Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in finance transformation, Workday implementations and intelligent automation?

I am a senior finance transformation leader with over 17 years of experience, specializing in global market operations, strategic financial reengineering, and automation-driven process optimization.

Professional Background

I currently serve as a Senior Manager of Finance Transformation at Alight Solutions / Strada Global (Rebranded), where I drive strategic and operational initiatives that redefine finance operating models and shared services structures. My expertise includes finance strategy development, target operating model (TOM) design, and performance KPI management. I have led multiple transformation engagements, partnering with CFOs and CEOs to optimize finance functions for better business alignment.

In my earlier role as an Assistant Director at EY GDS India LLP, I managed large-scale consulting and delivery projects focused on business process re-engineering and digital transformation across O2C, P2P, and R2R processes. I demonstrated proficiency in identifying process inefficiencies, creating automation roadmaps, and improving key financial performance metrics.

Finance Transformation Expertise

I have a strong foundation in designing and implementing finance transformation strategies, including shared services setup, cost optimization, and target operating model creation. My approach involves assessing current financial operations, developing future-state designs, and leading transitions that emphasize standardization, efficiency, and scalability.

Workday and ERP Implementations

I have hands-on experience in deploying ERP systems, including Workday, SAP, Oracle, BlackLine, Anaplan, and Hyperion. My role in ERP and finance transformation projects includes defining business requirements, preparing business cases, validating “as-is” and “to-be” process states, and managing cross-functional implementation teams.

Intelligent Automation Expertise

I have also implemented solutions using UI Path, Blue Prism, Automation Anywhere, Power Automate, AI/ML, and chatbots. I have successfully delivered hyper-automation projects that achieved labor savings equivalent to $3 billion and have driven innovations through low-code development platforms (LCDP). My automation strategies integrate predictive analytics, process mining, and AI to enhance financial operations and reporting accuracy.

Overall, my background reflects a deep capacity to blend technology and finance strategy—enabling digital transformation, efficiency gains, and sustained business value across global finance organizations.

 

Q2. The finance function is moving from operational to strategic — how do you see the role of hyper-automation (RPA + IDP + orchestration + AI) changing finance teams’ priorities and value contribution over the next 3 years?

Over the next three years, I envision hyper-automation—blending RPA, IDP, orchestration, and AI—as fundamentally reshaping finance functions from transactional processors to strategic business enablers.

Shift from Transactional to Strategic

Hyper-automation will drive finance teams away from repetitive, manual tasks such as reconciliations, journal entries, and invoice processing, toward higher-value activities like strategic forecasting, scenario planning, and business partnering. As automation platforms mature, finance leaders will use predictive AI models and process orchestration to anticipate financial risks, improve working capital management, and strengthen decision support.

Integration of Intelligent Systems

With tools like AI/ML, process mining, and orchestration engines, hyper-automation will enable end-to-end intelligent operations within O2C, P2P, and R2R cycles. This shift will result in continuous, self-optimizing systems that monitor processes, detect anomalies, and resolve issues autonomously. For finance, this means fewer bottlenecks, real-time audit trails, and deeper analytical insights driving strategic decision-making.

Workforce Transformation and Value Creation

As digital technologies assume more operational work, finance professionals will evolve into data-driven strategists responsible for insight generation and business innovation. Hyper-automation will free up capacity equivalent to dozens of FTEs, allowing finance teams to reinvest time into governance, business strategy, and sustainability performance analysis.

Future Outlook

In summary, hyper-automation will transform the finance function into a digital nerve center — continuously learning and adapting through AI, while orchestrating seamless collaboration across enterprise systems. By 2028, finance teams will measure success less by process efficiency and more by their contribution to profitable growth and enterprise agility.

 

Q3. Low-code/no- code AI and developer toolsets (for example Workday Build, Power Automate, UiPath low-code flows) are becoming more accessible. From your experience, how should consulting-led services and specialist automation vendors adapt their go-to-market and delivery models to remain differentiated?

Key Trends Shaping the Landscape

• Democratization and Citizen Development: Low-code and no-code platforms, empowered by AI—including generative models and natural language interfaces—enable domain experts outside IT to create complex automation solutions. This disrupts traditional consulting models, as clients now have direct and rapid access to digital innovation.
• AI Augmentation, Not Replacement: Strategic consulting is increasingly oriented toward combining human expertise—such as storytelling, transformation leadership, and design thinking—with AI-driven analytics, insights, and solution delivery. Human consultants are augmented by AI for routine analysis, allowing them to address truly complex or bespoke client needs.

Go-To-Market Adaptations

• Shift to Continuous Value and Long-Term Partnership: Rather than offering point solutions or time-boxed projects, leading consulting firms and automation vendors should position themselves as ongoing transformation partners. They should deliver measurable business outcomes and continuous improvement as platforms, business models, and client needs evolve.
• Productized Services and Reusable Assets: Vendors should create packaged solutions, accelerators, and frameworks—integrating AI and LCNC tools—tailored to sector-specific challenges (e.g., finance, HR, supply chain automation). This approach moves beyond pure services toward hybrid models that combine software, advisory, and change enablement.
• Hyper-Personalization and Verticalization: As AI enables process and workflow hyper-automation at scale, vendors should invest in domain specialization, personalized offerings, and real-time data-driven adaptation across industry verticals. This differentiation should be based on context, outcomes, and sector expertise.

Delivery Model Innovations

• Enablement, Co-Creation, and Ecosystem Play: Consulting-led services should focus on guiding clients through design thinking, enablement for citizen developers, governance frameworks, and federated operating models. Leveraging cross-functional partnerships and ecosystem alliances is also essential for delivering broader, integrated solutions.
• AI-Native Workforce Structure: The traditional pyramid model is being replaced by agile delivery pods, where both consultants and client stakeholders serve as “AI facilitators” trained on best-in-class platforms. These teams are responsible for rapid prototyping, experimentation, and process optimization.
• Transparent Value and Impact Measurement: With rapid delivery enabled by LCNC, vendors must differentiate themselves by demonstrating measurable business impact. This includes clarifying ROI, efficiency gains, and cost savings through process mining, analytics dashboards, and evidence-based reporting throughout engagements.

Strategic Imperatives for Differentiation

• Develop proprietary solution accelerators and sector-specific asset libraries.
• Invest in upskilling and retraining consulting teams in AI-enabled LCNC tools and responsible AI governance.
• Move away from commodity app-building to architecting enterprise-wide transformation roadmaps, focusing on synthesis, change management, and enablement.
• Foster agile cross-sector partnerships (across IT, operations, business units) and promote co-creation.
• Be leaders in responsible AI, ethics, and trust—clients will increasingly select partners who deliver both innovation and rigorous governance.
• Consultants and specialist vendors who proactively adapt their operating and delivery models—emphasizing long-term value, vertical expertise, and AI-powered service assets—will remain relevant and competitive in the era of democratized low-code and no-code automation.

 

Q4. Practical automation deployments often run into organizational bottlenecks. If investment were not a constraint, what non-financial factors — such as data quality, governance, change management or talent — would still limit automation outcomes?

Even with unlimited investment, several non-financial organizational factors can significantly limit automation outcomes. These typically include data quality, governance, change management, talent, legacy technology, and organizational culture—all of which have complex, persistent impacts that funding alone cannot resolve.

Critical Non-Financial Constraints

• Data Quality & Integrity: Poor data quality remains the top obstacle in automation and AI deployments. More than 60% of organizations in recent studies cite insufficient data quality and integrity as the primary limiting factor, resulting in unreliable outputs, automation errors, and low business trust in outcomes. This includes issues of completeness, accuracy, standardization, and timely availability.
• Governance & Controls: Automation often outpaces the development of governance protocols in many organizations. Without rigorous governance, automation initiatives can introduce new risks, propagate errors at scale, and fall short of compliance requirements. Controls around data access, versioning, auditing, and security are mandatory, yet they remain major stumbling blocks—especially as systems scale or cross functional boundaries.
• Talent & Skill Gaps: Even state-of-the-art platforms require skilled personnel to design, implement, and continually refine automation workflows. The shortage of cross-functional talent with expertise in both business processes and automation tools remains a persistent bottleneck. Upskilling, talent acquisition, and internal knowledge transfer are long-term issues that money alone cannot immediately fix.
• Change Management & Resistance: Automation projects frequently encounter organizational resistance. Employees accustomed to legacy processes may push back against new technology, leading to low adoption or the emergence of “shadow IT.” Change fatigue, insufficient communication, and unclear role definitions can derail even well-funded initiatives, making continuous change management and stakeholder engagement essential.
• Legacy Systems & Technical Debt: Integrating automation into fragmented or obsolete legacy IT environments often poses barriers more formidable than financial cost. These challenges include a lack of modern APIs, poor documentation, slow system responsiveness, and high maintenance complexity—all of which require substantial organizational alignment and strategic planning beyond direct investment.
• Culture & Collaboration: Automation success depends on a culture of collaboration and shared ownership between business and technical teams. When organizations operate in silos, lack standardized data and operational models, or fail to set shared objectives, the impact of automation is limited by poor communication, misaligned incentives, and a lack of unified vision.

 

Q5. The Workday ecosystem and partners like Strada are increasingly delivering payroll + people data services globally. What are the most important capabilities a partner must bring to ensure a smooth, compliant, and scalable global payroll implementation?

Partners delivering global payroll with Workday, including firms like Strada, must bring specialized capabilities to ensure implementations are smooth, compliant, and scalable across diverse geographies and regulatory environments.

Essential Capabilities for Global Payroll Partners

• Regulatory Compliance & Local Expertise: Deep understanding of regional payroll tax laws, social security, and labor regulations, paired with the ability to configure payroll to local legal requirements (deductions, reporting, filings, privacy, etc.), is crucial.
• Certified Integration & Data Flow: Partners must deliver proven, pre-built bi-directional integrations with Workday to synchronize workforce, payroll, and financial data across platforms. Robust API frameworks and productized connectors reduce manual tasks and deployment time, minimizing errors and duplication.
• Real-Time Data Accuracy & Visibility: Payroll partners should enable unified, reliable, and up-to-date global payroll data within Workday’s HCM, allowing for rapid reconciliation, analytics, and global labor spend insights—all with strong audit trail capabilities.
• Change Management & Employee Experience: Expertise in communication, training, and support to drive adoption and minimize friction is essential. Partners should offer strong self-service tools, clear payroll documentation, and support local languages/time zones to enhance engagement
• Process Localization & Scalability: Ability to process locally (meeting specific country needs) while managing globally, thus maintaining central control but with tailored, decentralized processing to suit business units in each geography. Partners must ensure solutions scale with workforce changes and organizational growth.
• Security & Data Privacy Controls: Ensuring data is securely transferred, stored, and accessed is non-negotiable. Partners should maintain strict privacy protocols and meet international data protection standards.
• Ongoing Support & Regulatory Updates: Partners must offer responsive global support, proactive issue resolution, and stay ahead of regulatory changes by pushing timely updates to payroll processing logic and compliance frameworks.

 

Q6. With leading RPA/automation vendors (UiPath, Automation Anywhere, Microsoft Power Automate) and consultancies (EY, Accenture, Genpact) all active, how do you evaluate vendor selection — what are the top criteria your teams use when choosing automation or implementation partners?

Vendor selection for RPA/automation tools and implementation partners is a strategic decision driven by criteria that ensure fit for both business requirements and long-term success. Teams typically use the following top criteria to evaluate and choose the right vendor or consultancy:

Top Evaluation Criteria

• Ease of Implementation & Integration: The chosen tool or partner should offer quick, seamless integration with existing systems—ERP, HR, finance, CRM—preferably with intuitive low-code/no-code features, robust APIs, and minimal disruption.
• Scalability & Performance: The platform must be proven to scale for high-volume, multi-department, and even global deployments, supporting thousands of automated tasks and users without compromising performance.
• Security & Compliance: Leading vendors provide enterprise-grade data security, privacy controls, and certifications (e.g., SOC 2, ISO, GDPR). Strong governance tools to ensure auditability and regulatory compliance are essential.
• Technical Features & Cognitive Capabilities: Advanced analytics, AI features (document processing, ML models, NLP), and support for unstructured data increase the value and future-proofing of RPA platforms.
• Cost & Total ROI: Transparent pricing, licensing, bundled support costs, and predictable TCO are key. Teams evaluate not just initial investment but also long-term ROI, including speed of results and ongoing support.
• Domain and Industry Expertise: Consultancies with deep vertical expertise (e.g., finance, healthcare) deliver better outcomes. Prior case studies, reference projects, and industry certifications are evidence of success.
• Support, Training & Change Management: Commitment to comprehensive support, upskilling, and change management is important, ensuring adoption and resilience against process disruptions.
• Vendor Trust & Experience: A proven track record of successful deployments, high client satisfaction, and a strong ecosystem (partner network, community, product roadmap) are vital.

 

Q7. If you were an investor looking at companies in the finance automation and cloud HR services space, what critical question would you pose to their senior management?

My question for companies in finance automation and cloud HR services is: "How does your solution deliver sustained, measurable business value beyond basic automation, and what competitive advantages (in data, platform, or talent) ensure scalability, compliance, and resilience amid ongoing regulatory and market changes?"

Key Focus Areas Investors Should Probe

• Business Value and ROI: How does the firm quantify the financial and operational ROI of its automation/HR offerings for clients, and how are those benefits proven and sustained over time rather than just achieved in initial deployment?
• Scalability and Platform Resilience: What architectural, data, and integration features enable the solution to scale across different geographies, business lines, and new regulations, without compromising system performance or data integrity?
• Regulatory Compliance Strategy: How does the company monitor for regulatory changes (e.g., in finance, labor, privacy), and how is compliance maintained across all client implementations—especially in complex regions or multinational environments?
• Talent and Leadership Depth: Does the senior team possess proven expertise in both technology and business domains? How is the company recruiting, training, and retaining critical talent (e.g., AI, data science, payroll, HR, cybersecurity) to remain ahead of competitors?
• Customer Success and Change Management: What are the success metrics for client implementations, and how does the company support change management, training, and ongoing client enablement in cloud HR and finance automation rollouts?

Why This Matters

Automated finance and cloud HR services are now table stakes; only companies with differentiated platforms and processes—demonstrating robust compliance, scalability, and deep understanding of client value—will thrive under investor scrutiny and earn sustained market leadership.