Inna Logunova: The power of data-driven strategies and soft skills

A recent wave of research highlights women’s strategic advantage in the tech industry through well-developed soft skills. While technical expertise remains fundamental, women’s strengths in areas like communication, emotional intelligence, and adaptability offer a complementary edge in traditionally male-dominated fields. Unlike their male counterparts, who often focus heavily on hard skills, women in tech leverage their interpersonal abilities to navigate complex workplace dynamics, break down silos, and foster innovation and inclusivity within teams.

Inna Logunova’s career is a vivid example of how these abilities can transform one’s path in the tech world. With a diverse background in consulting, venture capital, and startups, Inna has not only excelled in technical areas, but also leveraged her strong interpersonal skills to drive success across complex business functions. Her journey highlights the dual power of technical knowledge and emotional intelligence—showing how women in tech can lead with expertise and empathy, creating impactful and inclusive work environments.

Ms. Logunova, when you were doing a consulting project for a top pharmaceutical company in your early career, how did your communication skills help translate data-driven insights into actionable recommendations that resonated with technical teams and business leaders? 

Working on a people analytics project early in my consulting career at Willis Towers Watson taught me that technical insights only reach their potential when effectively communicated. The project involved analyzing various data for a pharmaceutical client, including engagement surveys, performance reviews, and compensation figures. As we dug deeper, we uncovered key correlations and insights that helped us develop a total rewards solution to increase employee engagement and retention.

The main challenge lay in translating these findings into actionable recommendations for different stakeholders. I focused on the data’s practical aspects for technical teams, highlighting patterns and specific technical adjustments. With executive leaders, my approach shifted toward broader strategic benefits—how these changes could enhance organizational effectiveness and support long-term growth. This experience reinforced the importance of tailoring communication to bridge the gap between technical and strategic perspectives, ensuring that our data-driven insights were understood and ultimately implemented to make a tangible impact on the client’s operations and culture.

Your consulting and venture capital background has shaped your data-driven solutions approach. How have your communication skills and adaptability helped you navigate projects across different industries and balance technical and business perspectives? 

My background in applied analytics from Columbia University has been essential in developing strategic and technical perspectives, which are critical in the data domain. Columbia’s program combined business strategy with advanced analytics, equipping me to analyze complex data while always considering its real-world applications. This dual skill set has allowed me to understand how data can directly support decision-making across different fields.

In my career, I’ve worked in consulting, where I critically evaluated client businesses, and venture capital, where I gained an investor’s high-level perspective and in-house roles that brought me closer to operational execution. These varied experiences have been invaluable as I adapted quickly to each sector’s needs, translating high-level business goals into precise technical requirements and viewing data through multiple lenses to drive impactful results.”

Your further development of a comprehensive automation solution for venture capital funds, which cut manual workload by over 50% for some of them, is a significant achievement. Ms. Logunova,  which skills were key in recognizing the need for this solution and leading it through implementation? 

Problem-solving was at the heart of each step to develop this automation solution. It all began with smaller improvements, like applying AI to analyze client feedback. This allowed us to gather it quickly and send critical insights straight to the product team, which sped up the loop between receiving feedback and implementing changes. It made our quarterly business reviews with general partners much more focused and data-driven, letting us identify specific trends and growth patterns instead of general observations.

As we worked with these incremental changes, it became clear that existing tools couldn’t keep up with the level of detail and automation we needed. Attempting to adapt them to our unique workflows didn’t deliver the desired outcomes, so we built an entirely new platform. The new solution automated key parts of the venture capital process, from investor onboarding and portfolio management to KPI analysis and next-round modeling.

This automation wasn’t just about saving time on manual tasks, it also let our team shift focus to higher-value work, like analyzing deal flows and building stronger investor relationships. Each solution layer required us to identify specific challenges, think creatively, and adapt our approach based on real-time feedback.

Can you share what influenced your shift into a Go-to-Market (GTM) strategy, and how your skills helped you drive measurable results, like achieving net dollar retention increase of 17% quarter over quarter? 

My decision to transition into the Go-to-Market (GTM) function stemmed from my passion for driving tangible results and my ability to connect different teams around common goals. GTM is unique in that it combines strategic vision with tactical execution, requiring constant collaboration across functions like marketing, customer success, and sales.

A holistic approach was essential to increase net dollar retention. This 17% improvement was achieved through close collaboration across customer success, product, and sales teams to prevent controllable churn, focus on product enhancements, and create upsell opportunities, respectively. Reaching this result required more than just accurate insights—ensuring each team understood what needed to be done, why it mattered, and how it could yield positive outcomes. Even the most precise data insights get lost if stakeholders don’t recognize their value. By presenting insights in a way that aligned with each team’s unique priorities and constraints, I ensured that everyone was equipped to work towards this goal.

Sounds inspiring! GTM also has a variety of tools to help make the strategy effective. And your leadership skills played a key role in making these tools genuinely valuable. With a 1/4 increase in new tool usage, how did you encourage such strong adoption? 

That’s a great question. Adopting new tools can be challenging, especially when users are more comfortable with familiar systems or encounter early frustrations like bugs or limited support. At first, we noticed low engagement, as some users struggled with the functionality. To change this, I focused on building a solid support framework to smooth the onboarding process and boost user confidence.

I assembled a dedicated team for real-time assistance to handle issues and minimize disruptions quickly. We also held regular office hours for anyone needing guidance and created open feedback channels where users could share their experiences, ask questions, or suggest improvements. This approach, which emphasized continuous support and open communication, made a difference by addressing concerns proactively and creating a sense of partnership, substantially increasing adoption. Users started to trust the tool more and integrated it into their daily workflows, turning it into a valuable, fully utilized resource for the team.

Ms. Logunova, how do you envision using your expertise in AI and analytics to shape the future of business, and where do you see yourself heading next? 

Looking ahead, I’m eager to support startups in finding their product-market fit and scaling effectively through data-driven Go-to-Market strategies. Advanced analytics and AI simplify complex data into actionable insights, and making these tools accessible can open up significant opportunities across teams and industries. As the business landscape evolves, democratizing data analytics will allow teams to tackle challenges with innovative solutions and drive sustainable growth. AI’s potential to create long-term value could reshape how companies operate, setting the stage for future growth and transformation.

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