On AI, Cloud, and Data & Analytics. Interview with Sastry Durvasula and John Almasan
“People are our biggest asset, and we have been continually investing in and advancing our People digital and data science capabilities.” –Sastry Durvasula.
I sat down with Sastry Durvasula, Global Chief Technology & Digital Officer, and John Almasan, Distinguished Engineer, Technology & Digital Leader, at McKinsey to learn how the firm is leveraging AI, cloud, and data & analytics to power digital colleague experiences and client service capabilities in the new normal of hybrid work.
Q1: Can you explain the role of technology and digital capabilities at McKinsey? What is your strategy for advancing the firm in the new normal?
SD: The firm has experienced significant growth over the last few years, with nearly 40K colleagues serving clients across 150 global locations. Our technology and digital strategy is focused on powering the future of the firm with a range of innovative capabilities, platforms, and experiences. Our strategic shifts include doubling our innovation in digital client service, firm-wide cloud transformations of all our platforms and applications, next-gen capabilities for AI and knowledge management, and leading-edge colleague-facing technology and hybrid experiences.
As per our recent study, Cloud is a trillion dollar opportunity for businesses, and we are very actively working with our clients to advance their cloud journey. Earlier this year, we acquired cloud consultancy Candid and their accomplished team of 100+ technical experts, helping us accelerate our clients’ end-to-end cloud transformations.
5K+ technologists at the firm are organized across our global guilds, which include Design, Product Management, Engineering & Architecture, Data Science, Cyber, etc., and they provide digital transformation solutions to our clients and development of assets and internal capabilities. Our agile Ways of Working (WoW) and build-buy-partner models are central to our product development, empowering teams to innovate at speed and scale, with psychological safety to experiment and learn.
Q2: What roles do cloud, data science, and AI play in your strategy? Can you provide some examples?
SD: AI and data science are central to this strategy in both serving our clients and transforming our internal capabilities. Thanks to the significant technological advancements in AI/ML powering our data science capabilities, we are unlocking innovative client-service and colleague digital experiences. We are building and advancing a hybrid and multi-cloud ecosystem to power distinctive solutions and assets for our clients, which includes strategic partnerships and integrations with leading industry hyperscalers and software products.
As an example, on the client-service side, we are completely transforming our core knowledge and expertise platforms leveraging cloud-native technologies and AI/ML. Similarly, McKinsey.com and the McKinsey Insights mobile app serve up strategic insights, analytics, studies, and content to a broad range of users across the globe — including the C-suite and aspiring students alike. Our cloud transformation of these iconic platforms enables innovation, scale, and speed in publishing, smart search, audience engagement, subscriber experience, and reach & relevance efforts.
On the colleague experience side, AI and AR/VR powered digital workplace capabilities, colleague-facing chatbots, and hybrid-in-a-box tools are a huge focus, as well as predictive and proactive services to detect and service technology issues for our global workforce. People analytics, recruiting, and onboarding journeys are also key areas where we are leading with distinctive capabilities and tools supported by data and AI-driven HR, allowing us to achieve a substantial step up from HR 2.0 to HR 3.0.
Q3: Can you elaborate on knowledge and expertise management, and the role AI plays in shaping this space at the firm?
SD: We have a unique and proprietary knowledge management platform that codifies decades of wisdom and integrates the firm’s extensive insights, studies, industry domain content, knowledge, structured and unstructured data, and analytics with a wide range of artifacts using secure and role-based access. This platform is widely used by our colleagues across the globe, creating profound impact to our clients as well as our firm’s business functions. We have been advancing this platform and the surrounding ecosystem by leveraging AI and cloud technologies for semantic searches, auto-curated and personalized results. Important to mention are our AI-powered chatbots with NLP, which provide valuable intelligence for our colleagues in various industry practices. Using graph database technologies and data science modeling for contextual understanding significantly enhances our knowledge search capabilities, including video scanning, speech to text, summarization, and the ability to index topics of interest.
For finding expertise, we are also making use of ML ontologies to uncover behaviors and relationships between various types of “skills” and Subject Matter Experts (SMEs) to manage, govern, and dynamically connect colleagues with the best domain experts based on desired skills and/or knowledge needs. Our colleague-facing “Know” mobile app provides on-the-go access to our curated knowledge databases and domain experts, integrating with all our internal communication channels and collaboration tools, and AI-driven recommendations.
Q4: Can you expand a little bit more on how AI and data science are powering the HR 3.0 agenda?
SD: People are our biggest asset, and we have been continually investing in and advancing our People digital and data science capabilities. For example:
People analytics play a vital role, and we consider them a stairway to impact with growing maturity in data, engineering, and data science capabilities. Our transformation to HR 3.0 relies on globally rich datasets, cloud capabilities, advanced analytics, and first-class data science and engineering teams, along with integrated operational processes. By making use of hybrid cloud-based graphs databases, R, Python, Julia, etc. to join disparate sources of data, our data engineering teams assemble not only one of the highest data quality ecosystems in the firm, but also a very resilient one. Being aware of the fact that, in general, 80% of data science effort is with data cleaning, our strategy removes such roadblocks and ensures an analytically ready, understandable data solution, so our data scientists can be effective in delivering people analytics rather than data curation and sanitization.
On the recruiting and onboarding front, given our scale of hiring talent every year across the globe — both fresh talent from innovative academic institutions and experienced hires from various industries with a wide range of skills— we have significantly invested in AI-driven capabilities for identifying, recruiting, and hiring talented individuals. As an example, our intelligent NLP driven “Resume Processing Review,” built with the use of deep learning models, enables us to process over 750,000 resumes annually and to identify characteristics of successful applicants. By making use of intelligent guidance with dynamic customizable questions, activities like scoring, prioritizing, and sorting candidates are simplified while the overall process timeline is tremendously reduced. Ensuring that solutions avoid AI bias in recruiting is also a major focus. Additionally, these AI capabilities are beneficial for enabling a smooth and personalized onboarding experience for candidates.
Our recent report the workforce of the future highlights the emerging trends and insights, which include flexibility and continuous learning opportunities to foster and retain an engaged workforce. Our “Job-to-Job Matching” ML system accelerates the discovery and matching of jobs with those looking for another opportunity. AI-driven learning is another big priority, which enables highly personalized learning tracks for our colleagues based on their skills, engagements, and aspirations as part of our proprietary platforms.
Q5: Can you share some insights and details on your technology ecosystem and how it powers your internal and external platforms and products?
JA: To power our global product development solutions and innovations, we focused on transforming the firm’s core technology architecture with a more robust yet flexible 7-layer stack. This new framework is based on hybrid and multi-cloud platforms, secure-by-design engineering capabilities, and futuristic tools to propel delivery at scale and speed.
Developer experience is a core focus, providing premium software engineering tools, APIs, and services across hyperscalers. Our modularized platform as a service, consolidated into a service catalog, allows developers the flexibility and agility to customize complex computing and infrastructure designs to address any internal and external tech ecosystem. Our AI driven CI/CD pipeline enables interoperability across a wide range of technologies, and identifies in real-time SDLC vulnerabilities to reduce potential risk and improve the overall software quality. Data scientists play a vital role across a range of studies and client-service. The stack includes a specialized studio for data scientists with state-of-the-art MLOps and AIOps tools and libraries.
We have developed a cloud security framework, enabling our E2E solutions to be built with secure-by-design and “zero trust” principles in mind, meeting or exceeding the industry “security posture” standards and regulatory needs. Lastly, our global presence demands proactive planning and innovative technologies to ensure that our internal and external platforms and products exist in ecosystems that comply with various country and region-level regulations.
Q6: Tell me about how AI powered colleague experiences helped during the pandemic.
JA: Digital colleague experience has been more crucial than ever during the pandemic and in a hybrid world. We are employing AI to enable seamless capabilities, tools, and rapid response time to client-service requests and issue handling.
First, let me start with CASEE (Caring And Smart Engineered Entity), our colleague-facing chatbot, which provides intelligent technology support and services across the globe. CASEE leverages conversational NLP, leading open source frameworks, and off-the-shelf tool integrations with the ability to improvise from every interaction and support request. It has been a huge help during the pandemic, when our global workforce switched to remote with an unprecedented spike in demand while we were also dealing with the effects on our global servicing teams. As an example, CASEE was specifically trained in less than a week to respond and handle 90% of the questions regrading remote working and common device and network issues. It has also been integrated with our digital collaboration tools as well as incident response systems.
Another example is the intelligent automation of our Global Helpdesk capabilities, which we turbo-charged during the pandemic and are widely recognized in the industry and by our clients as a go and see reference. We’ve augmented our tools with AI driven services that can intelligently detect hardware and/or software deterioration on our users’ machines and can proactively fix or mitigate these problems. The system is capable of initiating a laptop replacement, perform driver updates, trigger software patching, or even remove or stop glitched software.
Q7: I heard about the firm’s open source efforts. Can you elaborate?
JA: We recognized the fact that McKinsey tech has a great opportunity to support and to give back to the Open Source Community. Kedro, for example, is a powerful ML framework for creating reproducible, maintainable, and modular data science code. It seamlessly blends software engineering concepts like modularity, separation of concerns, and versioning, and then applies them to ML code. Kedro proved to be one of our most valuable ML solutions, and it was successfully used across more than 50 projects to date, providing a set of best practices and a revolutionized workflow for complex analytics projects. We’ve open-sourced Kedro to support both our clients and non-clients alike, and to foster ML and software engineering innovation within the community of developers. Our approach starts with our global guilds first, and then contributing to open source. Stay tuned for more exciting developments in this space.
Q8: How are you attracting and developing talent in this highly competitive market?
SD: As you can see, we have some very exciting and interesting problems across a wide-range of technologies, industries, geographies, and next horizon initiatives. We are constantly focused on attracting inquisitive and continuous learners. We have also been fostering deep strategic relationships with universities and industry networks across the globe.
We have been expanding our global hubs, adding new locations and advancing our hybrid/remote workforce capabilities across the US, Europe, Asia, and Latin America with several hundred active open jobs as we speak. We are also opening a major new center in Atlanta, which will be home to more than 600 technologists and professionals, and with strong diversity, inclusivity, and sense of community. We are partnering with leading non-profits including Girls in Tech globally, Chzechitas in Prague, and Black Girls Code and Historically Black Colleges and Universities (HBCUs) in the US.
We launched personalized development programs for our colleagues, including certifications in cloud, cyber, and other emerging technologies. Over 60% of our developers are certified in one or more cloud ecosystems. We’re proud of being recognized by Business Insider as one of the 50 most attractive employers for engineering and technology students around the world. At #19, we are the highest-ranked professional services firm on the list.
Sastry Durvasula is the Global Chief Technology and Digital Officer, and Partner at McKinsey. He leads the strategy and development of McKinsey’s differentiating digital products and capabilities, internal and client-facing technology, data & analytics, AI/ML and Knowledge platforms, hybrid-cloud ecosystem, and open-source efforts. He serves as a senior expert advisor on client engagements, co-chairs the Firm’s technology governance board, and leads strategic partnerships with tech and digital companies, academia, and research groups.
Previously, Sastry held Chief Digital Officer, Chief Data & Analytics, CIO, and global technology leadership roles at Marsh and American Express and worked as a consultant at Fortune Global 500 companies, with a breadth of experience in the technology, payments, financial services, and insurance domains.
Sastry is a strong advocate for diversity, chairs DE&I at McKinsey’s Tech & Digital, and is on the Board of Directors for Girls in Tech, the global non-profit dedicated to eliminating the gender gap. He championed industry-wide initiatives focused on women in tech, including #ReWRITE and Half the Board. He holds a Master’s degree in Engineering, is credited with 30+ patents, and has been the recipient of several honors and awards as an innovator and industry influencer.
John Almasan is a Distinguished Engineer, Technology & Digital Leader at McKinsey. He is a hands-on, accomplished technology executive with 20+ years of experience in leading global tech teams and building large-scale data, analytics, and cloud platforms. He has deep expertise in hybrid multi-cloud big data engineering, machine learning, and data science. John is currently focused on engineering solutions for the firm’s transformation and the build of the next gen data analytics platform.
Previously John held engineering leadership roles with Nationwide Insurance, American Express, and Bank of America focusing on cloud, data & analytics, AI and ML in financial services and insurance domains. He gives back through his pro bono consultancy work for the Arizona Counterterrorism Center, the Rocky Mountain Information Center, and as a member of the Arizona State University’s Board of Advisors.
John holds a Master’s degree in Engineering, a Master of Public Administration, and a Doctor of Business Administration. He is an AWS Educate Cloud Ambassador, Certified AWS Data Analytics & ML engineer, GCP ML Certified. John is credited with 10+ patents and has been the recipient of several awards.
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