What is Cognitive Automation? Evolving the Workplace

These AI assistants possess the ability to understand and interpret customer queries, providing relevant and accurate responses. They can even analyze sentiment, ensuring that customer concerns are addressed with empathy and understanding. The result is enhanced customer satisfaction, loyalty, and ultimately, business growth. Step into the realm of technological marvels, where the lines between humans and machines blur and innovation takes flight. Welcome to the world of AI-led Cognitive Process Automation (CPA), a groundbreaking concept that holds the key to unlocking unparalleled efficiency, accuracy, and cost savings for businesses. At the heart of this transformative technology lies the secret to empowering enterprises into navigating the future of automation with confidence and clarity.

Cognitive automation is an extension of existing robotic process automation (RPA) technology. Machine learning enables bots to remember the best ways of completing tasks, while technology like optical character recognition increases the data formats with which bots can interact. Cognitive automation adds a layer of AI to RPA software to enhance the ability of RPA bots to complete tasks that require more knowledge and reasoning. The potential of intelligent AI assistants extends across various industries. In healthcare, these AI co-workers can revolutionize patient care by processing vast amounts of medical data, assisting in accurate diagnosis, and even predicting potential health risks.

Organizations can monitor these batch operations with the use of cognitive automation solutions. Various combinations of artificial intelligence (AI) with process automation capabilities are referred to as cognitive automation to improve business outcomes. The company implemented a cognitive automation application based on established global standards to automate categorization at the local level. The incoming data from retailers and vendors, which consisted of multiple formats such as text and images, are now processed using cognitive automation capabilities. The local datasets are matched with global standards to create a new set of clean, structured data. This approach led to 98.5% accuracy in product categorization and reduced manual efforts by 80%.

What is the goal of cognitive automation?

Since cognitive automation can analyze complex data from various sources, it helps optimize processes. CPA tools primarily contribute to a significant enhancement in efficiency and productivity. By automating cognitive tasks, they can eradicate human errors and reduce manual labor. With automation taking care of repetitive and time-consuming tasks, employees can concentrate on activities that require human judgment and creativity. This redistribution of resources can propel overall operational efficiency and expedite business outcomes.

In this article, we embark on a journey to demystify CPA, peeling back the layers to reveal its fundamental principles, components, and the remarkable benefits it brings. When introducing automation into your business processes, consider what your goals are, from improving customer satisfaction to reducing manual labor for your staff. Consider how you want to use this intelligent technology and how it will help you achieve your desired business outcomes. It mimics human behavior and intelligence to facilitate decision-making, combining the cognitive ‘thinking’ aspects of artificial intelligence (AI) with the ‘doing’ task functions of robotic process automation (RPA). Through cognitive automation, enterprise-wide decision-making processes are digitized, augmented, and automated.

Read “The Nail in the ‘I Can’t do Automation’ Coffin”Want to learn more about Digital Coworkers in your business? Cognitive automation typically refers to capabilities offered as part of a commercial software package or service customized for a particular use case. For example, an enterprise might buy an invoice-reading service for a specific industry, which would enhance the ability to consume invoices and then feed this data into common business processes in that industry. Through this data analysis, cognitive automation facilitates more informed and intelligent decision-making, leading to improved strategic choices and outcomes. It streamlines operations, reduces manual effort, and accelerates task completion, thus boosting overall efficiency. The foundation of cognitive automation is software that adds intelligence to information-intensive processes.

For example, if there is a new business opportunity on the table, both the marketing and operations teams should align on its scope. They should also agree on whether the cognitive automation tool should empower agents to focus more on proactively upselling or speeding up average handling time. For example, in an accounts payable workflow, cognitive automation could transform PDF documents into machine-readable structure data that would then be handed to RPA to perform rules-based data input into the ERP.

The human element–that expert mind that is able to comprehend and act on a vast amount of information in context–has remained essential to the planning and implementation process, even as it has become more digital than ever. It represents a spectrum of approaches that improve how automation can capture data, automate decision-making and scale automation. It also suggests a way of packaging AI and automation capabilities for capturing best practices, facilitating reuse or as part of an AI service app store. It is used to streamline operations, improve decision-making, and enhance efficiency through the integration of AI technologies, leading to optimized workflows, reduced manual effort, and a more agile response to dynamic market demands. Cognitive automation enhances the customer experience by providing accurate responses, round-the-clock support, and personalized interactions. This results in increased customer satisfaction, loyalty, and a positive brand image, ultimately leading to business growth and a competitive advantage in the market.

They make it possible to carry out a significant amount of shipping daily. The Cognitive Automation solution from Splunk has been integrated into Airbus’s systems. Splunk’s dashboards enable businesses to keep tabs on the condition of their equipment and keep an eye on distant warehouses. These processes need to be taken care of in runtime for a company that manufactures airplanes like Airbus since they are significantly more crucial. “The whole process of categorization was carried out manually by a human workforce and was prone to errors and inefficiencies,” Modi said. Cognitive RPA can not only enhance back-office automation but extend the scope of automation possibilities.

Cognitive automation is the strategic integration of artificial intelligence (AI) and process automation, aimed at enhancing business outcomes. In the realm of HR processes such as candidate screening, resume parsing, and employee onboarding, CPA tools can automate various tasks. With the implementation of AI-powered assistants, companies can analyze job applications, match candidates with suitable roles, and automate repetitive administrative tasks. This frees up HR professionals to focus on strategic initiatives like talent development and employee engagement. Even if the RPA tool does not have built-in cognitive automation capabilities, most tools are flexible enough to allow cognitive software vendors to build extensions.

RPA vendors embracing cognitive

Manual duties can be more than onerous in the telecom industry, where the user base numbers millions. A cognitive automated system can immediately access the customer’s queries and offer a resolution based on the customer’s inputs. A new connection, a connection renewal, a change of plans, technical difficulties, etc., are all examples of queries. Intending to enhance Bookmyshow‘s client interactions, Splunk has provided them with a cognitive automation solution. Make automated decisions about claims based on policy and claim data and notify payment systems. You can check our article where we discuss the differences between RPA and intelligent / cognitive automation.

However, cognitive automation extends the functional boundaries of what is automated well beyond what is feasible through RPA alone. RPA automates routine and repetitive tasks, which are ordinarily carried out by skilled workers relying on basic technologies, such as screen scraping, macro scripts and workflow automation. RPA performs tasks with more precision and accuracy by using software robots. But when complex data is involved it can be very challenging and may ask for human intervention.

This creates a whole new set of issues that an enterprise must confront. Depending on where the consumer is in the purchase process, the solution periodically gives the salespeople the necessary information. This can aid the salesman in encouraging the buyer just a little bit more to make a purchase. Once implemented, the solution aids in maintaining a record of the equipment and stock condition.

By augmenting human cognitive capabilities with AI-powered analysis and recommendations, cognitive automation drives more informed and data-driven decisions. Its systems can analyze large datasets, extract relevant insights and provide decision support. Cognitive process automation starts by processing various types of data, including text, images, and sensor data, using techniques like natural language processing and machine learning. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

• Let’s see some of the cognitive automation examples for better understanding.
• These are the solutions that get consultants and executives most excited.
• Cognitive automation describes diverse ways of combining artificial intelligence (AI) and process automation capabilities to improve business outcomes.
• New insights could be revealed thanks to cognitive computing’s capacity to take in various data properties and grasp, analyze, and learn from them.
• Comparing RPA vs. cognitive automation is “like comparing a machine to a human in the way they learn a task then execute upon it,” said Tony Winter, chief technology officer at QAD, an ERP provider.

Intelligent automation is undoubtedly the future of work and companies that forgo adoption will find it difficult to remain competitive in their respective markets. A cognitive automation solution is a positive development in the world of automation. The way RPA processes data differs significantly from cognitive automation in several important ways. However, if you are impressed by them and implement them in your business, first, you should know the differences between cognitive automation and RPA.

Cognitive computing systems become intelligent enough to reason and react without needing pre-written instructions. Workflow automation, screen scraping, and macro scripts are a few of the technologies it uses. To assure mass production of goods, today’s industrial procedures incorporate a lot of automation. In this situation, if there are difficulties, the solution checks them, fixes them, or, as soon as possible, forwards the problem to a human operator to avoid further delays. You can foun additiona information about ai customer service and artificial intelligence and NLP. Additionally, it can gather and save staff data generated for use in the future. In this article, we embark on a journey to delve into the world of Cognitive Process Automation and its profound influence across diverse industries.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem’s work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

This synergy between human intelligence and artificial intelligence is what makes CPA a game-changer in today’s business world. In contrast, Modi sees intelligent automation as the automation of more rote tasks and processes by combining RPA and AI. These are complemented by other technologies such as analytics, process orchestration, cognitive process automation BPM, and process mining to support intelligent automation initiatives. Meanwhile, hyper-automation is an approach in which enterprises try to rapidly automate as many processes as possible. This could involve the use of a variety of tools such as RPA, AI, process mining, business process management and analytics, Modi said.

The Symphony of Cognitive Process Automation

Furthermore, scalability should be a primary consideration, opting for tools that can manage escalating workloads and support the organization’s expansion. By assessing these aspects, organizations can make informed decisions and choose the most appropriate CPA tools for enhanced productivity and efficiency. Deloitte explains how their team used bots with natural language processing capabilities to solve this issue. You can also check our article on intelligent automation in finance and accounting for more examples. “We see a lot of use cases involving scanned documents that have to be manually processed one by one,” said Sebastian Schrötel, vice president of machine learning and intelligent robotic process automation at SAP. These tasks can range from answering complex customer queries to extracting pertinent information from document scans.

This makes it easier for business users to provision and customize cognitive automation that reflects their expertise and familiarity with the business. In practice, they may have to work with tool experts to ensure the services are resilient, are secure and address any privacy requirements. For maintenance professionals in industries relying on machinery, cognitive automation predicts maintenance needs. It minimizes equipment downtime, optimizes performance, and allowing teams to proactively address issues before they escalate. By automating tasks that are prone to human errors, cognitive automation significantly reduces mistakes, ensuring consistently high-quality output.

It also helps organizations identify potential risks, monitor compliance adherence and flag potential fraud, errors or missing information. ‍RPA is a phenomenal method for automating structure, low-complexity, high-volume tasks. It can take the burden of simple data entry off your team, leading to improved employee satisfaction and engagement. He focuses on cognitive automation, artificial intelligence, RPA, and mobility. Yet the way companies respond to these shifts has remained oddly similar–using organizational data to inform business decisions, in the hopes of getting the right products in the right place at the best time to optimize revenue.

It not only answers routine questions but also learns and adapts, becoming more efficient with each interaction. Data mining and NLP techniques are used to extract policy data and impacts of policy changes to make automated decisions regarding policy changes. While chatbots are gaining popularity, their impact is limited by how deeply integrated they are into your company’s systems. For example, if they are not integrated into the legacy billing system, a customer will not be able to change her billing period through the chatbot.

From customer service to fraud detection and decision support, CPA is revolutionizing various industries and unlocking new opportunities for growth. As organizations embrace this transformative technology, it is crucial to balance the benefits of automation with ethical considerations and human-AI collaboration, ensuring a future where CPA enhances our lives and work. It combines elements of AI and automation to emulate human thought processes in decision-making and problem-solving.

NLP and ML algorithms classify the conveyed emotions, attitudes or opinions, determining whether the tone of the message is positive, negative or neutral. Like our brains’ neural networks creating pathways as we take in new information, cognitive automation makes connections in patterns and uses that information to make decisions. It uses AI algorithms to make intelligent decisions based on the processed data, enabling it to categorize information, make predictions, and take actions as needed. Consider you’re a customer looking for assistance with a product issue on a company’s website. Instead of waiting for a human agent, you’re greeted by a friendly virtual assistant. They’re phrased informally or with specific industry jargon, making you feel understood and supported.

Cognitive automation can also use AI to support more types of decisions as well. For example, a cognitive automation application might use a machine learning algorithm to determine an interest rate as part of a loan request. These skills, tools and processes can make more types of unstructured data available in structured format, which enables more complex decision-making, reasoning and predictive analytics. The same is true with Robotic Process Automation (also referred to as RPA). The phrase conjures up images of shiny metal robots carrying out complex tasks. Especially if you’re not intimately familiar with the tech industry and its automated contributors, Robotic Process Automation probably sounds impressive.

This not only enhances the overall speed and effectiveness of operations but also fuels innovation and drives organizational success. If your organization wants a lasting, adaptable cognitive automation solution, then you need a robust and intelligent digital workforce. That means your digital workforce needs to collaborate with your people, comply with industry standards and governance, and improve workflow efficiency. By automating cognitive tasks, organizations can reduce labor costs and optimize resource allocation. Automated systems can handle tasks more efficiently, requiring fewer human resources and allowing employees to focus on higher-value activities. Training AI under specific parameters allows cognitive automation to reduce the potential for human errors and biases.

This can include automatically creating computer credentials and Slack logins, enrolling new hires into trainings based on their department and scheduling recurring meetings with their managers all before they sit at their desk for the first time. Craig Muraskin, Director, Deloitte LLP, is the managing director of the Deloitte U.S. Innovation group. Craig works with Firm Leadership to set the group’s overall innovation strategy. He counsels Deloitte’s businesses on innovation efforts and is focused on scaling efforts to implement service delivery transformation in Deloitte’s core services through the use of intelligent/workflow automation technologies and techniques. Craig has an extensive track record of assessing complex situations, developing actionable strategies and plans, and leading initiatives that transform organizations and increase shareholder value. As a Director in the U.S. firm’s Strategy Development team, he worked closely with executive, business, industry, and service leaders to drive and enhance growth, positioning, and performance.

The emerging trend we are highlighting here is the growing use of cognitive technologies in conjunction with RPA. But before describing that trend, let’s take a closer look at these software robots, or bots. RPA is best deployed in a stable environment with standardized and structured data.

For instance, at a call center, customer service agents receive support from cognitive systems to help them engage with customers, answer inquiries, and provide better customer experiences. According to experts, cognitive automation is the second group of tasks where machines may pick up knowledge and make decisions independently or with people’s assistance. Additionally, large RPA providers have built marketplaces so developers can submit their cognitive solutions which can easily be plugged into RPA bots.

An organization invests a lot of time preparing employees to work with the necessary infrastructure. Asurion was able to streamline this process with the aid of ServiceNow‘s solution. The Cognitive Automation system gets to work once a new hire needs to be onboarded. Let’s see some of the cognitive automation examples for better understanding. This is where Cognitive Process Automation (CPA) strides in as a game-changer. CPA is like having an intelligent assistant in the customer service team.

Traditional RPA usually has challenges with scaling and can break down under certain circumstances, such as when processes change. However, cognitive automation can be more flexible and adaptable, thus leading to more automation. Cognitive automation has the potential to completely Chat PG reorient the work environment by elevating efficiency and empowering organizations and their people to make data-driven decisions quickly and accurately. The coolest thing is that as new data is added to a cognitive system, the system can make more and more connections.

Cognitive automation can use AI techniques in places where document processing, vision, natural language and sound are required, taking automation to the next level. Cognitive automation performs advanced, complex tasks with its ability to read and understand unstructured data. It has the potential to improve organizations’ productivity by handling repetitive or time-intensive tasks and freeing up your human workforce to focus on more strategic activities. As CIOs embrace more automation tools like RPA, they should also consider utilizing cognitive automation for higher-level tasks to further improve business processes. Another viewpoint lies in thinking about how both approaches complement process improvement initiatives, said James Matcher, partner in the technology consulting practice at EY, a multinational professional services network. Process automation remains the foundational premise of both RPA and cognitive automation, by which tasks and processes executed by humans are now executed by digital workers.

Accounting departments can also benefit from the use of cognitive automation, said Kapil Kalokhe, senior director of business advisory services at Saggezza, a global IT consultancy. For example, accounts payable teams can automate the invoicing process by programming the software bot to receive invoice information — from an email or PDF file, for example — and enter it into the company’s accounting system. In this example, the software bot mimics the human role of opening the email, extracting the information from the invoice and copying the information into the company’s accounting system. Many organizations are just beginning to explore the use of robotic process automation.

TalkTalk received a solution from Splunk that enables the cognitive solution to manage the entire backend, giving customers access to an immediate resolution to their issues. Identifying and disclosing any network difficulties has helped TalkTalk enhance its network. As a result, they have greatly decreased the frequency of major incidents and increased uptime.

In contrast, cognitive automation excels at automating more complex and less rules-based tasks. Cognitive automation unleashes high levels of efficiency and productivity. Mundane and time-consuming tasks that once burdened human workers are seamlessly automated, freeing up valuable resources to focus on strategic initiatives and creative endeavors.

Once a cognitive automation platform understands how to operate the enterprise’s processes autonomously, it can also offer real-time insights and recommendations on actions to take to improve performance and outcomes. Cognitive automation describes diverse ways of combining artificial intelligence (AI) and process automation capabilities to improve business outcomes. Ability to analyze large datasets quickly, cognitive automation provides valuable insights, empowering businesses to make data-driven decisions. This leads to better strategic planning, reduced risks, and improved outcomes. Intelligent automation streamlines processes that were otherwise composed of manual tasks or based on legacy systems, which can be resource-intensive, costly and prone to human error. The applications of IA span across industries, providing efficiencies in different areas of the business.

Cognitive technologies extending RPA’s reach

Some examples of mature cognitive automation use cases include intelligent document processing and intelligent virtual agents. Deploying cognitive tools via bots can be faster, easier, and cheaper than building dedicated platforms. By “plugging” cognitive tools into RPA, enterprises can leverage cognitive technologies without IT infrastructure investments or large-scale process re-engineering. Therefore, businesses that have deployed RPA may be more likely to find valuable applications for cognitive technologies than those that have not. Picture a world where customer interactions are elevated to a whole new level. With cognitive automation powering intuitive AI co-workers, businesses can engage with their customers in a more personalized and meaningful manner.

With AI, organizations can achieve a comprehensive understanding of consumer purchasing habits and find ways to deploy inventory more efficiently and closer to the end customer. As the predictive power of artificial intelligence is on the rise, it gives companies the methods and algorithms necessary to digest huge data sets and present the user with insights that are relevant to specific inquiries, circumstances, or goals. RPA is limited to executing preprogrammed tasks, whereas cognitive automation can analyze data, interpret information, and make informed decisions, enabling it to handle more complex and dynamic tasks. Cognitive automation streamlines operations by automating repetitive tasks, quicker task completion and freeing up human for more complex roles. This efficiency boost results in increased productivity and optimized workflows.

Business analysts can work with business operations specialists to “train” and to configure the software. Because of its non-invasive nature, the software can be deployed without programming or disruption of the core technology platform. Comparing RPA vs. cognitive automation is “like comparing a machine to a human in the way they learn a task then execute upon it,” said Tony Winter, chief technology officer at QAD, an ERP provider. Cognitive automation maintains regulatory compliance by analyzing and interpreting complex regulations and policies, then implementing those into the digital workforce’s tasks.

Furthermore, CPA allows organizations to manage and analyze large volumes of data more efficiently. The pursuit of efficiency, cost reduction, and streamlined operations is unceasing and CPA is reshaping how businesses manage intricate and repetitive tasks. CPA is not just a tool but a strategic asset that can significantly enhance business operations. It’s like having an extra pair of hands that are not only capable but also intelligent, learning from each interaction to become more efficient.

What we know today as Robotic Process Automation was once the raw, bleeding edge of technology. Compared to computers that could do, well, nothing on their own, tech that could operate on its own, firing off processes and organizing of its own accord, was the height of sophistication. However, that this was only the start in an ever-changing evolution of business process automation.

As the volume and complexity of tasks grow, CPA can efficiently scale up to meet the requirements without significant resource constraints. Furthermore, CPA tools can be easily configured and customized to accommodate specific business processes, allowing them to swiftly adapt to evolving market conditions and regulatory changes. CPA tools are adept at consistently applying rules, policies, and regulatory requirements. Automation of cognitive tasks allows organizations to achieve higher levels of accuracy. CPA also ensures standardized execution of processes, minimizing the risk of errors caused by human variability. With in-built audit trails and robust data governance mechanisms, organizations can maintain transparency and accountability throughout automated processes, thereby reducing compliance risks.

“Cognitive automation refers to automation of judgment- or knowledge-based tasks or processes using AI.” Beyond automating existing processes, companies are using bots to implement new processes that would otherwise be impractical. “RPA is a great way to start automating processes and cognitive automation is a continuum of that,” said Manoj Karanth, vice president and global head of data science and engineering at Mindtree, a business consultancy. RPA is a simple technology that completes repetitive actions from structured digital data inputs. Cognitive automation is the structuring of unstructured data, such as reading an email, an invoice or some other unstructured data source, which then enables RPA to complete the transactional aspect of these processes. Intelligent virtual assistants and chatbots provide personalized and responsive support for a more streamlined customer journey.

Automating time-intensive or complex processes requires developing a clear understanding of every step along the way to completing a task whether it be completing an invoice, patient care in hospitals, ordering supplies or onboarding an employee. “The biggest challenge is data, access to data and figuring out where to get started,” Samuel said. All cloud platform providers have made many of the applications for weaving together machine learning, big data and AI easily accessible. By enabling the software bot to handle this common manual task, the accounting team can spend more time analyzing vendor payments and possibly identifying areas to improve the company’s cash flow.

Intelligent Document Processing (IDP), a type of intelligent automation, facilitates precise data extraction from diverse documents, simplifying the process of information handling. CPA’s adaptive learning guarantees perpetual enhancement, making it capable of adjusting to changing business environments. By utilizing NLP, IDP, and adaptive learning, CPA tools relieve humans from routine and time-intensive tasks, allowing them to concentrate on more strategic https://chat.openai.com/ initiatives and promoting a more productive and efficient work setting. In essence, cognitive automation emerges as a game-changer in the realm of automation. It blends the power of advanced technologies to replicate human-like understanding, reasoning, and decision-making. By transcending the limitations of traditional automation, cognitive automation empowers businesses to achieve unparalleled levels of efficiency, productivity, and innovation.

Realizing that they can not build every cognitive solution, top RPA companies are investing in encouraging developers to contribute to their marketplaces where a variety of cognitive solutions from different vendors can be purchased. “One of the biggest challenges for organizations that have embarked on automation initiatives and want to expand their automation and digitalization footprint is knowing what their processes are,” Kohli said. Cognitive RPA has the potential to go beyond basic automation to deliver business outcomes such as greater customer satisfaction, lower churn, and increased revenues. “Cognitive RPA is adept at handling exceptions without human intervention,” said Jon Knisley, principal, automation and process excellence at FortressIQ, a task mining tools provider. RPA usage has primarily focused on the manual activities of processes and was largely used to drive a degree of process efficiency and reduction of routine manual processing.

Cognitive process automation tools can streamline and automate complex business processes and workflows, enabling organizations to achieve greater operational efficiency. By automating cognitive tasks, Cognitive process automation reduces human error, accelerates process execution, and ensures consistent adherence to rules and policies. This also allows businesses to scale their operations without a corresponding increase in labor costs. Intelligent/cognitive automation tools allow RPA tools to handle unstructured information and make decisions based on complex, unstructured input. Cognitive automation (also called smart or intelligent automation) is an emerging field that augments RPA tools with artificial intelligence (AI) capabilities like optical character recognition (OCR) or natural language processing (NLP). It deals with both structured and unstructured data including text heavy reports.

Technological and digital advancement are the primary drivers in the modern enterprise, which must confront the hurdles of ever-increasing scale, complexity, and pace in practically every industry. RPA and Cognitive Automation differ in terms of, task complexity, data handling, adaptability, decision making abilities, & complexity of integration. From your business workflows to your IT operations, we got you covered with AI-powered automation. Explore the cons of artificial intelligence before you decide whether artificial intelligence in insurance is good or bad. There are a lot of use cases for artificial intelligence in everyday life—the effects of artificial intelligence in business increase day by day. It gives businesses a competitive advantage by enhancing their operations in numerous areas.

For example, an attended bot can bring up relevant data on an agent’s screen at the optimal moment in a live customer interaction to help the agent upsell the customer to a specific product. Figure 2 illustrates how RPA and a cognitive tool might work in tandem to produce end-to-end automation of the process shown in figure 1 above. RPA is taught to perform a specific task following rudimentary rules that are blindly executed for as long as the surrounding system remains unchanged. An example would be robotizing the daily task of a purchasing agent who obtains pricing information from a supplier’s website. All of these create chaos through inventory mismatches, ongoing product research and development, market entry, changing customer buying patterns, and more. This occurs in hyper-competitive industry sectors that are being constantly upset by startups and entrepreneurs who are more adaptable (or simply lucky) in how they meet ongoing consumer demand.