In a market awash with marketing messaging, the discussion of the difference between‘ digital transformation’ and ‘digitization’ is a common one. Whilst it is not uncommon for the terms to be used interchangeably, this is technically incorrect and the distinction is an important one, especially for businesses looking to make the most of the data they uncover as part of these projects.
Digital transformation is a broad concept that applies to all aspects of a business. Digitization, on the other hand, is a process that helps to drive the transformation.
When both operate in tandem, it is possible to create a more customer-driven experience. Customer experience improvement is a common goal in digital transformation.
Thirty-five percent of organizations report that meeting customer expectations was the primary driver in their transformation strategy.
Global spending on digital transformation efforts could reach $2.3 trillion by the year 2023. Digitization is a vital part of these initiatives and governs a lot of the return on this enormous level of investment. As a result, it is crucial not to compare digital transformation vs. digitization as apples to oranges. Instead, we must understand how the two complement one another.
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Defining digital transformation and digitization
Digital transformation typically refers to the overarching strategy of technological change that has the potential to impact all parts of the business.
It centers on replacing old, outdated manual methods and procedures with technology-driven ones but does so in a holistic fashion - targeting business processes, models, domains, and culture. By addressing all these components, leaders are far more likely to have a successful transition.
As an organization sets about transforming how it operates: legacy processes are altered or completely removed as a consequence of bringing new technologies to bear. The efforts result in a combination of increased speed or efficiency, reduced costs, greater versatility, and/or improved customer satisfaction.
By comparison, Digitization is a critical component of digital transformation. It is the process of converting hand-driven manual information into a fully digital format. A standard example occurs when old client files are scanned into a computer system and organized with software.
As an office full of filing cabinets is removed and replaced with a computer-based interface for the same information, a business has successfully embraced the first phases of digitization.
Digitization can also refer to converting manually intensive or human-oriented tasks into automated or semi-automated computer processes, such as using chatbots and artificial intelligence to rapidly respond to inquiries, instead of making customers wait for a human representative.
All these facets have one thing in common -they represent an opportunity for a business to gather data. As such they show that data is the currency of offer certainty for businesses looking to embrace digital transformation projects.
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Combining transformation and digitization for data-driven strategies
The vast amount of data generated from digitization as part of digital transformation efforts has enabled businesses across myriad industries to develop far more assured, customer-focused strategies to improve services and offerings.
Data provides empirical evidence—rather than speculation—that helps companies plan processes and predict customer behavior. Consider traditional A/B testing. Actual users receive multiple options based on the same concept. The data collected during this experience will tell the firm which option resonates more with its intended audience. The empirical evidence allows the company to guarantee a more positive customer experience. Simply put, better data equals better decisions.
However, there is a major hitch in data collection that could limit its effectiveness. That problem lies in customer trust. Almost half of Americans have had their private data breached at some point within the past five years. In the UK, June 2021 saw a comparatively low 9,780,931 breached records from publicly disclosed security incidents. Consumers are – sadly – already far too familiar with the feeling of being burned by the bad data storage practices of companies.
The impact of security and overcoming the risks in a data-driven strategy
This matters because anything that compromises consumer trust, kills the ability to collect the data that helps ensure digital transformation success. Any company that wants to take a customer-driven approach must adopt practices and principles that guarantee the safety of this private information. These security measures not only protect customers and businesses alike against a breach but also become a strong selling point to any target market, loudly stating: “We respect you and the trust you place in us.”
As mentioned earlier, thirty-five percent of organizations cite meeting customer expectations as the primary driver in their transformation strategy. However, all those efforts go to waste when the plan exposes personal information and breaches trust. It is vital to incorporate security at the deepest layers of the program to protect the integrity of data while also harnessing its full potential.
There are four pillars of an approach to manage this:
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Security as Code: Security as code adds protective measures into the very foundation of the program. Developers code in things like tests, gates, and other security checks to allow for continuous monitoring and improvement of the system. Security as Code creates a scalable solution ideal for controlling ever-changing data; security as Code is not some grandiose process and should not add complexity to the development process or tooling stack. For example, if a test suite includes assumptions that test an input to ensure it is hardened against SQL injections, then that is an example of security as code!
Automated Compliance: The requirements involved in managing customer data can vary widely by industry. For example, those in the healthcare industry must contend with HIPAA, while financial sectors are more concerned over the Gramm–Leach–Bliley Act. Applying the right compliance standards to data, and automating the methods of enforcement, ensures companies meet legal responsibilities to customers.
Cyber Threat Intelligence: Customer data will always be the target of bad actors, and they are forever changing their tactics. Open-source intelligence is incredibly valuable, as it allows companies to stay up to date on threats specific to their industry. With the right cyber threat intelligence, they can understand why specific data is at risk and assess attack sources.
Data Tagging: One significant risk to data security is disorganization. A firm cannot protect what it does not understand. Data tagging practices ensure companies can establish risk levels and provide the right standards of protection for confidential assets. Fortunately, the process of digitization provides the perfect opportunity to ensure that every piece of incoming information is appropriately tagged with the right classifications.
Digitization is a one-time, often labor-intensive process, best to get maximum benefit for the effort!
It is essential to be transparent about security measures in any digital transformation strategy or digitization program. Customers must trust an organization to share their data and having clearly established security protocols builds that confidence. Transparent security helps companies to take advantage of a customer-driven strategy while maintaining system integrity.
It is only then that the data can feed the digital transformation program and ensure that the changes brought about are in line with customer expectations and demands.
Andrew Leigh, CMO, Copado