Business Automation Quotes

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Anything that can be automated, cognified, decentralized, digitized, disintermediated or virtualized will be.

Techistentialism studies the nature of human beings, existence, and decision-making in our technological world. Today, we face both technological and existential conditions that can no longer be separated. We define this phenomenon as Techistentialism.

AI won’t replace humans, but people who can use it will.” This sounds reassuring, but it oversimplifies the complex future of work and AI integration. Experts predict a surge in opportunities, but the intricate interplay between cognification, mass automation, and how we work remains uncharted. The net effect of AI on employment is unknown - we have no data on the future.

Maybe the existential risk is not machines taking over the world, but rather the opposite, where humans start responding like idle machines - unable to connect the emerging dots of our UN-VICE world.

Automation is cost cutting by tightening the corners and not cutting them.

Artists, musicians, composers and writers are all experiencing upheaval which could match that of a factory becoming automated.

Many presume that integrating more advanced automation will directly translate into productivity gains. But research reveals that lower-performing algorithms often elicit greater human effort and diligence. When automation makes obvious mistakes, people stay attentive to compensate. Yet flawless performance prompts blind reliance, causing costly disengagement. Workers overly dependent on accurate automation sleepwalk through responsibilities rather than apply their own judgment.

A true revolution of values will soon look uneasily on the glaring contrast of poverty and wealth. With righteous indignation, it will look at thousands of working people displaced from their jobs with reduced incomes as a result of automation while the profits of the employers remain intact, and say: “This is not just.” It will look across the oceans and see individual capitalists of the West investing huge sums of money in Asia, Africa and South America, only to take the profits out with no concern for the social betterment of the countries, and say: “This is not just.” It will look at our alliance with the landed gentry of Latin America and say: “This is not just.” The Western arrogance of feeling that it has everything to teach others and nothing to learn from them is not just. A true revolution of values will lay hands on the world order and say of war: “This way of settling differences is not just.” This business of burning human beings with napalm, of filling our nation’s homes with orphans and widows, of injecting poisonous drugs of hate into the veins of peoples normally humane, of sending men home from dark and bloody battlefields physically handicapped and psychologically deranged cannot be reconciled with wisdom, justice and love. A nation that continues year after year to spend more money on military defense than on programs of social uplift is approaching spiritual death. America, the richest and most powerful nation in the world, can well lead the way in this revolution of values. There is nothing to prevent us from paying adequate wages to schoolteachers, social workers and other servants of the public to insure that we have the best available personnel in these positions which are charged with the responsibility of guiding our future generations. There is nothing but a lack of social vision to prevent us from paying an adequate wage to every American citizen whether he be a hospital worker, laundry worker, maid or day laborer. There is nothing except shortsightedness to prevent us from guaranteeing an annual minimum—and livable—income for every American family. There is nothing, except a tragic death wish, to prevent us from reordering our priorities, so that the pursuit of peace will take precedence over the pursuit of war. There is nothing to keep us from remolding a recalcitrant status quo with bruised hands until we have fashioned it into a brotherhood.

As a new entrepreneur, you're probably gonna have to hustle hard to get things going at first. But as the business grows and becomes more established, that unrefined hustle should be replaced by automated profit-producing processes and systems. Hustle is good as a temporary mode of operating, but it's unsustainable long term and unprofitable long term.

As we face inseparable technological and existential conditions, we enter an era of Techistentialism. AI will increasingly provide insights that enable more-informed predictive decision-making, humans should remain wary of an inadvertent reliance on prescriptive algorithms dictating specific decisions. Complex and uncertain environments inherently involve unknown unknowns; these are situations where we need to be agile despite the lack of immediate answers.

Paradox of Automation: the more efficient the Automated system, the more crucial the contribution of the human operators of that system.

Plus, from my experience, for most problems, AI development is the easy part. The hard part? Everything else that goes around it. For example, how do you find the right problems to solve?

Recognizing your own progress is a huge part of feeling motivated to do more. Your brain is a great tool for your success. It is hard at work and automating the new things you are doing even when you are taking a break.

Where workers do lose their jobs due to automation, it’s not because they themselves are replaced by some piece of software. It’s often because the firms they work for fail. And the firms they work for fail because their management or shareholders are unwilling or unable to keep up with the new possibilities of technology. That failure often extends to failing to invest in the training that their employees need to implement the latest technologies.

The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency. —BILL GATES,

It is useful for companies to look at AI through the lens of business capabilities rather than technologies. Broadly speaking, AI can support three important business needs: automating business processes, gaining insight through data analysis, and engaging with customers and employees.

A Checklist is an Externalized, predefined Standard Operating Procedure for completing a specific task. Creating a Checklist is enormously valuable for two reasons. First, Checklisting will help you define a System for a process that hasn’t yet been formalized—once the Checklist has been created, it’s easier to see how to improve or Automate the system. Second, using Checklists as a normal part of working can help ensure that you don’t forget to handle important steps that are easily overlooked when things get busy.

Automation promises to execute certain tasks with superhuman speed and precision. But its brittle limitations reveal themselves when the unexpected arises. Studies consistently show that, as overseers, humans make for fickle partners to algorithms. Charged with monitoring for rare failures, boredom and passivity render human supervision unreliable.

Although inefficiencies present themselves in different ways, AI can be a great tool to automate repetitive and time-consuming work where human-level decision-making is involved.

The good news is that you can minimize the bias preserved by AI, but this comes as a joint responsibility between leaders, domain experts, and developers.

The human job losses we’ve seen were primarily due to attrition of workers who were not replaced or through automation of outsourced work.

I began looking for these four: Smart. It doesn’t mean high IQ (although that’s great), it means disposed toward learning. If there’s a best practice anywhere, adopt it. We want to turn as much as possible into a routine so we can focus on the few things that require human intelligence and creativity. A good interview question for this is: “Tell me about the last significant thing you learned about how to do your job better.” Or you might ask a candidate: “What’s something that you’ve automated? What’s a process you’ve had to tear down at a company?” Humble. I don’t mean meek or unambitious, I mean being humble in the way that Steph Curry is humble. If you’re humble, people want you to succeed. If you’re selfish, they want you to fail. It also gives you the capacity for self-awareness, so you can actually learn and be smart. Humility is foundational like that. It is also essential for the kind of collaboration we want at Slack. Hardworking. It does not mean long hours. You can go home and take care of your family, but when you’re here, you’re disciplined, professional, and focused. You should also be competitive, determined, resourceful, resilient, and gritty. Take this job as an opportunity to do the best work of your life. Collaborative. It’s not submissive, not deferential—in fact it’s kind of the opposite. In our culture, being collaborative means providing leadership from everywhere. I’m taking responsibility for the health of this meeting. If there’s a lack of trust, I’m going to address that. If the goals are unclear, I’m going to deal with that. We’re all interested in getting better and everyone should take responsibility for that. If everyone’s collaborative in that sense, the responsibility for team performance is shared. Collaborative people know that success is limited by the worst performers, so they are either going to elevate them or have a serious conversation. This one is easy to corroborate with references, and in an interview you can ask, “Tell me about a situation in your last company where something was substandard and you helped to fix it.

One way of saving on energy use would be to do away with unnecessary transportation. For instance, people commute between work and home, or travel long distances to engage in business conferences. With the development of improved communications and increasing automation, it will become possible in the not-too-distant future, for people to control and maintain business operations and machinery at a distance.

When you feel the need to escape your problems, to escape from this world, don't make the mistake of resorting to suicide Don't do it! You will hear the empty advice of many scholars in the matter of life and death, who will tell you, "just do it" there is nothing after this, you will only extinguish the light that surrounds you and become part of nothingness itself, so when you hear these words remember this brief review of suicide: When you leave this body after committing one of the worst acts of cowardice that a human being can carry out, you turn off the light, the sound and the sense of reality, you become nothing waiting for the programmers of this game to pick you up from the darkness, subtly erase your memories and enable your return and I emphasize the word subtle because sometimes the intelligence behind this maneuver or automated mechanism is wrong and send human beings wrongly reset to such an extent, that when they fall to earth and are born again, they begin to experience memories of previous lives, in many cases they perceive themselves of the opposite sex, and science attributes this unexplainable phenomenon to genetic and hormonal factors, but you and I know better! And we quickly identified this trigger as a glitch in the Matrix. Then we said! That a higher intelligence or more advanced civilization throws you back into this game for the purpose of experimenting, growing and developing as an advanced consciousness and due to your toxic and destructive behavior you come back again but in another body and another life, but you are still you, then you will carry with you that mark of suicide and cowardice, until you learn not to leave this experience without having learned the lesson of life, without having experienced and surprised by death naturally or by design of destiny. About this first experience you will find very little material associated with this event on the internet, it seems that the public is more reserved, because they perceive themselves and call themselves "awakened" And that is because the system has total control over the algorithm of fame and fortune even over life and death. Now, according to religion and childish fears, which are part of the system's business to keep you asleep, eyes glued to the cellular device all day, it says the following: If you commit this act of sin, you turn off light, sound and sense of reality, and from that moment you begin to experience pain, fear and suffering on alarming scales, and that means they will come for you, a couple of demons and take you to the center of the earth where the weeping and gnashing of teeth is forever, and in that hell tormented by demons you will spend eternity. About this last experience we will find hundreds of millions of people who claim to have escaped from there! And let me tell you that all were captivated by the same deity, one of dubious origin, that feeds on prayers and energetic events, because it is not of our nature, because it knows very well that we are beings of energy, then this deity or empire of darkness receives from the system its food and the system receives from them power, to rule, to administer, to control, to control, to kill, to exclude, to inhibit, to classify, to imprison, to silence, to infect, to contaminate, to depersonalize. So now that you know the two sides of the same coin, which one will your intelligence lean towards! You decide... Heads or tails? From the book Avatars, the system's masterpiece.

A use case is a description of the way that an automated system is used. It specifies the input to be provided by the user, the output to be returned to the user, and the processing steps involved in producing that output. A use case describes application-specific business rules as opposed to the Critical Business Rules within the Entities.

In Webvan’s case premature scaling was an integral part of the company culture and the prevailing venture capital “get big fast” mantra. Webvan spent $18 million to develop proprietary software and $40 million to set up its first automated warehouse before it had shipped a single item. Premature scaling had dire consequences since Webvan’s spending was on a scale that ensures it will be taught in business school case studies for years to come. As customer behavior continued to differ from the predictions in Webvan’s business plan, the company slowly realized it had overbuilt and over-designed. The business model made sense only at the high volumes predicted on the spreadsheet.

THE RIVE BROTHERS used to be like a technology gang. In the late 1990s, they would jump on skateboards and zip around the streets of Santa Cruz, knocking on the doors of businesses and asking if they needed any help managing their computing systems. The young men, who had all grown up in South Africa with their cousin Elon Musk, soon decided there must be an easier way to hawk their technology smarts than going door-to-door. They wrote some software that allowed them to take control of their clients’ systems from afar and to automate many of the standard tasks that companies required, such as installing updates for applications. The software became the basis of a new company called Everdream, and the brothers promoted their technology in some compelling ways.

Why does Joe Normie think it’s a litmus test for morality if one returns one’s shopping cart? Big-box stores put out of business local retailers, they automated their systems to reduce employees, and they got customers to be their own cashiers without getting paid for their labor, and yet to prove I’m a good person, I’m supposed to do more unpaid work for them to streamline their operation?

Kensi Gounden, Highly innovative new technologies can be both disruptive and transformative, but technology adoption can also be incremental, such as simply automating a manual process. So introducing business technology innovations, either incremental or step-change, may embrace increasing online connectivity across the business, strategic technology acquisition and use or using time-saving technologies to improve internal communication.

If You Only Track Five Metrics… Track as many of these as you can in your sales force automation system’s dashboards: New leads created per month (also, from what source). Conversion rate of leads to opportunities. Number of, and pipeline dollar value of, qualified opportunities created per month. This is the most important leading indicator of revenue! Conversion rates of opportunities to closed deals. Booked revenues in three categories: New Business, Add-On Business, Renewal Business.

Simon Leigh Pure Reputation, The Role of AI in Online Reputation Management (ORM) Artificial Intelligence (AI) plays a transformative role in Online Reputation Management by automating monitoring, analysis, and response to online content. AI-powered tools scan social media, review platforms, forums, and news sites in real time to detect mentions of a brand or individual. Through sentiment analysis, AI evaluates whether the mentions are positive, negative, or neutral, helping businesses gauge public perception instantly. AI also enables predictive analytics, identifying emerging reputation risks before they escalate. Chatbots and automated response systems use natural language processing (NLP) to manage customer interactions quickly and consistently. Additionally, AI supports content generation and SEO optimization, ensuring positive brand stories and authoritative profiles rank higher in search results. Overall, AI enhances ORM by making it faster, data-driven, and proactive, allowing organizations to protect and strengthen their digital reputation efficiently.

Humpty-Dumpty is the familiar example of the clown unsuccessfully imitating the acrobat. Just because all the King’s horses and all the King’s men couldn’t put Humpty-Dumpty together again, it doesn’t follow that electromagnetic automation couldn’t have put Humpty-Dumpty back together. The integral and unified egg had no business sitting on a wall anyway. Walls are made of uniformly fragmented bricks that arise with specialisms and bureaucracies. They are the deadly enemies of integral beings like eggs. Humpty-Dumpty met the challenge of the wall with a spectacular collapse.

Listen,” said Aurora, hands up, like a policeman halting traffic. “Everyone stop saying cat.” The men went silent. Aurora took a deep breath. “Do you know why we have the Australia Cards? The universal basic income?” “Dunno,” said Jack. “Charity, I suppose.” “Yes,” said Minh. “Why?” “Well—you ever notice the biggest supporters of a universal wage aren’t charities or churches?” “Nah,” said Tommy. “It’s those rich bastards.” “Exactly. Silicon Valley. The banks. You know why? They need customers for the businesses they own, and they own bloody everything. They need our disposable income. But there’s no jobs anymore, the automation they invented took them all. Forty percent unemployment, half the rest working part-time gigs. So: they lobbied the government to give out free money.

GET BEYOND THE ONE-MAN SHOW Great organizations are never one-man operations. There are 22 million licensed small businesses in America that have no employees. Forbes suggests 75 percent of all businesses operate with one person. And the average income of those companies is a sad $44,000. That’s not a business—that’s torture. That is a prison where you are both the warden and the prisoner. What makes a person start a business and then be the only person who works there? Are they committed to staying small? Or maybe an entrepreneur decides that because the talent pool is so poor, they can’t hire anyone who can do it as well as them, and they give up. My guess is the latter: Most people have just given up and said, “It’s easier if I just do it myself.” I know, because that’s what I did—and it was suicidal. Because my business was totally dependent on me and only me, I was barely able to survive, much less grow, for the first ten years. Instead I contracted another company to promote my seminars. When I hired just one person to assist me out of my home office, I thought I was so smart: Keep it small. Keep expenses low. Run a tight ship. Bigger isn’t always better. These were the things I told myself to justify not growing my business. I did this for years and even bragged about how well I was doing on my own. Then I started a second company with a partner, a consulting business that ran parallel to my seminar business. This consulting business quickly grew bigger than my first business because my partner hired people to work for us. But even then I resisted bringing other people into the company because I had this idea that I didn’t want the headaches and costs that come with managing people. My margins were monster when I had no employees, but I could never grow my revenue line without killing myself, and I have since learned that is where all my attention and effort should have gone. But with the efforts of one person and one contracted marketing company, I could expand only so much. I know that a lot of speakers and business gurus run their companies as one-man shows. Which means that while they are giving advice to others about how to grow a business, they may have never grown one themselves! Their one-man show is simply a guy or gal going out, collecting a fee, selling time and a few books. And when they are out speaking, the business terminates all activity. I started studying other people and companies that had made it big and discovered they all had lots of employees. The reality is you cannot have a great business if it’s just you. You need to add other people. If you don’t believe me, try to name one truly great business that is successful, ongoing, viable, and growing that doesn’t have many people making it happen. Good luck. Businesses are made of people, not just machines, automations, and technology. You need people around you to implement programs, to add passion to the technology, to serve customers, and ultimately to get you where you want to go. Consider the behemoth online company Amazon: It has more than 220,000 employees. Apple has more than 100,000; Microsoft has around the same number. Ernst & Young has more than 200,000 people. Apple calls the employees working in its stores “Geniuses.” Don’t you want to hire employees deserving of that title too? Think of how powerful they could make your business.

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There's a clear link between this cultural pattern and Germany's place in history as one of the first countries in the world to become heavily industrialized. Imagine being a factory worker in the German automative industry. If you arrive at work four minutes late, the machine for which you are responsible gets started late, which exacts a real, measurable financial cost. To this day, the perception of time in Germany is partially rooted in the early impact of the industrial revolution, where factory work required the labor force to be on hand and in place at a precisely appointed moment. In other societies -particularly in developing world- life centers around the fact of constant change. As political systems shift and financial systems alter, as traffic surges and wanes, as monsoons or water shortages raise unforeseeable challenges, the successful managers are those who have developed the ability to ride out the changes with ease and flexibility.

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The cheerleaders of the new data regime rarely acknowledge the impacts of digital decision-making on poor and working-class people. This myopia is not shared by those lower on the economic hierarchy, who often see themselves as targets rather than beneficiaries of these systems. For example, one day in early 2000, I sat talking to a young mother on welfare about her experiences with technology. When our conversation turned to EBT cards, Dorothy Allen said, “They’re great. Except [Social Services] uses them as a tracking device.” I must have looked shocked, because she explained that her caseworker routinely looked at her purchase records. Poor women are the test subjects for surveillance technology, Dorothy told me. Then she added, “You should pay attention to what happens to us. You’re next.” Dorothy’s insight was prescient. The kind of invasive electronic scrutiny she described has become commonplace across the class spectrum today. Digital tracking and decision-making systems have become routine in policing, political forecasting, marketing, credit reporting, criminal sentencing, business management, finance, and the administration of public programs. As these systems developed in sophistication and reach, I started to hear them described as forces for control, manipulation, and punishment

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For a well-defined, standard, and stable process involving hand-offs between people and systems, it is preferable to use a smart workflow platform. Such platforms offer pre-developed modules. These are ready-to-use automation programs customized by industry and by business function (e.g., onboarding of clients in retail banking). In addition, they are modular. For example, a module might include a form for client data collection, and another module might support an approval workflow. In addition, these modules can be linked to external systems and databases using connectors, such as application programming interfaces (APIs), which enable resilient data connectivity. Hence, with smart workflows, there is no need to develop bespoke internal and external data bridges. This integration creates a system with high resiliency and integrity. In addition, the standardization by industry and function of these platforms, combined with the low-code functionality, helps to accelerate the implementation.

There are no ready-to-use modules with RPA. Most of the development is bespoke, and all process flows need to be built almost from scratch. The connections also need to be constructed. This results in a more flexible design and implementation of the programs developed, which can fit with more specific business requirements. The key advantage of RPA is that it allows the creation of automation programs that can involve legacy systems (e.g., those which can’t use APIs) or address non-standard requirements (e.g., onboarding of clients for a broker insurance company under Singapore regulations). However, with RPA, the lack of native integration amongst the components has weaknesses. For example, it involves less robustness, weaker data integrity, and lower resilience to process changes. If one part of an RPA program fails, the whole end-to-end process is stopped. As an outcome, based on our experience, the leading practice is to use low-code and smart workflow platforms as a foundation of the overall automation platform. In contrast, RPA is used for any integration of the overall platform with legacy systems or for automation of bespoke processes.

Algorithms are to white-collar workers what tractors were to farmers: a tool to dramatically increase the productivity of each worker, and thus shrink the total number of workers required to produce the same output. But unlike tractors, algorithms can be shipped instantly around the world at no additional cost. Once an algorithm has been sent out to millions of users, it can be continuously updated and improved with no need to create a new physical product.

Today, more people die from overwork and stress than from wars. More than 75 percent of people are dissatisfied with their jobs, which they view as too tedious and repetitive. Countries are facing growing debts, a constant fear of a coming recession, and later retirement ages. The cost of human error and fraud is almost equivalent to the total amount of money allocated globally to education.

All businesses are going digital: the winners will be those who do so the quickest and to the greatest extent. It may be informed speculation to say the landscape of companies will change dramatically over the next few decades. Still, one thing is sure: the winners – even the survivors – will be highly automated, with the bare minimum of human involvement.

Deloitte survey also shows that the benefits of adopting IA are significant. Participants reported that payback was less than 12 months, with an average of 20% of full-time equivalent (FTE) capacity provided by IA programs. Automation met and even exceeded expectations in many areas, including improved compliance (92%), quality and accuracy (90%), productivity (86%), and reduced costs (59%).35 According to a study by Statista, 84% of business organizations adopt AI because it gives them a competitive advantage over their rivals.36

3.1. New digital business building Insurance companies, banks, energy providers, and incumbent telecommunication companies need to digitalize their businesses to stay competitive against new pure digital entrants. In most cases, the fastest and most efficient way to achieve this is not to digitalize their existing business, but to create entirely new digital businesses that are highly automated.

3. What do employees expect as an experience? 69% of employees expect that automation will give them more time to do their primary job duties, and 86% of employees think the use of automation in the workplace will let them think of work in new and innovative ways.55 The question is then, besides removing tedious tasks, what would make people happier and more engaged at work? Studies have found that people like to have opportunities to solve problems in their work. Also, variety among tasks at work leads to increased happiness and higher productivity.56 Based on these findings, the promise of IA to change how people work seems a welcome development. Based on our research, the employee experience would be improved by switching to the “ideal” daily division of activities,

4. The potential levers to improve employees’ experience We have identified three levers to enable the transition from the current breakdown of employee activities to the ideal division of activities. They are: Automate: companies should identify and automate routine activities, such as generating a PowerPoint presentation for a weekly meeting or recording invoices in accounting software. Augment: organizations should seize the opportunity to increase the value of work activities delivered by employees. IA is used as a crucial component here, with, for example, the generation of insights through advanced analytics to help decision making. Abandon: some work activities do not fit with leading practices for efficient work, and represent an obstacle to the employee’s experience. These activities should be reduced or eliminated. For example, restricting the volume of meetings and email traffic is essential. We call these levers the “Triple-A artifact”. It has proven to be a handy framework to help organizations build their action plans to boost their employee experience.

IA not only makes transaction processes more efficient, but it also generates log files for every action, creating transparency and ease of compliance. Machine learning leverages the digital information created by these programs to recognize predictive patterns and project trends.

The cost of errors is enormous: o Medical errors in the US incur an estimated economic value of almost USD 1 trillion78 – and 86% of those mistakes are administrative.79 o 80% of US medical billings contain at least minor mistakes – creating unnecessary annual healthcare spending of $68 billion.80

4. When to use RPA versus smart workflow platforms? These technologies can be used interchangeably. The leading practice is to use smart workflow and low-code platforms as a foundation of the overall automation platform. RPA is used when IA needs to be integrated with legacy systems or automation of bespoke processes.

As an outcome, based on our experience, the leading practice is to use low-code and smart workflow platforms as a foundation of the overall automation platform. In contrast, RPA is used for any integration of the overall platform with legacy systems or for automation of bespoke processes.

For example, regressions support workforce planning to ensure adequate staffing, or the identification of the talents that an organization should retain based on relevant traits, practices, and skills. Other applications include predicting the level of liquidity required for a finance department based on trends in disbursement.

Decision trees are not new; what machine learning brings here is the capacity to identify the optimal split of the problem into relevant questions and connect them together in a logical way to achieve a final decision.

In other words, it is about finding homogeneous subgroups within the data. Some uses of clustering algorithms include network traffic classification, document categorization, gene clustering, or product categorization.

Deep learning techniques are used when data features are numerous and there is a lack of domain understanding to identify and understand them. This data is typically complex, such as images, videos, or voice recordings. For example, an image contains an indefinite amount of data features (e.g., points, edges, shapes, or objects), and some are relevant to the problem being solved, but others are not. Deep learning is used to solve problems such as image classification, natural language processing, and speech recognition.

In conclusion, smaller companies with a limited budget might opt for open source platforms. Larger, more established, and more demanding companies would typically go with a commercial platform, enabling them to connect their different applications under the same roof. Companies with high growth objectives should leverage scalable cloud-based platforms.

Another common issue is the lack of interdisciplinarity in the transformation. In our experience, the highest impact is the result of multi-lever end-to-end process automation – not small, siloed implementations, focused on one single technology lever. To achieve this, management should advocate for getting the right talents from across the different parts of an organization to work together (e.g., data scientists, developers, business analysts). Interdisciplinarity is also about avoiding limiting the transformation to the implementation of one single technology lever (e.g., RPA), and about implementing IA on end-to-end processes instead of only a few process tasks. By combining talents and technology levers and targeting end-to-end processes, the organization will create synergies, build economies of scale, and remove potential bottlenecks. Organizations failing to achieve this are not able to scale their IA transformation.

The absence of appropriate project governance results in a lack of monitoring of the impact generated by the transformation, and confusion between the roles of the different actors on the project. Most

some work activities are displaced, but new ones, more fulfilling and value-adding, arise. What are the new ones? Think of these activities that everyone knows are crucial, but that actually none has the time to perform – for example, spending one hour per week with each team member to coach them.

As emphasized in the critical success factors related to “Management support, vision, governance, and structure” earlier in this section, a leading practice to secure support from management is to provide a high-level estimation of the benefits expected from the transformation. This is often referred to as a “high-level automation assessment” or a “top-down automation assessment”. For example, such an estimation might show that, by leveraging IA, the organization has the potential to increase revenue by 20% while reducing costs by 30% in the coming 18 months.

Maintaining an automated process is estimated to be about 20% of the initial implementation cost per year.

The tone comes from the top”: As with any transformation that brings structural changes to an organization, top management support is a prerequisite to succeed at any IA transformation.

Think big, start small, and scale fast”: Initiate the transformation with the definition of a multi-year, company-wide vision, roadmap, and business case. These plans need to be flexible and adaptable. Then, “start small” with the implementation of a pilot, and take the time to learn from this first experience. Finally, implement the broader scope in stages to manage the risks. Gradually increase the speed and scale of the transformation, and as a result, generate high impact. “IA is a business transformation, not a technology project”: The perspective of business benefits should guide the transformation. This transformation involves not only technology, but more importantly, people – with change management, and retraining – and processes – with redesigns. “IA is a journey, not a destination”: IA is not a one-off exercise; it is a never-ending transformation journey. It continually brings additional benefits to the organization by applying evolving concepts, methods, and technologies. Hence, building teams with the right skills to guide the company in this transformation is critical. “Infusing IA into the culture of the company”: Implementing IA with siloed, isolated teams does not work. Automation needs to be infused into the company. Change management, education, empowerment, and incentivization of everyone in the company is vital. Every employee should know what IA is and what its benefits are, and be empowered and incentivized to identify use cases and build automation.

IA initiatives have to be sponsored by the highest level of management in the company (i.e., its C-levels). Management is supported by a documented vision (strategic objectives of the transformation), business case (estimating the benefits and costs of the project), and a high-level roadmap (key milestones of the implementation for the coming 1 to 3 years). The design of the program is a top-down exercise, while the implementation is a bottom-up one (e.g., it starts with the deployment of a pilot).

The talent required within the CoE is wide and ranges from business and operations excellence to risk and IT departments. According to McKinsey’s survey, the CoE of top-performing companies includes a large variety of profiles such as delivery managers, data scientists, data engineers, workflow integrators, system architects, developers, and, most critically, translators and business analysts.152 A

The long tail of lower-value automation opportunities should involve less focus on the redesign. The value will be captured through the systematic use of the lean methodology to improve the processes incrementally (e.g., simplify, reduce the number of actions).

Leveraging the support from consulting and delivery partners (they can be the same) is critical for gaining the right momentum in the organization with minimum investment.

That unregulated automation could be bad for workers is also the instinct of most Americans on the right and the left. One place, remarkably, where Republican and Democrat poll respondents agree is in their opposition to letting companies decide how much to automate. Eighty-five percent of Americans would support limiting automation to “dangerous and dirty jobs,” with no difference between Democrats and Republicans. Even when the question is posed in a more politically pointed way, asking whether “there should be limits on the number of jobs businesses can replace with machines, even if they are better and cheaper than humans,” 58 percent of Americans, including half of Republicans, say yes.

Step by Step… Can you write out your ideal business step by step Here is a business I am setting up for a client. She wants to shipping start her own shipping company… One she will need a US partner to collect and transfer packages to her in Jamaica. She will also need one in China. I have two contacts. One has a warehouse in Florida The other has two in China. Chinese connect makes goods available within 3 weeks, she has to tell her customers four. The US connect makes it within 3-5 days. She has to tell them within a week… Next she will need a website where her customers can login and track their packages. This will come with individual dashboards. She will need an interface and warehouse management software and logistics APIs. She will also need an automated email set up (journey) to send emails to her customers without her or her agents needing to do that. Without this Saas she would have to hire someone to reply to messages and emails about , someone to call and track, use usps and FedEx tracking numbers to track and reply back to customers. She also needs a beta ApI to allow her warehouse guy to update the CRM with information about her customers packages… Key nodes such as - Intransit to destinations Held at customs Clearance In transit to store Pick up available etc… These will come in as email notifications Fully automated. Everything will be connected using Webhooks… entire system. Saas she might need to use a combination of GOhighlevel, Workiz and To run this as a System as as Service. Each platform can work together using webhooks. Gohighlevel as a Saas is $500 a month Workiz is $200 dollars She can use Odoo which is open source alternative as a CRM And Clickup as Management. This is how a conversational business plan looks. You can see it. You can research it. You can confirm that it’s plausible. It doesn’t sound like pipedreams. It sounds workable to credit companies /banks and investors. It sounds doable to a BDO Client. I also sound as if I know what I am doing. Not a lot of technical language. A confused prospective business investor or banker don’t want to use a dictionary to figure out everything… They want to see the vision as clear as day. You basically need to do to them what I did to you when you joined my programme. It must sound plausible. All businesses is a game of wit. Every deal that is signed benefits both party. Whether initially or in the long term. Those are the sub-tenets of business. Every board meeting or meeting with regulatory boards, banks, credit facilities, municipalities is a game of convincing people to see your thing through… Everyone does Algorithm is simple. People want you to solve their problems with speed and efficiency. Speed is very important and automation. Progress, business and production are tied to ego… that’s why people love seh oh dem start a business or dem have dem online business and nah sell one rass thing. Cause a lot of people think being successful and looking successful are one and the same thing until they meet someone like me or people who done the work… Don’t rush it… you are young and you have time. There are infact certain little nuances Weh yuh only ago learn through experience. Experience and reflection. One of the drawbacks of wanting to run your business by yourself with you and your family members is that you guys will have to be reliant on yourself for feedback which is not alw

Myth—DevOps is Just “Infrastructure as Code” or Automation: While many of the DevOps patterns shown in this book require automation, DevOps also requires cultural norms and an architecture that allows for the shared goals to be achieved throughout the IT value stream. This goes far beyond just automation.

Spending some additional money to get high-quality products will give more profit. But anyway, it is not true that expensive products are high-quality products. Even an inexpensive or cheap product can be high-quality if it meets the Customer’s needs/expectations.

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Event Rental Systems provides software for party rental and bounce house companies. ERS offers web-based software packages that allow bounce house rental businesses to run on near auto-pilot. The goal of the software is to boost sales while automating and digitizing all tasks related to a party rental business.

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But what aren't you doing already? What more can you possibly do?’ ‘I guess he means the team stuff’, I said. ‘The bonding. The camaraderie I've never really been –‘. ‘Don't start judging yourself’, she said sharply. ‘Don't start seeing yourself in the light of those kinds of standards.’ ‘No, but it's true. There's always been the part of work I've struggled with, the unquestioning side. The feeling of joining in. I've always tried to do it at this kind of remove. Maybe what he's saying is –‘ ‘Of course you've done it at a remove. How else are you supposed to do it and still be you?’ ‘But maybe those days are gone’, I said. ‘Maybe I have to accept that. Maybe there just won't be those kind of jobs anymore - the ones where you can roll out of bed and staggering without speaking to anyone and keep your head down and just do it, you know? maybe this is what work is, now’ […] ‘Definitely. Simple tasks can be automated. They've already almost got the machine learning to do what you do. It's about what else a human can bring to the table, which is, literally, their humanity.’ It was possible, I realised, to imagine. A semi-global future in which the bulk of paid human employment would revolve not around hard skills, but around the messy, blurry business of interpersonal success. A new divide would open up, between the well liked, The easy to get along with, and the awkward, The rude, the unfriendly. I pictured the encampment on which I had lived, filled not as it was then, with migrants, unfortunates, hard drinkers, the out of luck. But instead, the abrasive, the poorly adjusted, the excessively reserved and painfully shy. (p.136-7)

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Engineering autonomy in healthcare solutions must be a human-centered process. Engineers should not conflate automation, where AI can consistently repeat a task, with AI having autonomy. Humans must remain in the loop.

the roughly $800 billion in available stimulus, we directed more than $90 billion toward clean energy initiatives across the country. Within a year, an Iowa Maytag plant I’d visited during the campaign that had been shuttered because of the recession was humming again, with workers producing state-of-the-art wind turbines. We funded construction of one of the world’s largest wind farms. We underwrote the development of new battery storage systems and primed the market for electric and hybrid trucks, buses, and cars. We financed programs to make buildings and businesses more energy efficient, and collaborated with Treasury to temporarily convert the existing federal clean energy tax credit into a direct-payments program. Within the Department of Energy, we used Recovery Act money to launch the Advanced Research Projects Agency–Energy (ARPA-E), a high-risk, high-reward research program modeled after DARPA, the famous Defense Department effort launched after Sputnik that helped develop not only advanced weapons systems like stealth technology but also an early iteration of the internet, automated voice activation, and GPS.

IA automates knowledge workers’ activities by mimicking four main capabilities: Vision (e.g., viewing the environment, recognizing objects and signs), Execution (e.g., typing, clicking, filling in forms, and authenticating), Language (e.g., using language to read, speak, write, and interact), and Thinking and learning (e.g., analyzing, creating insight, predicting, making decisions, and adjusting).