Skip links

Digital Business Empowers Growth

Jump To Section

Digital business is a paradigm shift away from simple digital transformation. It is an evolution that will change how businesses respond to their respective markets and deliver what matters most to customers.

Redefining Enterprise Operations: The Evolution of Digital Business

Digital business is a paradigm shift away from simple digital transformation. It is an evolution that will change how businesses respond to their respective markets and deliver what matters most to customers. This avatar of enterprise business will bring new growth in terms of revenue, profit, cash, and market share by simplifying business and technology without disrupting business operations or a company’s clients. Why is this important? Because

Companies can now move with greater speed and agility and develop simplified usage of complex data models to identify and more swiftly respond to opportunities. It creates a new discipline and culture of thinking outside of the current complex environment and enables innovation, collaboration, and speed. Many people think digital business is transformation; rather, it is a fundamental change driven by continuous innovation and cultural excitement in organizations that enable higher productivity and tangible business outcomes. Key elements to digital business are:

Innovation
Creating a single source of truth
Launching simplified digital products

Innovation

Perhaps the biggest benefit stemming from the digital business comes from empowering employees to be more innovative. This shift in the enterprise culture motivates every employee to think outside the parameters of complex business and technology with new, simpler solutions.

Digital Business Innovation

This business benefit brings speed that shrinks the time between ideation and launching new products. It represents a migration to a well-organized, coordinated team discipline, culture of experimentation, and focus on return on investment.

Innovation will accelerate through gains in greater consistency across the enterprise while improving collaboration and recognition. It requires a cloud-based digital business platform to facilitate an agile and engineering environment for collaboration across business and technology.

Creating a Single Source of Truth

One of the most important initiatives for digital business is to develop business intelligence in real-time. It is based on relevant data from various sources (e.g., internal, external, open/social media) with appropriate attributes and algorithms. The business team collaborates with technology teams to create this in a true agile fashion, bringing speed and greater effectiveness.

Single Source of Truth

A single source of truth is deployed across business functions, including demand creation and management, supply chain, manufacturing, and logistics. It also helps to create new business models based on insights gleaned from customer needs in real-time.

Unlike the big bang approach of big data and data lakes, creating a single source of truth is an incremental approach. The business team takes ownership of data and collaborates with technology teams to build a road map for implementation.

The output is data/analytic assets that can be leveraged across all business functions for decision-making and investment optimization. This is facilitated by a business digital platform that brings data from various sources together and connects them in a truly agile environment for usage across the enterprise. Data is used collaboratively to create assets for a specific business outcome such as revenue, profit, cash, and market share.

Launching New Simple Digital Products (Business Models)

The culmination of continuous innovation and a single source of truth leads to a collaborative culture that can develop new digital products or businesses quickly. Market intelligence informs innovative ideas and permits rapid experimentation that leads to new products and business models through simplified end-to-end workflows and effective customer solutions.

Digital Business Launch

A business digital platform can facilitate agile through an end-to-end engineering environment in the cloud to bring speed, reusability of assets, security, and compliance. Digital maturity continues to accelerate and spreads to other parts of the company, leading to reduced ideation-to-launch product cycles. Employee satisfaction increases and organizational culture benefits as it embraces and adopts this better way to launch products quickly and efficiently.

Digital business is not a trend; it is the most direct path to accelerate business outcomes such as revenue, profit, cash, and market share. It is also the catalyst that permits continuous innovation, creates a single source of truth for better decision-making, dramatically improves time to market for product launches, and improves organizational culture and collaboration.

Digital business isn’t expensive, can be done quickly, and is not complex, although it needs a disciplined approach. It results in what companies want most: better results for the enterprise and improved product experiences for their clients.

Raj Vattikuti

Raj Vattikuti

Raj Vattikuti is an American-Indian entrepreneur, business executive and philanthropist. He is the Founder and Chairman of Altimetrik Corp. He is also the founder of Vattikuti Foundation. through which he is involved in many charitable causes.

Latest Reads

Subscribe

Suggested Reading

Ready to Unlock Yours Enterprise's Full Potential?

Adaptive Clinical Trial Designs: Modify trials based on interim results for faster identification of effective drugs.Identify effective drugs faster with data analytics and machine learning algorithms to analyze interim trial results and modify.
Real-World Evidence (RWE) Integration: Supplement trial data with real-world insights for drug effectiveness and safety.Supplement trial data with real-world insights for drug effectiveness and safety.
Biomarker Identification and Validation: Validate biomarkers predicting treatment response for targeted therapies.Utilize bioinformatics and computational biology to validate biomarkers predicting treatment response for targeted therapies.
Collaborative Clinical Research Networks: Establish networks for better patient recruitment and data sharing.Leverage cloud-based platforms and collaborative software to establish networks for better patient recruitment and data sharing.
Master Protocols and Basket Trials: Evaluate multiple drugs in one trial for efficient drug development.Implement electronic data capture systems and digital platforms to efficiently manage and evaluate multiple drugs or drug combinations within a single trial, enabling more streamlined drug development
Remote and Decentralized Trials: Embrace virtual trials for broader patient participation.Embrace telemedicine, virtual monitoring, and digital health tools to conduct remote and decentralized trials, allowing patients to participate from home and reducing the need for frequent in-person visits
Patient-Centric Trials: Design trials with patient needs in mind for better recruitment and retention.Develop patient-centric mobile apps and web portals that provide trial information, virtual support groups, and patient-reported outcome tracking to enhance patient engagement, recruitment, and retention
Regulatory Engagement and Expedited Review Pathways: Engage regulators early for faster approvals.Utilize digital communication tools to engage regulatory agencies early in the drug development process, enabling faster feedback and exploration of expedited review pathways for accelerated approvals
Companion Diagnostics Development: Develop diagnostics for targeted recruitment and personalized treatment.Implement bioinformatics and genomics technologies to develop companion diagnostics that can identify patient subpopulations likely to benefit from the drug, aiding in targeted recruitment and personalized treatment
Data Standardization and Interoperability: Ensure seamless data exchange among research sites.Utilize interoperable electronic health record systems and health data standards to ensure seamless data exchange among different research sites, promoting efficient data aggregation and analysis
Use of AI and Predictive Analytics: Apply AI for drug candidate identification and data analysis.Leverage AI algorithms and predictive analytics to analyze large datasets, identify potential drug candidates, optimize trial designs, and predict treatment outcomes, accelerating the drug development process
R&D Investments: Improve the drug or expand indicationsUtilize computational modelling and simulation techniques to accelerate drug discovery and optimize drug development processes