Digitization (dig-​i-ti-​za-tion) and digitalization (dig-​i-​tal-​i-za-tion) may sound similar and are often used interchangeably, but the reality is they are two separate concepts that accomplish unique goals. 

Digital aspects have become interwoven into the steady rhythm of our lives, so much so that we often don’t even realize it anymore. We can go for hours with only our smartphones and limited human interaction without batting an eye. 

Imagine a typical afternoon of running errands:

• You swing by a fast-food restaurant for lunch and order on the touchscreen
• You hop on the highway, and your digital wallet is charged by the tollway
• You order groceries on your phone app and stop by the store, having them placed in your trunk for you

These scenarios all encompass digital transformation across numerous areas of business and various verticals.

Each digital touchpoint has a business behind it that is working to incorporate numerous digital aspects that contribute to transforming a process to be more ‘seamless’ to the end-user, whether through digitization or digitalization. Understanding these different versions of digital can quickly lead to confusing tongue-twisters. 

In this blog, we’ll break it all down and discuss ways digital transformation can help optimize your business processes and benefit the future of your enterprise as a whole.

What is Digitization? 

According to Gartner, digitization is defined as “the process of changing from analog to digital form, also known as digital enablement. Said another way, digitization takes an analog process and changes it to a digital form without any different-in-kind changes to the process itself.”

Digitizing is when data is converted to a digital format but the data itself does not change. Digitization can have notes of nostalgia since many of the examples hearken back to past decades. Digitization could involve taking a photograph from an old-school album and scanning it to create a digital file, or converting your home movies from clunky VHS to MP4 video files.

The process of digitizing has changed the game in business environments, especially with the strategies required for companies to stay competitive in the current economic climate.

According to the McKinsey Global Survey of executives, participant companies have accelerated the digitization of their customer and supply-chain interactions, and even their internal operations by three to four years. This includes areas such as back-office, production, and R&D processes. 

Here are two examples of digitization of business processes in action:

• Fast-food chains: So, you want a burger with extra cheese, no ketchup, and extra onions? You can have just that when ordering at a drive-through lane speaker.

More and more fast-food and fast-casual restaurants are making the leap from analog person-to-person ordering to giving customers the digital tools to customize their orders and eliminate miscommunication opportunities. In-restaurant kiosks let customers easily place their specific orders, log in to access their favorite items for faster ordering, or input their rewards numbers to pay with points. 

• Customer service: Interactive Voice Response (IVR) is an automated business phone system feature that adapts to callers' real-time responses. The system recognizes a caller’s intent and performs actions based on how the caller responds through either the telephone keypad or with their voice. Evidence of digitizing in contact centers is that companies have removed all traces of paper. Agents take call notes within their CRM, and notes are searchable for future interactions and shareable with other agents via chats or wikis. 

What is Digitalization?

Now it’s time to understand digitization vs digitalization. One of the main differences between digitization and digitalization is that while digitization is about the transfer of data, digitalization is about optimizing the processes for data. Per the Gartner glossary, digitalization is “the use of digital technologies to change a business model and provide new revenue and value-producing opportunities; it is the process of moving to a digital business.”

As the prevalence of digital transformation grows, examples of digitalization become more and more widespread.

Digitalization has sped up the development of new digital technologies such as cloud computing, artificial intelligence, and machine learning. Perhaps we are seeing the incorporation of digitalization the most in light of the shift to remote and hybrid work. According to a McKinsey survey of business executives, 85% of respondents said their businesses have somewhat or greatly accelerated the implementation of technologies that digitally enable employee interaction and collaboration, such as video conferencing and file sharing.

Offices now leverage programs such as Zoom for virtual meetings, Slack for chatting, and Asana for productivity. At Kenway, we use Microsoft Teams to manage operations like storing files in the cloud or hosting client meetings. Microsoft Teams usage has seen rapid growth in recent years, steadily progressing from 150 million active monthly users in 2020 to 320 million active monthly users in 2023. 

Digitalization did not go away with the pandemic. A Gartner poll showed that 48% of employees will likely work remotely at least part of the time after COVID-19 versus 30% before the pandemic. This means that many companies will continue relying on digitalization to make their processes more efficient, simplify business decision-making, and improve business outcomes.

What Is Digital Transformation? 

Digital transformation is the process of leveraging technology, organizational processes, and people to develop or enhance existing business models and revenue streams. Digitization and digitalization are essentially digital transformation’s supporting players. 

In fact, several different platforms are implemented across enterprises to perfect and accelerate the adoption of a more digital-forward workforce. Salesforce is the ultimate example of a tool companies leverage to help them enable enterprise-level digital transformations. Salesforce comprises a suite of cloud-based applications that unify customer data into a single, shared view, turning information into insight. 

As a Salesforce Partner, Kenway partnered with a leading financial services company to help them comply with new regulatory requirements by using Salesforce to implement firm-wide process automation.

The era of automation is here to stay, especially after benefits were realized when organizations were forced to shift to a digital environment in 2020. 

Below are some stats that could help put this migration into a digital-forward world into perspective:

• 91% of organizations say they need solutions that automate processes so they can do more with less
• 77% of workers say automation has provided them with the time to deepen relationships with customers and stakeholders.

Digitization vs Digitalization vs Digital Transformation 

It’s crucial to understand the nuances between digitization, digitalization, and digital transformation. 

Here are simple definitions of these terms for quick reference: 

• Digitization involves the conversion of analog data into digital form, streamlining accessibility and management. 
• Digitalization builds upon this foundation, leveraging digital tools to optimize processes and create value. 
• Digital transformation represents a more profound shift, encompassing strategic restructuring across organizational culture, business models, and customer experiences. 

In summary, digitization and digitalization lay the groundwork for technological integration and operational efficiency, while digital transformation drives fundamental change, reshaping businesses for sustained relevance and competitiveness in the digital era.

How Digitalization Translates into the Real World 

Kenway recently worked with an industry-leading healthcare solutions provider to define and implement data transformation to support an improved future state. The client faced a worst-case scenario when it learned that the strategic partner it had leveraged to help collect and aggregate data was not only terminating its agreement but also becoming a direct competitor in just 12 months. 

The client’s most significant obstacle was getting all the data from the existing solution provider and migrating that data to the new solution provider. Further complicating the situation, the existing data set had quality issues that needed to be addressed prior to the migration. Kenway delivered this digitally transformative solution:

• Migrate and transform: Developed a Python-based data migration process to improve the data quality prior to loading the data files. Data quality reports were used to detect issues so any needed remediation could be applied.
• Audit, balance, and control: Best practices were applied through automated procedures and daily reports to ensure data integrity.
• Process transparency: There was full visibility into the status of the digital transformation with daily progress updates, allowing the client to pivot business resources and priorities as needed.

How to Benefit From Digital Transformation

A thorough understanding of these three terms is essential for their potential benefit to your company. Whether you need help with digitization, digitalization, digital transformation, or some intersection of all three, Kenway is here to ensure your organization navigates the digital landscape with expertise and optimal execution. 

We address your digital transformation requirements by identifying the capabilities and services required to solve your business challenges–it’s never a one-size-fits-all approach. 

Are you ready to accelerate your business processes? Connect with us to learn how we can help with your digital transformation needs.

FAQs

Why is digital transformation important for businesses?

Digital transformation is crucial for businesses to adapt and remain competitive in the ever-changing digital landscape of modern business. Whether pursuing simple digitization or complex digitalization, using the digital tools at your fingertips will push your organization to greater heights. 

How does digitalization affect customer experiences?

Digitalization can aid in customer experiences by simplifying processes for employees, therefore creating more space for employees to develop relationships and serve customers with their full attention. 

What industries are most impacted by digital transformation?

In the world of modern business, digital transformation impacts every sector. A few to pay particular attention to are healthcare, banking, and IT.

How do companies innovate successfully? What’s the secret to sustainable growth? How do you build a thriving corporate culture? There’s no single answer to these questions, but a common thread among companies that innovate, grow, and build a thriving culture successfully is their ability to leverage data to drive decision-making.

According to a recent Tableau survey, companies that effectively use data analytics and data-driven decision-making increase revenue and profits by 8% and reduce costs by 4%. This likely doesn’t come as a surprise—data has the potential to accelerate business success. That’s why so many companies aim to improve their ability to leverage data and technology to support their growth.

However, while companies have access to vast amounts of data, many struggle to truly leverage data to develop a strategy that aligns with their business goals. To leverage data effectively, it’s essential to embrace both data governance and data management practices. With a holistic, strategic approach, you can unlock new possibilities and use data to drive decisions across your organization.

Challenges to Leveraging Data Successfully 

Despite having access to significant amounts of data, many companies struggle to leverage data effectively. Often, more immediate and urgent challenges—like customer satisfaction, competition, and regulatory compliance—take precedence over data initiatives. Client-facing projects, operational efficiencies, and daily fires compete for their attention, and data projects get deprioritized.

Because organizations don’t prioritize data management and governance, data is managed reactively. This leads to siloed data, making it difficult to connect data points and extract actionable insights. Instead of a proactive approach to leveraging technology and data, companies end up implementing isolated, reactive solutions that don’t contribute to a broader data strategy.

Four Ways Better Data Capabilities Improve Your Business Strategy

1. Understand Your Customers Better: Customers increasingly expect personalized experiences.  When you leverage data to develop a strategy tailored to customer needs, it becomes easier to engage prospects at the top and middle of the funnel and promote loyalty once they become customers:

• Gain insights on customer sentiment: Thorough data analysis complemented with analysis of surveys and reviews can help identify the true sources of customer concerns.
• Anticipate your customer’s needs by building comprehensive customer profiles: By leveraging data, you can anticipate customer needs, segment your audience, and tailor your marketing strategies.
• Create seamless omnichannel experiences: Master data management enables you to have a 360-degree view of customers, ensuring accurate information and smoother interactions.

2. Maximize the value of your Contact Center: Data-driven reporting for call centers can be useful in a variety of different ways depending on the needs of your organization:

• Improved decision-making: Real-time data means that you now have access to the most accurate information available about your customers and call center, which contributes to more confident and informed decision-making. 
• Enhanced customer experience: Better insights help resolve frustrations quickly, reduce delays, boost satisfaction, and support target achievement.
• Increased operational efficiency and performance management: Increased efficiency: With effective reporting, you can prioritize resources confidently, addressing key customer needs and improving performance.

3. Improve Agility:  Agile transformation offers a powerful solution to navigate constant business changes, as agile organizations consistently outperform their competitors and are better equipped to adapt to disruption. The ability to leverage data effectively is central to achieving this agility:

• Data-based decision making: Using KPIs, OKRs, and key outcome metrics provides an objective guide to decision-making. Choosing and then trusting the right data to continuously monitor your industry and business will alert you to changes and trend.

• Strategic internal partnerships creation: In agile organizations, departments like HR and finance are seen as key strategic partners. Relying on data to deliver insights is key. For instance, leaders across the business rely on finance for forecasting and analysis, and HR is tasked with addressing an ever-growing swath of issues, including employee performance and well-being.
• Empower employees to problem-solve quickly. Employees at all levels face new challenges every day. Access to comprehensive data makes it possible for them to identify root causes, model future scenarios, respond quickly, and repeat.

4. Tap Into Your Employees’ Needs More Effectively: Like customers, employees also expect personalized experiences. Leverage technology to analyze employee wellness data, survey feedback, and performance metrics. By understanding employee turnover, diversity, and performance, you can use data to improve HR strategies.

5. Identify Successful and Sustainable Growth Strategies: Sixty-one percent of companies with mature data practices enter new markets successfully. Behind their success is the ability to leverage data improve R&D efforts and implement the most viable strategies:

• Identify growth opportunities across the customer lifecycle: Discover new ways to offer value to customers and predict revenue impact.
• Prioritize opportunities systematically: Conduct cost-benefit analyses to determine the most viable opportunities.
• Optimize customer experience across channels: Ensure seamless rollouts of new products or services by leveraging insights from customer data.

Provide easy ways to log and track feedback: Make it easy to collect and centralize feedback so you can measure the effectiveness of your new strategy and adapt when needed.

Improving your data analytics capabilities doesn’t simply mean collecting more data or hiring more analysts. Without a guiding strategy, even the best data won’t deliver its full value. To truly leverage data to develop a strategy, it’s critical to invest in data governance and data management practices to enhance data maturity and use information more effectively across the organization.

That’s what we help our clients do at Kenway. This case study stands as a powerful testimony of how Kenway helped a software firm improve its analytics capabilities by building a business intelligence roadmap, implementing standardized reporting, building and interpreting reports, and establishing the framework for sustainable value realization.

Ready to Leverage Data and Technology?

Do you want to use analytics more effectively for your business, but don’t know where to start? Kenway can get your analytics engine up and running. To learn how, contact us.

FAQs

How do you leverage data to develop a strategy?

To leverage data in developing a strategy, companies need to adopt a holistic, strategic approach that includes data governance and data management. This enables them to effectively use data throughout their organization to make informed decisions and create strategies that align with their business goals.

How to leverage big data?

Big data can be leveraged by ensuring it is integrated into the company’s strategic initiatives. This involves creating robust data analytics capabilities, prioritizing data governance, and employing data-driven decision-making to identify and act on business opportunities, customer insights, and operational efficiencies.

How to leverage customer data?

Customer data can be leveraged by integrating it across all channels to gain actionable insights. This enables creating personalizing experiences and driving informed decisions. Effective data governance and management are key to maximizing its value.

Thirty percent of the world’s data volume is generated by the healthcare industry. From the minute details of individual patient records to the large-scale datasets generated during clinical trials, healthcare organizations constantly generate new information.

This data holds the keys to solving the healthcare industry’s biggest challenges. However, that is easier said than done. Poor data quality and lack of interoperability can make data feel like more of a burden than an asset. A strong data governance program allows you to take control of your data and create a foundation to use it to improve the quality of care, control costs, meet compliance requirements, and innovate.

WHAT IS DATA GOVERNANCE IN HEALTHCARE?

Data governance is the collection of clearly defined roles, policies, procedures, and standards that ensure the effective and efficient use of data in enabling an organization to achieve its goals. Data—generated internally and externally—is constantly flowing through healthcare organizations. Without a disciplined, structured approach to managing it, it is impossible to be confident in the accuracy of that data or access it when you need it. Data governance in healthcare provides that structure and discipline.

Data governance is related to, but not the same as, data management. Your data governance strategy outlines who can take action, how they can act, the data they can interact with, the situations in which they can act, and the methods they use. Data management is the day-to-day work of implementing that strategy and effectively architecting and storing the data for use.

The Data Lifecycle

According to AHIMA, healthcare data governance encompasses the people, processes, and systems used to manage data throughout its lifecycle. This lifecycle, specific to healthcare, is:

• Capture - Data is recorded in various healthcare systems.
• Process - A series of actions are taken to create a product and/or service.
• Use - Data is accessed, shared, and analyzed.
• Store - Data is maintained and stored.
• Dispose - Data is destroyed based on retention schedules.

A healthcare data governance framework should be implemented across the entire organization, with the goal of creating a culture of data security, reliability, accessibility, and value. This moves beyond Technology, Reporting, and Data Science departments to all groups that contribute to data and leverage information.

For example, physician and nurse champion groups, as well as financial leadership, generate and rely on massive amounts of data. This data often impacts other areas of the business throughout its lifecycle. If they are not engaged in data governance in healthcare settings, they will unknowingly and unintentionally contribute to the mismanagement of data, only adding to the cycle of poor data practices.

WHY IS DATA GOVERNANCE IN HEALTHCARE ESSENTIAL?

Despite the fact that healthcare outpaces other industries in terms of data volume, many organizations struggle to use that data to improve patient care and make critical business decisions. Underlying this issue is a lack of trust in data, and an inability to leverage it for analytics. According to a survey of healthcare executives conducted in 2021:

• 80% say they cannot trust the quality of their data.
• 51% say data interoperability and integration is the biggest barrier to achieving strategic data analytics priorities.
• Nearly half of respondents say data management challenges lead to long delays, difficulty scaling and democratizing data, and limited time to analyze the data.

These issues prevent healthcare organizations from leveraging their data to solve problems. Workarounds and manual processes are all too common, which only lead to lost productivity and errors. When healthcare organizations deal with inefficiencies and inaccuracies on a regular basis, improving patient care and meeting compliance requirements are exceedingly difficult. Implementing advanced IT processes that can improve competitiveness and drive innovation is practically out of the question.

Why is Data Governance in Healthcare So Difficult?

Even though healthcare leaders see the value of data, structural and historical issues prevent them from making the progress they should:

• Traditional, manual processes are deeply entrenched, and many organizations lack the bandwidth and capabilities to modernize their practices.
• There are insufficient standards to support data interoperability between systems and stakeholders.
• Healthcare technology adoption often lags behind other industries.
• Healthcare data is more complex and sensitive than that of other industries. It is more difficult to implement automations and advanced analytics without increasing the risk of harm to patients or violating privacy.

The Benefits of Data Governance in Healthcare

Implementing a healthcare data governance framework empowers healthcare providers to take control of the vast amount of information they generate and make it trusted and actionable. It allows you to standardize data and make it accessible to the people who need it when they need it. Everyone, from frontline workers to executives, can use data to make faster, more informed decisions.

1. Improve data accuracy and reduce the likelihood of duplicated or incomplete records.
2. Improve efficiency of decision-making, care coordination, care delivery, and communication between providers, payers, etc.
3. Reduce errors in treatment.
4. Provide employees with more effective tools and information.
5. Use machine learning and artificial intelligence with confidence.
6. Improve compliance reporting.
7. Increase effectiveness and efficiency of data science staff and their insights.
8. Set the foundation for a scalable approach to data management.

Plus, most of the innovation in healthcare requires trusted data to succeed. As organizations implement value-based care and create products and services that solve complex healthcare challenges, many are looking to advanced analytics, machine learning, and artificial intelligence. These cutting-edge technologies must be built on a foundation of reliable, structured data.

HOW TO IMPLEMENT A HEALTHCARE DATA GOVERNANCE FRAMEWORK 

The first step to implementing a data governance framework is to develop your approach. There are a variety of paths to achieve data governance, but the most basic approaches center on three pillars:

1. Roles and Responsibilities: The individuals involved in data governance in healthcare will be responsible for making the strategy a reality and taking accountability for adhering to policies, standards, and processes.
2. Processes: Processes define how the policies and standards will be implemented. They should include change management and training to promote the adoption of the data governance strategy.
3. Policies and Standards: Guide how data is structured and used. Policies and standards enable organizations to use data in consolidated reporting and analytics platforms and ensure that data is fit to be used in whichever capacity the organization needs it.

Once your approach is set, you can use it to help build consensus among leadership. Data governance programs require a cultural shift and need company-wide buy-in to be successful. If the Technology and Data Analytics teams are the only departments engaged in data governance, then it will undoubtedly fall short. Implementing a data governance strategy may also require external expertise, which will require budget approval from leadership.

DEFINE OR REFINE YOUR DATA GOVERNANCE PROGRAM WITH KENWAY

At Kenway, we work with healthcare organizations to define and refine their data governance programs. We start by understanding your organization’s mission and vision, then creating a healthcare data governance framework that aligns with it. We identify where data governance will have the most value and assess where you are along the data maturity curve. From there, we create your data governance roadmap.

Whether you have an existing data governance program or want to start from the ground up, we can jump in to ensure that your next step is the right one. Contact us to begin the process! In the meantime, you can read more about our past experience with other healthcare organizations here.

FAQs:

How is Data Governance used in Healthcare?

Data governance in healthcare is used to ensure the accuracy, security, and accessibility of data throughout its lifecycle. It involves establishing clear roles, policies, and procedures to manage data effectively, from capturing and processing to storing and disposing of it. This structured approach allows healthcare organizations to improve patient care, control costs, meet compliance requirements, and innovate through reliable data.

Why is Data Governance in Healthcare so difficult?

Data governance in healthcare is challenging due to entrenched traditional processes, insufficient data interoperability standards, slower technology adoption, and the complexity and sensitivity of healthcare data. These factors make it difficult to modernize practices, implement automations, and ensure data security without risking patient privacy.

Is HIPAA Data Governance?

No, HIPAA is not data governance. HIPAA (Health Insurance Portability and Accountability Act) sets national standards for the protection of patient health information, focusing on privacy and security. Data governance, on the other hand, involves comprehensive policies, procedures, and roles for managing data accuracy, accessibility, and usability across its lifecycle to improve patient care and operational efficiency.