12 Notable Tech Trends in 2022

 


Gartner predicts that these 12 technologies will "become a starting point for innovation and the foundation of digital business in the next three to five years."

In this article, we will explain each technology in an easy-to-understand manner. We've covered three things to work on first. Everyone involved in management, business strategy, and DX, please take a look.

 

[Caution] Cloud native platform

 

“The cloud-native platform is a technology that builds new resilience, resilience, and agility application architectures that enable rapid adaptation to digital transformation.

Cloud-native platforms improve the traditional “lift-and-shift” cloud approach that leverages the cloud to complicate maintenance".

Source: Gartner Japan Co., Ltd. website

 

Even in these days when cloud computing is being called for, about 40% of companies operate servers on-premises (a method of setting up a server in-house) due to resistance to managing personal information outside the company. The biggest challenge on-premises is the maintenance period. Once the maintenance has expired, you will not be able to install new memories or products of the same type.

 

Therefore, each company is switching from "on-premises" to "cloud". However, since the application was not originally developed to adapt to the cloud, additional refurbishment costs for migration will be incurred.

 

Therefore, in the future, we recommend that you develop on the premise of the cloud from the beginning and then use the "cloud native platform" that uses the cloud server. This frees internal IT personnel from tasks such as infrastructure construction and server maintenance, allowing them to focus on service development that accelerates their business.

 

[Attention] Total experience

 

Total experience is a business strategy that integrates employee experience, customer experience, user experience, and multi-experience across multiple points of contact to accelerate growth.

Total Experience gives you comprehensive control over your stakeholder experience and enhances customer and employee trust, satisfaction, loyalty, and advocacy (recommendations).

Source: Gartner Japan Co., Ltd. Homepage

 

In addition to UX (user experience) and CX (customer experience) that you often hear, EX (employee experience) and multi-experience ( VR and AR) are collectively called "total experience".

 

UX and CX are all focused on direct contact with end users, but EX tends to be postponed. All experiences are connected, so low employee engagement, such as "overtime work" or "not rewarding," can go around and ultimately reduce the value you provide to your customers.

 

However, there are some caveats with EX. Even if the introduction of cloud services increases productivity, makes it easier to work with remote work, and lowers the turnover rate of employees, it is meaningless unless it leads to the provision of value to customers. Let's connect the improvement of EX to the improvement of UX / CX and increase the corporate value.

 

[Attention] Composable application

 

Composable applications are built from business-centric modular components. Composable applications make it easier to use and reuse code, shorten the time to market for new software solutions, and unlock corporate value.

Source: Gartner Japan Co., Ltd. Homepage

 

"Composable application" is an approach to ensure quality even for development teams with a mixture of members of various skills and languages, such as inexperienced people and overseas engineers.

 

Until now, the mainstream style was to proceed with development from scratch no matter what was made. Therefore, the output varied depending on the skills of the members in charge, and the quality could not be standardized.

 

On the other hand, the "composable application" is a style in which parts are first created, parts are assembled like a Lego block in a virtual space on the cloud, and development is advanced while simulating whether or not it works properly. Since communication costs are reduced, it is easy to collaborate with overseas, and efficiency can be improved by diverting parts once made to others.

 

Let's take a brief look at the remaining nine technologies.

 

Data fabric

 

The data fabric integrates data that exists across multiple platforms and business users for greater flexibility and resilience. The data fabric covers the data of multiple applications as a whole and makes the data available where it is needed, without being constrained by a single platform or tool.

Source: Gartner Japan Co., Ltd. Homepage

 

The data fabric can also learn what data is being used with built-in analytics. Its true value lies in its ability to recommend more diverse and superior data, and data fabrics can reduce manual data management by up to 70%.

 

With the tightening of cookie regulations, there is an accelerating movement to store customer personal information and behaviour history in the company's CDP (Customer Data Platform) and centrally manage it. However, due to the convenience of pulling data from any platform or system, it was necessary to manually align and store the data format and granularity.

 

The "data fabric" is an approach that eliminates inefficient data management tasks by pre-arranging data formats that can cover multiple applications.

 

Privacy enhancement computation

 

The Privacy Computation (PEC) ensures the security of personal data processing in unreliable environments. This is becoming more and more important due to the evolution of privacy / data protection laws and growing consumer concerns.

The Privacy Computation uses a variety of privacy protection approaches to help you derive value from your data while meeting your compliance requirements.

Source: Gartner Japan Co., Ltd. Homepage

 

When the data stored in the CDP is passed to another system for business use, it is necessary to process it into data that does not identify an individual from the viewpoint of privacy protection. However, if the information is deleted, the value of the data itself will be lost.

 

Therefore, the "Privacy Enhancement Computation" is an effort to safely utilize data while encrypting and dividing it, instead of deleting information.

 

Cyber ​​security mesh

 

Cyber ​​Security Mesh Architecture (CSMA) provides a composable security approach based on identity, building scalable and interoperable services.

Cybersecurity meshes enable best-of-breed and stand-alone security solutions to work together to improve overall security and bring control points closer to the assets that are inherently protected by those solutions. You can also quickly and reliably verify your identity, context, and policy compliance, whether in the cloud or not.

Source: Gartner Japan Co., Ltd. Homepage

 

Until now, security tools have been introduced with different services such as for on-premises, cloud servers, and business terminals, and maintenance has been troublesome. The "cyber security mesh" is to integrate these and manage them efficiently.

 

In the unlikely event of an accident such as an information leak, a common security tool can quickly identify the cause. In 2022, security vendors will announce integrated solutions.

 

Decision intelligence

 

Decision intelligence is a hands-on approach to improving an organization's decision making. Use intelligence and analytics to inform, learn, and improve decision making to model decision making as a series of processes.

Decision intelligence supports and enhances human decision making and, if possible, automates it through the use of enhanced analytics, simulation, and AI.

Source: Gartner Japan Co., Ltd. Homepage

 

"Decision-making intelligence" uses AI for the dashboard checked on SFA / CRM to predict future sales and support sales activities and staffing decisions.

 

Specifically, there is information such as "Customer A is expected to purchase this much in the near future, so if you open this much, your profit will be like this in two months. On the contrary, if you do not open it, you will lose this much opportunity." It is an image that appears on the dashboard.

 

Hyper automation

 

Hyper-automation is a disciplined, business-driven approach to quickly identify, validate, and automate as many business and IT processes as possible.

Hyper-automation enables greater scalability, remote operations, and disruption of business models.

Source: Gartner Japan Co., Ltd. Homepage

 

As the name implies, "hyper-automation" is the idea of ​​expanding the scope of automation. For example, we will expand the scope of automation by incorporating optimal tools for each business process, such as RPA (Robotic Process Automation) for the sales department and OCR (Optical Character Recognition) for the management department.

 

However, if management becomes complicated due to the mixture of automation tools, it will be overwhelming. Let's proceed with the introduction while assessing the priorities from a company-wide perspective.

 

AI engineering

 

“AI engineering automates data, model and application updates and streamlines AI delivery.

By combining AI engineering with strong AI governance, you can operate AI delivery and ensure continuous business value”.

Source: Gartner Japan Co., Ltd. Homepage

 

In most cases, AI so far has "created a model and finished". However, that does not provide continuous value, so the idea of ​​operating and nurturing the model itself is necessary. The technology for that is "AI engineering".

 

Generative AI

 

“Generative AI learns about deliverables from data and produces new, innovative outputs that are similar to the original but never repeat.

Generative AI has the potential to create new forms of creative content such as videos, and accelerate R & D cycles in a wide range of fields, from pharmaceuticals to product creation”.

Source: Gartner Japan Co., Ltd. Homepage

 

In order to utilize AI, it was necessary to prepare a large amount of sample data and train it. "Generative AI" is a technology that allows AI to synthesize even sample data by itself and proceed with learning without permission. Even if you don't have a lot of data, you will have more chances to utilize AI.

 

Distributed enterprise

 

“Decentralized enterprises reflect digital-first, remote-first business models, improve employee experience, digitize consumer and partner contacts, and enhance product experience.

Decentralized enterprises can effectively meet the needs of remote employees and consumers who are driving the demand for virtual services and hybrid workplaces”.

Source: Gartner Japan Co., Ltd. Homepage

 

With the epidemic of the new coronavirus infectious disease, digitalization has progressed at a stretch even in store-type businesses. "Distributed Enterprise" is an effort to improve the customer experience and employee experience by integrating offline and online customer data.

 

Autonomic system

 

“An automatic system is a self-managed physical / software system that learns from the environment and dynamically rewrites algorithms in real time to optimize behavior in complex ecosystems.

Autonomic systems create a range of agile technology capabilities that can support new requirements and situations, optimize performance, and defend against attacks without human intervention”.

Source: Gartner Japan Co., Ltd. Homepage

 

Until now, software installed on business terminals had to be manually updated and managed. On the other hand, the "autonomic system" is a mechanism in which the system rewrites the program by itself to optimize the performance based on the past update information.

 

Lastly

 

Investing in technology is essential to continue to provide value to our customers five to ten years from now. If any of the trends introduced this time match your company, please try to incorporate them.

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