In today’s business landscape two things are undeniable:
The first, you must innovate or face extinction and the second;
Innovators have dilemmas.
In this age of disruptive technology and globally integrated markets, an innovation strategy is key to success. Some companies even define their raison d’être as being at the forefront of innovation, but what does innovation actually mean?
Innovation is many things. It is an essential evolutionary mechanism that allows species, and—for our purposes—businesses, to survive the changes in their environment and/or prosper in a new environment. It can happen purposefully or accidentally. It can be radical or subtle. It happens in some companies and some countries with much greater frequency than others.
The history of business is littered with examples of companies that failed to innovate and died as a consequence of that failure, and also those bold firms who innovated their way to global relevance seemingly overnight.
There are four major types of innovation:
1. Incremental innovation is by far the most common type of innovation. It is the process of implementing an existing technology within an existing marketplace to add value and deliver a better product or service more efficiently. The continual incremental improvements to user interfaces in software products are examples of incremental innovation.
2. Architectural innovation is the process of taking your existing skills, technologies and lessons learned and creating value by applying them to a new market. For example, NASA-developed viscoelastic polyurethane foam is now commonly used to build mail-order memory foam mattresses, and consequently a booming industry.
3. Radical/breakthrough innovation gives rise to completely new industries. Electricity, the telephone, the internal combustion engine, the airplane, the mobile phone are all examples of radical innovation.
4. Disruptive Innovation is perhaps the most misunderstood of the four. It is the application of new technology to an existing marketplace. That technology is initially more expensive and addresses an underserved market, as such, the products or platforms using the new technology are considered niche. But as maturity and economies improve, the technology eventually becomes compelling to mass audiences and renders incumbent companies uncompetitive. Blockbuster video’s fall to Netflix is an example of disruptive innovation. We call disruptive innovators “blindside attackers” because you usually don’t realize your business is threatened until it is much too late.
Innovations Strategies – what are they and why do they matter?
What are they?
An innovation strategy is a plan to improve profitable revenue or market share through service or product innovation. Innovation strategies most often involve the application of technology. They are conceived through deep analysis of customer needs and “jobs-to-be-done” (filling a gap) or through the nurturing of certain kinds of company culture and/or leadership style. Innovation strategies define how much and what kind of resources need to be assembled and how they will be deployed, and can even be used as a means of creating an early warning system of disruptive innovator threats and preparing responses to potential competitive threats.
Why does it matter?
The traditional approach to a company’s strategy has been the application of operational excellence. This makes perfect sense—if we can service our customers more efficiently then our products will be more competitive, and we will be rewarded with greater market share and repeat business, improving the returns to our investors. The challenge is that the predominance of this lens can leave a company vulnerable to missed opportunities and competition from companies that are not playing by the same rulebook.
Almost all established companies should leverage their core competencies and work to more efficiently address their existing customer’s needs. Succeeding in this is what keeps the lights on and your employees showing up to work each day. However, in this age of increased change and technological advancement, it is becoming more and more difficult to stay in business, let alone succeed at a rate better than average. If you don’t have an innovation strategy, work diligently to foster a culture of innovation, develop distinctive measurements, and protect the budget and people allocation against the inevitable quarter to quarter pressures of delivering bottom-line results, your company is going to have problems.
The innovation strategy should be a core element of any company’s business strategy.
7 reasons every company needs an innovation strategy
Reason #1: We live in an era of rapid change. Artificial intelligence, blockchain, IoT, 5G, 3D printing, intelligent automation, autonomous transportation, and low earth satellites all have the potential to redefine existing markets and create new ones. Charting a course to survive and prosper is fundamental to business success.
Reason #2: The danger of blindside attacks is very real. Disruptive innovators are leveraging technology in entirely new ways the consequences of which can be hard to recognize until it is too late (as Netflix example above). You may spend way too many resources trying to protect your market share only to wake up one morning and discover that the rules have changed, and your market no longer exists.
Reason #3:Customers are more informed and more engaged. Customer behaviour is being shaped by technology and ready access to real-time information. Customers increasingly view innovative companies as better aligned with their needs.
Reason #4: The rate and pace of change are accelerating. As the pace of technology-driven change and shifting customer expectations accelerate, companies will need to show up in the marketplace with new products that better address customer needs on an increasingly shorter timeline.
Reason #5: technology transfer friction has fallen. Advances in one field can now quickly jump to and impact another industry. For example, digital imaging put film manufacturers out of business and personalized medicine will redefine the pharmaceutical space.
Reason #6: Skill acquisition and retention are much easier for innovative firms. Talented people want to work for firms that have a vision, are forward-thinking and do not tend towards complacency as a result of their success. They view working on something innovative as being meaningful, and get fulfillment from “inventing the future”.
Reason #7: Brand value is accelerated by innovation. Customers and investors value innovative companies. Customers believe that their purchases are more future-proofed and that their value is magnified through innovative extensions, new versions, and the network effects caused by other like-minded customers. Investors value companies that don’t sit on their laurels and are leveraging technology and the rapid and scalable value magnification enabled by it.
By: Douglas Heintzman, Innovation Practice Lead at The Burnie Group
Here at The Burnie Group, even in our downtime, we like to be on top of the ideas and innovations that are dramatically changing the businesses we work with, our country, and the world we live in. With that in mind, we’ve prepared this list of our favourite innovation themed books and podcasts.
If you’re getting into that ‘back-to-school‘ study groove like we are, our innovation list will get sparks flying so you’re ready to hit the ground running this September.
Shankar Vedantam uses science and storytelling to reveal the unconscious patterns that drive human behaviour, shape our choices and direct our relationships in Hidden Brain.
Why we like it:
The stories are fascinating, engaging, and well told. There are not only great lessons to be learned but also a way of looking at the world. This type of in-depth analysis gives us ideas about how to better engage the crowd, inspire creativity, and drive innovative thinking.
Getting Unstuck – At one time or another, many of us feel stuck: in the wrong job, the wrong relationship, the wrong city – the wrong life. Psychologists and self-help gurus have all kinds of advice for us when we feel rudderless. This week on Hidden Brain, we explore a new idea, from an unlikely source: Silicon Valley. Listen here.
What’s Not On The Test – Smarts matter. But other factors may play an even bigger role in whether someone succeeds. This week, we speak with Nobel Prize-winning economist James Heckman about the skills that predict how you’ll fare in life. We’ll also look at programs that build these skills in the neediest of children – and new research that suggests the benefits of investing in kids and families can last for generations. Listen here.
2. NPRs How I built this
Guy Raz dives into the stories behind some of the world’s best-known companies. How I Built This weaves a narrative journey about innovators, entrepreneurs and idealists—and the movements they built.
Why we like it:
You really get a sense of how many different ways there are for an idea to grow. Some success is due to collaboration, some due to someone’s singular vision, some due to dogged persistence and sometimes it’s pure luck. It is great to hear stories told by inspiring entrepreneurs.
Instagram: Kevin Systrom & Mike Krieger – Kevin Systrom and Mike Krieger launched their photo-sharing app with a server that crashed every other hour. Despite a chaotic start, it became one of the most popular apps in the world. Listen here.
Patagonia: Yvon Chouinard – In 1973, Yvon Chouinard started Patagonia to make climbing gear he couldn’t find elsewhere. Over decades of growth, he has implemented a unique philosophy about business, leadership and profit. Listen here.
WeWork: Miguel McKelvey – In 2007, architect Miguel McKelvey convinced his friend Adam Neumann to share an office space in Brooklyn. That was the beginning of WeWork: a shared workspace for startups and freelancers looking for an inspiring environment to do their work. Today, WeWork has created a “community of creators” valued at nearly $16 billion. Listen here.
Bumble: Whitney Wolfe – At age 22, Whitney Wolfe helped launch Tinder, one of the world’s most popular dating apps. But a few years later, she left Tinder and filed a lawsuit against the company alleging sexual harassment. The ensuing attention from the media – and cyberbullying from strangers – prompted her to launch Bumble, a dating app where women make the first move. Today, the Bumble app has been downloaded close to 30 million times. Listen here.
3. Interchange Podcast – GTM Green Technology Media
The Interchange is a weekly podcast on the global energy transformation, hosted by Stephen Lacey and Shayle Kann. Each week, the duo provides deep insights into technology, markets, projects, company financials, mergers and acquisitions, policy changes, and market data.
Why we like it:
Transactive energy is a great passion of ours. Interchange looks at the colliding forces of energy, climate change, business, technology, policy and consumer behaviour. Every week this podcast looks at another dimension of the evolution of this essential industry that touches all of us. The interviews are well structured and very engaging.
A Guide to Blockchain and Energy: Over the last 18 months, blockchain has evolved from an obscure concept in cryptocurrency circles into a mainstream corporate tool for “disrupting” entire industries.If you don’t have a blockchain strategy, you are not innovating hard enough. People love throwing around the term. But wait, what is it again? And why is it relevant to energy? Listen here.
A Blueprint for the Transactive Grid: Ryan Hanley is convinced that the distributed electric grid will create vastly more economic, security and societal value than today’s centralized system.Over the course of his career as a civil engineer — working at Pacific Gas & Electric, SolarCity, Tesla and now Advanced Microgrid Solutions — Hanley has worked to understand and extract that value. In this week’s conversation, Shayle Kann talks with Hanley about the tools at hand to re-engineer the distributed, transactive grid system. Listen here.
What Should We Do With All This Distributed Energy? Distributed energy resources (DERs) are going to double in the U.S. grid by 2023, according to our researchers at Wood Mackenzie. By then, we’ll likely have somewhere around 100 gigawatts of flexible capacity — made up of distributed solar, combined heat and power, electric vehicles, smart thermostats, and battery storage. Those technologies alone could amount to the current bulk power system in Texas. Today, utilities are less likely to see those DERs purely as a threat. But figuring out how to manage all those resources is still a monumental challenge. Now that we’re squarely in the middle of this doubling of DERs, how do we get markets right? This is an age-old question that many are working to answer — and we think it’s a good time revisit it. Listen here.
4. Economist Radio’s Babbage – Science and Technology
Babbage is the Economist’s weekly podcast on science and technology. It examines the innovations, discoveries and gadgetry making the news. New episodes are posted every Wednesday.
Why we like it:
It is very topical and currently relevant look at technologies impact on business people and society. It brings with it the high quality of Economist journalism and often features some very engaging interviews with newsmakers.
Babbage: Big data versus privacy: Data is becoming the world’s most valuable resource. Governments use it to monitor and control their citizens. Corporations use it to persuade consumers to buy their products. But as machine learning and algorithms advance, will people still be able to harness the power of big data without losing too much individual privacy?Listen here.
Babbage: Megatech: Technology in 2050: This feature-length episode dives into the technology that will shape our world over the next decades. Host Kenn Cukier and The Economist’s Executive Editor Daniel Franklin are joined by experts in artificial intelligence, cyber-security, healthcare and warfare to discuss how technology will transform many aspects of our lives. Listen here.
Babbage: The automation game: How quickly will robots disrupt global industries and what will the implications be? We explore with economist Andrew McAfee at the World Economic Forum in Davos. Also, neuroscientists often compare the human brain to a computer chip, so what happened when the idea was put into practice? Listen here.
5. HBR Ideacast
This podcast highlights some of the best articles from the Harvard Business Review. Top leaders in business management, discuss the future of work and what innovation means from and individual and team perspective.
Why we like it:
The stories are well-conceived and very interesting. You almost always finish an episode with one or two ideas that bounce around in your head for a number of days until you figure out how you might approach something in your own life a little differently.
375: What the Best Decision Makers Do: Ram Charan, coauthor of “Boards that Lead,” talks about what he’s learned in three decades of helping executives make tough decisions. Listen here.
645: Understanding Digital Strategy: Sunil Gupta, a professor at Harvard Business School, argues that many companies are still doing digital strategy wrong. Listen here.
436: Making Good Decisions: Stanford’s Ron Howard, one of the fathers of decision analysis, explains how it’s done. Listen here.
1. Prediction Machines: The Simple Economics of Artificial Intelligence
Author: Ajay Agrawal, Joshua Gans, Avi Goldfarb
What is it?
From the publisher: Artificial intelligence does the seemingly impossible, magically bringing machines to life–driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.
But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policymakers, investors, and entrepreneurs.
When AI is framed as a cheap prediction, its extraordinary potential becomes clear:
Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity–operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.
Why we like it:
Like many books, there are only a few big ideas, but those ideas are slotted into an accessible intellectual framework and brought to life with some fascinating stories.
2. Thank You for Being Late: An Optimist’s Guide to Thriving in the Age of Accelerations
Author: Thomas L Friedman
What is it?
From the publisher: In his most ambitious work to date, Thomas L. Friedman shows that we have entered an age of dizzying acceleration–and explains how to live in it. Due to an exponential increase in computing power, climbers atop Mount Everest enjoy excellent cell-phone service and self-driving cars are taking to the roads. A parallel explosion of economic interdependency has created new riches as well as spiralling debt burdens. Meanwhile, Mother Nature is also seeing dramatic changes as carbon levels rise and species go extinct, with compounding results.
How do these changes interact, and how can we cope with them? To get a better purchase on the present, Friedman returns to his Minnesota childhood and sketches a world where politics worked and joining the middle class was an achievable goal. Today, by contrast, it is easier than ever to be a maker (try 3-D printing) or a breaker (the Islamic State excels at using Twitter), but harder than ever to be a leader or merely “average.” Friedman concludes that nations and individuals must learn to be fast (innovative and quick to adapt), fair (prepared to help the casualties of change), and slow (adept at shutting out the noise and accessing their deepest values). With vision, authority, and wit, Thank You for Being Late establishes a blueprint for how to think about our times.
Why we like it:
It is by Tomas Friedman. Pretty much everything he writes is well researched, thought-provoking and highly relevant. In this book he looks at many of the major forces that are shaping the world we will be living in, and not only presents us with difficult challenges, but also with some pragmatic solutions.
3. The Innovator’s Dilemma
Author: Clayton M. Christensen
What is it?
From the publisher: The bestselling classic on disruptive innovation, by renowned author Clayton M. Christensen.
His work is cited by the world’s best-known thought leaders, from Steve Jobs to Malcolm Gladwell. In this classic bestseller—one of the most influential business books of all time—innovation expert Clayton Christensen shows how even the most outstanding companies can do everything right—yet still lose market leadership.
Christensen explains why most companies miss out on new waves of innovation. No matter the industry, he says, a successful company with established products will get pushed aside unless managers know how and when to abandon traditional business practices.
Offering both successes and failures from leading companies as a guide, The Innovator’s Dilemma gives you a set of rules for capitalizing on the phenomenon of disruptive innovation.
Sharp, cogent, and provocative—and consistently noted as one of the most valuable business ideas of all time—The Innovator’s Dilemma is the book no manager, leader, or entrepreneur should be without.
Why we like it:
It’s a classic. One of the most profound and useful business books ever written about innovation. It examines the difference between sustainable & disruptive innovation. The phenomenon of the blind side attacker leveraging disruptive innovation to redefine a marketplace is both fascinating and very important. As the authoritative source of much of the innovation worlds buzzwords, this is worth a read or re-read.
4. The Innovator’s DNA: Mastering the Five Skills of Disruptive Innovators
Authors: Jeffrey H. Dyer, Hal B. Gregersen, Clayton M. Christensen
What is it?
From the publisher: You can be as innovative and impactful — if you can change your behaviours to improve your creative impact. In The Innovator’s DNA, authors Jeff Dyer, Hal Gregersen, and bestselling author Clayton M. Christensen (The Innovator’s Dilemma, The Innovator’s Solution) build on what we know about disruptive innovation to show how individuals can develop the skills necessary to move progressively from idea to impact. By identifying behaviours of the world’s best innovators — from leaders at Amazon and Apple to those at Google, Skype, and Virgin Group — the authors outline five discovery skills that distinguish innovative entrepreneurs and executives from ordinary managers: Associating, Questioning, Observing, Networking, and Experimenting. Once you master these competencies, the authors explain how you can generate ideas, collaborate with colleagues to implement them, and build innovation skills throughout your organization to sharpen its competitive edge. That innovation advantage can translate into a premium in your company’s stock price — an innovation premium — that is possible only by building the code for innovation right into your organization’s people, processes, and guiding philosophies. Practical and provocative, The Innovator’s DNA is an essential resource for individuals and teams who want to strengthen their innovative prowess.
Why we like it:
In this follow on to “The Innovators Dilemma” and the “Innovators Solution”, the authors explain the skills required to move progressively from idea to impact. An easy read with great storytelling making great points very concisely and providing some practical guidance on how to integrate innovation into your way of looking at the world.
In the last 10 years, automation technologies have evolved dramatically to become what we know today as Intelligent Automation. Desktop Automation—software that supports human actions by automating repetitive tasks on a local machine— was the first iteration, later evolving to Robotic Process Automation (RPA)— software that mimics human actions by automating tasks performed by humans seamlessly across various applications and systems.
Today, Intelligent Automation, built on the foundation of its predecessors, leverages traditional RPA technology and combines it with digitization and artificial intelligence to augment human intelligence and expand the realm of possibility.
Intelligent Automation can be a difficult topic to wrap one’s head around, but like a lot of things, future success starts with solid fundamentals. And if you’re looking to learn, you’ve come to the right place.
Intelligent automation is the evolution of Robotic Process Automation. At its core, Intelligent Automation is the intersect of Digitization, RPA and AI. Where RPA addresses manual, structured and repetitive tasks that can be mimicked and automated by a Bot, Intelligent Automation introduces reason and cognition to “digitize and structure” inputs so that judgement-based decision making can be completed without human intervention.
Sounds great right? But before a company can truly capitalize on intelligent automation they must first digitize their paper-based data. Why? Because AI is highly reliant on large volumes of data in order to learn and be most effective. If a part of a process is paper-based rather than digital then the capacity for AI intervention in that process is limited.
In the example in the image below you can see how intelligent automation can be leveraged to automate an entire business area, where in the past only a single process would be within the scope of robotic process automation.
With increased scope comes the opportunity to realize new benefits from your automation, including:
1. Fraud Prevention: Intelligent Automation can be leveraged in Fraud Prevention due to the use of key AI tools, such as Machine Learning. Machine learning uses a large volume of data to autonomously learn patterns, predict outcomes, and act without being explicitly programmed with specific tasks. With large amounts of user data, intelligent automation can:
• efficiently perform analytics and calculate risk in real-time,
• monitor for suspicious payments,
• verify transactions with greater accuracy than a human would be able to, and
• notify account holders of suspicious activity in order to stop fraud in its tracks
Leveraging Intelligent Automation for fraud prevention will increase trust and overall reputation with customers, ensuring that everybody from the company to the user wins.
2. Improved Customer Service: Chatbots or conversational AI are a prime example of how Intelligent Automation can improve the customer experience. Even the most basic of chatbots can handle thousands of customer inquiries, reducing call-center wait times and increasing overall customer satisfaction.
• The AI being leveraged in this form of intelligent automation is Natural Language Processing (NLP). NLP uses statistics and learning algorithms to analyze textual information in order to understand the meaning, sentiment and intent. In the customer service context, a customer can raise a support ticket with a chatbot in the form of free text. This text is then processed with NLP to determine the level of urgency in the request, the sentiment (e.g. frustration) and then manage the interaction according to the level of severity/priority.
3. Improved Process Efficiency: Intelligent automation can dramatically reduce process handling times, significantly improving process speed and customer satisfaction. Intelligent Automation also provides enhanced process analytics and management information which can help organizations precisely pin-point process bottlenecks and areas for improvement.
• Machine learning algorithms that Intelligent Automation solutions incorporate can gather, organize, track, analyze, report on and store valuable data. This data can then be used to improve existing operations, address and correct issues in a timely manner, accurately forecast needs and develop best practices, all ensuring greater process efficiency.
4. Improved Quality: Intelligent automation greatly helps reduce the risk of transactional errors—including erroneous data inputs, mistakes in rule application and missed steps —to improve overall data accuracy and data-driven decision making.
5.Expanded Scope: The combination of digitization, RPA and AI significantly increases the number of processes that are in scope for automation. The combination of technologies allows an organization to automate much more, or even all, of an end-to-end process.
Savvy organizations are already leveraging intelligent automation in its varied forms to gain competitive advantage by enabling easier access to relevant data, more informed decision making, and the streamlining of processes. If you wish to learn more about how you can leverage intelligent automation, don’t hesitate to contact The Burnie Group today.
Blockchain’s unavoidable link to the highly tumultuous cryptocurrency market (i.e. Bitcoin) has recently made it vulnerable to criticism and dismissal. Despite this climate, blockchain technology, now in its fourth generation, continues to push forward, evolving beyond its cryptocurrency origins and becoming increasingly simple to use.
The evolutionary generations of blockchain
Before we discuss the future business impact of the fourth generation of blockchain, let’s first look at the stages of blockchain’s evolution since it was first conceived in 2008.
Developed by the mysterious Satoshi Nakamoto, the first generation of blockchain saw the emergence of distributed ledgers and enforced digital scarcity, as exemplified by Bitcoin. Blockchain appealed to cryptocurrency creators because of its Proof of Work1 algorithm, which validated transactions and prevented people from “double spending”, or using the same money for more than one transaction.
The second generation of blockchain, led by the automation and the development of trusted code platforms like Ethereum and Hyperledger, introduced the concept of smart contracts and made possible the digital tokenization of physical assets.
It was also around this time that the technology suffered initial scrutiny and concerns with regard to scalability, transaction speed and network efficiency.
Third-generation blockchain platforms like Aion, Cardano, and EOS, introduced technology such as sharding to tackle scaling issues in order to cut down on cost and speed of transactions.
These platforms also matured the distributed application capabilities of blockchain. (eg. La’Zooz, a decentralized, community-owned transportation platform that turns a vehicle’s unused space into a variety of smart transportation solutions.)
Fourth Generation Blockchain
The first three generations have been pivotal in increasing the scope of blockchain’s applicability, but there remained challenges (e.g. complexity, cost) that hindered widespread adoption.
Fourth generation blockchains resolve prior challenges and enable trust in easy-to-consume ways, accelerating the formation, operation, and reconfiguration of business networks. In addition to greater ease of onboarding, these lower cost, and highly scalable platforms make pragmatic trade-offs such as recognizing that not all transactions are created equal. For example, a variable consensus mechanism will allow you to incur different transaction time and cost when buying a cup of coffee when compared to buying a house.
Fourth generation Blockchain platforms like Insolar2 and Aergo, are enabling business networks to be easier to use through business-oriented interfaces that hide the complexity of the underlying blockchain technology. It is this moment in the evolution of blockchain technology–where we stop talking about blockchain and just start using it– that we believe will spark the true disruptive potential of blockchain.
What does it all mean?
Business networks—companies combining their resources in the pursuit of common objectives—are the key drivers of value creation and innovation in our modern economy. Their productivity and potential have traditionally been constrained by transactional frictions, principally informational and trust. The internet has significantly reduced informational friction and blockchain is the mechanism that can radically reduce trust friction. A world with low informational and trust friction will innovate and create value at a dramatically accelerated pace.
By: Douglas Heintzman, Innovation Practice Lead at The Burnie Group
Blockchain is a technology that holds the potential to disrupt several industries with many innovative applications. Despite its roots in cryptocurrency, some of the most creative and disruptive applications of blockchain go beyond pure financial transactions.
Automation through smart contracting, security through encryption, and transparency through shared information are just of a few of the novel ways that blockchain is enabling business disruption. As a peer-to-peer, distributed network, blockchain technology is helping the businesses that use it become more transparent, democratic, decentralized, efficient, and secure.
Blockchain has shifted the way we view security and transparency and will continue to transform several industries as it becomes more popular and widely adopted. Below, we look at six industries currently adopting blockchain to gain competitive advantage.
1. Financial Services
Financial services have traditionally received the most attention within the blockchain ecosystem. Blockchain’s secure approach to exchanging data, increased transparency, and lower operating costs make it attractive to the highly regulated and security-focused financial services industry.
In 2019, some of the biggest opportunities for blockchain in financial services will be in:
• AML/ KYC
• Clearing and settlement
• Trade finance
• International payments
• Identity as a service
Blockchain’s features offer countless benefits in the healthcare and long-term care industries. It can improve the accessibility and accuracy of patient data, facilitate better and faster treatment and enhance patient safety. It can also create a common, secure health information database that medical staff can access seamlessly. With less time spent on administrative tasks and better access to patient data, the quality of patient care can be greatly improved.
Blockchain helps reduce instances of fraud, reduces operational cost through optimized processes, and improves transparency and interoperability, reducing duplication of work in the healthcare space. These areas, in particular, are ripe for blockchain:
• Electronic health records
• Clinical trials
• Claims adjudication and billing management
• Prescriptions – provenance, double-Rx
3. Supply Chain Management
Today’s supply chains are increasingly complex, involving multiple parties across multiple regions and modes of transport. Blockchain provides these intricate supply chain networks with increased transparency, improved traceability and optimization through automation.
In supply chain, we expect to see blockchain used most prominently in:
• Provenance tracking, ex. Agricultural and pharma products (any place where spoilage or counterfeit can be introduced)
• Monitoring location, conditions (e.g. temperature, exposure to elements, any agitation/tremors) and security of products during transport
• Contract and Sub-contract management
• Bidding systems
• Invoicing and bills of lading
• Customs clearance
4. Government and Public Service
Governments have generally been slow to prioritize blockchain’s potential. At present, Canada is one of more than a dozen countries that are examining blockchain’s potential and running exploratory pilots. The public sector is expected to leverage blockchain for the benefits of increased security, efficiency and enhanced customer experience.
Record management in public services and government is an area where blockchain can automate paper-based processes, minimize fraud, and increase accountability between governmental agencies and those they serve.
Areas with a high degree of promise for blockchain include:
• Civil registries and identity management
• Immigration management
• Refugee management
• Land and personal property registries
• Voting systems
• Micro-loan capitalization (enforce scarcity)
Insurance is an industry that is ready for the adoption of blockchain. Blockchain’s ability to increase transparency, manage identity, and generate smart contracts will allow the insurance industry to improve efficiency (e.g. Oracles1 will provide inputs to smart contracts, reducing manual processing and instances of fraud.) and enhance the ability to accurately underwrite risk.
Some of the areas where we expect Blockchain to gain traction include:
• Parametric insurance
• Claims processing
• Risk modelling
Individuals can take out insurance policy with eachother rather than through an insurance provider
A historically centralized industry that relies on intermediaries and inefficient energy transport across long distances, blockchain provides the infrastructure to support innovation in the form of peer-to-peer energy networks, microgrids, electric vehicle (EV) charging, automated billing, and invoice settlement.
The energy sector, in particular, will be impacted by IoT devices creating an opportunity for blockchain. For example, having a ledger of things to complement the Internet of Things will ensure that all the many minute IoT data transfers and transactions are accurately represented and logged.
In the energy sector, we expect to see blockchain used in:
• Microgrid/ decentralized management
moving electrons in barter
establishing contracts for peer-to-peer storage/extraction
use of smart appliances
• EV charging
Transactions & identity management
• Metering and payments
The Final Word
Businesses in these and countless other industries need to consider incorporating blockchain into their strategies so as not to fall behind. As we look forward in 2019, Blockchain’s potential to transform the way companies operate to reduce costs and create new revenue streams will be transformative.
As businesses explore the disruptive potential of blockchain, we will begin to see more progress made beyond proofs of concept and limited scale pilots.
If you have questions about how blockchain could impact your industry, contact us. The Burnie Group will help you to set the right strategy and build the right foundation to help you become a pioneer in this emerging technology.
By: Madison Wright, Associate
An oracle, in the context of blockchains and smart contracts, is an agent that finds and verifies real-world occurrences and submits this information to a blockchain to be used by smart contracts. https://blockchainhub.net/blockchain-oracles/
TORONTO, October 30, 2018 — The Burnie Group is pleased to announce #EDGETalks: Artificial Intelligence in Operations: Where Can AI Fit in My Organization? Featuring a keynote address by Mike Rhodin, former SVP at IBM and founder of IBM’s Watson Group. Mr. Rhodin’s 33-year career at IBM was infused with a passion for helping clients extract value from technology, improving business performance, and simplifying the way people work. Mr. Rhodin’s keynote will provide insight on the ways that artificial intelligence and automation are reshaping operations, augmenting human capacity, and changing the future of work.
“AI has been called the fourth industrial revolution. It is hard to conceptualize just how incredibly transformative its potential is,” says Doug Heintzman, Head of Innovation at The Burnie Group.
#EDGETalks: Artificial Intelligence in Operations: Where Can AI Fit in My Organization? will take place on the evening of Wednesday, November 7, 2018, at The National Club. Following the keynote address, we will have a fireside chat featuring Kathryn Hume, Frank Tsiribis, and Mike Rhodin.
Kathryn Hume – Vice-President, Product and Strategy at integrate.ai Frank Tsiribis – Head of Insight Strategies and Risk Management, Enterprise Infrastructure, Initiatives, and Innovation (EI3) at BMO Financial Group.
Increasingly, companies are investigating the potential implications of AI on their enterprise, and if and how they should adopt it. This event will help separate hype from reality and fact from fiction. It will identify some key areas where AI is changing the way business is done.
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.
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.
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.
Artificial intelligence (AI) and intertwined concepts such as machine learning and predictive modelling have become indispensable in modern industries. It is often estimated that by 2030, AI will contribute up to $15.7 trillion to the global economy. AI has the potential to transform a wide number of industries. All over the world, AI is helping people do their jobs more effectively, from doctors who diagnose sepsis in patients to scientists who track endangered animals in the wild. In this article, we explore some of the more unusual uses of AI.
Rather than creating ominous issues for humankind, AI is helping people around the world do their jobs more effectively, including doctors who diagnose sepsis in patients and scientists who track endangered animals in the wild.
Below are some of the most unusual uses of AI that provide value to our society and go beyond their traditional and widely applied usages across industries.
AI technology is helping first responders find victims of earthquakes, floods and other natural disasters.
Normally, responders need to examine aerial footage to determine where people could be stranded. However, examining a vast amount of photos and drone footage is very time and labour intensive; this is a problem as time is a critical factor for victims’ survival.
AI developed at Texas A&M University permits computer programmers to write basic algorithms that can examine extensive footage and find missing people in less than two hours.
Sepsis is a potentially life-threatening complication of an infection, but it is treatable if identified promptly. When not identified in time, patients can experience organ failure or even death. Today, AI algorithms that analyse electronic medical records data can help physicians diagnose sepsis an average of 24 hours earlier than previously used methods, according to the Johns Hopkins Whiting School of Engineering. The AI system, called Targeted Real-Time Early Warning System (TREWScore) can also be used to monitor other conditions, including diabetes and high blood pressure.
Better Surgeries and Prosthetics
Surgical robotics today are machine learning-enabled tools that provide doctors with extended precision and control. These robots enable shortening the patients’ hospital stay, positively affecting the surgical experience, and reducing medical costs.
Mind-controlled robotic arms and brain chip implants have begun helping paralyzed patients regain not only mobility but also sensations of touch. Machine learning and AI are further helping these technologies improve the patient experience.
Earth and Wildlife
Bees are indispensable to crop pollination, however, they are very susceptible to pesticides, diseases, and other environmental concerns that lead to their fragile populations dwindling. To ensure that these concerns do not lead to famine, researchers have developed a robot bee drone that incorporates artificial intelligence, GPS, and a high-resolution camera to pollinate in a manner similar to honeybees.
Tracking Wildlife Populations
Applications like iNaturalist and eBirds, that collect data from vast circles of experts on the species encountered, are helping to keep track of species populations, favourable ecosystems, and migration patterns. These applications also have an important role in the better identification and protection of marine and freshwater ecosystems.
Wildlife Poaching Prevention
Wildlife poaching is a global problem as species get hunted toward extinction. For example, the latest African census showed a 30 per cent decline in elephant populations between 2007 and 2014. Wildlife conservation areas have been established to protect these species from poachers, and these areas are protected by park rangers. The rangers, however, do not always have the resources to patrol the vast areas efficiently. Predictive modelling has been used and tested in Uganda’s Queen Elizabeth National Park to predict poaching threat levels. Such models can be used to generate efficient and feasible patrol routes for the park rangers.
Neural networks are starting to be used to deliver smart agricultural solutions. Besides the use of both artificial and bio-sensor driven algorithms to provide a complete monitoring of the soil and crop yield, there are technologies that can be used to provide predictive analytic models to track and predict various factors and variables that could affect future yields.
For example, Berlin-based agricultural tech startup PEAT has developed a deep learning algorithm-based application called Plantix that can identify defects and nutrient deficiencies in the soil. Their algorithms correlate particular foliage patterns with certain soil defects, plant pests, and diseases.
By: Jenya Doudareva, Senior Associate
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