Canada’s economy and society are becoming more digital

This article is part of our Mastering Data Series. This series examines the digitization underway in Canada’s economy, why it’s important, the data governance issues it creates, and how to address them. It also looks at the role you can play as a CPA in guiding your organization through the transition.

READ THIS ARTICLE TO LEARN:

• what is digitization
• why digitization is important
• digitization of Canada’s economy
• the value of data
• the challenge of data
• the role of CPAs in digitization

What is digitization?

Digitization is an enterprise-wide, ongoing effort to use artificial intelligence (AI) and other digital technologies to achieve the following objectives:

• Prediction: Anticipate events and trends through data analytics and react in real time.
• Automation: Automate processes and actions whenever possible.
• Optimization: Generate new insights to solve existing problems.

Achieving these three objectives improves the efficiency and effectiveness of ongoing processes, can lead to the creation of new digital products and services, and will add value to your organization.

Why digitization is important

Whether you work in services, manufacturing, resource extraction or the public sector, your organization is probably looking to digitize some aspect of its operations. The goal may be to access online sales data to better understand customer preferences, to use digital technology to streamline manufacturing processes, or to turn an existing physical product into a subscription service, to name just a few possibilities.

In addition to the benefits it can deliver, widespread digitization of Canada’s economy has created a massive explosion in potentially useful data. Being able to capitalize on the benefits of digitization and data while managing the risks is likely to be a key competitive advantage for your organization.

More than that, organizations that lag in embracing the benefits of digitization risk being left behind. A recent report on the manufacturing sector from the Canadian Economic Strategy Table put it bluntly: “We will either digitize our operations or we will die.”

Digitization of Canada’s economy

Read any business, information or communication technology journal and you will find many examples of companies going “digital.”  Outcomes include increased efficiencies, enhanced predictive capabilities, real-time reaction to events and the creation of new digital products and services

AI alone is enabling significant advances in diverse areas of value creation. These include:

• speech recognition, speech translation, image recognition, autonomous vehicles, crime and cybercrime prevention, and digital assistants
• forecasting customer demands, financial performance, and the onset of chronic disease in patients
• classifying realms of data from databases, text, images, movements and sounds

Once-small companies have become disrupters by using digitization to overcome deficits in both economies of scale and networks:

• Amazon, Alibaba and Kijiji are powerful retailers without the traditional investment space.
• Uber does not own taxis and is yet the largest taxi company in the world.
• Airbnb revolutionized the hospitality industry although it does not own any accommodation real estate.

Digitization also allows established organizations to become more efficient, effective and competitive:

• John Deere now collects data from sensors embedded in its tractors. The data is analyzed and marketed to farmers as a tool to improve their operations and bottom line.
• Humana, one of the largest insurance providers in the US, improved customer experience with a conversational AI chatbot. It uses AI to understand caller needs, verify their identity, and determine how best to provide the requested information.

If your organization is in the manufacturing sector, the potential is significant. Using technologies such as robotics, digital twins (a digital replica of a living or non-living physical entity), additive manufacturing (i.e. 3D printing), and big data analytics (advanced analytic techniques for very large, unrelated and diverse datasets), Canadian manufacturers can spur innovation and transform the efficiency of their operations. Digitization will impact how products are researched, designed, fabricated, distributed and consumed, how manufacturing supply chains integrate, and factory floors operate.

Public service delivery is also ripe for digitization. Data sharing and collaboration initiatives spanning departments and organizations will become key to maintain efficient government programs that generate better outcomes. Expect the creation of new data collaboratives to share data and generate insights in sectors as varied as public health, smart cities, transportation, distributed energy, public safety and security. 

In this environment, it will be imperative for consumers to trust that governments and businesses are not using data for unintended or disclosed purposes.  Trust will underpin all transactions and be vital for the economy to flourish.

The value of data

Digitization and data creation go hand in hand. When properly handled, data has immense value. Some believe data has the potential to displace oil as the most lucrative global commodity.

But unlike oil, data is not a finite resource. All organizations, from micro-sized businesses to multinational corporations continually generate and collect data in their daily operations.

Key sources of data include:

• traditional data in the form of financial (e.g. sales and expenses) and, operational (e.g. logistics and purchasing) databases and multiple reports generated across the organization
• new sources of data such as customer web clicks; digital objects; web traffic on social media accounts; Internet of Things (IoT) devices and sensors data; and GPS tracking of employees, vehicles, packages, etc. 

The challenge of data

Because there is an increasing amount of data made available, leaders in most organizations tend to agree that they are becoming data rich but remain information poor. A variety of factors are contributing to this reality:

• Rapid deployment of AI has led to issues such as algorithmic bias and concerns about the ethics of decisions made by machines.
• Secondary use of data (that is, using data generated for a purpose and applying it to another purpose) and data sharing between organizations have created new issues. associated with trust in datasets, data quality and transparency of data collection
• To choose the right datasets and make the right assumptions, AI scientists need additional information (metadata) such as data categorization and labelling, that is not always available.
• The emergence of businesses focused on data collection, aggregation and monetization has created new issues associated with data ownership, tagging and tracking.
• As the cost of storing data is decreasing, it is now possible to locate, access and use vast realms of data stored in data lakes (a collection of unstructured data) through cloud applications.
• Finally, the rapid deployment of billions of IoT devices is creating a tsunami of data for organizations to use in their quest to digitize operations and improve efficiency.

Clearly, issues such as common definitions and terms as well as interoperability (interfaces that work with interfaces of other products or systems) to allow data to flow through data platforms will need to be addressed. Common standards will have to be developed and adopted by a large number of organizations across various sectors for digitization to occur. Internally, organizations will need to understand the data value chain (the process of turning raw data into something of value) and develop robust digital strategies and governance policies.

The role of CPAs in digitization

In today’s uncertain environment, it makes sense for leaders to plan their transition to digitization carefully. Compliance with privacy regulations and adherence to accepted ethical norms contribute to the complexity of bringing data projects to successful completion. Data projects and strategies need a sound business case and organizational buy-in as well as proper enabling policies, procedures, risk management metrics and oversight. CPAs are well positioned to play a leading role in developing and managing the required data governance frameworks, including:

• corporate data policies to properly manage data governance issues
• corporate data strategies aimed at creating new markets; generating new insights for existing business lines or monetizing datasets through secondary use
• compliance to data privacy legislation
• frameworks for managing data quality and integrity
• frameworks for managing the access, storage and retention of data slated for secondary use
• methodologies to understand complex and large datasets and generate insights
• the financial value of an organization’s datasets
• risks associated with secondary data use.

Although specialists like data engineers, controllers and scientists are essential in performing day-to-day data operations, organizations also need to manage and oversee data and digitization policies and strategies. Many competencies required for a CPA designation are those needed to establish digital strategy and implement enterprise data solutions. These competencies include acting ethically and demonstrating professional values, strategy and governance.

Whether you work in the private or public sector, or for a not-for-profit organization, you are probably looking at new ways to harness data. Private sector corporations, big and small, are investing in digitization, including AI initiatives, to remain competitive. Organizations have begun to share data and generate valuable insights to meet public policy objectives and governments are digitizing historical paper-based records to create open sources of data to foster private sector innovation to trigger their economies. CPAs must use their foundational proficiencies in business expertise, judgment, skepticism, analysis and systems to be a part of that. 

MASTERING DATA SERIES 

More information is forthcoming on the critical role CPAs can play in mastering data, including the following issues:

• Understanding the data value chain
• Corporate data policy and its elements
• Creating a digitization strategy
• What is your data worth?