Swapna Malekar
Principal Product Lead @Microsoft | Copilot, GPTs, LLMs, Search platforms
Seattle, Washington, United States
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Swapna is a Principal Product Lead at Microsoft, currently leading Enterprise Search & M365 Copilot productivity experiences for enterprise users and has previously led OEM partnerships for OneDrive that served 50M+ users worldwide.
In her previous life, Swapna led products in the fintech space at a Canadian bank, involving R&D innovation in digital payments, cards and emerging technologies. While at RBC, Swapna also led experiences in the financial planning & personal investments space.
Swapna was the Head of Product at a SaaS data intelligence company that provided insights to enterprise clients through AI models. Whilst in Singapore, Swapna was responsible for driving eCommerce growth in Asia and Europe for the world’s largest publishing company, Scholastic, as their Product Manager.
She started her career with Accenture, and is a technology buff. Her current passion lies in scaling and monetizing enterprise and consumer platforms.
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Quantifying Productivity benefits for GPT products
As Copilots and ChatGPT applications get normalized across the industry, organizations want to quantifiably measure the benefits of having these GPT products in their ecosystem – whether it’s in terms of supercharging employee productivity and efficiency in the workplace, decreasing the operational costs of the business (cost-savings!), and/or translating these benefits to their end consumers in the form of increased revenue impact.
Productivity measurement in the enterprise also then flows down to various employee personas, roles and functions, since each group might perceive and consume these GPT applications for their own nuanced use cases, thus gaining varying flavors of productivity benefits along the way.
This talk focusses on three things –
1. How should we define enterprise ROI for GPT & LLM specific apps - areas of impact
2. How to define ROI impact for various personas and roles
3. Data collection approaches to help make the ROI measures come to life
Impact of GPT & LLM experiences on Product Development & Innovation
Product Management has come a long way – from innovative software development lifecycles such as Agile and Kanban, the way we conceptualize and prioritize our requirements through PRDs and one-pagers to the various tools up our arsenal through the entire lifecycle of the product.
And now we have another ‘tool’ at our disposal – LLM and GPT based Copilots and Chats. They can be thought of as more than a tool, an assistive device if you will, or your partner in crime that guides you through your PM workday. The way we identify customer challenges and articulate our hypothesis, use prompt engineering to mine vast enterprise knowledge base to extract key insights for our funding proposals or the way we communicate with our stakeholders (& customers) to bring alignment, manage expectations, measure product success and respond to experience snags – all of this has vastly been influenced by the arrival of LLMs and GPTs in our PM lives. Additionally, we’re making step shifts in how we identify and prioritize the latest AI developments into the very hearts of our product experiences – conversational chatbots, productivity software and much more.
So, are we using AI-based tools to their full potential? Conversely, are we trying to force-fit AI into everything – our PM processes and into products themselves, just because it’s the latest trend?
This talk aims to provide a point of view on how AI is and has changed the life of a Product Manager, and how can we optimize its usage to enhance our PM art and our products further.
From Query Boxes to Conversational Companions: How Search and Chat are Redefining Productivity
The way we work with information is changing. Keyword-driven search, once the king of enterprise productivity, is giving way to chat-like interfaces and AI-powered copilot experiences. This talk explores this revolutionary shift, examining how GPT (Generative AI), Large Language Models (LLMs), and conversational interfaces are transforming how individuals and organizations find, access, interact with, and act on information.
In this talk, we'll delve into the impact of Enterprise Search and LLM-based Copilot / Chat experiences on:
1. Individual Productivity: Explore how conversational search interfaces improve user experience, reduce cognitive load, and personalize information access.
2. Organizational Efficiency: Uncover how AI-powered assistants can automate tasks, streamline workflows, and democratize knowledge sharing.
3. Business Effectiveness: Discover how LLMs can unlock hidden insights, generate creative solutions, and support data-driven decision-making.
Designers and product managers will gain valuable insights into:
(1) Designing for Conversational Search: Learn best practices for building intuitive and engaging chat interfaces for enterprise environments.
(2) Integrating LLMs into Existing Workflows: Understand how to leverage AI technology to enhance existing applications and tools.
(3) Adapting to the Changing Information Landscape: Discover how to future-proof your products and stay ahead of the curve in the age of conversational AI.
Why, What, How : Product Partnerships
Partnerships in a product organization might mean you want to bring in skills & product differentiation that are outside your product purview, or you want to scale your product quickly without training resources yourself, or you want to capture a new market segment and bring synergies amongst new lines of businesses.
Whatever your product goals might be, partnerships come in a variety of different formats - getting things done with external vendors, negotiating your requests on internal product team's roadmaps or partnering with external product companies to benefit from each other's industry monopolies.
How do then product managers make these partnerships a success?
- What’s the process of goal setting with your partners?
- How do you reconcile communication styles whilst working with your internal or external stakeholders?
- What happens when partnerships don’t go according to plan?
I’ll recount real-world examples from my previous work experiences – partnering with a tech company as a large banking behemoth, partnering with the world’s largest Mobile OEM as a cloud storage provider at Microsoft, and then partnering with internal product teams as the productivity organization at Microsoft (that I’m a part of today).
Learning objectives would be :
1. Understanding different flavors of partnerships across startups & corporates
2. Learning how to set goals, objectives and success metrics for different types of partnership scenarios
3. Identifying strategies to work the partnership in your favor – creating a win-win scenario.
4. Determining ways to add value to your partners in challenging situations
Employee Productivity through Enterprise Search
Employee productivity is a key success metric that organizations track and yearn to improve year after year, especially with the model shift to hybrid. A key component of being productive at work is to be able to find, access, and use cross-functional information efficiently across various internal channels, portals and websites within (and sometimes outside) their organizations. This enables employees to find the right documents for reference, search for co-workers having domain expertise, access relevant, personalized information based on their roles and preferences and helps to accomplish multitudes of such day to day tasks, in order to be able to do their core job/s in a super productive manner.
As organizational content expands and becomes ever more distributed and siloed across different tools and portals, it’s causing loss in employee productivity by as much as 30-40% every week, as employees spend up to one-quarter of their day searching for the right information to complete a given task. How can we then make enterprise search work for employees, working in a new world, distributed across boundaries, roles and contexts?
This talk will focus on -
- providing an overview of the enterprise search industry and opportunities for taking it to the next level (recommendations, automation)
- measuring success of programs that focus on improving employee productivity
- balancing between user engagement and providing pro-active opportunities to make employees successful in their workday.
Would you even "Search" anymore with the advent of GPT?
'Search' is evolving at a rapid pace with the introduction of chatGPT, Bard and other LLM (large language models), and is acting as a forcing function for organizations to re-define their Search strategy - consumer and enterprise.
In this talk, we'll discuss the historical evolution of search in the last few decades, how user behaviour is shifting to become more interoperable across devices and canvasses, the major trends we're witnessing in the industry with advances in ML models, and how organizations can adapt to this fast paced trajectory.
This talk will arm you with an understanding of what Search might look like in the future, both from a consumer and an enterprise search perspective, and help you gain insights on how you can adapt to these new search trends.
Key Take-aways -
1. Search and Task Automation will tightly integrate to create faster user workflows.
2. Voice technology will see a resurgence as more users employ multiple devices to accomplish tasks.
3. LLM (large language models) will evolve into Multi-modal models to encompass image, video and audio search.
4. Recommendations would become more proactive and actionable i.e. taking the form of actionable AI-generated content.
5. 'Search' as we know it, might not exist.
Swapna Malekar
Principal Product Lead @Microsoft | Copilot, GPTs, LLMs, Search platforms
Seattle, Washington, United States
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