Automation Archives - The Burnie Group

PRESS RELEASE: The Burnie Group achieves second consecutive top 100 rank in 2018 Growth 500 ranking of Canada’s Fastest-Growing Companies

Posted on September 13, 2018December 4, 2018 by Bruna Simoes

–Canadian Business unveils its 30th annual list of Canada’s Fastest-Growing Companies –

TORONTO, ONTARIO– (Sept. 13, 2018) – The Burnie Group is pleased to announce that it has ranked No. 82 in the Growth 500 ranking of Canada’s Fastest-Growing Companies. This is the 2^nd year that The Burnie Group has ranked in the top 100, with five-year revenue growth of 1,030%. The Toronto-based management consulting firm ranked No. 2 in the category of Canada’s fastest-growing professional services companies for 2018.

“The companies on the 2018 Growth 500 are truly remarkable. Demonstrating foresight, innovation and smart management, their stories serve as a primer for how to build a successful entrepreneurial business today,” says Deborah Aarts, Growth 500 program manager. “As we celebrate 30 years of the Canada’s Fastest-Growing Companies program, it’s encouraging to see that entrepreneurship is healthier than ever in this country.”

“Ranking in the Growth 500 two years in a row is a great honour, and we’re delighted to find ourselves amongst Canada’s best and brightest companies,” says David Burnie, Principal and Founder of The Burnie Group. “I believe this second nod confirms that we’re on the right track with our approach to client service and innovation. We want to thank our team and clients for making this possible once again.”

Ranking Canada’s Fastest-Growing Companies by five-year revenue growth, the Growth 500—formerly known as the PROFIT 500—profiles the country’s most successful entrepreneurial businesses. The Growth 500 is produced by Canadian Business. Winners are profiled in a special Growth 500 print issue of Canadian Business (packaged with the October issue of Maclean’s magazine) and online at Growth500.ca and CanadianBusiness.com.

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About The Burnie Group

The Burnie Group is a Canadian-based management consulting firm that helps clients improve their businesses through the application of innovative strategy, rigorous analysis, world-class technology, and the continuous pursuit of operations excellence. The Burnie Group specializes in Strategy, Operations, Robotic Process Automation (RPA), Artificial Intelligence (AI), Blockchain, and Workforce Management (WFM). Our programs deliver measurable, transparent, and guaranteed results.

About the Growth 500

For 30 years, the Growth 500 ranking of Canada’s Fastest-Growing Companies has been Canada’s most respected and influential ranking of entrepreneurial achievement. Developed by PROFIT and now published in a special Growth 500 print issue of Canadian Business (packaged with the October issue of Maclean’s magazine) and online at Growth500.ca and CanadianBusiness.com, the Growth 500 ranks Canadian companies on five-year revenue growth. For more information on the ranking, visit Growth500.ca.

About Canadian Business

Founded in 1928, Canadian Business is the longest-serving and most-trusted business publication in the country. It is the country’s premier media brand for executives and senior

business leaders. It fuels the success of Canada’s business elite with a focus on the things that matter most: leadership, innovation, business strategy and management tactics. Learn more at CanadianBusiness.com.

Media Contact:

Bruna Sofia Simoes

Marketing & Sales Manager

Bruna.simoes@burniegroup.com

416-909-6379

Managing people in a time of automation

Posted on August 22, 2018September 13, 2018 by Bruna Simoes

Managing people in a time of automation

As the presence of Robotic Process Automation (RPA) and Artificial Intelligence (AI) in today’s workplaces continues to grow, the topic of job security and displacement becomes increasingly important for managers to consider.

With a widely held misconception that technology is a threat to traditional workforces, employers have an imperative to consider how RPA and AI will affect people and organizational culture when determining where and how these technologies should be used in their organizations.

Regardless of how well designed an RPA or AI strategy is, if the human side of implementing change is not a focal point of that strategy, it stands to fail. This article explores some tangible ways companies can approach change management, ensuring employee buy-in.

Automation, after all, is less about replacing employees and more about streamlining work processes. It allows an employee’s role to be redefined from a focus on mundane and repetitive tasks to one that is more complex, more value-added, and ultimately more meaningful. Managed properly, automation can lead to a more engaged workforce.

Based on our experience designing and implementing broad-scale automation programs, we’ve identified three strategies that every organization should consider when adopting RPA and AI.

Prepare not just for automation, but for a cultural shift

When preparing for an automation project, managers are often tasked with developing a list of processes that AI and RPA can quickly improve. During this discovery phase managers also need to blueprint the broader impact of automation on people and culture. Such a blueprint can help to navigate the transition towards automation, identifying required changes to employee mindsets and behaviours and building an effective communication and change management plan.

By positioning automation and AI as employee allies—put in place to help alleviate staff from repetitive and mundane tasks—organizations can rally employees to become champions for technological advancement. For this to work, transparency is key. Conversations reminding employees that these technologies are tools that are supposed to work for them are fundamental to ensuring a smooth transition. Employees of all skill levels are better served when they understand how and why their work landscape is changing.

Encourage ongoing learning and development

In typical employee onboarding, time and resources are committed to ensuring staff are trained on the skills that are required to work effectively and efficiently. For many organizations, this is where learning and development starts and ends. However, organizations that thrive know that ongoing learning is essential to both employee and company growth.

Automation and AI provide an excellent opportunity for organizations to re-invest in the skills and capabilities of their employees. With the capacity that automation and AI unlock, time can be invested in training employees on more advanced skills. Staff can be redeployed to work on more value-added activities, including customer-facing interactions and revenue-generating initiatives. Automation and AI initiatives also require employee oversight and support, and current Subject Matter Experts are often well positioned to transition into an Automation or AI Centre of Excellence. With a thoughtful approach to training and upskilling employees and designing new value-added roles, a transition to automation and/or AI can lead to a more rewarding work environment that motivates staff and boosts morale and engagement in the workplace.

A Burnie Group client recently illustrated how to positively engage employees while embracing automation. In addition to clearly communicating their automation strategy, our client gave employees the opportunity to be trained in automation core skills and join the automation Centre of Excellence to participate in the automation implementation. Employees were also encouraged to identify automation opportunities in their work area, with the commitment that capacity released through RPA would be repurposed towards growth initiatives in the organization. This approach made employees feel that they were a part of the automation transformation and resulted in a very positive attitude towards the change.

As AI and RPA become more prevalent in the workplace, employees that are equipped with future-proof skills will be less fearful of automation and better prepared to work alongside this technology.

Position your company as an innovator

People want to work for organizations that support and empower their employees, and automation can be a tool that enables this. An organization’s investment in technology can help position it as an innovator in its field, helping it to attract and retain top talent.

When organizations embrace innovation and build it into their “DNA” to —continuously reinvent work, they reduce barriers to change and create an innovative culture where everyone wins.

One Burnie Group client implemented Robotic Process Automation as part of a broader strategic focus on innovation. With innovation being core to the values of the company, RPA was viewed as a natural fit. Rather than challenging the implementation and resisting change, employees sought ways to build RPA into their day-to-day work and leverage it to spend more of time with customers and on growth-focused initiatives.

Conclusion

Introducing AI and RPA into the workplace is no small undertaking. While most leaders address the effectiveness and efficiency gains that these technologies can deliver, truly successful leaders take a broader view to consider the best way to engage employees in the change.

Successful companies take the time to understand how automation can complement the work of employees and then invest in building a workplace where people and automation live in harmony.

By: Jenya Doudareva, Senior Associate

INFOGRAPHIC: Demystifying Machine Learning

Posted on July 3, 2018July 3, 2018 by Bruna Simoes

Machine Learning is the science of finding patterns in data and using those patterns to make predictions. It is the process by which, over time, machines (computers) are enabled without explicit programming, to learn, grow, and change autonomously through real-world interactions. It is a subsect of Artificial Intelligence (AI).

AI refers to a computer system’s ability to perform tasks that normally require human intelligence, such as visual perception, speech recognition, communication, decision-making, planning, learning, and the ability to move and manipulate objects.

The infographic below explores the different applications of Machine Learning in a variety of industries, to learn more about AI and Machine Learning opportunities in your industry, please contact us for a free no-obligation discussion. We look forward to hearing from you.

PRESS RELEASE: The Burnie Group receives Blue Prism Silver Partner Award in Robotic Process Automation

Posted on June 1, 2018September 17, 2018 by Bruna Simoes

TORONTO, ONTARIO– (June 1, 2018) – This latest achievement builds upon an already deep and long-standing relationship with Blue Prism. One of North America’s first Blue Prism partners, The Burnie Group helps clients transform their operations through the delivery of robotic process automation, augmented by thoughtful business process redesign and performance management. This approach provides substantial cost savings, streamlines and simplifies operations, and eliminates waste, errors and the risk of fraud.

“The Burnie Group is honoured to be recognized as a Blue Prism Silver Partner,” said David Burnie, Principal and Founder of The Burnie Group. “We constantly strive to be at the forefront of what’s new, and what stands to have incredible influence. We were the first consulting firm in Canada to adopt and embrace Robotic Process Automation (RPA), and we’ve been very successful in building this practice, this award is a testament to that.”

Recently, The Burnie Group supported ATB Financial in achieving Blue Prism’s 2018 ROM Excellence Award. An accolade presented to the company who has been judged to have achieved the best performance through implementing the Robotic Operating Model that leverages object reusability, appropriate controls and organizational design to maximize business benefits and scalability.

With the demand for RPA and The Burnie Group’s services continuing to increase, together The Burnie Group and Blue Prism are helping clients deploy digital workforces across North America.

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About The Burnie Group

The Burnie Group is a Canadian-based management consulting firm that helps clients improve their businesses through the application of innovative strategy, rigorous analysis, world-class technology, and the continuous pursuit of operations excellence. The Burnie Group specializes in Strategy, Operations, Robotic Process Automation (RPA), Blockchain, and Workforce Management (WFM). Our programs deliver measurable, transparent, and guaranteed results.

Media Contact:

Bruna Sofia Simoes

Marketing & Sales Manager

Bruna.simoes@burniegroup.com

416-909-6379

INFOGRAPHIC: 22 Benefits of RPA

Posted on March 5, 2018March 12, 2018 by Bruna Simoes

This infographic is a window into the world of Robotic Process Automation. If you are interested in exploring RPA opportunities in your industry or want to know more about implementing RPA in your organization, please contact us for a free no-obligation discussion. We look forward to hearing from you.

29 Cutting Edge Applications of Artificial Intelligence

Posted on March 5, 2018March 12, 2018 by Bruna Simoes

Artificial Intelligence (AI) is the theory and development of computer systems that can perform tasks that normally require human intelligence. These tasks include visual perception, speech recognition, decision making, and language translation. Systems capable of performing such tasks are steadily transitioning from research laboratories into industry usage.

AI technology is unique in that it is flexible in application. It can be used to improve processes, enhance interactions, and solve problems that, until recently, could only be performed by humans. AI’s advanced abilities include natural language processing (NLP), machine learning, machine perception, and enhanced analytics.

The list below details 29 cutting-edge applications made possible by AI technology.

NATURAL LANGUAGE PROCESSING

Natural language processing (NLP) is a sub-category of AI that attempts to bridge the gap between human and computer communication. AI-enabled systems such as IBM’s Watson use NLP to understand and respond to the nuances of human language. This allows for more accurate analysis of data sets and communication of insights.

Customer interaction chatbots — Chatbots are computer programs that are commonly used to interact with customers by audio or text. Conversica, for example, is a virtual sales assistant that communicates persistently and politely with prospective sales leads. Conversica uses email to engage, qualify, and follow-up with leads, allowing the sales team to focus their efforts on closing deals.
Financial chatbots — In the financial industry, chatbots such as aLVin are used to interact with brokers. They can answer questions, understand intent, and direct brokers to their desired products and information.
Virtual assistants — Beyond chatbots, AI can power more complicated virtual assistants that can recognize client needs and complete various tasks. Expensify‘s virtual assistant, Concierge, assists in the automation of expense reports and travel arrangements for companies. It can inform clients of real-time price changes and can even file receipts on their behalf.
Communication systems – AI-powered communication systems can also be used to manage relations between peers and stakeholders. CrystalKnows, a personality detection software, uses NLP to evaluate LinkedIn accounts and develop a profile of how to most effectively speak to, work with, or sell to an individual. Crystal can even draft emails to anyone based on the preferred tone suggested by his or her online presence.
Legal assistants — The language processing capabilities of AI assistants can be tailored to a specific industry. LegalRobot’s AI assistants are designed to review legal documents and make suggestions for language clarity and strength.
Cognitive retail – Virtual assistant capabilities can be integrated with other customer relationship management products to provide in-person levels of service via online platforms. The North Face‘s personal web-shopper, XPS, uses NLP to understand customer need as would a human representative. It then uses machine learning to make informed product recommendations based on customer history, location, and other data.
Personal assistants – AI can also be used on a personal device to simplify daily tasks. Gluru technology, for example, is used to power a task management application that uses NLP to analyze a user’s conversational data, such as their email. This app can identify tasks, generate a personalized to-do list, and even provide actionable buttons to complete each task.
Web speech – New language-based technological advancements in AI can improve the web navigation and searching experience. These web speech APIs integrate voice recognition technology, syntactical analysis, and machine learning to seamlessly convert voice to text and vice versa. This click- and typing-free internet interaction can improve information accessibility for those with a disability or low technological acumen.

MACHINE LEARNING

Machine learning is an application of AI that allows systems to process data and learn to improve the performance of a specific task without explicit programming. Deep learning is a form of machine learning that mimics human learning patterns to gain an understanding of unstructured data sets and generate intelligent decisions.

Medical decision making — Deep-learning programs such as Enlitic can optimize physician decision making by analyzing a patient’s past medical history, diagnostic information, and symptoms to provide actionable insights. These programs learn as they process data, improving their ability to identify diseases and provide treatment planning.
Healthcare analytics — Deep learning can also be used to compile, analyze, and interpret collaborative data. Flatiron, for instance, has developed a cloud-based platform for healthcare professionals that compiles insights, empirical data, and patient experiences to improve oncological care on a real-time basis.
Bioinformatics – In the field of bioinformatics, scientists use AI-software to identify patterns in large data sets, such as sequenced genomes and proteomes. This analysis can help in the development of new drugs to tackle diseases by determining which proteins are encoded by a certain gene. Atomnet is a deep-learning technology that analyzes the structure of proteins known to cause disease and designs drugs accordingly.
Emotional detection —Emotional detection systems powered by AI can detect human emotions without visual input. Researchers at MIT have developed EQ Radio, a system that learns to identify human emotions based on heartbeat data collected by wireless signals. This technology may one day be used by smart homes to detect if a resident is experiencing a heart attack.
Fraud detection — Fraud prevention has always been a major challenge for the financial industry. PayPal and other eCommerce companies have started to use deep-learning fraud-detection algorithms to monitor customers’ digital transactions and identify suspicious behaviours. A study by LexisNexis found that this deep-learning approach to security has reduced PayPal’s fraud rate to 0.32% of revenue, a 1% improvement over the industry average.
Cyber Security — AI-enabled cybersecurity programs analyze and organize internal network data to identify potential threats. The security program RecordedFuture uses machine learning and NLP to contextualize information and provide actionable analyses.
Procurement optimization – Companies can use AI internally to enhance business operations such as procurement. Tamr, a data unification software, uses machine learning to clean, analyze, and sort procurement data. It identifies savings opportunities, bundles spending across business units, and exposes supplier risk.
Customer interactions — While NLP allows virtual assistants to interact easily with customers, deep learning allows them to locate and provide the desired information. The AI model DigitalGenius analyzes historical customer service transcripts in order to recognize successful customer interactions. This allows the model to predict meta-data for new cases and provide suggestions for automated customer responses.
Optimized gaming — The gaming industry, previously focused on the level distinctions of “easy,” “medium,” or “hard,” is now using AI technology to develop self-optimizing and -evaluating games. These new AI-powered games keep players engaged by continuously adjusting difficulty and strategy to suit player ability.
Military planning — In a military setting, AI can be used to increase deployment efficiency. Autonomous machines (including drones and satellites) share data in real time to develop actionable strategies. The U.S. military AI system JADE evaluates historical data, combines information with learned reasoning, and presents suggestions to execute large-scale plans in minimal time.

MACHINE PERCEPTION

Machine perception is the ability of a system to simulate human perception of the world. AI uses machine perception to extract information from different data sources. Computer vision is a type machine perception that allows AI to extract information from images.

Medical imaging — Computer vision represents a huge technological advancement for medical imaging and preventative care. The diagnostic program Zebra Medical Vision collects and analyzes medical scans for various clinical identifiers. It then accesses a database of millions of scans, enabling it to provide critical information such as the location of a tumour or a patient’s risk of cardiovascular disease.
Manufacturing — The manufacturing sector is increasingly turning to robotics to speed up repetitive tasks. AI-enabled robots use computer vision to complete tasks and to adapt to changing environmental conditions, broadening the types of tasks available to robots and preventing costly mistakes on the assembly line. Fanuc‘s Gakushu robots use computer vision and a machine learning software to collect and evaluate data for path, speed, and task optimization in aerospace manufacturing.
Service industry – Some AI-enabled robots can not only understand human language but can recognize human emotions. Using computer vision, Softbank‘s humanoid robot Pepper can interpret facial expressions as human emotions and generate responses accordingly. Pepper can also recognize and remember individual faces and preferences. It is primarily used as a greeter in Japanese office buildings, restaurants, banks, and stores.
Financial industry — In the financial industry, AI programs can learn to identify potential high-yield customers, to recognize fraud, and even to forecast changes in stock trends. To further reduce fraud, the financial application Face++ uses computer vision for facial recognition to secure users’ financial transactions.
Autonomous delivery – Companies are increasingly using AI for commercial navigation purposes. Autonomous delivery systems, such as Amazon‘s delivery drones and Domino‘s Robotic Unit, use computer vision to efficiently navigate obstacles and optimize routes. Beyond commercial delivery, Matternet’s autonomous drone network in Switzerland aims to reduce medical testing times by flying diagnostic materials between hospitals and labs.
Transit safety — AI technology is paving the way for autonomous cars and accident-free transit systems. The combination of deep learning and computer vision allows cars to observe and safely interact with the surrounding environment. Road safety can be further increased by AI-enabled navigation systems, which alert drivers to potential accidents and suggest alternative navigation routes.
Geospatial analytics — Geospatial analytics use computer vision to gather and compare satellite imagery with historical data in order to develop insights. Using these insights, AI-enabled satellites can track economic trends from space. Orbital Insight, for example, predicts retail sales based on satellite images of retail store parking lots.
Childcare — AI devices use computer vision to recognize faces and navigate around obstacles, but a new Google patent suggests they can even be used to provide childcare. Google’s AI babysitter system learns to recognize different features of a home and to differentiate between family members. The system can recognize when a child has been left alone for too long, or has wandered dangerously close to a socket, and alerts the parents accordingly.

PREDICTIVE ANALYTICS

Predictive analytics are used by programs to analyze historical data in order to predict future outcomes. When combined with AI platforms, analytic ability increases in speed, scale, and application.

1. Marketing — Some predictive models can be used to analyze consumer data and inform marketing decisions. Magnetic, for instance, can predict the most effective advertisement to present a particular consumer and can choose to present the selected advertisement to the consumer without human supervision.
2. Data extraction — Data-extraction programs use AI to analyze and extract specific information from documents. Xtracta, for example, allows various retail applications to extract data from receipts. This information, combined with predictive analytics, generates useful statistical reports and relevant buying suggestions for the application user.
3. Social Network Analytics — Social networks can provide valuable marketing data, but also produce linguistically complicated datasets. In order to produce usable information, user profiles must be semantically analyzed using NLP. Companies can then use predictive algorithms to identify a customer’s preferences and web navigation patterns in order to provide targeted web advertising.

Development of AI technologies is actively being encouraged through projects like Soar—a cognitive architecture project aimed at developing computational building blocks for intelligent agents—and OpenCog—an open-source software project intended to create a framework for artificial general intelligence. Through such collaboration, AI capabilities continue to advance, thus expanding application potential.

By: Jenya Doudareva, Associate & Lokesh Patil, Associate

EDGEtalks: Executing on the Blockchain hype

Posted on February 6, 2018February 8, 2018 by Bruna Simoes

On January 15th, 2018, The Burnie Group hosted EDGEtalks: Executing on the Blockchain hype, the potential application of blockchain technology to business practices. The keynote was delivered by Don Tapscott (CEO, Tapscott Group; Executive Chairman and Co-founder, Blockchain Research Institute; Co-author, Blockchain Revolution). A panel discussion followed, moderated by Doug Heintzman (Head of the Blockchain practice, The Burnie Group). Panelists included Dr. David Jaffray (EVP Technology and Innovation, University Health Network), Dr. Marek Laskowski (co-founder, Blockchain Lab; Professor, Information and Computing Technologies, York University), Dr. Atefeh Mashatan (Professor, Ted Rogers School of Information Management, Ryerson University), and Chris Owen (VP, Enterprise Shared Platforms–Blockchain, TD Bank).

Blockchain: Solving Problems for the Digital Economy

In 2008, a person, or group, known as Satoshi Nakamoto, published a paper describing the first blockchain database. Three months later, it was used by Nakamoto to launch the bitcoin cryptocurrency network. Since then, interest in cryptocurrency investment has exploded, but industry experts insist that crypto’s true value lies in its underlying technology: blockchain.

A blockchain is a distributed ledger technology. Its core value lies in its ability to provide a reliable common version of the truth to members of a business network. Digital records (transactions) receive a unique signature (hash) of a fixed length. Transactions are then bundled and stored in time-stamped “blocks” that are “chained” to the blocks of previous transactions. This chain of blocks is synchronized across a network of distributed “nodes.” By comparing the last hash in a chain, nodes find consensus on the contents and integrity of the blockchain, making it virtually immutable.

This new technology was the first real solution to a problem that had plagued digital transactions since their inception: the double-spend problem The issue being that a digital payment was merely a copy of a token of value. Tokens could be copied multiple times and spent in more than one location. With blockchain’s continuous validation and replication of transaction history, single-use for digital tokens can be guaranteed. This, in turn, positively affects the trust deficit.

Another valuable characteristic of the technology is “smart contracts,” which can be stored and executed on a blockchain. This coded feature enjoys the same immutability, and therefore trustworthiness, as the data it manipulates. It allows for the use of business logic with automated transaction attributes, solving, amongst other things, the renege problem. In this situation, a customer might leave a queue (reneging) for various reasons before completing a transaction. When a smart contract is introduced, the customer is no longer disengaged by redirection to a banking intermediary to complete the transaction. The smart contract easily completes the transaction by triggering and validating payment securely and independently.

These problem-solving characteristics are representative of blockchain’s many potential advantages. The following will explain how blockchain can generate value, enhance business efficiencies, and bring about the new era of the Internet.

The True Value of Trust and Data

Business networks are built on top of available infrastructure, which inherently contains deficiencies that can introduce friction into business activities. Many business networks, therefore, engage third-party intermediaries to mitigate deficiencies, such as trust deficits between parties. These third parties can take many forms: banks, credit card companies, insurance companies, PayPal, Alibaba, auditors, and regulators. However, this centralized intermediary system is hackable, infamously slow, and costly.

Because a blockchain network addresses the trust deficit problem it allows for peer-to-peer transactions (P2P) completely independent of intermediaries. Individuals become owners of their own data, and that data an asset, protected on a blockchain from theft and fraud by immutable, time-stamped record keeping. In a blockchain-powered world, an individual’s medical records, financial records, academic degrees, voting history, professional history, and consumer history, can all be stored in encrypted transactions. A musician’s intellectual property might be stored on a blockchain, with smart contracts triggering automatic payments every time a song is featured in a film. A patient could allow a government temporary access to medical records to help identify and prevent possible outbreaks of disease. The sharing of this information with specific people for a fixed duration is the choice of the individual, un-beholden to the delays, rules, privacy exposure, or costs associated with an intermediary.

Rethinking the Firm

According to Ronald Coase’s theory of the firm, companies only exist due to the high cost of transactions within markets. Traditionally, performing activities in-house has kept these costs low and companies strong. The Internet, created as a network of information, began the process of unbundling the firm. With the creation of blockchain as an entirely new network of information, these transaction costs are so greatly affected that companies have no choice but to evolve as the underlying rationale for their existence is altered.

Blockchain features, such as smart contracts and autonomous agents, can cut costs by enhancing business efficiencies through automation. The scale of this automation can alter the very concept of what constitutes a company; a decentralized autonomous organization (DAO), for example, is a company run entirely through computer programs with next-to-no human participant. This model uses business logic and decision making embedded in smart contracts to automatically execute actions when triggered by pre-determined situational criteria. This new platform dramatically reduces business network friction, and eliminates nearly all traditional transaction costs, paving the way for distributed companies that resemble networks rather than centralized firms.

The Second Era of the Internet

Blockchain is a new paradigm that addresses the very purpose of computing: to automate business processes with the goal of reducing headcount and friction in business networks. It provides unprecedented peer-to-peer trust and can enhance business efficiencies in nearly any industry. When the existing Internet of Things—which is currently held back by the available software infrastructure and related trust deficits—is combined with blockchain’s new “ledger of things,” a partnership is formed. This partnership represents a second era of the Internet, in which discrete devices can confidently engage and contract each other to accomplish a goal. With widespread blockchain implementation, intermediary functions become redundant, companies more automated and decentralized, and the individual consumer more autonomous with improved privacy and increased control of their information assets.

Working with an experienced partner can help you harness the full potential of blockchain technology for your business. As a leading professional services enabler of blockchain strategy and implementation in North America, The Burnie Group will help you to identify areas where blockchain can increase your business’s security and efficiencies, set the right strategy and build the right foundation to substantively advance business goals.

Contact us to learn more about blockchain.

Key insights from the #EDGEtalks panel of speakers:

“This is nothing less than the second era of the Internet”