It wasn’t: SURI hit £3 million revenues in its first year of shipping toothbrushes, and is on track to sell £10 million this year. A £2 million fundraising last October was invested in marketing and inventory, and today stockists include Amazon, Boots, and Selfridges, while its subscription brush head service has 25,000 subscribers.

Ex-ad men selling recyclable toothbrush come up smiling

Companies that produce the most CEOs are desirable for prospective employees as they can increase the likelihood of ascending to the top of firms.

The Top 25 Companies That Produce The Most CEOs

These Employers Have Track Record Of Minting CEOs

At SB’23 San Diego, a variety of brands and innovators discussed on-the-ground improvements cleaning up global and regional supply chains — and how to drive them further. Archila, drawing on Fair Trade’s experience working with a network of almost 2 ...

Supply Chain Brands Betting the Farm on Decarbonized, Regenerative Supply Chains

and Procter & Gamble launched its “Take on Race” fund to support racial justice organizations. The list goes on. More from WWD Lush Modernizes Distribution With Ulta Partnership Bath & Body Works Unveils New Holiday Scents and Collections Dr.Jart+ Taps ...

Tracking Diversity, Equity and Inclusion Progress at Beauty’s 20 Biggest Companies

In this article, we discuss the 13 best Warren Buffett stock picks for beginners. To skip reading Warren Buffett’s investment strategy and Q2 bets of Berkshire Hathaway, go directly to the 5 Best Warren Buffett Stock Picks for Beginners.

13 Best Warren Buffett Stock Picks for Beginners

In this article, we discuss the 13 best FMCG stocks to buy now. If you want to skip our industry analysis you can see the 5 Best FMCG Stocks To Buy Now. Consumer confidence has remained relatively stable throughout the summer.

13 Best FMCG Stocks To Buy Now

The parent to home, personal, oral and pet-care products has repeatedly raised prices over the last year to combat inflationary pressures, boosting its profit margins. Procter & Gamble which makes Crest toothpaste, also raised prices to boost margins in its earnings posted last week.

Colgate-Palmolive raises prices again and says the consumer is ‘resilient’

Procter & Gamble

proctergamble

Open Innovation is the Cornerstone of Your Startup’s Success

Nowadays, we are constantly bombarded with such a high volume of information from various sources. This massive influx of data, coupled with the development of content generation from AI, undoubtedly gives us greater access to knowledge than we’ve ever had before. However, it also brings in the problem of information overload. Think of a typical working day for yourself or a colleague. You might open your inbox, which is absolutely stacked with threads, internal bulletins, calendar invitations, phishing emails, and PR emails. This is just one strand of working life, and yet, it’s entirely possible to be overwhelmed by these emails alone within 5 minutes of starting your day. When you add into the mix newsletter subscriptions, social media, and workplace communication channels, there is just an incredible amount of transitory knowledge. Experts have often pointed towards information overload as the cause of productivity issues, particularly in industries that rely on smooth knowledge sharing. There are roughly 328.77 million terabytes of data created each day, so naturally, there is an awful lot of information to unjumble. Industries across the board are undergoing sweeping digital transformations, with 89% of businesses adopting a digital-first strategy, the sheer amount of information asks a lot of questions on how we can maintain productivity and make informed decisions.Let’s delve into the topic of information overload in the workplace and analyze how, by making adjustments to research content curation, companies can go a long way to limiting its impact The Digital Transformation and Infobesity Workplaces have come a long way in a short space of time. From packed filing cabinets filled with papers to now huge online databases, the digitization of workplaces has undeniably altered the way we access and manage information. While this transformation has its advantages, it has also given rise to the phenomenon of "infobesity,” whereby there is simply too much information being thrown at workers.Forbes identifies infobesity as a formidable challenge, particularly in environments where companies need to make decisions quickly. In fact, the cost of information overload to the US economy is staggering, amounting to nearly $900 billion in annual productivity loss. Some particular industries that are facing an ongoing battle with information overload include e-commerce, where companies such as Procter & Gamble can suffer from analysis paralysis due to the deluge of market research and consumer data, and financial services companies, which handle an extensive array of financial transactions and regulatory data. There are roughly four areas that categorize the information which can be a burden to employees. Repetitive, Irrelevant, Intensive, and Inconsistent information leads to around 4 hours of wasted time in a working week. CEOs and C-suite executives are also feeling the heat of “always being on” and the relentless pressure of managing so much information is a byproduct of that. The solution is getting help with AI-enhanced tools that can efficiently manage and prioritize information flow to alleviate the burden of information overload. AI-Powered Solutions for Content Curation In response to this escalating issue of information overload, innovative solutions leveraging artificial intelligence (AI) are emerging. In the same way as with your favorite streaming platforms such as Netflix and Spotify, AI-based content intelligence systems offers a clear way to address this challenge. These systems are designed to sift through vast amounts of online content, identifying authoritative sources and condensing information into digestible chunks. AI curators can be utilized for workplace learning and knowledge discovery. These AI-powered platforms harness advanced algorithms, which enable users to make informed decisions without being inundated by irrelevant or overwhelming data. The Concept of Anti-search for Streamlining There is a natural propensity from humans to expand their quest for information, but consider the concept of anti-search, which distills content from authoritative sources into bite-sized, structured, and manageable pieces of knowledge. Instead of relying on algorithms to rank content on Google or other search engines, the concept of anti-search is a more considered approach. It takes into account the author’s credibility, the content value, and user context. This gives users genuine insights rather than just generic information.There are plenty of examples of organizations creating workarounds for actually limiting content access to be more streamlined. For example,as stated in an HBR article, the New South Wales Department of Planning and Environment (NSW DPE) recently established an audit for their new intranet. They implemented a quarterly accuracy review and an experience review, which led them to condense 2,000 web pages into just 500.Elsewhere, the “Information Overload Research Group” (IORG) was a non-profit organization dedicated to addressing the issue of information overload. The members included experts from various sectors, including technology companies like Microsoft Research, IBM, and Google. The group’s work focused on understanding the root causes of information overload, such as the rapid growth of connected devices, new communication channels, and globalization, and developing strategies to manage and reduce its impact. Unfortunately, they are no longer in operation, but hopefully, they have laid the groundwork, and similar groups will pop up moving forward. Empowering Lifelong Learning Lifelong learning is something essential for any profession in any walk of life. Lifelong learning through knowledge distillation is not a new concept, educational organizations have been plucking the best resources from the mountain of potential journals and books for centuries. However, these traditional methods naturally struggle to keep pace with the scale and speed of information flow in the digital age. AI-powered solutions bridge this gap by offering knowledge distillation and personalized learning experiences. There is no doubt that Information overload is an inevitable result of our desire to constantly engage with each other in a work setting, but it can lead to employee disengagement and poor decision-making. It’s vital to create a low-burden culture and not pile unnecessary pressure on employees. As organizations strive to navigate this tricky path, AI-driven solutions for content curation and knowledge management emerge as key strategies for combating information overload. Through leveraging advanced algorithms and AI technologies, these solutions offer a path toward a balanced and productive digital workplace. The coexistence of search and anti-search platforms should lead to a future where knowledge is accessible and personalized to individual needs. Using AI intelligently, we can create a future where information overload is no longer a huge barrier to overcome but an opportunity for growth and innovation. Nowadays, we are constantly bombarded with such a high volume of information from various sources. This massive influx of data, coupled with the development of content generation from AI, undoubtedly gives us greater access to knowledge than we’ve ever had before. However, it also brings in the problem of information overload. Nowadays, we are constantly bombarded with such a high volume of information from various sources. This massive influx of data, coupled with the development of content generation from AI, undoubtedly gives us greater access to knowledge than we’ve ever had before. However, it also brings in the problem of information overload. Think of a typical working day for yourself or a colleague. You might open your inbox, which is absolutely stacked with threads, internal bulletins, calendar invitations, phishing emails, and PR emails. This is just one strand of working life, and yet, it’s entirely possible to be overwhelmed by these emails alone within 5 minutes of starting your day. When you add into the mix newsletter subscriptions, social media, and workplace communication channels, there is just an incredible amount of transitory knowledge. Think of a typical working day for yourself or a colleague. You might open your inbox, which is absolutely stacked with threads, internal bulletins, calendar invitations, phishing emails, and PR emails. This is just one strand of working life, and yet, it’s entirely possible to be overwhelmed by these emails alone within 5 minutes of starting your day. When you add into the mix newsletter subscriptions, social media, and workplace communication channels, there is just an incredible amount of transitory knowledge. Experts have often pointed towards information overload as the cause of productivity issues, particularly in industries that rely on smooth knowledge sharing. There are roughly 328.77 million terabytes of data created each day, so naturally, there is an awful lot of information to unjumble. 328.77 million terabytes of data 328.77 million terabytes of data Industries across the board are undergoing sweeping digital transformations, with 89% of businesses adopting a digital-first strategy , the sheer amount of information asks a lot of questions on how we can maintain productivity and make informed decisions. Let’s delve into the topic of information overload in the workplace and analyze how, by making adjustments to research content curation, companies can go a long way to limiting its impact 89% of businesses adopting a digital-first strategy 89% of businesses adopting a digital-first strategy The Digital Transformation and Infobesity Workplaces have come a long way in a short space of time. From packed filing cabinets filled with papers to now huge online databases, the digitization of workplaces has undeniably altered the way we access and manage information. While this transformation has its advantages, it has also given rise to the phenomenon of "infobesity,” whereby there is simply too much information being thrown at workers. Forbes identifies infobesity as a formidable challenge, particularly in environments where companies need to make decisions quickly. In fact, the cost of information overload to the US economy is staggering, amounting to nearly $900 billion in annual productivity loss. Some particular industries that are facing an ongoing battle with information overload include e-commerce, where companies such as Procter & Gamble can suffer from analysis paralysis due to the deluge of market research and consumer data, and financial services companies, which handle an extensive array of financial transactions and regulatory data. There are roughly four areas that categorize the information which can be a burden to employees. Repetitive, Irrelevant, Intensive, and Inconsistent information leads to around 4 hours of wasted time in a working week. CEOs and C-suite executives are also feeling the heat of “always being on” and the relentless pressure of managing so much information is a byproduct of that. The solution is getting help with AI-enhanced tools that can efficiently manage and prioritize information flow to alleviate the burden of information overload. AI-Powered Solutions for Content Curation In response to this escalating issue of information overload, innovative solutions leveraging artificial intelligence (AI) are emerging. In the same way as with your favorite streaming platforms such as Netflix and Spotify, AI-based content intelligence systems offers a clear way to address this challenge. These systems are designed to sift through vast amounts of online content, identifying authoritative sources and condensing information into digestible chunks. AI curators can be utilized for workplace learning and knowledge discovery. These AI-powered platforms harness advanced algorithms, which enable users to make informed decisions without being inundated by irrelevant or overwhelming data. The Concept of Anti-search for Streamlining There is a natural propensity from humans to expand their quest for information, but consider the concept of anti-search, which distills content from authoritative sources into bite-sized, structured, and manageable pieces of knowledge. Instead of relying on algorithms to rank content on Google or other search engines, the concept of anti-search is a more considered approach. It takes into account the author’s credibility, the content value, and user context. This gives users genuine insights rather than just generic information. There are plenty of examples of organizations creating workarounds for actually limiting content access to be more streamlined. For example, as stated in an HBR article , the New South Wales Department of Planning and Environment (NSW DPE) recently established an audit for their new intranet. They implemented a quarterly accuracy review and an experience review, which led them to condense 2,000 web pages into just 500. Elsewhere, the “Information Overload Research Group” (IORG) was a non-profit organization dedicated to addressing the issue of information overload. The members included experts from various sectors, including technology companies like Microsoft Research, IBM, and Google. as stated in an HBR article as stated in an HBR article The group’s work focused on understanding the root causes of information overload, such as the rapid growth of connected devices, new communication channels, and globalization, and developing strategies to manage and reduce its impact. Unfortunately, they are no longer in operation, but hopefully, they have laid the groundwork, and similar groups will pop up moving forward. Empowering Lifelong Learning Lifelong learning is something essential for any profession in any walk of life. Lifelong learning through knowledge distillation is not a new concept, educational organizations have been plucking the best resources from the mountain of potential journals and books for centuries. However, these traditional methods naturally struggle to keep pace with the scale and speed of information flow in the digital age. AI-powered solutions bridge this gap by offering knowledge distillation and personalized learning experiences. There is no doubt that Information overload is an inevitable result of our desire to constantly engage with each other in a work setting, but it can lead to employee disengagement and poor decision-making. It’s vital to create a low-burden culture and not pile unnecessary pressure on employees. As organizations strive to navigate this tricky path, AI-driven solutions for content curation and knowledge management emerge as key strategies for combating information overload. Through leveraging advanced algorithms and AI technologies, these solutions offer a path toward a balanced and productive digital workplace. The coexistence of search and anti-search platforms should lead to a future where knowledge is accessible and personalized to individual needs. Using AI intelligently, we can create a future where information overload is no longer a huge barrier to overcome but an opportunity for growth and innovation.

Information Overload: How AI With Research Content Curation Could Lead the Way

Product Hypothesis Validation: Best Practices & Examples

In the nearly 100 years since the inception of modern product management, the role of product managers has evolved many times over. As technology advances exponentially, the tools available to PMs have also played a big role in innovating how they manage their teams. Project management dates back thousands of years to the time of the Egyptians, according to from George Washington University. research But the modern era of can be traced back to the 1930s and 40s, where companies such as Procter & Gamble (now P&G) and Toyota were innovating new methodologies to launch new household products and vehicles. In fact, the Kanban methodology, which still plays a big role in product management today, was developed in the 1940s by Toyota engineer Taiichi Ōno. product management From the 1950s to 1970s, more project management methodologies began to emerge, including some like CPM/PERT, which were calculated in gigantic computers and helped guide government sector projects in the United States such as the National Aeronautics and Space Administration (NASA)’s Apollo mission. By the 1970s, software companies began rolling out project management products for industry, including legacy firms like Artemis (1977), Scitor Corporation (1979), and Oracle (1977), according to research from George Washington University. Discouraged with clunky, and sometimes inefficient product management methodologies, a group of software engineers the Agile Manifesto to the world in the early 2000s, turning the industry on its head by allowing for more communication from engineers building the product and putting the user experience (UX) at the forefront of building products. introduced Today, most industries run on technology tools that streamline product management and workflows. From creatives, to factories, to space exploration companies, 85% of businesses project management software, and the market is at nearly $6 billion. actively use valued Project management tools are evolving at a rapid pace. To keep up, let’s take a look at three cool new innovations in project management. Project Management for Creatives Creatives, essentially artists that work within an organization to help create products or marketing assets, often have a different personality and work traits than other team members. According to Tomas Chamorro-Premuzic, a visiting professor at Harvard University, creatives a different style of project management, that allows for more freedom, a greater sense of purpose in what they’re building, and an opportunity to fail and try again, among other distinctions. demand Some traditional project management tools may be too rigid, or not robust enough, to manage creative projects. Meredith Bailey, a product marketing expert who helped manage creative assets at companies like Google, Apple and Warner Bros., recently StreamWork, a full-suite creative workflow management platform built for creative teams. The platform aims to help creative agencies, as well as in-house marketing and sales teams, to collate creative feedback, automate stakeholder approval flows, and streamline creative project management. launched According to the San Francisco-based company, StreamWork is the only PM software available that combines all critical creative workflows — including video, FIGMA, After Effects, PPTs, PDFs, audio, images and more — into a single platform. Feedback is streamlined, allowing team members to annotate creative assets in real time. , including customers outside of the organization, can be quickly added to the platform to provide feedback, and the platform allows PMs to turn creative feedback from stakeholders into actionable tasks immediately. Stakeholders Similar to another creative project management platform ZiFlow, StreamWork also supports automated approval workflows geared toward teams that need to route creative through multiple departments or teams, both internal and external — a feature that many traditional project management tools do not support. The company offers a free version of the tool and team packages start at $36 per user. Innovation in Project Cost Management An integral part of product management is ensuring that products are delivered on time, and within budget. Therefore, product cost planning and control — estimating costs, setting a budget, and managing the costs against that budget — becomes crucial for the success of any project manager. The Association of Project Management has many useful that project managers can leverage to execute cost planning and control, and there are a number of different cost-management tools from private companies that are easing the difficulties PMs face to deliver projects on budget. resources Procurify, a Canadian project spend management , aims to upend traditional cost management solutions that focus mainly on tracking expenses. The tool provides data insights that allow project managers to be more proactive and profit-driven in their project planning. SaaS solution The tool can help PMs speed up purchase cycles by centralizing communication amongst decision-makers across departments and providing real-time spending insights on different projects. In the end, this helps to speed up product development and deployment. The company integrates with several different business management tools, including most recently with Microsoft Dynamics 365 Business Central. The tool is built for SMEs and is a bit more accessible for small to midsize companies than other spend management software like SAP Ariba. Pricing starts at around $2,000 per month. Workflow Management in Heavy Industry Heavy industrial manufacturing, with its expensive and often enormously complex workflow, provides a landscape ripe for digital transformation and technology-enabled project management. According to McKinsey, heavy industry could stand to by three to five percentage points by applying digital technologies and advanced analytics. increase profit margins Project management solutions that don’t just guide a workflow, but can provide real-time insights from data can help gigantic manufacturing projects become more nimble and efficient. Allie, an artificial intelligence (AI)-enabled workflow automation company, focuses on serving clients in heavy industries and manufacturing. The Mexico-based firm works closely with project managers at industrial firms in emerging markets. Their suite of project management and analytics tools helps PMs predict when machines may need maintenance, increase their productivity metrics, and connect all team members and machines into a centralized platform for a birds-eye view of the entire project operation. This project management tool connects to machines to track operational efficiencies across teams and production lines, helping to root out bottlenecks. Using machine learning (ML), Allie can help PMs detect machine failure ahead of time to reduce costs and increase efficiency. What’s more, the company has integrated thousands of machinery manuals and other content into AI language models that act as a sort of FactoryGPT. PMs can ask questions via an integration with chat service WhatsApp and receive important information about different machine functionality in real time, helping to keep operations running smoothly. In the US, other comparable tools include Archdesk, a project management software for the construction industry, and Prodsmart for manufacturing. The long history of project management methodologies and tools is gaining more references and examples each year, as technology exponentially propels the industry forward. Project managers across all industries should keep abreast of available tools to help them better succeed. This article was originally published by on Stiven Cartagena The Sociable.

Project Management Innovations Enhancing PMs' Success

AI is approaching the next level of maturity, coming out of the hype cycle, says Gartner. Its adoption is expanding across industries beyond automation to building new-generation intelligent products and services for business growth. Around 90% of companies in the US and UK view artificial intelligence as a priority, with AI projects either in planning or production. However, half of them acknowledge that they lack the skill to make the most of AI advances. This is where experienced AI consulting firms come in to help. The market of AI consulting is vast, ranging from tech giants like IBM and Accenture to Big 4 firms and smaller-scale innovators. Here, we’ve compiled a list of the top 10 AI consulting firms that have earned a reputation for disruptive innovations. These experts run product discovery and deliver proofs of concept (PoC) and MVPs. This way, they help organizations bring pioneering products and services to the market and build proprietary AI systems for transforming operations. Let’s explore these top AI consulting companies — they are worth their salt. In this blog, you will find an overview of each of them and useful tips on picking the right partner for your AI project. Our list of the top 10 AI consulting firms for 2023 1. ITRex is a full-cycle AI and big data solutions provider with teams in Poland, the US, and Mexico and a dedicated R&D lab where they design new AI concepts and build prototypes. They are tech savvy in all AI-related fields (ML, deep learning, NLP, and computer vision), delivering AI projects end to end, from preparing data for algorithms to rolling out systems to thousands of users. ITRex Having adopted a start-small-and-scale-up approach, ITRex helps Fortune 500 companies and startups launch breakthrough AI products, apart from automating operations, boosting customer experiences, and supporting smart decision-making. They’ve delivered quite a number of impressive AI projects, from an AI-powered big data platform for the world’s biggest retailer to a fitness mirror with a personal coach experience, an ML-based clinical decision support system for cancer patients, a SaaS cybersecurity solution using face recognition, and many others. Walmart, 21st Century Fox, and Warner Bros. Entertainment Inc. are just some of their big-name clients. Rates: $50 – $99/hr Size: 300+ Founded: 2009 Headquarters: Aliso Viejo, California 2. Deeper Insights The UK-headquartered is fully focused on providing AI consulting and development services, with its expertise spanning from AI exploration to ML engineering, NLP, and computer vision. As they say on their website, they solve their clients’ “impossible problems,” helping them achieve the desired business results. Deeper Insights The company develops custom AI algorithms and ML models using either their clients’ data sets or data collected via their proprietary ML web scraper – the Skim Engine™. They have delivered many innovative AI projects for big-ticket and smaller clients, including an automated insights app for sales teams at Deloitte, a custom media monitoring platform for the global real estate services company Jll, and bespoke computer vision algorithms integrated with deep learning to recognize body parts in images in robotic surgeries. Rates: $50-$99/hr Size: 10-49 Year: 2014 Headquarters: London, UK 3. InData Labs also specializes in AI consulting and implementation services. As most top AI consulting firms on our list, they offer not only advice but also AI R&D, PoCs, MVPs, and development of AI web/mobile apps, empowering clients with data science and AI technology. InData Labs The company helps clients leverage predictive analytics, NLP, computer vision, and intelligent automation to get meaningful insights from data, understand audiences, forecast demand, reduce risks, and eliminate cost overruns. Examples of their AI-powered solutions include a computer vision system for pose estimation in fitness, face recognition for a surveillance system, image analysis for ticket processing software, and many more. They’ve also delivered different kinds of predictive analytics systems for logistics, eCommerce, sports, entertainment, and healthcare, along with NLP tools for simultaneous interpreting, remote education, and sentiment analysis. Rates: $50-$99/hr Size: 80+ Year: 2014 Headquarters: Nicosia, Cyprus 4. Cambridge Consultants With over 20,000 sqm of R&F facilities and a 900-strong team, helps organizations develop AI-based products that “will transform how we live and the world around us.” Cambridge Consultants Being part of the French-based tech consultancy Capgemini, Cambridge Consultants is a big and established player on our top AI consulting firms list, operating since 1960. Cambridge Consultants is honored for AI breakthroughs in many fields across industries. Projects in their portfolio range from a drone delivery service to military robots using AI-based navigation and reinforcement learning, a proprietary crop spraying technology, an AI system for an automated response to cyberattacks built for the UK Ministry of Defence, and a piano music classification tool. Rates: Undisclosed Size: 900+ Year: 1960 Headquarters: Cambridge, UK 5. ThirdEye Data Based in Silicon Valley with delivery centers in the US and India, describes itself as a one-stop shop for data science, analytics, and engineering services. Apart from providing end-to-end big data and AI solutions, the company has developed its own open-source tools for anomaly detection and predictive analytics. ThirdEye Their expertise is recognized by multiple industry awards. Microsoft, Walmart, British Petroleum, and AWS are among their Fortune 500 clients. The company has implemented over 30 end-to-end data and AI projects, such as an image quality detection system for Southern California Edison, MLOps engineering for XPERI, and predictive metrology for Glas Trosch. Rates: $25 – $49 hr Size: 51 – 200 Founded: 2010 Headquarters: San Jose, California 6. LeewayHertz Operating since 2007, specializes in many AI fields, from ML and NLP to computer vision. Among its big-name clients are Procter & Gamble, McKinsey & Company, Siemens, and Hershey’s. LeewayHertz With the mission to help organizations adopt AI at scale, LeewayHertz has entered our top AI consulting firms list for delivering innovative AI solutions across sectors. Among its landmark projects in collaboration with an Indian food tech startup, which has resulted in the creation of the world’s first tea-making robot Arya using ML, speech recognition, and NLP. They’ve also built a computer vision-enabled marketplace for AI applications and an AI-based employee time-tracking app. Rates: $50-$99 hr Size: 51-249 Founded: 2007 Headquarters: San Francisco, California 7. DataRoot Labs is a fast-growing company with teams in Ukraine and Israel. As a top AI consulting firm, it helps ambitious startups and startup accelerators turn their boldest AI ideas into reality. DataRoot Labs DataRoot Labs prides itself on driving tech innovation by running the DataRoot University, which offers data engineering and data sciences courses. They have accomplished a great number of projects around computer vision and other AI technologies for clients, delivering, for instance, a solution for defect detection in solar panels, a personal coach app, an in-store customer activity tracking app, an empathetic virtual assistant, and many others. Rates: $51-$99/hr Size: 10-49 Founded: 2016 Headquarters: Kyiv, Ukraine 8. Azati Software Creating fully functional AI solutions since 2016, shares its expertise on a consultancy basis across AI fields, from supervised/unsupervised learning to NLP, computer vision, predictive analytics, and conversational AI. Azati Software Their featured AI-based projects include a data processing tool to analyze inputs from oil and gas meters using ML and computer vision, an ML model for pharmaceutical marketing, a semantic search engine to tap into scientific datasets, and an AI-powered app that changes the interior of smartphone pictures. With an R&D center in Poland, this top AI consulting firm successfully helps clients translate their AI vision into prototypes and MVPs. Rates: $25-$49/hr Size: 150 Founded: 2001 Headquarters: Warsaw, Poland 9. Tooploox The EU-based AI consultancy has built its AI expertise by working extensively with US startups, innovators, and VCs. Tooploox With the mission to improve people’s lives through cutting-edge technology, Tooploox has extensive R&D capabilities that have widened after the company joined forces with Microscope IT, a development shop offering AI-related services for healthcare, medtech, and life sciences. Their skillsets around AI now extend to computer and 3D vision, deep learning, sensor fusion, NLP, data capture & OCR, and beyond. Tooploox has been recognized for its research at international conferences, such as NIPS and ICML. They are also known for building Virtum, an AI-powered image analysis system that helps spot cancer cells. Rates: $100-$149/hr Size: 150 Founded: 2012 Headquarters: Warsaw, Poland 10. Addepto is another fast-growing company that deserves a spot on our list of top AI consulting firms. It was established in 2017 and now helps companies grow with the power of data and AI. Addepto With expertise in all data-related fields, the Addepto team has won the trust of a few Fortune 500 companies, which they support in creating complex AI solutions. Among them are Citibank and P&G. Addepto has helped build a digital twin monitoring airport operations, an intelligent passenger and baggage tracking system, a shipping schedule and inventory management system using predictive modeling for the world’s second-largest aluminum company, and an ML-powered demand forecasting tool for postal services. Rates: $50-$99/hr Size: 10-49 Year: 2017 Location: Warsaw, Poland How to choose your AI partner - Tips from the ITRex CTO Reducing a lot of options available in the AI consulting market to just a few should make life simpler. However, you still need to choose only one of them at the end of the day. What should you consider? We’ve asked ITRex CTO Kirill Stashevsky, who has over 15 years of experience helping companies deliver innovative solutions, to share his tips. Here they are: 1. Explore the vendor’s website to make sure they indeed offer AI consulting services, not just development. [ ] This can be especially helpful for those with little or no technical background. The thing is, an experienced consulting partner might figure out a more elegant tech solution for translating your vision into a reality. This solution can be cheaper, quicker, and more efficient than the one you had in mind. The latest AI breakthroughs can be fascinating, but it is useful to make sure first before any coding begins that they are exactly what you need to build a fascinating product. A good AI consulting firm would be happy to look at your vision from different perspectives and give you free advice over the phone. Don’t hesitate and ask for it first. 2. Look through the vendor’s portfolio to check if they delivered a similar solution in the past. [ ] Companies’ portfolios with featured projects or case studies are a great source of valuable information. They let you understand which clients they served and what projects they accomplished previously. It is best to reduce your list of top AI consulting firms to companies that have a demonstrable experience with what you are trying to achieve. These guys should know your domain well so you will speak the same language with them without having to waste time explaining the basics. They are also likely to know all the potential pitfalls that might be typically encountered on a journey like yours. However, don’t be too quick to strike off a vendor of your choice that doesn’t have the exact expertise you are looking for. The firm can still be a perfect fit for your project if they specialize in AI consulting services (see the first tip). 3. Do a bit of homework to define your business objectives clearly. [ ] Instead of contacting all the 10 or 20 companies on your top AI consulting firms list to discuss your future product, prepare a one-pager describing what you are trying to build from the business point of view, and send it out. Some vendors would reply they don’t know how to help; some might figure out how they can implement your idea best, while others might offer you cost-efficient customization of a tool already in the market. This way, you will narrow down your list quicker, saving time and energy. 4. Don’t forget about social proof [ ] Check out previous reviews from clients who partnered with the company and the company’s rating. This information can be found on sites like clutch.co or goodfirms.co. Ask your acquaintances, colleagues, and people you meet at hackathons and industry conferences — they might have heard something about a firm of your choice. You can also ask the vendor for feedback from their previous clients. Wrapping it up Artificial intelligence is already profoundly impacting our daily lives while transforming the business landscape. that AI could add more than $15 trillion to global GDP by 2030, meaning that it has the potential to change the way we live completely. Capitalize on the emerging trend and put your company at the front of the line by partnering with the right AI consulting firm. PwC estimates Originally published . here

Top 10 AI Consulting Firms Today

In 2014, investor Mark Mobius declared: “Shareholder activism is not a privilege—it is a right and a responsibility.” Essentially, Mobius believed investors ought to be actively involved in company decision-making and use their power to bring about positive change in corporate structures. Shareholder activism is hardly a new concept. For example, activist investors like attracted significant attention in the 80s for aggressively pushing for change at portfolio companies. Carl Icahn Shareholder activism in recent years, as investors find ways to coordinate and express their views on company issues. Today, activist investors promote positive changes, such as greater institutional commitment to environmental sustainability and diversity and inclusion, financial transparency, and more. has become more popular [ ] Image source However, the flawed nature of modern corporate governance limits the effectiveness of shareholder activism. Problems such as centralization of decision-making and inadequate participatory mechanisms reduce investor capacity to have their voice heard in corporate settings. Decentralized autonomous organizations (DAOs) are a new class of institutions that democratize corporate governance. DAOs operate on peer-to-peer protocols (like blockchains) and abandon hierarchical structures in favor of vertical power distribution. With their decentralized nature, DAOs can empower investors and create favorable conditions for shareholder activism. But, before we go further, let's look at shareholder activism in detail. What Is Shareholder Activism? According to Investopedia, a shareholder activist is "a person who attempts to use their rights as a shareholder of a publicly-traded corporation to bring about change within or for the corporation." The objectives of shareholder activists can vary between the financial (increasing investor dividends) and the non-financial (promoting employment diversity). Whatever the motive, shareholder activism is a major tool for investors to express their views on matters concerning a company. Mark Mobius, whom we earlier quoted, said of shareholder activism: "When we invest in a company, we own part of that company and we are partly responsible for how that company progresses. If we believe something is going wrong with the company, then we, as shareholders, must become active and vocal." [ ] Image source Shareholder activism exists because investors cannot always trust company management to act in their best interests. This problem is captured in a strand of political-economic theory known as the "principal-agent problem." In a principal-agent arrangement, the agent is allowed to make legally binding decisions on behalf of the principal. However, a problem occurs when the interests of the agent aren't aligned with those of the principal. Rogue agents may use their proxy power to authorize decisions that benefit them at the expense of principals. The principal-agent problem is often on full display in companies where the agent (an elected board of directors) may be at odds with the principal (shareholders). In absence of effective checks, company directors might pursue policies that harm investor interests. Shareholder activism prevents corporate management from running rampant and executing selfish action (like taking fat compensation packages). However, modern-day shareholder activists need better tools if they are to successfully force change. The Many Problems of Traditional Corporate Governance In most cases, investors looking to participate in company decision-making have to wait until the Annual General Meeting (AGM). The AGM is a yearly ritual with the outlined purposes of providing up-to-date information on company activity, enabling discussion, and facilitating voting on important decisions, like mergers or appointments. AGMs are ideal for shareholder activists because it provides a forum to air concerns and, more importantly, allow them to table or vote on proposals. However, modern-day AGMs fail to deliver on their promises and stifle shareholder participation. [ ] Image source For starters, the limited timeframe of these yearly meetings makes it impossible for an extended discussion on issues. With mere hours to cover a large agenda, activist investors may be prevented from sparking a debate around pressing matters. We also have the problem of logistics. Not every investor is able—or willing—to travel miles to a company's HQ to sit through a half-day meeting. Doing so may be sensible for large shareholders, but smaller shareholders may deem the cost too high, leading to at shareholder voting sessions. massive declines in turnout Companies have tried to solve this problem by introducing proxy voting. Here, investors receive documents outlining issues under consideration, before the meeting. They can choose to vote on these proposals through mail or via the agreed electronic system. However, proxy voting has flaws. For instance, there's no way for shareholders to verify if votes were correctly counted and ballot results represent the majority's wishes. The notorious case of Procter & Gamble vs Nelson Peltz illustrates this point: On the heels of its 2017 shareholder meeting, Procter & Gamble that shareholders had voted to reject activist investor Nelson Peltz's bid to join the company's board of directors. However, an independent audit P&G's claim and instead awarded the victory to Peltz, leading to the latter's . announced disputed appointment to the board [ ] Image source Scenarios like the one described above discourage well-meaning investors from exercising their rights as part owners of a company. We have seen the major problems with modern-day governance, namely: Annual shareholder meetings are limited avenues for discussion due to their short duration Logistical costs (time, travel, effort) prevent shareholders, especially retail investors, from participating in meetings Proxy voting systems are susceptible to mismanagement and may disenfranchise voters These problems exist because the thinking around companies and governance has remained unchanged for years. For example, article 70 of the UK's 1856 states: Joint Stock Companies Act "Once at the least in every year the directors shall lay before the company in general meeting a statement of the income and expenditure for the past year, made up to a date not more than three months before such meeting." What's surprising here is that sections of the 2006 contain very similar provisions. These two laws may have been enacted centuries apart, but they share the same flawed thinking. UK Companies Act Improving corporate governance and enhancing shareholder activism in corporations requires novel solutions that empower stakeholders and facilitate transparent decision-making. As Albert Einstein noted, "we cannot solve our problems with the same thinking that created them." This is where DAOs come into the picture. Why Shareholder Activism Needs DAOs A DAO is a collective of individuals who pool resources together to achieve specific objectives. This could be governance (Aragon), provision of financial services (MakerDAO), or in the case of BanklessDAO, media production and education. DAOs are like companies, except they operate differently. Instead of issuing shares, a DAO sells tokens to prospective members (investors). These tokens confirm holders' membership of the DAO and empower them to participate in governance. In a DAO, power is distributed across the membership. Every decision must be ratified by the majority of token holders, and no entity can arbitrarily make decisions on behalf of others. Moreover, any member can initiate proposals and seek support from their colleagues. The rules governing a DAO are encoded into a smart contract and recorded on a transparent and immutable blockchain, preventing any alterations (except when agreed on by the majority). Voting is conducted on-chain, with DAOs allowing stakeholders to cast their votes in an open, decentralized, and secure process. [ ] An example DAO governance process. Image source DAOs solve the principal-agent problem by distributing decision-making power across board. There is no board of directors or CEO calling the shots and pulling the strings for private benefits. More importantly, DAOs streamline corporate governance and make it easier for investors to initiate or weigh in on proposals. DAOs are location-agnostic institutions and mostly operate through online forums and social networks like Discord. This reduces participation barriers, promoting higher stakeholder engagement in discussion and decision-making. Besides, DAOs encourage members to submit proposals and give feedback regularly—which means no one has to wait months to table important matters before other stakeholders. The involving the Ethereum Name Service (ENS) and its Director of Operations Bryant Millegan is a good example of how DAOs make it easier to call for changes in an organization. case After Millegan was accused of homophobia and misogyny over a series of resurfaced tweets, DAO members initiated a proposal for his removal. Here's a screenshot showing the final results of that proposal: Now, Millegan eventually held on to his position because the majority voted in his favor. But to focus on the failure to remove him is to miss the forest for the trees. In a traditional organization, a proposal to remove a high-ranking member would've been a drawn-out process doomed to fail. Or, the decision would've been placed in the hands of a board whose decision may fail to reflect the majority's wish. However, the ENS DAO's flexible governance structure allowed members to initiate a proposal for change. More importantly, it allowed the entire community to coordinate and express their position on the issue . seamlessly This is why DAOs matter for activist investors. Finally, it's important to note that the use of on-chain voting in DAOs increases the integrity of shareholder voting. Thus, it becomes difficult for the management to manipulate results to block activist efforts, as P&G did with Nelson Peltz. Already, voting tools like Snapshot and Tally ease voting on proposals for DAO participants. Since blockchain transactions can be viewed by anyone, voters can verify results for themselves. And cryptographic security mechanisms make information stored on blockchains immune to alteration. Why Don't We Just DAO It? The idea of using blockchain technology to improve corporate governance has old origins. In his 2016 , Vice Chancellor J. Travis Laster called modern shareholder voting a 'daisy-chained system of share ownership', describing blockchain technology as a "superior external solution" to problems confronting corporate governance. Council of Institutional Investors Keynote Speech While early experiments at mixing company ownership with blockchains, such as , failed—the industry has matured since then. Today, there are more DAOs than ever, bringing together people from different backgrounds to coordinate and produce value. The DAO If applied correctly, DAOs have the potential to give power back to investors and strengthen their capacity to positively influence company policies. Shareholder activism won't be limited to hedge funds and deep-pocketed investors anymore; retail investors, too, can make their voices heard on issues. There's still a long road before DAOs become mainstream and provide these benefits. However, if the last years have shown us anything, it's that transformation is starting to happen quickly. With time, DAOs may replace traditional companies—and shareholders will be better off for it. Cover image courtesy of Financial News

Using DAOs for Shareholder Activism to Overcome Traditional Corporate Governance

Labor shortages and rising transportation costs are pushing consumer brands to increase efficiency. Having the right stock on the shelves is more important than ever, and the growing demand for data-driven insights is inspiring new AI-based predictive solutions. In 2021, the producer price index, a measure of wholesale prices for goods and services, 9.7%. Due to supply chain issues and inflation, many big consumer brands have raised their prices. This trend is projected to continue through the coming year. was up In March, Kraft Heinz plans to on several of their products, ranging from a 6.6% increase on Velveeta cheese to a 30% increase for a three-pack of Oscar Mayer turkey bacon. Procter & Gamble, too, price hikes on fabric care products, such as Tide detergent and Downy dryer sheets, coming at the end of February. raise prices announced But higher prices alone aren’t enough to fight inflation or guarantee a net profit. Shoppers can turn to cheaper alternatives. That’s where technology comes in: to help brands stay ahead of the competition. AI could help big companies increase efficiency with better inventory management, improved customer experience, and data-driven insights. Not only do the major consumer brands feel squeezed from inflation; the private labels, too, have tried raising their prices to absorb the increasing cost of goods. However, these brands have less power and control over pricing in wholesale channels than the major brands. In a situation, where the margin squeeze is imminent and unavoidable, AI-powered merchandising could help private labels boost efficiency & sales. Predictive Merchandising Predictive merchandising is currently one of the most promising segments of the AI retail market, expected to reach 19.9 billion by 2027, according to a , published by Meticulous Research. new report Key companies operating in the space include Amazon.com, Google, Intel, Microsoft, IBM, Intel, Oracle, SAP, Salesforce, and others. But the field is dynamic — new players and solutions are emerging. For example, in early February, Onebeat, an AI-powered startup helping retailers and brands analyze their customers’ needs, received an initial $5 million round of funding. Pivot, a Miami-based startup allowing brands to pick the ideal location and in-store space to showcase their merchandise, raised a pre-seed venture capital round. And an AI-based SaaS startup, Inspector Cloud, which lets vendors receive insights to increase stock performance, recently raised a new round, bringing its total investment to $1.25 million. Using eleven different neural networks, Inspector Cloud recognizes goods, collects data, and provides reports. The platform also allows merchandisers and sales reps to save store visit time, eliminating the need for manual operations. Currently, around 40,000 merchandisers and sales reps around the world are using Inspector Cloud. The platform processes over 50 million images monthly. A few big FMCG companies, including PepsiCo, Unilever, and Nestle have already implemented the startup’s solution. Conclusion The future looks bright for AI-powered startups that provide predictive merchandising services. A recent study from IBM revealed that 72% of customers out of 19,000 people shop at physical stores, despite the preponderance of online-only options. Reasons given include touching and feeling products before buying them online. As long as consumers choose a hybrid shopping model, merchandising will keep driving sales. As a result, more brands and retailers will embrace AI to learn about their customers, receiving data-based insights and recommendations.

AI-Powered Predictive Merchandising is Shaping the Future of Shopping

Introduction Digital Product Management is a vast, diverse, and exciting field. It pays to have an outstanding product management team in a world where consumers can easily compare different products using the Internet. Digital Product Management means focusing on products that are on laptops, phones, tablets, and other devices. Take an app; for example, it could be a company's primary focus and cash count. A website is another example of a digital product. Expedia, Amex Travel Portal, Priceline, and Kayak are all examples of websites that are digital products. These travel search engines identified their need and built a product they believed could solve the customers. Of course, monetizing a product takes a little more finesse and creativity. A great product alone will not convince everyone equally to pay for a product in one single format. An exceptional product management team can manage the lifecycle of an existing product, scope new product ideas, validate those ideas through testing, and identify dependencies while building a product. We will cover many areas, including the role of a product manager, the other disciplines they might work closely with, their knowledge areas, what makes a great product and the tools product managers use. Lastly, this article will present . The made-up RFP will outline what the company wants to build or enhance, budget, current technology feasibility/infrastructure, and timeline. The mock response will include a product roadmap, work breakdown structure, a priority guide, and suggestions of technology implementations. The mock response to the RFP will incorporate many knowledge areas and justification using knowledge obtained from previous academic courses to explain the approach. a mock response to an RFP (Request for Proposal) Digital Product Management The Product Manager role is more well-known nowadays, and it shows an increasing amount of upskilling schools/courses centered around the product manager role. ProductSchool.com and Brainstation.io are two providers out of the many that offer certifications to complete their Product Management coursework. ProductSchool also provides their version of a constructive definition, yet simple, for a Product Manager. On page 10 of The Product Book, "Put simply, a product manager (PM) represents the customer" (Anon, Villaumbrosia, & Carlos, 2017). Although that definition might sound like they are oversimplifying the role of a Product Manager, the description does provide an excellent bottom-line understanding for those that would like to look into the ever-increasing in-demand role. A quick search on Glassdoor would reveal that a Product Manager role is #3 on the "Best Jobs in America for 2021" with a median base salary of $121,107. Glassdoor's grading criteria involve weighing earning potential, overall job satisfaction, and the number of job openings. The job satisfaction reported on Glassdoor isn't the highest at 3.9/5. Still, the other two factors, median base salary and 14,515 job openings, definitely contributed significantly to the PM role taking the #3 spot (Glassdoor, 2021). According to the Product Book and the LucidChart article, modern product management descended from the 'brand men' role created by Neil H. McElroy, the then president of Procter & Gamble in the 1930s. The 'brand men' role was mentioned in a memo by McElroy to be "uniquely responsible for a brand, from sales and marketing to client relationships" (McElroy & Rogan, 1931). Reading the original document by McElroy, one can get the sense that the main responsibility of a "Brand Man" is ensuring the good quality of their product. Then moving on to the third item of the responsibilities of the "Brand Man," McElroy also mentions identifying opportunities, doing a SWOT analysis, keep documentations, albeit not word for word. Still, these are vocabularies closely related to the modern Digital Product Manager. There are many different career paths one can follow to become a PM. The most obvious route is software engineer/developer turned product manager, or project manager turned product manager. Many product managers would also say they "happened upon" the role and didn't exclusively seek it out during a job search. Most start in a different position in an adjacent department like customer service, business, marketing, operations, or engineering. Figure one is an informative graph of a possible career path for a product manager. Figure 1- The Product Manager Career Path from LucidChart According to an article by 80,000.org, the modern Digital Product manager is considered "one of the best non-programming roles in the tech industry, and tech is one of the most attractive industries to work in" (Batty, 2016). Having development skills is a plus for the Digital Product manager, but we can go into more detail in the upcoming sections about knowledge areas. Ultimately, a digital product manager is responsible for building or developing a successful digital product. Digital Products include software tools, web/mobile applications, etc. One big difference between product managers and other tech professionals is that product managers aren't specialists in any given field. They are more of the quarterback involved with planning, strategizing, and communicating with everybody on a cross-functional team. The many interfaces could include engineering, design, customer success, sales, marketing, operations, finance, legal, and more. They don't necessarily decide what gets built because some organizations might have a Product Owner role for that type of responsibility. However, taking on a structured approach to innovating and ensuring product success is the critical responsibility of the product manager. The Product Manager and their teammates The many interfaces of a modern digital product manager could include the design team, engineering/development, data science/analytics, sales and marketing, finance, management, and even legal. The number of interfaces a product manager interacts with will depend on the scope of the product. An outstanding product manager will take advantage of everyone in the cross-functional team and even leverage resources outside of the team to help form better decisions. The product manager and the design team should work closely because UX/UI is a vast portion of a product. Great UX/UI affects desirability a considerable percentage of the time. It's important to understand that the design team's sole purpose is not to make designs pretty but also to build the best possible experience for users. This is where coming up with user personas, understanding user pain points, and identifying use cases are especially important. The product manager and design team have to ask difficult questions to make sure they fully understand the motivation behind the users. If the product manager and the design team must understand what the user wants, then a majority of figuring how to get there is the engineering team's job. Here, the product manager's job is to provide valuable information about the users, their motivation, and use cases to the engineering team. The engineering team will take this information and develop optimal implementation to build the necessary solution and simultaneously communicate tradeoffs. An important thing to note here is that product managers don't necessarily have to worry about the timelines of deliverables. However, they still have to communicate with all stakeholders to manage expectations. The timeframe of deliverables is usually a project manager's responsibility. The sales & marketing team's primary responsibility is taking a tested product with identified product-market fit to either bring to market or amplify growth. The product manager will provide the marketing team with user personas, behavior, and value propositions. An essential factor to a successful and robust interface is constant touchpoints with all your team members. Depending on resource allocation, your product team might afford a project manager and a data science professional. A project manager is a great resource to lean on when communicating dependencies for the product. They are also great to have on your side when managing the timeline and scope of the product development process. Data science professionals such as an analyst could be a robust interface when you can provide sufficient information for them to form a strong hypothesis. You could then determine how and what data to collect and hopefully iterate and act upon the data collected to improve the product. The Prompt StayWithUs Company: StayWithUs is a 20-year-old travel accommodation reservation company. We are one of the first companies to be on the market with a digital booking portal allowing our customers to find various accommodations for their vacations. Our strategy is to offer vast selections of travel accommodations, including hotels, beds and breakfasts, hostels, and individual hosts with unique stays. We currently operate solely in Canada and the U.S, with future operations on the horizon. StayWithUs now has 500k+ listings and 8 million registered users from Canada and the U.S. Background: The purpose of this RFP is to highlight and anticipate our company's need to have a mobile application on mobile devices for our users. We are currently experiencing rapid growth, and many investors have poured in money to help us scale and amplify growth. A mobile application is slowly trending up as a user-requested software obtained from surveys and through other forms of feedbacks. Current Architecture: We currently have a leading booking platform website that all our users use to book travel accommodations. The front-end is built with JavaScript/React, and the backend is built with Ruby and the Rails framework. We use MySQL for our database solution, and that's a relational database. These are the main technologies for our website to be functional. We don't foresee any drastic changes soon (3+/- years) that would call for a framework change or switching to a different front-end library. Our third-party vendors, not conclusive, include Google(for analytics), Amazon cloud services, Twilio, Mixpanel, GitHub, and many others. What we would like to see: We would like to see a proposal that includes, at a minimum, a product roadmap, work breakdown structure/package index, and a priority guide or wireframe. The mobile application should consist of all the functionalities our website can do. There is flexibility around what features should be on the mobile application, but please provide insights along with your recommendations. My Proposal to the Prompt I don't think it's best to work on a proposal in response to an RFP by yourself, but this is an excellent opportunity to practice and prepare for future case studies, whether for academia or professionally. First, one would read through an RFP thoroughly and filter some of the fluffs or unnecessary information that might not be pertinent to the work required. The client's useful information is their current software architecture and technology stack, where they operate, and a little bit of what they want us to build. We could use this information to produce more questions and request more requirements gathering sessions. The client sometimes approaches a digital product agency with a vague idea of what they want. They might have a list of business requirements that might not make much sense to a designer or engineer. However, we can view these business requirements from a customer/user's angle and help other team members understand better through use cases or user stories. Below are the we identified to be important to the client: four goals We need to allow users to search and make bookings with ease. We want our rewards program to provide value to our customers. We want or rewards program to encourage loyalty, retain customers, and increase usage of our mobile app. We want to provide added convenience to our customers through a mobile app without compromising on functionalities. After identifying the goals of the client's project, requirements are also equally important. Needs could come from the business/client, users, or technical standpoint. Another helpful way of thinking about requirements is that they could also be conditions in which the project must meet or work within. Below are the initial requirements we identified for this project: The client determines third-party vendors. The technology stack has to integrate well with the existing framework. Security measures have to meet or exceed current standards. The mobile app has to meet or exceed accessibility guidelines from A11Y. https://www.a11yproject.com/checklist/ The client determines collaboration software and will facilitate meetings between all vendors and our project team. Now that we finished identifying the goals and requirements of this project, we would usually move on to finalize the scope of an MVP. The MVP (minimum viable product) will be considered a Phase I release, and all additional enhancements/features will be added to future releases or later phases. Identifying an MVP helps us build a product that can immediately provide value to users, thus increasing the product's desirability. The product also has to be viable so the client can justify their spending. Below are other deliverables/outputs we would use to communicate with the client to help them visualize our vision. Other deliverables that could result from collaboration sessions with your team: Figure 2 — Priority Guide for StayWithUs Mobile App Figure 2 shows a priority guide for the StayWithUs Mobile App. A priority guide is similar to a wireframe in which it will communicate what components will need to be included on a specific screen. A wireframe will usually look very similar to a finished working product. Still, a significant benefit of using a priority guide instead is that it allows all collaborators to focus on the goal of each screen and experience. Often, when looking at wireframes, we might focus too much on the minute details of font type, sizes, shapes, and other texts that might change later. A priority guide will allow us to focus on user experience and ensure the screen we are working on helps us accomplish our goals. Figure 3 — Collaboration Output for StayWithUs Mobile App Figure 3 is a collection of sticky notes with ideas, questions, and assumptions. Some assumptions will need to be included in future fact-finding or requirements gathering sessions with the client to find out more information, and other assumptions might need to receive approval from the client. For example, our team assumes that the IOS version of the mobile app should be released first in Phase I due to the higher market share in North America, and that's also taking into account that our client's HQ and operations are located in North America. However, the client might have other ideas in mind which they might not have communicated during our first meeting (O'Dea, 2021). Figure 4 — Collaboration Session Output for StayWithUs Mobile App Figure 4 is output from feature prioritization. The client came to us with an RFP with a list of features they want, and we have to prioritize the features into different baskets. The Must-haves will make it into the MVP for Phase I release, and there's usually more wiggle room for the other two baskets. Sometimes it is also a good idea to suggest new features/enhancements that might increase the appeal or usage of the mobile app. Many people would consider push notifications as a standard enhancement, but it isn't a primary feature that the client needs. So push notifications might end up in Should-Haves after a few more requirements gathering sessions with the client/end-users. Authentication and authorization are essential to a business because they have to safeguard valuable data, and their customers also have privacy concerns. One could argue that users don't need to log in or register to make or view current bookings as long as they have a confirmation number. This would mean that anyone can view your booking information if they happen to come across your confirmation number. Another important reason to include authentication and authorization into Phase I is that the rewards program will depend on proper authentication and authorization. A mobile app user needs to register to enroll in the rewards program, and a user needs to log in to access their account information, which will include their loyalty tier. This also meets the client's business requirement of having their rewards program into the MVP. Other features like editing account information, preferred payment methods, and editing bookings could wait until later phases, as indicated in Figure 4. This is because the client's website offers these solutions, and we could allocate resources to build a great MVP without scattering our focus. It will undoubtedly cause minor inconvenience to our mobile app users, but sometimes the budget doesn't allow us to tackle too many items at once. Works Cited: Anon, J., Villaumbrosia, G. D., & Carlos. (2017). Product School. The Product Book: How to Become a Great Product Manager. Batty, R. (2016, 12). . Retrieved 11 21, 2021 80,000Hours, Product manager in tech Glassdoor. (2021). . Retrieved November 21, 2021 Glassdoor, 50 Best Jobs in America for 2021 McElroy, N., & Rogan, R. (1931, May 13). Marketing, Brand Teams. Nash, D. (2020, May 12). Retrieved 11 21, 2021 280Group, What is Digital Product Management? O'Dea, S. (2021, 08). . Retrieved from Statista: Subscriber share held by smartphone operating systems in the United States from 2012 to 2021 https://www.statista.com/statistics/266572/market-share-held-by-smartphone-platforms-in-the-united-states/ Team, L. C. (n.d.). . Retrieved 11 21, 2021 LucidChart, The Product Manager Career Path van Nues, H., & Overkamp, L. (2018, 5 3). . Retrieved 11 21, 2021 A List Apart, Priority Guides: A Content-First Alternative to Wireframes

How to Approach A Case Study For A Product Management Interview

Early adopters of the Internet of Things (IoT) are more likely to stay ahead of the competition with enormous data that they can act upon before the competition understands what’s at stake. A rising shift towards edge computing is a revolutionary opportunity that can potentially prove to be a substantial competitive advantage. Organizations in today’s world operate with data and advanced business solutions within the enterprise, in the cloud, and at customer touchpoints using edge devices. These devices often create new technologies such as the Internet of Things (IoT). To enable a quick and reliable decision-making process, integrating IoT devices with conventional cloud-based enterprise data is becoming increasingly crucial for small, medium, or large organizations. The projected to reach USD 8.21 billion by 2027, according to Emergen Research, which is why it’s not surprising that numerous organizations are engaged in developing applications that support these devices. IoT integration essentially means generating a mix of new IoT devices, IoT platforms, IoT data, and IoT applications in combination with IT assets that work seamlessly in the context of implementing end-to-end IoT business applications. Most businesses have plans to deploy IoT shortly, with 82% already connected to IoT. If Google’s acquisition of smart thermostat, Nest, for USD 3.2 billion is anything to go by, IoT is set to be the next big disruptor in technology. Internet of Things (IoT) Integration market Internet of Things – An Abstract IoT or Internet of Things is a suite of smart connected devices that transmit data over a network without needing any human intervention. In the consumer market, IoT technology is synonymous with products related to the concept of smart homes, such as devices and appliances that support one or more ecosystems and can be accessed and controlled via devices related to that ecosystem such as smartphones or smart speakers. Kevin Ashton of Procter & Gamble and later of MIT’s Auto-ID Center coined the term “Internet of Things” in 1999. At that time, he considered Radio Frequency Identification (RFID) as an essential aspect to the Internet of Things, allowing computers to handle thins independently. Some of the most popularly used IoT devices are smartwatches, Fitbits, smart televisions, electric meters, smart lights, and voice assistants, among others. The Crucial IoT Integration Scenario Businesses are extensively relying on IoT technology with organizations now focusing on cloud-native technology that is a perfect fit for the IoT technology as it allows rapid and precise integration of applications and cloud for driving better decision-making solutions and actionable business insights. Such quick integration capabilities are incredibly beneficial in the rapidly developing world of device data generation for several industry verticals such as healthcare, transportation, manufacturing, energy, hospitality, etc. According to the Perficient guide ‒ “The Why, What and How of IoT,” “Integration enables capturing data from smart devices and moving it into business applications to automate processes, support real-time monitoring, and apply analytics for insights.” IoT and integration are two peas in a pod. With IoT, companies are now shifting towards cloud-based systems to enable the digital transformation of the business sphere. IoT Integration is about application programming interfaces (APIs), the logical connectors that allow applications to communicate with IoT devices. APIs access data that will enable devices to transmit data to the applications, essentially acting as a data interface or enable the application to control the device, and acts as a functional interface. Connecting Conventional Systems and IoT Devices Large enterprises are revamping their product portfolio and customer experiences using IoT platform devices. From edge devices, such as point-of-sale (POS) systems and retail sensors to portable devices like medical devices and wearable devices, all devices can be transformed into one giant integrated system. This deep integration can allow firms to mine the big data generated to comprehend the customers’ preferences and alter the portfolio to efficiently deliver the products and services in demand. Challenges associated with IoT Integration While the enterprises are actively starting their IoT journeys, they still don’t fully comprehend the integration challenges it will give rise to in the future. For instance, the large volume of data generated by IoT devices can be overwhelming at times. Additionally, the cost associated with developing an integration platform to address complicated IoT projects can be financially stressful on an organization. Businesses often face a plethora of challenges when integrating data and devices on an IoT platform. One of the significant challenges faced is the integration of operational technology (OT) and information technology (IT). It is, however, imperative that there is minimal loss of data and security vulnerabilities during the process. Security The majority of the firms using IoT devices in the United States have faced a major security breach leading to massive revenue losses. This is one of the crucial challenges faced by firms during IoT integration. This can be because IoT systems often fail to get periodic security updates, thereby increasing their vulnerability to a data breach and malware attacks. Data Integration Enterprises struggle to cope with the enormous amount of data generated by the disparate sensors and devices. With each IoT system equipped with numerous sensors, the need to clean the data by eliminating redundant or unusable data is more challenging. API-based IoT networks come to play here. They enable easy communication between smart devices and minimize data discrepancies. Combating the IoT Integration Challenges with iPaaS As the business landscape expands, the number of IoT devices also increase exponentially. The Internet of Things covers numerous devices, a wide range of APIs, and an enormous amount of data. This data needs to be gathered, processed, analyzed and distributed efficiently. However, traditional platforms are not equipped to deal with these needs. This is where the iPaaS platform plays an integral role. Integrated Platform-as-a-Service (iPaaS) offers a cloud service for application, data process, and is a set of automated tools that connect software applications to be deployed in varied environments. iPaaS provides organizations access to advanced integration capabilities that allow them to incorporate multiple workflows and IoT projects. It enables enterprises to facilitate data integration amongst sensors, devices, and enterprise systems, in a way that the “things” can be used to maximum potential to automate processes to enable rapid exchange of data. iPaaS solutions offer other advanced features like multiple-user management, usage audit logs and granular monitoring that enables seamless and real-time communication between IoT services, devices and other applications. The demand for iPaaS is predominantly driven by the need for agile platforms, fast deployment, enhanced scalability, minimal costs, and optimum resource utilization. In conclusion, iPaaS provides comprehensive flexibility while simultaneously catering to the progressive nature of the digital transformation needs of an organization. Bottom Line IoT has a plethora of benefits and abilities, and integration works to keep the IoT on a forward path. Capturing IoT’s complete ability needs a flexible ecosystem with integration at its core to gather and distribute data for automation and analysis.

IoT Integration: A New Era of Digital Transformation 

While product management enjoys unquestioned support in the world’s most successful tech companies, other organisations that could substantially benefit from product management are still yet to adopt and embrace the discipline. So, I want to go through why you need product management in your tech or digital organisation. Product management isn’t a new discipline. It began around 1931, starting with a memo from Neil McElroy at Procter & Gamble (P&G) about the need to hire people to own and understand P&G’s individual brands (products). Hewlett-Packard later credited this approach as a key piece of its success and combined it with Kaizen’s methods (think continuous improvement) out of the Toyota Way. More recently, the Agile Manifesto helped it evolve further. It has been heavily adopted by the likes of Google, Airbnb, Facebook, Netflix and others. Product management has become a distinct function alongside engineering and marketing (rather than falling into one or the other), often reporting directly to the CEO ( for a detailed history read The History and Evolution of Product Management by Martin Eriksson ). So, what is product management exactly? Let’s look at a brief definition before we jump into why it is needed. What is Product Management? Product management is a discipline focused on (our customers choose to buy or use), (the solution works within the many constraints of the business), (the user can figure out how to use), and (our engineers, staff and capabilities are able to deliver on). creating products or services that are valuable viable usable feasible Source: Marty Cagan The key to this definition is the cross-cutting nature of product management, stretching from engineering and technology through to go-to-market, usability and business models. Organisations without product management often have disciplines, functions, and roles focusing on each element, but nothing bringing it together. To round this out, that is a bit more verbose and focused on specific activities, but helps provide more of a sense of what product management is: “product management is an organisational function within a company dealing with new product development, business justification, planning, verification, forecasting, pricing, product launch and marketing of a product at all stages of the product lifecycle.” Wikipedia provides a definition Another diagram that adds more detail to the previous one on where product management fits: Source: Mironov Why You Need Product Management If your organisation delivers on your value proposition to your customers solely or primarily through your product(s), then you need product management. Websites, apps, APIs and technology platforms often are product for many organisations. Customers and users primarily buy, interact and experience an organisation through these channels. the Meaning you require the discipline of considering your customers’ needs (or users or citizens), alongside technology, in line with your business’s needs. This discipline, as outlined above, is called product management. Without this discipline (or role), you will likely have a disjointed approach. Sales, marketing and support will take the view of the customer, but they’ll view it through their own objectives and issues without an idea of what’s technically possible. Engineering, technology and operations will want to build and often lack a strong understanding of the customer. The executive team and the business will have goals and objectives that may not account for a strong enough voice of the customer or a full appreciation of the feasibility. To add some colour to this, here is of the value that the discipline of product management provided to an organisation. They needed to allow their customers to customise and rebrand some of the emails the product sent. The team and management had many months of requirements planned to provide extensive customisation – some were seriously technically challenging. a concrete example An experienced product manager joined the team, interviewed a handful of their customers and cut the roadmap down to a single requirement: just let the customer change their logo. This was easy to implement, and customers loved it because they could “customise” as much as they needed. They just wanted their logo, not font, colour and layout changes. And, they needed this customisation before they could really use the product. of the value of product management is where an organisation’s commercial goals meant that it wanted a product in a specific, complementary market. Rather than selling to businesses, they wanted to go direct to the consumer. For the business, at a macro-level, this made sense: “we can own the relationship with the consumer”, “we can leverage our operating capabilities in [large scale finance activity]”. Another example However, a disciplined approach to product management revealed technical challenges and operating capabilities needed to serve consumers that just weren’t present within the organisation. Product management also yielded a large gap between the strategy the business wanted to pursue and what consumer customers really wanted. F.A.Q. You or your colleagues might still be questioning the value of product management in your organisation. There are a few common questions and objections that come up: 1. We don’t have customers, we have citizens, members or something else. This doesn’t change the logic of needing the discipline of product management. Just focus them on the citizen (or member) rather than the customer. 2. The customer or product is owned by another department. Some digital teams trying to implement best practice face the challenge of other departments having a product manager who owns the product, such as in a bank where a product manager owns the credit card. The discipline of product management is still needed within the digital team for digital products in these instances. The digital product is often the way the customer interacts or is enabled. Given the revenue and opportunities on the line, it’s worthwhile investing in ensuring the digital component of the offering is as best as it can be. 3. But we already have a project manager looking after XYZ initiative or system. Product management is heavily focused on ensuring you do the right work, whereas project management is heavily focused on ensuring the work is done right. They are complementary roles, both needed for successful outcomes.

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