INFOGRAPHIC: Demystifying Machine Learning

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.


INFOGRAPHIC: Demystifying Machine Learning

INFOGRAPHIC: Demystifying Machine Learning

The Most Unusual Uses of Artificial Intelligence

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.


Helping People

Rescue Missions

The Most Unusual Uses of Artificial Intelligence  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.


Diagnosing Sepsis

The Most Unusual Uses of Artificial Intelligence  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

The Most Unusual Uses of Artificial Intelligence  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

Robot Bees

The Most Unusual Uses of Artificial Intelligence  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

The Most Unusual Uses of Artificial Intelligence  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

The Most Unusual Uses of Artificial Intelligence  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.


Smart Agriculture

The Most Unusual Uses of Artificial Intelligence  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.


The Most Unusual Uses of Artificial Intelligence

 By: Jenya Doudareva, Senior Associate

Understanding AI and Machine Learning

The terms artificial intelligence and machine learning have gained a lot of hype in the news lately, and a lot of articles seem to use both terms interchangeably, even though they are different. The aim of this article is to make more sense of all the technical jargon out there.

The term artificial intelligence (AI) is derived from the phrase, “man-made ability to learn and understand.” This means AI is a broad brand association name which covers all things man-made with respect to the human ability to understand and disseminate information. Data, which is unprocessed information, is the foundation to which all man-made systems learn, hence the rise of the term, “big data.”

Now to data science. The hottest and sexiest job of 2018, as proclaimed by The New York Times, is the science of understanding and interpreting data into meaningful and usable information. The bulk duty performed by a data scientist is called data wrangling, and this means taking the data and trying to find meanings in it. During data wrangling, data is cleansed, regrouped, transformed, and tested with various hypothetical assumptions to better understand the true composition of the data. This data wrangling is required because most machine algorithms are sensitive to outliers, non-normal data distribution, and unscaled or untransformed data input.

A product or service can be said to be powered by AI if the product/service is comprised of a learning path, where the product/service improves or tries to improve over time. The more you use the product /service, the smarter and more optimized the product becomes (e.g. the Nest home thermostat). Therefore, an equation can be formed to represent what AI truly means:

P = programming to get data

I = information from data

(S\NN) = machine learning algorithm (including neural networks)

O = programming to interpret output to client

FB = feedback to data stage to improve model (this can be periodical or instant, depending on the nature of the product or services).

AI = P + I + FB + (S\NN) + O

Where FB starts with initial value as 0

What about predictive modelling? Well, predictive modelling, or analysis, simply means trying to predict the possible outcomes of a scenario or equation. So, yes, machine learning falls under predictive analysis/modelling, but it also falls under non-linear, linear, and integer programming; Monte-Carlos simulations; etc.

The key difference between the mentioned techniques and machine learning is the presence of an objective function. This objective function is an interpretation of the problem at hand. This is the reason why machine learning algorithms have become very popular these days; it gets you the objective functions to any given dataset.

Understanding AI and Machine Learning

Machine Learning Scope

There are three main scopes for machine learning;

  1. Supervised Learning:

This is the most popular type of machine learning scope. It involves using a labeled data set to develop models that define the given dataset. The output of a supervised learning can be continuous (regression), such as the price of a house or product, or categorical (classification), as in,  “yes, I will buy a product, or no, I would not buy a product.”

Regardless of the type of the output required, all supervised learning algorithms try to solve an equation, which is y = f(x) (output is a function of the input). There are many algorithms already packaged in various programming languages.

Examples of supervised machine learning algorithm and three drawbacks:

Regression algorithms: These are algorithms that solve for a real value for the output, as stated earlier. They are often called regressor, and they cover a wide range of algorithm types, from solving a simple line equation to solving polynomial relationships that include regularization. You can find out more about the list of present algorithms at, where you will see a full description of all regression algorithms, from linear to quadratic, to kernel and support vectors machines.

Classification algorithms: These are algorithms that solve for categorical outputs, such as yes or no (0, 1). Algorithms in this category are called classifiers,  and there are various ways in which classification problems are present. Some classification problem are bi-class in nature, such as predicting yes (0) or no (1), while others are multiclass, predicting yes (0), no (1), or maybe (2). Also, some of the algorithms predict the specific probability of each class, e.g. [0.2, 03, 0.5].

You can find more resources on the page. Also check out for a comprehensive list of all algorithms supported by the scikit-learn package.


  1. Unsupervised Learning:

Unsupervised learning is a machine learning scope that deals with an unlabeled dataset. It is usually employed for cluster analysis where the categories or sub-categories of the dataset is unknown. It is also used for novelty and outlier detections on labelled data sets during preprocessing, before a form of supervised learning is applied. Other types of clustering that are done with unsupervised learning include mixed models and hierarchical clustering.  A collection of samples and documents can be found on the page.

Below is an algorithm cheat sheet that helps in the selection of algorithms using the python’s scikit-learn package.

Understanding AI and Machine Learning

Algorithms below the black line are popularly used for unsupervised learning, while algorithms above the black line are used for supervised learning.

  1. Reinforcement Learning

This is more a advanced and difficult machine learning area to implement. This is an hybrid technique between supervised and unsupervised learning in which an agent/model is trained by supplying  feedback during training, and the agent learns from the feedback. This is mostly used in visual environments where the agent interacts with the environment and learns while the environment changes. This mimics the fundamental way in which humans (and animals) learn. As humans, we have a direct sensor-motor connection to our environment, meaning we can perform actions and witness the results of these actions on the environment. This idea is known as “cause and effect,” and it undoubtedly is the key to building up knowledge of our environment throughout our lifetime.

The “cause and effect” idea can be translated into the following steps for an RL agent:

  1. The agent observes an input state
  2. An action is determined by a decision-making function (policy)
  3. The action is performed
  4. The agent receives a scalar reward or reinforcement from the environment
  5. Information about the reward given for that state/action pair is recorded

By performing actions and observing the resulting reward, the policy used to determine the best action for a state can be fine-tuned. Eventually, if enough states are observed, an optimal decision policy will be generated and we will have an agent that performs perfectly in that particular environment.

There is some research being done with large hedge funds to create smart agents who are better at predicting and anticipating stock price movement.


AI is not a singular algorithm, programming paradigm, or entity,  but is rather a combination of steps and techniques that build up a product and service. In reading this article, you should now have a good starting point for determining how algorithms are established as well as the concise path that determines how the best algorithm is displayed.


Understanding AI and Machine Learning

 By: Tom Adedeji, Senior Associate

#EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement

This post is based on a panel discussion held on June 4, 2018. The 90-minute session focused on panellists’ experiences shaping culture and fostering engagement in their companies. Moderated by Darshan Jain, Head Technology and Operations of The Burnie Group, Norman Bacal, author and former managing partner, Heenan Blaikie LLP delivered the keynote and the panellists were Richard Anton, Senior Vice President and Chief Operations Officer at CIBC Mellon, Cathie Brow, Senior Vice President, Human Resources and Communications, Revera, Christina McClung, Vice President, Human Resources and Chief of Staff, Capital One, and Rob Lokinger, President and Chief Operating Officer, AppCentrica Inc.

#EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement  Many companies hire the best and the brightest to seize new opportunities and increase profits. Unfortunately, impressive résumés don’t always translate to an engaged employee base or a stimulating and innovative workplace culture. Individual contributors who once brimmed with enthusiasm and new ideas now only raise their heads to check the time. Regardless of systems put in place or reorganizations, teams struggle to get ahead.

Culture and engagement can be forgotten or an afterthought when setting and executing corporate strategies. Leaders should consider the mindsets and behaviours needed to support their company’s vision and goals.


How does culture fit within your corporate strategy?

You need to define the workplace culture required for teams to meet targets and create new opportunities. Whether team-centric, focused on high potentials, honed on improving shareholder value, (etc.), a culture strategy needs to be determined as well as its supporting tactics.

“You need to decide what your cultural imperative is, as part of your corporate strategy,” says Norman Bacal. “Once you understand what it is, it ought to put you in the direction of your tactics, day-to-day behaviours, and ultimately whom you recruit to your vision.”

Bacal offers three pieces of advice for leaders looking to set, change or improve corporate culture:

1. Be consistent

Policies, programs, and behaviours must align with culture vision and not vary across your organization regardless of geography or environment. Employee trust grows when words and actions align. If you, your peers, or other leaders say one thing and do another, you risk damaging your and the company’s credibility.

“Never confuse strategy with tactics. If you take those tactics and separate them from your cultural vision, they won’t work. In fact, they do the opposite of what you want and can build a level of cynicism, because you need to be consistent between your vision and execution.”

2. Recognize the importance of your front-line staff on a regular basis

#EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement  It’s easy to focus attention on only senior management or those with “star” quality. In fact, it’s the public’s or client’s first point of contact—receptionists, service agents, or call centre employees—who can be the linchpin to your organization’s success. They are often your company’s face and voice and some of your most valuable employees. Telling them you recognize this signals you understand their role and you appreciate what they do.

“I’d arrive in the morning and say to the receptionist, ‘You’re the most important person in this firm.’ If you say that once to somebody, they won’t believe you; if you say that to them on a regular basis, they begin to believe it.”

3. Walk the halls

It’s unlikely your staff will proactively tell you what’s happening or their collective mood. The best way to know these is to step outside your office and talk to employees. Have informal chats—saying “hello” and finding out how they’re doing or how their family is will help build goodwill and trust. Ask your leaders to do the same.

“It’s the small things you may consider completely insignificant to your life that have a huge impact on other people’s lives.”

Engaging your employees while building corporate culture

We know a strong corporate culture can be a competitive advantage when attracting employees or securing clients. When a company decides to define or redefine their culture, change doesn’t occur overnight: it takes time to learn and develop traits and behaviours. While organizations can launch campaigns focused on ethics, teamwork, or client-centric service, successful shifts often happen when leaders commit to and model desired behaviours and attitudes.

Who are engaged employees?

Engaged employees go above and beyond so the company realizes its corporate vision and strategies. Working isn’t “just a job” or a paycheque. They are front and centre when needed most. As individuals, they proactively update their skillset to be part of the organization’s future. They are active problem solvers and offer ideas to help shape the company.

“I really think engagement has to do with people’s passion and enthusiasm. We have a really great vision for our company that touches everybody. Employees need to feel connected—if they aren’t, they’re not going to be able to deliver the service we expect from them.”

~ Cathie Brow, Senior Vice President, Human Resources and Communications, Revera

How do you build employee engagement?

Smart strategies and tactics build, maintain, and grow engagement over time. They are rolled out at the corporate level and supported by leaders.

Corporate tactics

Your corporate values should be defined, so everyone understands what they are and how to bring them life. You need to ensure all levels, especially C-suite and other senior leaders, walk the talk. Otherwise, employees will see the disconnection and may assume a double standard.

Find different ways to involve employees in corporate programs. Corporate Social Responsibility projects (such as Habitat for Humanity builds, sorting food bank donations, or registering teams for a charity bike ride) or internal problem-solving competitions for specific issues (ranging from hackathons to projects resolving client pain points) are more than team-building exercises: They reinforce company values and allow staff to participate in corporate projects in fun, meaningful, and non-financial ways.

Take the time to listen to your employees and don’t immediately jump to prescribing remedies. Instead, ask your employees for their ideas and implement solutions that need little lead-time (before putting into place more complex ideas). This way, you signal you hear your staff. Similarly, staff input when setting up a formal recognition program is important—don’t assume a gala or dinner with the CEO would appeal to the majority.

“Alignment around the right goals and cultural imperators yields great benefits. It carries through when people interact with each other and with customers. We founded our company on four principles that really defined our culture. They’re used to make our hiring decisions, evaluate people and make sure we have the right approach within our organization.”

~ Rob Lokinger, President and Chief Operating Officer, AppCentrica Inc.

Individual leaders’ tactics

Your behaviour, attitude, and presence go a long way in shaping corporate culture. Sit with your team to get a feel for their day-to-day environment and issues. Be seen. Have informal chats with specialists and coordinators as well as more senior staff at their desks or in the cafeteria. Encourage peers and people leaders under you to do the same.

Trust in leadership is essential. Employees want to see the genuine you. Façades won’t gain their trust and may make you harder to follow. Your actions need to be consistent, and you must deliver on your commitments.

Celebrate team wins, but also find ways that are personal to you to congratulate or acknowledge staff accomplishments. Equally crucial is being there and supporting your staff in challenging times.

“My role is about fostering the kind of culture and principles we want. It’s about how I handle myself every single day, and also how I expect my management team to handle themselves. I am a firm believer that if I display those characteristics, those traits across the organization, that’s when people start to buy into that idea that it’s not more than a one-off that’s quickly forgotten.”

~ Richard Anton, Senior Vice President and Chief Operations Officer at CIBC Mellon


How do you measure culture?

#EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement  Annual and biannual employee satisfaction and sentiment surveys may not be helpful because they are lagging indicators. Instead, get timely feedback by measuring employee experience after critical points in their tenure: onboarding, first three months, performance reviews (etc.). Ask questions about diversity and inclusion, and track indicators such as employee referrals and attrition rates.

“It’s hard to measure feelings, but we try. I think there’s a lot to be said about the anecdotal feedback—look at what you might measure. I think some measurements that can be found along with the survey scores. Make sure you deep dive into topics where people are feeling engaged and the various contributors, such as enablement to getting work done.”

~ Christina McClung, Vice President, Human Resources and Chief of Staff, Capital One

Working with an experienced partner can help build and improve your employee engagement. Choose a partner who can efficiently lead the project, keep it on track, and who will develop your internal capabilities. The Burnie Group will help you to set the right strategy and build the right foundation. Contact us to learn more about employee engagement.


#EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement

INFOGRAPHIC: 22 Benefits of RPA

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.

INFOGRAPHIC: 22 Benefits of RPA

INFOGRAPHIC: 22 Benefits of RPA

Transformation with RPA: Best Practices and Lessons Learned

Transformation with RPA: Best Practices and Lessons Learned  On November 20, 2017, The Burnie Group led a panel discussion on enabling Robotic Process Automation (RPA) in the workplace. Moderated by David Burnie, Principal and Founder of The Burnie Group, panellists discussed their reasons for automation as well as key learnings from RPA implementation projects. Panellists were Erik Kalin, VP & COO of Retail Operations at Empire Life Insurance Co., Michael Marchuk, Chief Technology Evangelist at BluePrism, and Dan Semmens, Managing Director of Transformation-Process Automation at ATB Financial. 

When looking for ways to boost efficiency, improve service quality, or increase customer satisfaction, many companies turn to RPA to transform their businesses.

Through automation, clerical tasks usually executed by people (for example, recording a change of address) are done more quickly and accurately by software robots. By removing mundane repetitive work, employees can be better engaged and contribute meaningfully to the company’s core mission.

In this article, we’ve summarized some best practices step-by-step, and following that, some key learnings shared by the industry experts at our recent panel discussion.

Eight steps to transforming your business with RPA:

Like any change project, successful adoption and implementation are the results of good planning.  These steps will help ensure your company’s RPA project goes smoothly:

Step 1: Identify the opportunity

Every solution begins with a problem. Ideally, the issue should tie to the strategic plan or core business function. It could be people-focussed (such as issues related to high turnover or poor customer experience) or operations-focussed (such as evolving compliance requirements or complicated processes rooted in legacy systems).

Step 2: Gather information

Engage your subject matter experts—including IT, risk, audit, and security—to develop a good high-level understanding of the processes and their related issues. You need to determine not just if automation is a viable solution but how much automation is needed for the best results. Here, RPA practitioners can build your knowledge (technological and otherwise) and provide resources to support your proof-of-concept.

Step 3: Develop the business case and win executive buy-in

After determining scope, create a business case by defining the project’s objective(s). Recruit a senior level champion and socialize the plan amongst executive stakeholders. After the project is green-lighted, shortlist RPA process candidates based on stakeholder needs. Select an RPA practitioner to help manage your project.

Step 4: Build your team

Build the team needed to put the transformation in place and support it, through the processes of change, implementation, and post-implementation. Your change team should include those functions needed for a smooth transition (such as communications, HR, and ER). A post-implementation team will need to deal with unexpected issues that may affect the robots after putting RPA in place (such as a vendor-initiated upgrade).

Step 5: Capture the processes

Often companies do not have fully-documented processes, as tasks and behaviours may reside with the SME, but not on paper. Create well-documented, end-to-end understandings of full processes instead of spotlighting particular aspects. Develop thorough baselines. Find out who and how the final outputs are used. This step can be time-consuming, so be sure to budget sufficient time for your subject matter experts to thoroughly capture pre-RPA details.

Step: 6: Build and test the automated processes

From Step 5, identify tasks (or entire processes) that do not add value, and those that can be harmonized or re-engineered to be improved. Build a Centre of Excellence and an object library. Stakeholders should also identify unexpected problems and find solutions. Schedule your development and sprints and adjust accordingly.

Step 7: Implementation

Before going live, your communications resource should have developed and launched a communications plan targeting managers, staff, and other groups impacted by the RPA transformation. Ensure those who will be working with the new processes and those who are being redeployed have the appropriate training. Build in the necessary safeguards and checks to ensure all processes are being handled correctly.

Step 8: Evaluation

After the RPA is installed, objectively evaluate its performance. Conduct a gap analysis and determine if the business case’s goals were met. When monitoring stakeholder satisfaction, differentiate actual from perceived problems, and address them appropriately. Compare project costs and benefits against expectations. Capture lessons learned for future RPA (and other) implementations and document findings and recommendations.


Key Learnings

One of the things that we’re starting to do now is to supplement the whole program with better support around transforming our workforce, so it’s easy, whether it’s measuring customer experience or measuring benefits. How do we tie those numbers back and really get true value from the investment back into the organization? Having better baseline data can really help and give you a better understanding of not just goal setting, but those true opportunities that lie across the companies.

– Dan Semmens, Managing Director of Transformation-Process Automation at ATB Financial.


I think you have to build in a lot of time for testing. We underestimated the amount of time our subject matter experts would need to do this. We thought we could just ask them few questions—I walked down the hall and tapped them on the shoulder. Well, that ends up being a lot when the subject matter expert knows everything—especially when a lot of your procedures are undocumented and your test cases are just growing, growing, growing over time.

– Erik Kalin, VP & COO of Retail Operations at Empire Life Insurance Co.


You look at some of these things and think, ‘Do we really do this?’ You’ll find you actually really do and you realize that you made some optimization goals. Maybe you do something different, maybe just change and tweak the process a little bit, so you can automate some of it. But the reality is that there will be a lot more attention to the whole thing.”

– Michael Marchuk, Chief Technology Evangelist at BluePrism.


Working with an experienced partner can help make your RPA business transformation a success. Choose a partner who can efficiently lead the project, keep it on track, and who will build your internal capabilities. As a pioneer in North American RPA, The Burnie Group will help you to set the right strategy and build the right foundation. Contact us to learn more about robotic process automation.


Transformation with RPA: Best Practices and Lessons Learned

PRESS RELEASE: The Burnie Group Ranks No.1 amongst Professional Services Companies and in the top 100 in 2017 PROFIT 500

PRESS RELEASE: The Burnie Group Ranks No.1 amongst Professional Services Companies and in the top 100 in 2017 PROFIT 500  –Canadian Business unveils its 29th annual list of Canada’s Fastest-Growing Companies –

TORONTO, ONTARIO–(Sept. 14, 2017) – The Burnie Group is pleased to announce that it has ranked No. 87 in the 29th annual PROFIT 500 ranking of Canada’s Fastest-Growing Companies by Canadian Business. Published in the October issue of Maclean’s magazine and at, the PROFIT 500 ranks Canadian businesses by their five-year revenue growth. This is the first year that The Burnie Group has been included.

The Burnie Group ranked No. 1 in the category of Canada’s fastest-growing professional services companies for 2017, and No. 87 overall on the 2017 PROFIT 500 list with five-year revenue growth of 831%. 

“It is never easy to earn a spot on the PROFIT 500, but this year’s applicant pool was the most competitive yet,” says Deborah Aarts, PROFIT 500 program manager. “This year’s winners demonstrate the resilience, innovation and sheer management smarts it takes to build a thriving business today. Canada—and the world—needs more entrepreneurial success stories like these.”

“We’re thrilled to be included in this exclusive ranking alongside some of Canada’s best and brightest companies,” says David Burnie, Principal and Founder of The Burnie Group. “I really believe this recognition is a testament to the hard work and innovative ideas of our team members, as they are the driving force behind the growth and success we’ve managed to achieve.”

Ranking Canada’s Fastest-Growing Companies by five-year revenue growth, the PROFIT 500 profiles the country’s most successful growth companies. A joint venture between Canada’s premier business media brands, the PROFIT 500 is published in the October issue of MacLean’s, Canadian Business and online at




About The Burnie Group

The Burnie Group is a highly specialized operations consulting firm that helps clients improve their businesses through the application of innovative strategy, rigorous analysis, world-class technology, and top-tier domain expertise.  The Burnie Group specializes in Strategy, Operations, Robotic Process Automation (RPA), Blockchain, and Workforce Management (WFM). Our programs deliver measurable, transparent, and guaranteed results, including:

» 10-25% reduction in operating costs

» 5-10% increase in employee engagement

» 10-20% top-line revenue growth


About the PROFIT 500

For 29 years, the PROFIT 500 has been Canada’s most respectable and influential ranking of entrepreneurial achievement. Developed by PROFIT and now published in Maclean’s magazine and at, the PROFIT 500 ranks Canadian companies on five-year revenue growth. For more information on the ranking visit or


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


Media Contact:

Bruna Sofia Simoes

Marketing & Sales Manager




5 Tips for Entrepreneurial Success

5 Tips for Entrepreneurial Success  Being an entrepreneur means that you’ll often create your own path: No career guides, counselors or maps will guide you from one step to the next: You’ll have to make it up as you go.

Success or failure when you branch out on your own can be pretty precarious, and you will not always be clear about which steps to take next. Through his experience as an entrepreneur, David Burnie believes there are 5 essential things you need to know about starting and running a successful business.


1. Leverage your strengths

If you try to start a business in an industry you don’t know, trying to solve a problem that you’re not familiar with, without knowledge of any customers and what their needs are, it’s going to be very difficult compared to if you’re very good at something, you can take that and leverage it to build your business, and you’ll be much more successful.


2. Get out there and sell – if you build it, they will not necessarily come

Most people think that “if you build it, they will come”; if you create a great product or solution, customers will immediately come knocking on your door, and that’s just not true. If you want to be successful as an entrepreneur, you really have to be successful at selling yourself and selling your firm. And in order to do that, you have to build relationships.


3. Leverage your relationship skills – it’s a relationship business (coffee is your secret weapon)

My most effective weapon in growing The Burnie Group has been coffee. Going out, having coffee with people, building those relationships on a one-on-one basis. It creates trust, and ensures that you can leverage your relationships to sell.


4. Listen to your customer (work with your customer to build your product)

Listen. When building a business, you may have an idea about what you think people will want, but you have to be open to feedback. If you listen, your customers will take your initial idea and make it better, and you’ll end up with a product or solution that really meets client needs.

Too many times I’ve seen people who just have this idea, and they stick dogmatically to it even when it isn’t working. The most successful entrepreneurs are those who listen and react to what they hear.


5. Be LEAN – what do you truly need in order to build a business, build as needed/when ready

When I was first building The Burnie Group, my initial thought was “let’s put a whole bunch of money, time, and resources, behind marketing,” until Mandy, my wife, said “Dave, just get out there and sell projects. Put up a URL so people know you exist, but get the business going first, then worry about all the other stuff.” So, I would say relative to other mid-size consulting firms we’ve been very thoughtful about what we truly need in order to build a business. You have to be fiscally responsible, and so we’ve built incrementally, when we were truly ready to accept those changes, and that’s helped us to remain focused on the business and maintain financial stability.

5 Tips for Entrepreneurial Success


22 Benefits of Robotic Process Automation (RPA)

Robotic Process Automation (RPA) is a relatively new technology that has already firmly claimed its spot in improving the productivity of organizations alongside tried and true methodologies such as lean and six sigma. We’ve put together a comprehensive list of  22 RPA benefits based on our many years of experience implementing RPA solutions with Financial Services, Insurance, Telecommunications and Healthcare clients.

22 Benefits of Robotic Process Automation (RPA)  1. Decreased costs.  Cost savings of approximately 80-90% can be achieved when a business process performed by an FTE is replaced by a software robot.

2. Freeing up staff for higher value tasks. Automation of repetitive and time-consuming processes frees up your staff to make a more value-add contribution.  For example, when assessing an insurance claim more time can be spent in the assessment as opposed to populating the same data into 5 various systems.

3. Increased employee engagement. When staff can focus on high-value tasks they often feel more invested in the work they are completing. When implementing RPA projects, we often see staff engaging in repetitive activities e.g. copying data between 10 different systems while completing a single customer request, with RPA they can serve an additional 3 clients instead.

22 Benefits of Robotic Process Automation (RPA)  4. Reduced operational risk. RPA reduces the rate of errors because robots make less mistakes. Avoiding purely human mistakes, such as those made while tired, or by deviating from the process, means a lower level of operational risk.

5. Reduced output variability. Robots are great at duplicating tasks consistently with little to no distinguishable variability. It ensures that similar tasks are handled in the same way e.g. underwriting for insurance policies is consistent across the same risk groups.

22 Benefits of Robotic Process Automation (RPA)  6. Reduced paper use/waste. RPA forces digitization as it requires that companies have the data and files being manipulated by software robots in a digital form. Work that in the past may have been done partly or in full on paper, by an FTE, can now be purely electronic.

7. Driving process improvement. In an automation project you often first analyze and then simplify (where possible) the processes to be automated, creating more manageable processes (for both people and machines). For example, if you have 10 different ways to set up a new client in your system, it would make sense to streamline this process first and then automate it.

22 Benefits of Robotic Process Automation (RPA)  8. Increased output. Automation allows for work to be done 24/7/365 without people fatigue, or quality variance. Often, customers want to interact with service providers outside of a 9-5 timeframe—on evenings and weekends—automation allows you to offer this level of service.

9. Higher speed and throughput. Customers receive expedited service as machines are able to process requests in real time. e.g. credit checks, etc.

22 Benefits of Robotic Process Automation (RPA)  10. Improved customer experience. By deploying RPA you free up expensive and high-value resources, FTEs, from more menial and repetitive tasks and put them back on the front line assisting your customers.

11. Improved internal service levels. With RPA things like internal reports can be delivered faster and without mistakes, new employees can be set-up very quickly, and even IT issues can be enormously accelerated.

12. Defined governance structures. RPA forces companies to define clear governance structures around IT applications by forcing organizations to agree on who owns each application. Leading to a clearer definition of access rights for each application, since robots, like humans, will need to use the same access.

22 Benefits of Robotic Process Automation (RPA)  13. RPA does not require substituting existing IT systems.  An RPA virtual workforce uses all the same systems your FTEs use. This is one of greatest advantages of RPA in comparison to other automation solutions. In the past, Business Process Management solutions and workflow management tools had to be integrated with each application they interacted with. RPA simply uses the existing systems in the way your FTEs would.

22 Benefits of Robotic Process Automation (RPA)  14. RPA is Scaleable. Being able to easily scale up or down your operations as needed ensures that companies can make adjustments based on seasonality. In the insurance sector, for example, a virtual workforce can be ramped up in order to process snow/hail claims in the winter, flooding in the summer, etc.

15. Virtual workforces are highly secure. Managing IT security for RPA robots is very simple as they do not change roles, leave the company, or retire. They also don’t hack your data.

16. Increased expertise in core domains. By automating simple tasks, your company can develop increased expertise in your core domains, such as developing more sophisticated fraud analysis, and/or creating more accurate underwriting algorithms.

17.  RPA eliminates customer pain points. A successfully implemented virtual workforce can enhance your customer’s experience and eliminate common customer pain points. For example, traditionally when processing a loan the customer has to fill out several forms, submit required documents. These are then sent for processing, review and approvals. The overall process can take several weeks, with multiple human touch-points, after which the customer gets a feedback on the status of their loan application. With RPA, a robot can take over the complete process, reducing turnaround time to a few days or less.

18. Impact is delivered quickly. From the moment when robots are in place – a matter of weeks – organizations start seeing benefits. The Burnie Group’s typical implementation timeline for RPA projects is approximately 8 weeks.

22 Benefits of Robotic Process Automation (RPA)  19. Improved capacity for SLA analysis. RPA solutions allow management to know the progress of SLAs in real time. Dashboards tracking the output of your virtual workforce address a frequent problem of operations and back-office managers – understanding where his/her team stands and how volumes are evolving.

20. High-quality processes and output. Similar to a recipe being created by a five-star cook, a robot’s decision making logic is designed by your best SMEs, ensuring high-quality output. Your SME transfer knowledge of best practices with the RPA team ensuring your virtual workforce is performing at the highest standard.

21. Better record keeping. Robots always document what they’ve done, not only leaving a clear audit and control track, but also allowing for easy recovery after unexpected shutdowns.

22. Being an innovator. RPA is a cutting edge technology that is dramatically changing back-office operations enabling greater innovation by freeing up human labour to focus on idea-generating.

While RPA has many benefits, there continues to be a clear need for humans in the workforce. The question is no longer which jobs will be replaced, but rather, what work will be redefined, and how? In the future, most processes will consist of a mix of human and machine labour. Nothing will be fully automated. Even at the most highly automated production plant you will see there are still humans working.

Automation allows for traditional jobs to become more fluid, ensuring more effective human labour. With freedom from high-volume, low complexity administrative work, humans can continue to drive and innovate in areas such as customer service, expertise-based tasks, the development of new products, etc.

This article is just a glance into the world of RPA topics – should you be interested in exploring RPA opportunities in your industries or want to understand how to apply or deploy RPA in your organization, please contact us for a free no-obligation discussion. We look forward to hearing from you.


22 Benefits of Robotic Process Automation (RPA)