Reframing innovation processes at global IT consultancy
Background
Tata Consultancy Services (TCS) aims to expand its global footprint by developing comprehensive business consulting services.
TCS’s distributed knowledge across the organization could be transformed into a unified knowledge broker model for its client base.
Client's Team
TCS, a TATA Group company with a 154-year legacy, drives global IT consulting across five continents with 606,000 employees, partnering with leading businesses since 1968.
Our Team
Our Institute of Design team partnered with TCS to reimagine their innovation infrastructure, developing strategic capabilities to scale innovation across their global ecosystem.
TCS's Innovation team orchestrates internal expertise to solve complex client challenges globally.
Seeking to strengthen their market position, TCS explored multiple innovative approaches.
The initiative aimed to scale TCS's 'figure 8' innovation model across the company, optimizing efficiency and expanding its reach.
"The model integrates Foresight-Enabled Innovation with Agile Execution, connecting stakeholders and experts throughout.
TCS needed a system to efficiently leverage its expertise across industries, sectors, and domains, converting its knowledge into valuable services for clients.
TCS serves 1000+ clients across 14 industries and 11 domains, needing a cohesive system to orchestrate its global network effectively.
Our team was charged with designing infrastructure to scale open innovation across TCS globally
TCS sought to future-proof operations by enhancing innovation capabilities and establishing a dedicated unit to drive company-wide innovation initiatives.
Siloed expertise and fragmented workflows blocked TCS from realizing its full potential.
Inaccessible knowledge and departmental silos created bottlenecks, impacting productivity and results.
TCS's complex global infrastructure and distributed workforce created barriers to innovation. Disconnected processes and siloed teams hindered effective collaboration.
Complex barriers - underutilized capabilities, data security concerns, and inconsistent AI adoption - compromised TCS's ability to deliver swift, AI-driven solutions in an increasingly digital market.
TCS strives to lead global problem-solving through scalable innovation and a dynamic ecosystem.
TCS needed to harness its ecosystem and agile capabilities to transform internal innovation into client solutions.
Our project blended ecosystem strategies with agile prototyping to build TCS's innovation portfolio.
Transforming global challenges into local solutions, TCS leveraged internal innovation to establish itself as both knowledge broker and integrator.
Solution
Introducing Nexus: A unified model that amplifies TCS's innovation capabilities to drive strategic client impact.
Nexus functions as a knowledge engine, transforming insights into targeted client strategies.
The Nexus model harnesses AI and human expertise to distribute innovation across teams, while optimizing collaboration and eliminating silos within TCS's network.
The Nexus platform integrates internal and external insights with real-time market data, ensuring ethical oversight while empowering TCS's diverse workforce to scale innovation for clients globally.
We proposed capabilities that align TCS's core and auxiliary functions to meet client needs globally.
TCS can combine these capabilities to deliver precise solutions and strategic insights for global clients at every stage of innovation.
By strategically deploying the most suitable core and auxiliary capabilities, TCS can deliver targeted solutions and strategic recommendations.
TCS can leverage expertise from its global ecosystem, and position itself as an agile knowledge broker and integrator.
Distributed Innovation Planning
A shift from centralized innovation planning, to a distributed network of design practitioners closely working with other teams to generate innovative processes.
New Generative tools to accelerate iterative processes
Using generative AI to create prototypes and communicate ecosystem strategies more rapidly, with greater variation.
New capabilities for growth and optimization are required for Nexus to function.
To achieve the most impactful outcomes, growth and optimization capabilities must be embedded within the organizational ecosystem, designed to be flexible and easily combined or adapted.
Internal capabilities (Core) serve as innovation catalysts within the organization, while auxiliary capabilities drive ecosystem-wide innovation by supporting external partnerships.
These improvements include leveraging generative AI on latent data to enhance offerings, implementing blockchain cryptography for better security, and creating unified communication channels for organizational efficiency.
IP Protection Through Blockchain Affordances
Creating an open knowledge transfer system between teams while maintaining strict confidentiality by leveraging blockchain-enabled cryptography to ensure security.
Consolidated Communication Channels
Create a condensed and curated channel for organizational communication protocols to improve knowledge sharing efficiency.
Integrate Underutilized Generative Data to Refine Offerings
Use data bases of existing ideas from hackathons and innovistas to train generative tools that help realize offerings.
Generative Modeling
Use predictive & prescriptive analytics to interpret market conditions, business requirements, risk assessments as well as provide product and ecosystem recommendations.
External Design Thinking Organizations / Experts
Integrate specialized design consultancies into COIN and network experts to bring divergent insights into the ecosystem.
Aptitude Assessments & Design Training For New Hires
Use aptitude tests and training modules while onboarding new talent to create and internal database of employees capabilities to form project-based teams.
To improve TCS' outreach, we recommended implementing the following additional capabilities within the organizational ecosystem.
By leveraging both internal and external knowledge assets within the organizational innovation ecosystem, TCS can maximize its impact.
Beyond TCS' internal capabilities, they tap into global subject matter experts, distributed knowledge, external partners, and worldwide thought leadership.
To maximize these expert partners and insights, we strengthened TCS' external networks for swift, relevant, and localized global collaboration.
AI-based Outreach (Internal/External)
Use existing formal network databases to reach out to employees or external experts whenever needed in projects.
Case Specific Localized Stakeholder Collaboration
Form networks of local stakeholders in specific international projects to gain cultural insights and knowledge.
Leveraging rapid experimentation to test innovative business solutions.
The 5x5x5 experiment will enable TCS to rapidly test innovative business solutions for high impact with limited budgets.
The 5x5x5 model accelerates innovation: 5 team members, 5 days planning, 5 business experiments—each under $5,000 and completed within 5 weeks.
The 5x5x5 methodology drives innovation through simple, low-cost experimentation while managing risks and resource constraints.
Blu Safe Insurance
San Francisco, California
Blue Safe Insurance is a SF-based insurance company needing to innovate its digital records department to go from localized to global access for all its customers. They come to TCS asking how it hsould update its data infrastructure and how it might be able to implement such a strategy.
Client Brief
Many organizations are transitioning from fragmented data repositories to universally accessible system in order to make service, business and technical infrastructure improvements.
Blu Safe wants to remain competitive by innovating their current data infrastructure into a more robust and future proof model, that can handle new challenges and scale quickly.
Hypothesis
By using AI-based outreach TCS can expedite the Team building and expert selection selection process. Additionally, AI generative tools can speed up the collection, dissemination, and selection of secondary research, while also utilizing integrated data from past projects to improve strategic recommendations.
Team Roles
AI Recommendations Manager
Trains the data models which TCS uses to understand how to make better predictive suggestions.
Talent Specialist
Evaluates the recommendations from the outreach algorithms, and optimizes the recommendations when needed.
Future of Business Expert
Weighs the considerations of the generative models for faciltating Blu Safe’s digital transformation, providing a solution curated to Blu Safe’s specific needs.
Innovation Consultant
Builds strategies from the generative data gathered into a more packaged offering, with the help of experts.
Experiment
Use Generative tools trained on past TCS projects and
resources to generate recommendations, methods, and
pathways for current and future projects.
This approach would be particularly beneficial for the Future of Business, Innovation Consulting, and Agile Execution
teams.
By leveraging Generative training and integrated past project data, TCS can enhance its operations and recommendations for various departments.
Metrics
Success will be measured by the efficacy of implementing recommendations generated by new tools. HR will review allocation suggestions for personnel, resources, and data. Project leads will determine efficiencies of new technologies in facilitating strategies and prototypes.
Government of Ukraine
Kyiv, Ukraine
Ukraine's government comes to TCS to ask for help with the post-war rebuild - integrating technology for a nationwide educational outreach program that can help align the people with the new national economic goals. They are requesting TCS to come up with ways of utilizing local and distributed knowledge to build a better educational system.
Client Brief
Rebuilding an educational infrastructure to support 21st century standards, especially in a rebuilding nation, requires identifying new opportunities, activating pools of resources and building a deeper understanding of local cultures.
To facilitate this, TCS needs to assist Ukraine in ideating, identifying and suggesting actionable pathways to help the government streamline its resources to educate the public more effectively.
Hypothesis
By streamlining and diversifying the process through which TCS recruits team members and gathers human resources, it can build more relevant and diverse teams faster and more effectively.
Team Roles
AI Technologist
Creates training data and helps TCS to leverage its existing data towards AI generative tools.
AI Hiring Specialist
Utilizes AI tools, models, and systems within TCS to improve hiring processes and facilitate expansion. They are responsible for identifying relevant personnel, and resources, and evaluating internal and external talent for TCS.
IC/Future of Business Representative
Evaluates team structures to ensure they are optimized for the success of the project and aligned with TCS's vision for the future of business.
Experiment
TCS can use AI based outreach to build teams and identify local stakeholders to consult when building a strategy to activate Ukraine’s educational transformation.
AI tools can also locate cultural organizations and design thinking expert networks to integrate new knowledge. Adaptive aptitude tests and learning modules can be introduced to identify, recruit, and train talent within Ukraine.
Comparative tools can be used to identify internal and external skills sets within TCS to deploy in the Ukraine project. This 5-day iterative experiment will continuously mine talent and experts for the project’s success.
Metrics
Success will be measured by reduction of hiring timelines and overhead costs through AI-based recruitment tools. Benchmark baselines can be established by comparing logged time from previous projects relative to those with AI-based tools.
Next Wave
Singapore
NextWave is a mid-range consumer goods company that specializes in smart home appliances, headquartered in Singapore. They want to expand their presence in Asia within the next 7 years and need to know what strategic recommendations should employ to remain competitive.
Client Brief
As part of its growth strategy, NextWave intends to launch a new range of products in Asia by 2030. To ensure long-term competitiveness, the company seeks to evaluate the viability of its expansion plans.
To achieve this, NextWave has engaged the services of TCS to assess the potential risks, benefits, and financial feasibility of the plan, including a detailed analysis of the target market, competitive landscape, regulatory requirements, and cultural considerations.
Hypothesis
With the optimized process flow, TCS will be able to streamline the process of forecasting, research, resources allocation and sprint planning by employing AI-based outreach, smart forecasting and generative tools to help allocate resources and manage workflow.
This optimized process flow will allow TCS to deliver a set of opportunity areas that NextWave needs to consider for their logistics and manufacturing workflows, to build a resilient supply chain.
Team Roles
AI Hiring Specialist
Uses TCS AI tools and systems to improve hiring processes, evaluate talent, and facilitate expansion.
AI Project Manager
Uses AI-assisted tools to optimize project flows, requirements, and setup for TCS departments.
Experiment
The experiment starts with strategic idea development for NextWave’s product line, supply chain, distribution, and logistics.
TCS will use an AI platform to consolidate needs, optimize teams and workflows, and leverage past TCS projects and AI trend studies for smart forecasting.
The experiment will identify potential opportunity areas for NextWave’s logistics and manufacturing, accelerating their product line expansion with relevant resources.
Metrics
The metrics will compare current project resources with the effectiveness of AI recommendations and team designations. As AI improves, less human input is needed, reducing personnel. An Ideas Bank trained on TCS project data and external information will improve project direction and reduce redundancy in research, ideation, and implementation.
SwiftFleet
Santiago, Chile
SwiftFleet, a Detroit-based electric vehicle company, is looking to expand its operations by manufacturing autonomous tractors in Latin America in the next two years, starting with Chile.
Client Brief
The company’s expansion plan aims to achieve market leadership in autonomous vehicles and increase profitability. Chile’s strategic location, infrastructure, and skilled workforce make it an ideal choice.
The company has partnered with TCS to develop new ideas and an actionable plan for an autonomous tractor fleet, catering to LATAM market needs. Underutilized hackathon data will be structured into a database, and selected ideas will be converted to NFTs for protection.
Hypothesis
For SwiftFleet, TCS will leverage Integrative Generative Data from hackathons and open innovation hubs into the development process. This data will be used to create NFTs that facilitate collaboration and ensure transparency.
TCS will also use generative tools for prototyping to optimize the development process and help SwiftFleet achieve market leadership in autonomous fleet technology.
Team Roles
COIN Talent Specialist
Monitors institutions, competitors and influencers by staying up-to-date on industry developments and providing insights and recommendations.
TCS's Interdisciplinary Teams
Encourages innovation through Hackathons to harness internal capabilities by providing employees with dedicated time and resources to work on creative projects.
Data Broker Expert
Oversees the creation, distribution, and management of NFTs (non-fungible tokens), as well as brokers information and ensures data security.
Experiment
The experiment will begin once the project has an Innovation Portfolio in place, moving into research phase that will leverage the TCS AutoScape system to simulate the constraints of the problem.
Data generated from hackathons will be structured, and categorized into the relevant work streams.
There will be consolidated communication channels through AI based chatbots for scheduling and workforce management during the sprint planning stage.
Metrics
Success will be measured upon how hackathon data is integrated across others projects, and how contributed data weighs into current projects through the use of NFT tracking and cross-integration of data being shared between projects. Another metric will be monitored timesaving, as time normally allocated to scheduling between departments will be reduced due to AI assistive scheduling management.
NovoGenix Pharma
Billings, Montana
Novogenix, a pharmaceutical company, hires TCS to redesign its drug education program across multiple US locations. TCS works on-site to develop the optimal service design.
Client Brief
Novogenix, a pharmaceutical company, requires a revamp of its drug education program’s experiential educational service at various locations across the US.
To achieve this, they have engaged TCS to develop a multi-localized Ed-tech platform with specialized knowledge about pharmaceutical products, genetic mutation, and their impact on individual and societal interaction.
Hypothesis
TCS will employ a new rapid prototyping technique based on generative modeling and risk reduction for Novogenix. The approach will allow digital prototyping of ideas before conducting physical or further testing.
By testing ideas in a digital environment, the most promising ones will be selected and integrated with PESTEL/TPESTRY factors of different locations. This will enable the creation of customized platforms for specific regions or locations.
Team Roles
Data Modeller
Necessary to train the data models by which TCS uses to understand how to make better predictive suggestions.
Innovation Consultant
A representative from the IC team packages generative data, delivering final recommendations to experts. Data assists, not replaces TCS personnel.
F
A reviewer evaluates marketable solutions against the project’s original intent, ensuring the alignment of project intent and impact for successful strategic gains.
Experiment
Developing generative MVP tools for modeling will create various solutions for scenarios involving pharmaceutical product education and its impact on individuals.
Additionally, the linear tech tool will screen out solutions that align with local/regional PESTEL/TPESTRY factors, ensuring that the resulting solutions are both desirable and feasible at the local level.
These solutions will be simulated and adjusted to adapt to the market landscape, ultimately resulting in the best ed-tech platform.
Metrics
Success is measured by effective digital prototyping and streamlined recommendations that reduce dead-ends and improve prototype quality. Model selection saves time and lowers risk, increasing the chance of marketable solutions. Generative scaling algorithms model macro market conditions, creating durable products, services, and solutions.
Impact
Our strategy repositioned TCS's innovation unit, pivoted their sales approach, and streamlined partnerships for greater impact.
We helped TCS visualize their ecosystem, streamline processes, and refine their strategies for impactful organizational transformation.
Ecosystem mapping streamlined TCS's innovation processes and market approach, enhancing stakeholder engagement and focused partnership strategies.
Our strategic redesign streamlined TCS's ecosystem, enhancing agility and showing how design thinking drives organizational transformation.
"The great value was the mapping of our ecosystem. We took the visualization of our environment to better position our new department inside the greater TCS. We were better able to identify and communicate to relevant inside stakeholders. It also helped us pivot drastically in some of the ways we sell our offerings and removed partnerships that seemed superfluous."
Ron Martin
Innovation, Technology & Business Design Internal Innovation Team
Tata Consultancy Services
Process
Understanding TCS's innovation landscape required deep insight into their key departments, stakeholders, and operational dynamics.
Interviewed multiple TCS stakeholders to develop a foundational knowledge of the issues and opportunities.
Our first phase mapped TCS's open-innovation ecosystem through 10+ stakeholder interviews over six weeks, creating a platform for cross-organizational thinking and value discovery.
We converted complex insights into clear visual models through weekly interviews, aligning stakeholder understanding and revealing knowledge flow opportunities. The team then validated the platform with strategic use cases showing scalable innovation value.
Innovation Model Breakdown
The following is a visual breakdown of TCS' current innovation model and our proposed enhancements.
Team member Meghna Prakash created before-and-after videos showcasing TCS's current innovation model and our recommended enhancements.
These videos serve to further clarify TCS's model mapping and our recommendations to enhance its operational success.
These demonstrate the innovation engine's components, isolating and explaining their functions.