Beyond Algorithms: Reshaping a Startup's Data Science Strategy for Real-World Impact
Client Background
A Series B manufacturing startup was developing a proprietary process to inspect battery quality as they were made on the assembly line. They had built a 10-person in-house data science team, but weren't sure how to proceed. They reached out to Komodo to ensure their approach was optimal, aligned with industry best practices, and effectively supporting business objectives in a competitive, fast-evolving market.
The Business Challenge
Komodo Technologies was engaged to:
Evaluate the data science team’s modeling techniques
Assess their scientific approach to product quality
Explore alternative methods and data sources for more efficient problem-solving
Time was critical. A lengthy discovery process was not an option; the client required immediate contributions. Komodo was asked to integrate into the sprint process and provide weekly updates.
Using a sample of the client’s data, Komodo was tasked to:
Assess the data’s effectiveness in addressing product quality challenges
Recommend enhancements, including different modeling methods, analytical adjustments, or organizational changes to increase the team’s value
The Komodo Solution
Within three days, Komodo was fully integrated into meetings and sprint activities, generating new insights and approaches. We interviewed stakeholders and subject matter experts to deepen understanding of the data science approach and visited the client’s offices for further investigation.
Our assessment included:
Evaluating whether techniques and technologies were appropriate for the challenges
Determining whether the data science team’s efforts were aligned with high-value R&D objectives
Investigating the impact of past data science work on organizational understanding and outcomes.
We emphasized that successful data-intensive projects require alignment between data scientists’ efforts and organizational goals. Many companies struggle to extract actionable insights when data scientists focus narrowly on technical challenges rather than broader business objectives.
The Results
Within one month, Komodo identified major issues with the client’s scientific approach and data quality, including gaps in data collection that limited progress measurement. We proposed alternative methods to generate better ground-truth data.
We also recommended reorganizing the data science team to better support business goals, providing a detailed due diligence report and in-person presentation. Our suggestions included concrete changes to processes, project management, and organizational structure, with strategies for effective rollout and communication.
Key improvements included:
Enhancing training data quality
Recommending new analytical approaches and areas of study to refine business problem-solving
Designing a project management structure to improve engagement, transparency, and team efficacy
Identifying organizational adjustments to better promote and leverage data science for decision-making
Delivering an actionable roadmap for implementing improvements while enhancing transparency and communication of scientific results
Komodo demonstrated that accelerating progress is not simply a matter of hiring more data scientists. Often, the real solution lies in reassessing strategy and ensuring that data science aligns directly with business goals. By refocusing efforts and providing a clear roadmap, Komodo amplified the client’s data science impact, improving both efficiency and outcomes.
Komodo Technologies specializes in practical data science solutions. We think about data science in situ, rather than as a mathematical exercise. If you’re struggling with your data science projects or unsure if you’re addressing the right issues, contact us for a free consultation to discuss how we can help you achieve your goals.