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AI Empowerment: Data Excellence and Leadership Vision

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Artificial intelligence (AI) is one of the most transformative technologies of our time and has already made a major impact on industries such as banking, healthcare, retail, and manufacturing. Its potential is unlimited, and it can deliver huge ROI and disrupt entire ecosystems. The potential of AI to streamline operations, optimize processes, and enhance decision-making is unparalleled. From automating routine tasks to enabling breakthroughs in personalized medicine, the possibilities with AI are vast and continue to expand rapidly. With ongoing research and development, AI holds the promise of addressing some of the most pressing challenges facing humanity, from climate change to healthcare access.

However, as enterprise tools continue to enter the market, there is also a lot of hype and misunderstanding surrounding AI. Often overlooked are key considerations such as the central role of data quality and the integration of users’ ability to actively contribute to and refine AI models for better results. If the data is poor quality, the output will be as well. AI is a powerful tool, and we must understand how it works and what its limitations are to use it effectively. If done right, enterprises today can leverage AI to achieve unlimited growth.

Simply put, AI is powered by data. The more data that an AI system has, the better it will be able to learn and make predictions. The effectiveness of any AI system is intricately tied to the quality of the data it operates on. However, as companies grow so does the complexity in their data ecosystem creating silos, loss of quality, and disparate disconnected data repositories. These risks need to be addressed so that data is accurate, comprehensive, and unbiased. It is also important to have a solid understanding of the end-to-end data ecosystem in order to organize and use it effectively. 

AI Triumph: Data Empowerment, Talent Upskilling, Leadership Imperatives

To derive the benefits and ROI for new capabilities that AI provides, companies need to focus on the building blocks of data. These include domain data that is specific to a particular industry or field, core data assets that represent the critical information necessary for critical business processes, and a single source of truth (SSOT) for a unified and reliable data repository that serves as the authoritative source of all data. Upskilling talent and/or partnering with an expert firm to build the expertise to manage AI is also crucial, and a modern, scalable, cloud-based data platform should be created so that data stays secure and compliant.

AI’s success hinges on data — without the right fundamentals and infrastructure for data, the full potential of AI cannot be realized. According to Harvard Business Review, 75% of organizations believe a data-driven culture is very or extremely important to their overall success, but 40% cite data quality issues. To address this gap, companies must make substantial investments in data to build effective AI tools. 

AI-powered solutions need the ability to ingest huge amounts of data to create insights,       make predictions, automate repetitive tasks, and learn from data patterns for better decision-making. 

C-level leaders play a pivotal role in fostering a data-driven culture and ensuring the success of AI initiatives. They need to take ownership and actively lead their companies in building the necessary data ecosystem for AI. Executives must recognize data as a strategic asset and understand its potential impact on business growth and success.

Also read: How Gen-AI Supercharges Modern Anomaly Detection

Four areas these leaders need to focus on include:

  1. Prioritizing data management and governance to ensure data quality, security, and compliance
    Establish a dedicated team for data governance, ensuring that data is accurate, secure, and compliant with industry regulations. Implement robust enterprise data management policies and processes to maintain a high standard of data quality.
  2. Defining a clear AI strategy that aligns with business goals, focusing on areas where AI can generate maximum value      
    Collaborate across the company to articulate a clear AI strategy that aligns with overarching business objectives. Identify specific use cases where AI can generate maximum value and contribute to achieving strategic goals. 
  3. Concentrate on simpler use cases by embracing an incremental approach as part of a comprehensive and holistic strategy
    Address simpler use cases that improve data quality. For example, automate data validation processes, conduct regular data audits, and ensure collaboration between the business and technology to identify and remediate data quality issues.
  4. Upskill employee data skills and seek external partners to internalize and train talent    
    Strategic partnerships can unlock AI’s full potential giving companies a competitive edge. Invest in training programs to upskill existing talent in data management and analytics. Develop strategic partnerships with external experts to fill skill gaps and provide specialized knowledge. 

AI Revolution: Data Excellence and Leadership Vision

AI presents a transformative opportunity for companies to achieve unprecedented growth and success. McKinsey reports that companies that effectively integrate AI into their operations can achieve more than a 120% increase in their cash flow margins. However, to harness the full potential of AI, C-level leaders must recognize that AI’s success hinges on a strong data foundation, management, governance, taking an incremental approach, and upskilling talent. Investing in data will unlock the “AI revolution in the enterprise,” create a sustainable competitive edge, and deliver superior returns. 

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.

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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).

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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