Top Digital Transformation Trends in 2020

This post is one part of G2's 2020 digital trends series. 

In my post from G2's 2019 digital trends series, I suggested that digital transformation (DX), which has been around as a topic for more than a decade, was moving into a new, second generation of transformation for businesses.

That shift continued for the entirety of 2019, and is the leading trend for businesses and technology moving into 2020. The technology that provides the underpinning of DX went through an evolution in 2019, but not a revolution—mostly, anyway. 

Digital transformation: Looking back, and looking ahead

When looking to evolve, scale, or improve, businesses focus on making changes in five areas: business model, business strategy, business operations, customer interaction, and workforce. While examining technology and its potential impact, it’s effective to use these five areas as a framework for planning transformational projects. 

The five technologies I discussed last year—artificial intelligence (AI), blockchain, cloud platforms, internet of things (IoT), and conversational user interfaces (UI)—are still extremely relevant in 2020, but to that list we’re making a few adjustments and additions:

1. 1. 1. Cloud platforms → Cloud computing (to capture more of the broad impact of cloud on DX)
      2. Biometrics
      3. Customer experience (CX)
      4. Security and privacy 

Biometrics and business transformation

The use of biometric authentication for identity is becoming widespread; that trend will continue into next year. Users are familiar with the tech thanks to the implementation of fingerprint and facial scanners on mobile devices, which in turn creates an environment to support the expansion of use cases. 

Facial and retinal or iris scanners are already growing in use for airport security and border control.

Biometrics as a service (BaaS) is gaining traction as well. Providing developers with easier access to BaaS should encourage broader use in custom apps and new products. As in most cloud offerings, removing the need to manage the infrastructure results in savings from both a time and cost perspective.

Multimodal biometrics, or using more than one biometric in the same use case, can increase security. Unimodal is still by far the most prevalent method, but multimodal is gaining some wider use. It is, in effect, the multi-factor identification (MFA) that we use in all sorts of online logins for added security.  

Business privacy and security in 2020

Security and privacy intersect directly with biometrics. While this may seem odd—since the point of using biometrics is to more accurately establish identity—if you focus on the biometric data, you will find that it is just as vulnerable as any other digital data in transit. Most sensors do not store the identifying data locally but instead communicate bidirectionally with a central data repository. 

Privacy laws in Illinois, Texas, and Washington—and soon California, as CCPA takes effect on Jan. 1, 2020—are somewhat problematic for biometrics. For example, In Illinois, which passed the Biometric Information Privacy Act (BIPA) in 2008, employers must:

1. 1. 1. 1. Obtain informed consent before collecting or disclosing biometric data
         2. Securely store biometric data
         3. Destroy biometric data in a timely fashion 

The remedies include allowing individuals to file lawsuits and be compensated $1,000 per incident unless the company was negligent or intentionally violated the law, in which case the penalty is $5,000 per incident. The European Union's GDPR treats biometric data as a “special data class” and has some specific provisions spelled out. In the U.S., outside the state laws, there is no federal regulation on biometric data at present.

News related to security and privacy has continued to dominate headlines, and the impact of the different public instances of breaches, hacks, malware, and ransomware has created a long list of negative outcomes for businesses. Reputation is definitely at risk over the publicity for a major incident, but the economic damage extends well beyond a tarnished brand. Ransomware does direct monetary damage no matter which path the company chooses, paying the ransom or not. Because of the growing number of privacy laws (including GDPR and the upcoming CCPA), fines for mishandling data happen more frequently and can be substantial. There’s also exposure to civil lawsuits, which happen with some frequency.   

Fighting the different security battles is a massive problem in a world where threats can come from many different attack vectors, and have the potential to be government sponsored or at least extremely well-funded. AI is increasingly important, with more security software incorporating “intelligence” to detect patterns or threats, reduce response times, and assist in fighting DDoS attacks. Unfortunately, it has created an “arms race” environment with bad actors responding with their own intelligent attacks. Ransomware attacks in particular have often been in the headlines in the past year, and the frequency at which they are deployed is likely to continue to increase. Although difficult to defend against or recover from, even if the ransom is paid, improving disaster recovery plans can save attacked organizations a lot of pain and expense.  

The current hot approach, which incorporates the growth of risk-based security approaches over the past few years, is the zero trust security model (and the use of zero trust networking software to implement that model). The basic premise is that nothing on the network is trustworthy, outside or inside the firewall. In other words, every network access event is treated as a threat, verified, and offered only access to the resources needed to restrict lateral movement. The strategy is built on assuming every access is a breach and therefore must be explicitly verified using any and all data available—including location, device, time, anomalies, etc.—and then granting the least privileged access possible for the user to accomplish the task at hand. 

Cross-collaboration: The future of digital transformation

When looking at the trends for 2020, a lot of the “action” can be found at the intersection of multiple trends. Part of analyzing and understanding the trends, then, should involve these intersections. One of these I’ve already mentioned—the intersection of cybersecurity and AI.

The way companies operate has come a long way, but digital transformation will continue to be top of mind for most businesses—especially when supporting technology continues to mature and provide more obvious value. As most companies are still in the midst of transforming operations, the most common IT structure is a hybrid of cloud and on-premises. The hybrid environment can be particularly challenging as companies try to stitch together a complete data structure necessary to support data-driven business decisions across the applications silos. This has increased the importance of both integration and analytics solutions as a method of breaking down the data silos. 

Unlocking the value in business data is critical to a successful transformation and continued competitive advantage. This underlying need to connect legacy systems to new cloud-based solutions will become more obvious to businesses as they struggle to gain the benefits from transformation efforts in 2020, essentially making 2020 the year of breaking down data silos through tighter integration and wider use of analytics across all functions.