Following the economic slowdown perpetrated by the pandemic, global businesses are now on the way to regain pace. Meanwhile, most have learned to pivot, adapt and strategize in order to sustain the momentum. Our Tech Vision sheds light on the strategic plans we envision incorporating within our organizational structure.
The situation and state-imposed mandates have coerced the organizations into making most of the available technologies leading to disruption. This has also caused a worldwide acceptance of technologies, fuelling the quest for innovation – apparent as strategic technology trends.
Introducing the Concepts
The strategic technology trends may be classified into three aspects, interlinked at several points.
- Personnel Aspect– ‘People’ form the core of any business. They need digitized processes to cater to their various needs
- Location Aspect- the Pandemic has forced employees out of the discipline of a work environment. This demands the technology shift to support this new format.
- Operation Aspect– be it pandemic or recession, volatility must be faced. Businesses must reorient their structure to rebound from the shocks.
1.0 Personnel Aspect:
The Personnel Aspect involves development in three spheres:
1.1 Integration of Internet of Behavior (IoB) in the Internet of Things(IoT)
IoB is an extension of IoT. IoT connects electronic devices to the internet and this results in the revelation of information related to lifestyle and thought process: IoB captures this data to gain insights into the preferences and habits.
Example Scenario: Radio cabs utilize smartphone apps to track a user’s location. This helps them gain an insight into his routine visit points. This in turn allows them to make vehicles readily available near him during those times.
Integrating IoB in IoT in digital marketing strategies can be instrumental in enhancing sales.
Banks may utilize the same concept to detect potential customers, thus, saving up on resources and time while raising the conversion ratio.
1.2 Total Experience
Total-experience is computed from the measure of siloed disciplines such as Multiexperience (MX), Customer Experience (CX), Employee Experience (EX), and User Experience (UX).
Example Scenario: For a visit to the doctor’s clinic, a registered patient seeks an appointment through an app. They arrive around the time of the appointment. A tracker notifies the clinic authorities of their arrival. At the same time, the patient receives a form that collects their insurance data. Upon verification, another notification on their device guides them to a specific room where a nurse records their vitals and the information is forwarded to the doctor, who finally receives them.
In this process, the safety of the patient as well as the clinic staff can be maintained with minimum possible physical contact.
1.3 Privacy-Enhancing Technologies
Privacy-enhancing computation – the enormous amount of data generated per day can be structured, managed, and protected by the application of technologies collectively called Privacy-Enhancing computation. This contains three forms:
- Provide a trusted environment where data can be processed securely
- Analytics through privacy-aware Machine Learning
- Data and algorithms transformation including homomorphic encryption to keep the data confidential and multiparty computation
Privacy-Enhancing Technology (PET)- the different technologies that come together to protect user’s personal data are:
- Homomorphic Encryption
- Trusted Execution Environment
- Multi-party computation
- Differential privacy
- Personal data stores
Also Read: Blockchain Trends 2021
2.0 Location Aspect:
2.1 Distributed Cloud
A public cloud computing service that lets the user run public cloud infrastructure in multiple distinct locations. This happens not only on a subscribed cloud provider’s infrastructure but on-premises, in other cloud providers’ data centers, or in third-party data centers or colocation centers – and manages everything from a single control plane.
This needs to be achieved to ensure centrally managed distribution of public cloud services, Businesses can deploy and run applications. And so can individual application components in a mix of cloud locations and environments that best suits their requirements for performance, regulatory compliance, and more. Distributed cloud resolves the operational and management inconsistencies that can occur in a hybrid cloud or multi-cloud environment.
Internet of Things (IoT), artificial intelligence (AI), telecommunications (telco), and other applications that need to process huge amounts of data in real-time are primary seekers of Distributed Cloud Technology.
2.2 Anywhere Operation
Users, today, need to leverage the potential of cloud technology to work from anywhere. They might need to access their bank accounts, operate a business, or send work-related emails while traveling to business locations or otherwise. It is essential to provide users with secure network infrastructure to facilitate an all-over work environment.
This scenario demands far more than a stable internet connection. An IT operating model needs to be deployed that can cater to clients anywhere and enable employees to perform from anywhere. And also manage the deployment of business services across the distributed infrastructure. This essentially asks for:
- Collaboration and productivity
- Secure remote access
- Cloud and edge infrastructure
- Quantification of Digital Experience
- Automation to support remote operations
2.3 Cyber-security Mesh
Cybersecurity mesh is a distributed architectural approach to scalable, flexible, and reliable cybersecurity control.
The concept of cybersecurity mesh recognizes that networks have no physical boundaries.
More specifically, a Cybersecurity Mesh involves designing and implementing an IT security infrastructure that loops a single ‘perimeter’ around all devices or nodes of an IT network, but instead establishes smaller, individual perimeters around each access point.
This approach is capable of establishing a more robust, flexible, and modular approach to network security, by ensuring each node has its own perimeter.
3.0 Operation Aspect:
3.1 Intelligent Composable Business
Composable business refers to modularity in the business structure. The business implementing such an approach has its functions blocked down to interchangeable blocks of services. This approach enables organizations to reorient and rearrange as per external and internal shifting factors.
This modular approach may be integrated with business intelligence to transform decision-making and create interchangeable foundations.
This approach is driven chiefly by innovation and a lot rests on the Innovation head to bring this model to effect.
3.2 Artificial Intelligence
Artificial Intelligence (AI) is ideated to devise systems that emulate human beings in speeches and actions on a cognitive level.
A robust AI development strategy should impart performance, scalability, and interoperability. The strategy will, however, fail if encountered with issues related to maintainability, scalability, and governance.
Machine Learning (ML) is a part of AI in which historic data is fed into the algorithm which can detect the pattern and spot the inconsistencies to come up with a prediction for future outcomes. Such predictive analysis can be helpful in investment departments in enabling business-line managers to minimize risks and maximize profits in the investments of an organization’s capital.
Business Process Automation – A special mention
Efficiency and cost reduction are the prime factors that drive businesses towards automation. Automation combined with cognitive intelligence can achieve greater agility, lower risks, higher growth, and better customer experience. The Covid-19 reoriented the organizations into refocussing on the resilience in the mode of operation. This has spurred the implementation of automated business methods.
People in every department in an enterprise are often tasked with the mundane jobs of fetching information from, for instance, a financial reporting system and dropping the same into an HR reporting system. Bots are better suited to do such jobs minimizing the scope for error and significantly faster. RPA bots are appropriate for such rote tasks which do not involve higher-order judgment or learning.
Hyperautomation refers to automation to the hilt. In this process, businesses automate as many singular processes as possible leaving minimal scope for human intervention. To achieve this the organizations are to utilize the tools of AI, Machine Learning, Event-driven software, Robotic Process Automation, and other decision process and task automation tools.
Example: Accounts Payable (AP)
The accounts payable process includes receiving, processing, and paying out invoices from suppliers that provided goods or services to the company. Manual processing is expensive and leads to longer processing time, increases the risk of errors. With the addition of machine learning and document extraction technologies such as Optical Character Recognition (OCR) to the RPA, businesses can automate most of the tasks in AP processes.
The pandemic spanning the greater part of 2020 has enforced the series of readjustments, reorientations, adaptations to stay in the game. It has paved the way for heightened technological advancements and their adoption. Despite the challenges, the prospects look brighter.
Tech Vision 2021 looks forward to flexing available resources to imbue immunity in our operational framework.