Skip links

Driving Growth with Digital Business Methodology and AI

Jump To Section

unlocking the power of digital business

It’s been fifteen years since the inception of DevOps, a movement to break down silos and improve collaboration tools and practices between software engineers and technology operations. The objective was clear, to expedite software releases while ensuring their quality. Over time, DevOps has become a standard operating model, improving collaboration, delivery, and fostering an` agile digital culture. However, as digital business takes center stage as the primary driver of growth, a fresh mindset is required to achieve tangible outcomes.

To embrace this new paradigm effectively, it is crucial to acknowledge the importance of digital business and establish a robust methodology to govern its implementation.

Differentiating between digital business and digital transformation is very important. The term “digital transformation” has become synonymous with the adoption of data and digital capabilities, but this is a misconception. CEOs and C-Suite executives should shift their mindset away from a technology-first approach associated with digital transformation and instead shift to digital business and its emphasis on solutions that deliver tangible outcomes.

Digital business operates within a company’s existing ecosystem, but it functions independently of existing silos and complex technology environments, ensuring minimal disruption to the current business operations. At the heart of digital business lies the Digital Business Methodology (DBM), serving as the driving force for success.

As a holistic approach, the DBM enables companies to adopt and implement digital business, it provides a defined path that orchestrates and converges data, technology, and people, delivering an outcome-driven, incremental approach delivering results across the enterprise with speed, consistency, and scale. This is powered by a business led agile digital culture that focuses on bite-sized outcomes essential to accelerating business growth.

The business takes the lead in collaboration with key stakeholders from ideation to deployment, focusing on the simplification of end-to-end workflows and the establishment of a single sources of truth (SSOT).

DBM is a guided, adaptable ideation-to-deployment ecosystem that enables seamless collaboration between business owners, engineers, analysts, scientists, and operational teams to drive innovative solutions and achieve outcomes. The establishment of strict governance ensures engineering rigor, quality, security, compliance (audibility, and traceability), and cloud services enabling companies to operate with higher productivity and predictability.

A key outcome of the DBM is the establishment of strong data management and governance, bringing core and domain data into an enterprise SSOT as a precursor for AI/ML.

Also read: Top 10 DevSecOps Trends

Inadequate Data Foundation: AI Risks

According to Statista, global spend on AI in 2023 the worldwide market revenue for artificial intelligence is forecast to grow significantly from 2018 to 2030. Estimates vary but they could reach over half a trillion dollars by 2024 and over $1.5 trillion U.S. dollars by 2030. While many companies are quick to jump on the AI bandwagon and readily allocate significant funding, they do so out of anxiety or fear of missing out. Unfortunately, these emotions are pushing them to get ahead of themselves without building the underlying core foundation of data that enables the effective use of tools like AI. Adverse consequences of not creating a proper data ecosystem include:

  • Incomplete data or low quality leading to biased AI models, inaccurate predictions, and poor decision-making.
  • Low-quality data lacking the necessary robustness to generate meaningful insights, resulting in unreliable and inconsistent outcomes.
  • Limited Insights and decision-making capabilities due to low-quality data lacking the depth and breadth, hindering effective decision-making processes.
  • Unreliable automation caused by models trained on poor-quality data, negatively impacting automated processes and operational efficiency.
  • All these factors can negatively impact strategic decisions, automated processes, and operational efficiency.

To correctly sequence and construct the building blocks for a comprehensive end-to-end data ecosystem, it is critical to focus investments on specific components that include:

  • Data quality and governance ensuring high-quality, clean, and reliable data.
  • Integration of data across various core and domain sources, both internal and external, to create a comprehensive and unified SSOT.
  • Scalable and robust infrastructure for handling the volume and velocity of data, as well as providing the necessary computational resources required for AI applications.
  • Strong data security measures, implementing encryption protocols and data privacy practices to maintain trust with customers.
  • Team building and upskilling employees or find a partner with skills and expertise in data science, ML, and AI.

Creating an enterprise-wide data ecosystem that can be utilized for AI/ML optimizes business strategies for better outcomes and higher growth. It is critical to build a comprehensive end-to-end data ecosystem and achieve numerous competitive benefits, greater agility, and faster responsiveness. These benefits include:

  • Informed and improved decision-making through leveraging vast amounts of data, leading to enhanced strategic execution and agility.
  • Increased productivity through AI by automating repetitive tasks, producing greater operational efficiency and resiliency.
  • Personalized customer experiences created by AI-powered algorithms that analyze customer data, tailor marketing campaigns, and improve customer service levels.
  • Uncover patterns and insights in large datasets, enabling better predictive analytics, AI algorithms, forecasting, risk mitigation.
  • Drive Innovation and new product/service development, empowering companies to create competitive offerings and generate higher margins.

DBM Revolution: DevOps for Business Growth

DBM, in relation to digital business, can be compared to what DevOps is to software development. DevOps has revolutionized collaboration and improved the delivery of software, similarly digital business has emerged as the driving force for business growth, necessitating a mindset and methodology for achieving results. Digital business goes beyond digital transformation by focusing on business outcomes rather than a technology-first approach.

At the heart of digital business lies the Digital Business Methodology, which brings together data, technology, and people, delivering results with speed, consistency, and scale. DBM fosters a business-led agile digital culture, streamlining workflows, and emphasizing a SSOT. It establishes governance to ensure engineering rigor, quality, security, compliance, and cloud services, enabling companies to operate with productivity and predictability.

Notably, DBM also facilitates strong data management and governance, setting the stage to utilize AI/ML advancements. To fully leverage the potential of AI, companies must prioritize building a robust data ecosystem that addresses data quality, integration, infrastructure, security, and talent.

By doing so, they can harness the power of AI for informed decision-making, increased productivity, personalized customer experiences, uncovering insights, and driving innovation, ultimately achieving competitive advantages and accelerated growth. DBM is the pathway to digital business and AI; it is a game changer for growth and unlimited outcomes.

Picture of 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.

Suggested Reading

Ready to Unlock Your Enterprise's Full Potential?

Michael Woodall

Chief Growth Officer of Financial Services

Michael Woodall, as the Chief Growth Officer of Financial Services at Altimetrik, spearheads the identification of new growth avenues and revenue streams within the financial services sector. With a robust background and extensive expertise, Michael brings invaluable insights to his role.

Previously, Michael served as the Chief of Operations and President of the Trust Company at Putnam Investments, where he orchestrated strategic developments and continuous operational enhancements. Leveraging strategic partnerships and data analytics, he revolutionized capabilities across investments, retail and institutional distribution, and client services. Under his leadership, Putnam received numerous accolades, including the DALBAR Mutual Fund Service Award for over 30 consecutive years.

Michael’s dedication to industry evolution is evident through his involvement with prestigious organizations such as the DTCC Senior Wealth Advisory Board, ICI Operations Committee, and NICSA, where he served as Chairman and now holds the position of Director Emeritus. Widely recognized as an industry luminary, Michael frequently shares his expertise with various divisions of the SEC, solidifying his reputation as a seasoned presenter.

At Altimetrik, Michael plays a pivotal role in driving expansion within financial services, leveraging his expertise and Altimetrik’s Digital Business Methodology to ensure clients navigate their digital journey seamlessly, achieving tangible outcomes and exponential growth.

Beyond his corporate roles, Michael serves as Chair of the Boston Water & Sewer Commission, appointed by the Mayor of Boston, and is actively involved in various philanthropic endeavors, including serving on the board of the nonprofit Inspire Arts & Music.

Michael holds a distinguished business degree from Northeastern University, graduating with distinction as a member of the Sigma Epsilon Rho Honor Society.

Anguraj Kumar Arumugam

Chief Digital Business Officer for the U.S. West region

Anguraj is an accomplished business executive with an extensive leadership experience in the services industry and strong background across digital transformation, engineering services, data and analytics, cloud and consulting.

Prior to joining Altimetrik, Anguraj has served in various positions and roles at Globant, GlobalLogic, Wipro and TechMahindra. Over his 25 years career, he has led many strategic and large-scale digital engineering and transformation programs for some of world’s best-known brands. His clients represent a range of industry sectors including Automotive, Technology and Software Platforms. Anguraj has built and guided all-star teams throughout his tenure, bringing together the best of the techno-functional capabilities to address critical client challenges and deliver value.

Anguraj holds a bachelor’s degree in mechanical engineering from Anna University and a master’s degree in software systems from Birla Institute of Technology, Pilani.

In his spare time, he enjoys long walks, hiking, gardening, and listening to music.

Vikas Krishan

Chief Digital Business Officer and Head of the EMEA region

Vikas (Vik) Krishan serves as the Chief Digital Business Officer and Head of the EMEA region for Altimetrik. He is responsible for leading and growing the company’s presence across new and existing client relationships within the region.

Vik is a seasoned executive and brings over 25 years of global experience in Financial Services, Digital, Management Consulting, Pre- and Post-deal services and large/ strategic transformational programmes, gained in a variety of senior global leadership roles at firms such as Globant, HCL, Wipro, Logica and EDS and started his career within Investment Banking. He has developed significant cross industry experience across a wide variety of verticals, with a particular focus on working with and advising the C-Suite of Financial Institutions, Private Equity firms and FinTech’s on strategy and growth, operational excellence, performance improvement and digital adoption.

He has served as the engagement lead on multiple global transactions to enable the orchestration of business, technology, and operational change to drive growth and client retention.

Vik, who is based in London, serves as a trustee for the Burma Star Memorial Fund, is a keen photographer and an avid sportsman.

Megan Farrell Herrmanns

Chief Digital Officer, US Central

Megan is a senior business executive with a passion for empowering customers to reach their highest potential. She has depth and breadth of experience working across large enterprise and commercial customers, and across technical and industry domains. With a track record of driving measurable results, she develops trusted relationships with client executives to drive organizational growth, unlock business value, and internalize the use of digital business as a differentiator.

At Altimetrik, Megan is responsible for expanding client relationships and developing new business opportunities in the US Central region. Her focus is on digital business and utilizing her experience to create high growth opportunities for clients. Moreover, she leads the company’s efforts in cultivating and enhancing our partnership with Salesforce, strategically positioning our business to capitalize on new business opportunities.

Prior to Altimetrik, Megan spent 10 years leading Customer Success at Salesforce, helping customers maximize the value of their investments across their technology stack. Prior to Salesforce, Megan spent over 15 years with Accenture, leading large transformational projects for enterprise customers.

Megan earned a Bachelor of Science in Mechanical Engineering from Marquette University. Beyond work, Megan enjoys playing sand volleyball, traveling, watching her kids soccer games, and is actively involved in a philanthropy (Advisory Council for Cradles to Crayons).

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