Scaling Up in an Artificial Intelligence based video analytics software company
The case study of an organization operating in the field of AI-based video analysis software, which was seeking a more efficient adaptation to business and organizational growth. This was done with the aim of maintaining quality and ensuring predictability in the delivery of new product versions.
Context
A company dedicated to Video Analysis Software using Artificial Intelligence, consisting of over 50 employees, had its operations center located in the United States, while the Software Development and Artificial Intelligence teams were based in Barcelona. These teams, together, comprised approximately 25 individuals, including the CTO, engineering directors, head of product, product owners, software engineers, and machine learning engineers.
The initial context was:
- Failure to meet release dates and a lack of predictability in version content.
- Frequent inability to complete tasks within a 2-week timeframe.
- Excessive burden of responsibility on team leaders.
- Lack of continuous improvement.
- Complications in the production deployment process.
Their improvement aspiration aimed to increase efficiency, ensure product quality, enhance predictability in deliveries, and adapt to the planned growth of both the business and the organization.
Process
- Evaluation of the current situation through a systemic approach, identifying both areas requiring improvement and key factors facilitating the sustainable implementation of these improvements.
- A new organizational design co-created in collaboration with the management team and managers, aiming to enhance effectiveness, quality, predictability, and adaptability to the organization’s planned growth.
- Definition of roles and responsibilities in line with the new organizational structure.
- Definition and implementation of collaboration and interaction between teams based on the Team Topologies model.
- Day-to-day support for the Software Development and Artificial Intelligence teams to increase their speed, predictability, transparency, and delivery quality.
- Assistance to the Chief Technology Officer (CTO) and mentoring for engineering managers to support the new leadership culture and enhance their skills.
- Active involvement in the hiring process.
- Facilitation of kickoff meetings for new projects (Inceptions Decks) to align expectations and ensure shared understanding of the project to be developed.
- Utilization of data to estimate release delivery.
Results
- Achieving a 20% reduction in Lead Time resulted in an improvement in operational efficiency.
- Minimizing conflicts arising from role responsibilities, ensuring clarity in task descriptions, roles, and expectations, led to greater harmony within the team and more effective management of interactions among members.
- Promoting stronger collaboration between the Product and Software Development teams resulted in increased efficiency in product conception and solution implementation, translating into a more positive working synergy.
- Optimizing the distribution of cognitive load within teams ensured that tasks and responsibilities were allocated fairly and efficiently, preventing overburdening of any team member and promoting a balanced and productive work environment.
