
Scaling BPM efficiency in a start-up company

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challenge
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A SaaS BPM company struggled with slow product iteration cycles and inefficient team collaboration.
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Delays in feature delivery and inconsistent customer onboarding were major pain points.
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Rigid internal processes made it hard to adapt to rapidly changing client needs.
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outcome
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Enhanced product stability with a 92% reduction in critical bugs, removing the need for patch releases.
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Weekly meetings were cut by 70%, allowing more focus time for the team.
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Our ROI calculator estimates up to €88K in annual savings on bug fixes.
approach
Our team at data duke was brought in to help this BPM startup overcome growing pains by implementing an Agile transformation tailored to optimize both product development and customer-facing processes. Through discovery workshops with product development, engineering, and customer success teams, we identified a key challenge: while the company excelled at automating client workflows, its own internal product management lacked structure and transparency.
To address this, we introduced Scrum as the primary framework for product development and engineering, enabling structured workflows and clear prioritization. By integrating dual-track Agile, we ensured that product discovery and delivery worked in parallel, allowing teams to validate ideas before development began. Sprint planning and daily stand-ups created a consistent rhythm across teams, ensuring alignment on development goals and fostering faster iteration on critical platform features.
A major gap was the lack of collaboration between product development and customer success, which led to disconnects in feature communication and rollout. To bridge this, we implemented cross-functional workflows, ensuring that engineering, product management, and customer success collaborated throughout the release cycle. This aligned with Test Flow, enabling business teams to verify features before launch, reducing miscommunication and last-minute fixes.
Since the company specialized in automating client processes, we helped them apply the same principles internally. By integrating automated testing and AI-driven workflows, we reduced administrative burdens on teams, allowing product managers to focus on innovation rather than internal tasks. This reflected the Clear Tracks approach by embedding structured workflows and test-driven development (TDD) for continuous improvement.
One major challenge was incorporating customer feedback efficiently. We established a continuous feedback loop, ensuring insights from customer success directly influenced the product backlog. By shifting to a customer-driven roadmap, the company prioritized high-impact features, ensuring faster delivery of valuable updates. This supported the Release Train methodology by making feature releases more predictable and aligned with market demand.
By embedding structured workflows, automated processes, and AI-powered testing, the startup not only optimized internal operations but also significantly improved product quality and responsiveness.