacks about this model that we should explore. For the moment DAOs function in a fairly binary nature, you vote on proposals that you or others have submitted, typically these votes take place on blockchains by signing a transaction with your crypto wallet. That means the current state of DAOs is experiencing the highest growth in the blockchain industry. So whilst DAOs are now, they might be somewhat gravitating around the future of money. However crypto-centric it is right now, it is definitely laying out an exceptional framework that any organization type could be built upon. We are seeing many other non-crypto DAOs emerge too, using platforms like Aragon to create a DAO in minutes on the blockchain. This is achieved by creating a Governance Token on the Ethereum blockchain. When users hold these Governance Tokens they can vote on proposals put forward to the community. These communities can even have treasuries where the DAO can organize their finances. For example, members that hold these Governance Tokens can suggest making a payment, creating a vote inside the community so it can be approved or denied collectively. There are many lessons to learn about how to coordinate large groups of self-interested people. I recently wrote an article, " ", where I outlined my thesis on how I think we can even coordinate groups who don't explicitly share the same values, they instead just share the same mission. It's going to be very interesting to see what unfolds with the DAOs that are experimenting right now. Basically there is an entire unstoppable movement happening because of projects offering up a Governance Token as a bonus to those who are using some Decentralized Finance (DeFi) applications. I've heard many stories from folks achieving incredible results in less than 5 days. For example, "With YFI I earned like $3.5k on $24k", one community member shared with me. That example is a 14.58% increase in capital in just five days, no wonder it's getting attention. In the DeFi world, there is a new meme known as Yield Farming 👨‍🌾  its technical name is Liquidity Mining. This is where a user deposits crypto stablecoins like USDC, DAI & USDT to earn a reasonably safe and secure return, which lately seems to be roughly 8% APY. As well as this, these DeFi applications which have newly formed their own DAOs to oversee their protocols, are rewarding users with Governance Tokens when they have funds deposited into their various DeFi products. This has added rocket fuel to the DeFi community, with an explosive $3 Billion USD flowing into projects in just the last couple of weeks. This doesn't stop here either, there are many more DAO innovations that will be made known during this wave of Governance Tokens. One example is , where you can earn Governance Tokens for referring people to DeFi platforms without having to deposit any funds of your own. How is such a way of working together achieved? Failure shows us the way Why are DAOs exploding right now? Wait, how are people making money from these Governance Tokens? Referral Yield Farming Imo I think it's only a matter of months, maximum 1-2 years that we will see this business model having explosive growth in other industry verticals. The future is bright, but so is right now. I hope you are able to get involved so you can propose, vote and prosper too! What does the future of DAOs look like?

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