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

PRESS RELEASE: The Burnie Group hosts #EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement

TORONTO, May 28, 2018 — The Burnie Group is pleased to announce #EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement. Featuring a keynote address by Norman Bacal, who, in his best-selling novel, Breakdown: The Inside Story of the Rise and Fall of Heenan Blaikie, recounts the cautionary tale of the perils of ignoring a firm’s culture and vision, and the danger of hiring as CEOs individuals with little to no management experience.

This event provides an opportunity for our clients and colleagues to discuss the very significant implications of employee engagement on organizational culture. As many of our clients are finding themselves in a rapidly commoditizing marketplace, organizational culture—and especially, employee engagement—remains one of the few competitive advantages you can leverage as a senior leader to grow and out manoeuvre your competitors.” says Darshan Jain, Head of Technology and Operations at The Burnie Group.

#EDGETalks: Actively Engaged – Leadership and Innovation in Building Employee Engagement will take place on the evening of Monday June 4th 2018 in the Gallery at First Canadian Place. Norm Bacal’s keynote address will be followed by a panel discussion led by industry thought leaders, academics and practitioners, including:

Richard Anton – Senior Vice-President, Chief Operations Officer, CIBC Mellon
Cathie Brow – Senior Vice-President, Human Resources & Communications, Revera
Nathalie Clark – Vice-President, HR TD Securities & Risk Management, TD Bank Group
Rob Lokinger – Chief Operating Officer, AppCentrica

With extensive research showing that organizations face a radically shifting context in the workplace, an engaged workforce should be a top priority for senior management.  Converging issues such as flatter hierarchies leaving less 1:1 time with direct managers, accelerated career development expectations, and a technology-driven 24/7 work environment are driving the need to rewrite the rules of employee engagement.  With so much on the line, what does it take for an organization to really understand its culture and create an inclusive and engaging corporate environment?

For tickets visit:

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 StrategyOperationsRobotic Process Automation (RPA)Blockchain, and Workforce Management (WFM).

Media Contact:
Bruna Sofia Simoes
Marketing Manager


Source: The Burnie Group


INFOGRAPHIC: The Automation Race: Comparing 5 RPA providers

Robotic process automation (RPA) is a disruptive technology that can improve workforce productivity, accelerate process execution, reduce process error rates, and improve customer satisfaction. Companies that are quick to recognize the potential of automation stand to have considerable cost advantages and organizational agility. However, it can be difficult to know which provider has the automation solution specific to your company’s needs.

In this infographic, we compare the features and strengths of 5 leading RPA providers.

INFOGRAPHIC: The Automation Race: Comparing 5 RPA providers

INFOGRAPHIC: The Automation Race: Comparing 5 RPA providers


Digital Disruption and Private Equity: Understanding Effects and Opportunities.

Disruption is an age-old force of change that both drives and destroys. Forces such as globalization and the increasing pace of innovation diffusion are accelerating the frequency of disruption and the impact it can have on industry. As a result, value can be both created and destroyed seemingly overnight. By their nature, private equity (PE) firms have always had to be quick to respond to disruptive trends.

Digital Disruption and Private Equity: Understanding Effects and Opportunities.  With the rise of digital technologies, the pace of disruption and the speed of its diffusion has increased dramatically. If PE firms are to survive and thrive in this new era, they must consider the effect of digital disruption on their portfolios as well as their internal operations. They must also continuously adjust their strategy and decision-making framework, with consideration to how disruption affects industries, portfolios, and internal firm operations.


How does disruption alter industries?


With new disruptive innovations come new markets and value networks. These innovations can fuel new business models (e.g. ride-sharing applications helping to launch the sharing economy) and can disrupt existing markets and networks (e.g. how ride-sharing changed the taxi industry).

Furthermore, the very nature of what a business is changing. The power of “open innovation” means that the advantages of the classical firm as the most efficient means of creating value are giving way to ecosystems that have a much larger and more efficient means of assembling and reconfiguring resources in the pursuit of value creation.


2. Customers.

Digital disruption has irrevocably changed the customer journey. Customers of the “digital native” generation now expect information about a product to be accessible from the palms of their hands. They expect to be able to compare prices, see demonstrations, and receive feedback and recommendations from their social networks about products. Companies that can meet these new digital expectations can reap the value, while those that do not will rapidly succumb to irrelevance and insolvency.


3. Products.

As pressure mounts to meet increasingly demanding customer expectations of “the newest thing,” product lifespans get shorter. Long established products can quickly become obsolete. The advent of the smartphone leading to the decrease in relevance of Nokia, Blackberry and Motorola is a clear example. The fate of Kodak, once one of the most powerful brands in the world, serves as a stark reminder of what can happen when digital disruption is ignored. This example is especially poignant as it was Kodak itself that invented the digital camera and the digital SLR camera. In Kodak’s case, the curse of a powerful product-linked brand, an aversion to self-disruption, and the inability to recognize customers’ latent desire to share photos with friends and family in real time, led Kodak to fall from the Fortune 500 to bankruptcy in less than 15 years.


How does disruption create new value opportunities for PE?

As industries are disrupted, PE firms must themselves ask the following:

  1. Is a portfolio or target company at risk for becoming devalued by new technology?
  2. Is a target company appropriately prepared to embrace new technology?
  3. Is there an opportunity to capitalize on value emerging elsewhere as a result of disruption?

The ability to recognize the potential value of digital technologies in yet-unconsidered applications can add limitless value to a PE portfolio. Consider, for example, the emergence of bitcoin as a disruptive new asset class in the financial industry. It turns out that bitcoin’s underlying technology, blockchain, will be far more disruptive than bitcoin and will fundamentally impact countless industries. The ability to recognize the potential value of digital technologies in yet-unconsidered applications can add significant value to a PE portfolio.

Another source of value generated by digital disruption and efficient diffusion is accelerated innovation. Rather than focusing on developing a new product that may soon be outdated, accelerated innovation focuses on using new technologies to re-engineer research and development processes. Approaches include reducing lead times by engineering product elements simultaneously, reducing the learning curve by quickly incorporating user feedback, and increasing problem-solving efficiency by restructuring the organization. Despite the associated risk of failure, the ability of accelerated innovation to cut costs and reduce production times has proved highly valuable to customers, and worth considering not only as a framework to evaluate assets in a PE portfolio but as a means of improving the efficiency and effectiveness of the PE firm itself.  


How can PE firms realize new value opportunities?

In the age of digital disruption, it is no longer sufficient for PE firms to evaluate a target company using traditional value indicators (e.g. cash flow, capital expenditures, and historical performance). Historically valued companies may still be vulnerable to the newest wave of digital disruption. Others that appear to be digital laggards may actually have the potential for huge value generation given the right injection of capital, technology, and coaching.

To realize a valuable investment, PE firms must conduct due digital diligence on potential investments, asking the following:

  1. What is the target company’s level of digital maturity? I.e. have multiple aspects of the company–talent acquisition, marketing, sales, and customer relations, etc.—been digitized?
  2. What is the target company’s strategy for managing digital disruption?
  3. Does the target company have a method for measuring the financial impact of digital disruption and a formal discipline of data-driven decision making?
  4. Are the target company’s operations being reshaped by any industry trends?
  5. What technology has the potential to destroy profit across the current value chain?
  6. Which companies might emerge as unexpected competitors?
  7. Does the company’s senior leadership team support a culture of innovation and risk-taking?

Digital disruption can increase the potential revenue of a business that is culturally prepared embrace disruption. As a result, it can generate new business growth in new and adjacent markets. To capitalize on this potential value, PE firms must calculate risks and opportunities by conducting conduct rigorous digital due diligence on potential investments.  They should also consider what value they can contribute to prospective and existing investments to help those companies survive and prosper in an age of accelerating innovation.


How can disruption impact PE firms internally?

The primary focus of most PE firms is on the operations and business prospects of their portfolio companies. The internal operations of the firm itself are often of secondary importance. But digital disruption is as much of a risk, and a potential opportunity, for firms. Disruption can impact investors and partners alike, altering expectations of business conduct and introducing new security threats.

PE firms should address their own place in their digital ecosystems by asking:

  1. How will new and growing threats to privacy and cybersecurity be addressed?
  2. Should the firm buy an existing system to enhance its digital capabilities, or build its own?
  3. Which disruptive technologies can be utilized to improve and enhance firm operations?


How can PE firms use disruptive technology to optimize internal operations?

Despite sophisticated financial tools, transactions currently rely on manual processes that are legally and paperwork-intensive. As a result, PE firms are an ideal environment for leveraging many disruptive technologies. The following technologies can all be implemented to optimize PE internal operations:

  • Robotic process automation (RPA): Improves productivity through automation. Processes that can be improved using RPA include investor reporting, waterfall calculations, capital call and distribution notices, performance calculations, tax compliance, management reporting, and regulatory reporting.
  • Advanced cybersecurity: Enables proactive protection and improves risk mitigation. Can be used to secure internal PE firm operations, including the exchange of money and sensitive information during deals and the management of the portfolio company post-deal. Cybersecurity ensures the safety of finances, intellectual property, and customer data.
  • Cloud: Improves the operational speed and ease of deployment, resource utilization, the agility of adjustments, security of materials, and containment of costs.
  • Advanced analytics: Drives decision making and insight with deep pattern recognition and outcome prediction. Use of analytics can also improve and accelerate the due diligence process. Advanced analytics also can rationalize unstructured and complex data sets already available.
  • Blockchain: Improves workflow efficiency, fraud reduction, and onboarding and identity management. Blockchain can also be used to secure deal execution.
  • Artificial Intelligence: Improves insight and exception handling. AI can be applied to valuations, using qualitative and quantitative variables to estimate the odds of achieving higher risk-adjusted returns. Natural language processing can improve sentiment analyses, identify trends, and automate call centres. A noteworthy example, Deep Knowledge Ventures uses an AI system, called VITAL, with its investment committees. This system makes decisions by scanning prospective companies’ intellectual property, clinical trials, financing, and previous funding rounds to determine the attractiveness of an investment and assess related risk. 


The final word.

To develop the operational framework necessary to manage internal and external disruption, organizations require a well-designed strategy led by an aligned and engaged management team. By combining a robust operating framework with a formalized approach to strategic innovation, organizations can foster a culture of continuous improvement and adjustment. This includes looking outside of the organization to forecast possible scenarios, new domains, and potential offerings. Internally, this includes the reallocation and definition of roles and responsibilities with leadership capabilities. With these strategies in place, the focus can shift to the creation of an innovative culture that seeks new value in both internal operations and external performance.


Digital Disruption and Private Equity: Understanding Effects and Opportunities.


The impact of employee engagement on organizational performance

The impact of employee engagement on organizational performance  There is a well-supported link between employee engagement and business performance. The logic is simple: a more engaged workforce leads to increased operational efficiency, happier customers, and higher profits.  But how does a more engaged workforce produce these desirable outcomes, and how can a business improve engagement?

One of the key differences between the performance of an engaged and a disengaged employee is “discretionary effort,” or “the level of effort people could give if they wanted to, but above and beyond the minimum required.”[i]  Simply put, if employees are involved in and enthusiastic about their work and workplace they are likely to exceed the expectations and requirements of their position. But how can businesses encourage higher levels of engagement in their staff? Moreover, how can they prevent disengagement from occurring in the first place?

Engaged employees are passionate about their work. They feel motivated by their leaders and are confident they can achieve success in their roles. Engaged employees see the purpose in what they do every day and play a significant role in business successes.

However, many workers do not experience this level of engagement. According to research conducted by Gallup, around 50% of the US workforce is disengaged, and 15% to 20% is actively disengaged.[ii] Disengagement may be caused by a poor relationship with a direct manager or by a lack of meaningful feedback or recognition. It may even be a basic misalignment between the company and employees’ values. Without a way to measure employee engagement, business leaders are left to guess at what actions will improve the employee experience.

Collecting and monitoring employee engagement metrics enhances business leaders’ ability to detect problems in their organization, take specific action to address issues and opportunities, and evaluate subsequent progress.

With our EnGauge employee engagement program, we at The Burnie Group help our clients understand how their businesses are performing across ten key engagement metrics:

  1. Happiness
  2. Wellness
  3. Satisfaction
  4. Personal growth
  5. Relationship with peers
  6. Feedback
  7. Recognition
  8. Relationship with manager
  9. Alignment
  10. Ambassadorship

The impact of employee engagement on organizational performance  Using this information, we work with leaders to develop action plans to improve employee engagement.  Through a repeatable improvement cycle, we help businesses take control of employee engagement and achieve the desired results: increased operational efficiency, happier customers, and higher profits.

Looking at the list of metrics above, how do you think your business compares? If you see room for improvement, give us a call and realize the potential of an engaged workforce.

The impact of employee engagement on organizational performance

 By: Bret McCaffrey, Senior Associate

[i] Earning Above and Beyond Performance: Understanding the effective use of positive reinforcement (ADI Aubrey Daniels International)

[ii] State of the American Workplace (Gallup News), 2017