Agile and Flexible Services Deployment with OKR Centric Delivery

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At Databricks, our core focus is enabling customers to achieve their business outcomes with measurable impacts. In our Professional Services teams, we have been executing on this via our OKR-centric delivery model. This post builds on our previous story, demonstrating how Databricks Professional Services (PS) amplifies results by integrating OKR-driven methods with our agile 'Pod' deployment and leveraging AI for maximum impact.

This blog highlights our learnings on how this model is helping accelerate value and has been transformative for engineering-focused customers. These are the key tenets of this model:

Customer-Centric Execution: By aligning with customers’ OKRs, Databricks PS ensures project scope and priorities truly reflect business-critical needs, not just technical checklists. The value delivered centers on ROI to the business, ensuring outcomes like landing new capabilities, improving performance, and decreasing costs, and securing a strategic impact that goes beyond technical completion.
Agility and Partnership: The new model is all about agility through continuous joint planning. Instead of rigid SOWs, teams engage in real-time collaboration, with the flexibility to add goals, revise key results, and pivot as customer priorities change.
Skill and Resource Fit: OKR-centric models allow PS teams to match specialist skills to specific key results, bringing in the right expertise at the right moment and fostering true co-ownership of project outcomes.
Measurable Impact: Mutual OKRs facilitate continuous progress tracking, review, and reporting. This ensures transparent accountability and directly links activities to customer ROI.

Professional Services pod deployment for OKR-driven engagements

Back in 2024, we introduced a bold new way to accelerate customer value: Pods, small autonomous cross-functional teams purpose-built for speed and impact.

Unlike traditional delivery models that assign one or two engineers for the duration of a project, Pods operate as self sufficient units with full ownership. Pod leads can instantly pull in the right expertise at the right moment without lengthy change requests or disruptions to contracted hours. The result is faster decisions, seamless execution, and dramatically improved agility.

Designed for flexibility and accountability, Pods empowered customers to move from strategy to outcomes faster than ever before, turning complexity into momentum and ideas into results. Here’s how they executed:

Cross-Functional Composition: Each team blends architects, engineers, DevOps/cloud specialists, and technical project managers, bringing extensive skillsets needed to execute on OKRs within one efficient unit. These forward-deployed engineers are embedded within customers, ensuring a deep understanding of the objectives in the overall business context, leading to swift problem-solving and achieving the key results.
End-to-End Ownership and Autonomy: Our teams operate independently, empowered to make decisions and adapt to changing requirements and key results on the fly. They are guided by our one true north star - “Customer Success.”
Customer Success at the Core: Our teams don't just deliver technical outputs, but they align directly with the OKRs, keeping critical business milestones front and center. These teams constantly engage with the Databricks core product and engineering team to drive forward features and remove technical blockers needed for the customer’s specific business use-cases.

Impacts On Many Large Enterprise Customers

The integration of our team structure with OKR-focused delivery is already providing demonstrable value for Databricks customers.

Accelerated High-Quality Delivery: Streamlined execution, faster launches, fewer blockers, and robust platforms deployed on time and within budget.
Major Cost Savings: Strategic cloud migrations have unlocked 20-40% cost reductions for customers. For example, Dropbox’s migration to Databricks, guided by clear OKRs and our agile teams, combined transformational savings with full business continuity.
Increased Customer Satisfaction: Transparent progress communication, clear accountability, and continuous alignment mean customers trust PS as a true strategic partner.

Through ongoing advisory, enablement, and risk mitigation, Databricks and its partners help customers reduce the total cost of ownership, build in-house expertise, and pave the way for sustained digital transformation. Real-world engagements, like our joint success with Shell, demonstrate the tangible benefits of this approach.

Embedding Impact: The Forward Deployed Engineer Model at Databricks

Our Pod-based Delivery Model, particularly its emphasis on embedded expertise and outcome-driven delivery, has essentially been operating with the spirit of the Forward Deployed Engineer (FDE) model, gaining popularity in the AI-first world. Their service encompasses the full spectrum of software engineering, including infrastructure development, CI/CD, data engineering, and application development. This embedded approach allows them to deeply understand the unique operational contexts, proactively address challenges, and collaboratively build tailored solutions leveraging modern AI tools alongside the Databricks Platform to deliver meaningful impact. Through continuous engagement and an OKR-driven delivery approach, we have consistently reduced customers' time to market and boosted satisfaction for both technical and business stakeholders.

Based on our success over the past year, we are in the process of officially formalizing this OKR-driven FDE model as part of Databricks Professional Services offerings. This will enhance our established commitment toward hands-on partnership, flexibility, and outcome-driven delivery. Moving forward, the FDE approach will continue to provide Databricks customers with personalized, high-velocity innovation, keeping them at the forefront of data and AI transformation.

Databricks PS Difference: Summary

The Professional Services (PS) team at Databricks plays a pivotal role in accelerating the adoption of advanced AI and machine learning solutions for our customers. By bringing together joint OKRs and the pod delivery model together with a FDE motion, Databricks PS provides a forward-looking model for organizations seeking to transition from standard consulting to proactive, business outcome-focused collaborations, driving:

Higher delivery quality and throughput
Boosted resource efficiency and cost savings
Stronger customer partnerships and satisfaction
Scalable, sustainable value as data needs grow

This approach has been praised by customers like Rivian, Dropbox, and Walgreens, who credit the joint OKR model for creating shared goals, clear accountability, delivery confidence, and removing ambiguity from even the most complex projects.

Databricks Professional Services (PS) works with a trusted global network of partners to accelerate customer innovation and deliver exceptional business outcomes. Combining Databricks' deep technical expertise with an extensive partner ecosystem provides seamless, scalable support tailored to each customer’s unique journey.

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