Bio
Sarabjit is working closely with McKinsey on Enterprise Transformation (Infinity Program 2018 for Infosys), recipient of McKinsey Infinity Award 2018 - Agile Track. An Enterprise, Agile Coach Trainer, an Agile Scout and an Agile Program Consultant with experience of managing and leading software development and release management teams and in the successful implementation of various software applications and infrastructure initiatives. He has hands-on experience in setting up and transforming IT organizations in the people, process and tools & technology dimensions. Experienced in result oriented CIO /CTO coaching and consulting in the areas of ‘change’ and ‘run’ programs of Enterprise IT. Working towards Enterprise Business Agility and retransforming towards the second Wave of transformation for Edgeverve an Infosys Company.
Session Title
ScaleBan - A Rolling Program Forecasting Framework for Scaling.
Session Overview
Our Scaling journey was no different than many other organizations. While in our journey we achieved certain major wins we also had setback which led us to evolve a new framework model which is helping us big time now . While we were venturing into our scaling journey for team sizes of 60+ we were unable to protect the scope of fixed cadences. The Technology uncertainty added fuel to fire leading to big surprises in estimation and slowly losing trust in the process as well as execution. The execution pressure led to have non ready backlogs, Utilization thinking and team burnouts due to over commitments. This eventually led to misalignment between BO and Teams from Value proposition.
We worked hard on the “Who” (Fit for purpose) part more which led to the evolution of our own framework which helped us in planning using frequently forecasting learning cycles . The evolution of the framework solely depends on the Flow from ideation to deployment. In this journey we adapted basic Kanban principles and later combined them with some good industry practices helping improved business R&D trust in setting expectations.
Kanban helped us to -
- Moving from commitment culture (in uncertain environment) to frequently forecasting based on learning cycles
- Focus on flow of MVFs. From idea to deploy
- Postpone decisions (preserve options), stop starting start finishing
- More team’s involvement, empowerment and accountability
- Reduce any waste of estimation due to “commitment” culture in uncertain environment
- Improve Business-R&D trust in uncertain environment. Better prediction and setting expectations.
Post adoption of the Scaleban framework
- There was a productivity increase
- Ownership, Trust and pride re- established. Business got a lot of flexibility of make changes on the fly
- Teams were able to define Class of Services leading less ceremonies /estimations and hence saving huge cost
- It eventually became a Learning Organization which paved the way towards re-skilling on the job and helped.
Learning Objectives
- Benefits of Visualization and Data - Outcome driven
- To Scale define the boundary context (known unknowns)
- Set your business context and release on the fly (Predictable and Forecasting)
- Stop Starting Start Finishing - DOR, DOD
- Respect Flow - Visualize your value streams and reset WIP accordingly.