Mike and Adam discuss a Service-Oriented Future: how to move from a 'one-and-done' Digital Transformation mindset to a continuous improvement / technology lifecycle approach. This starts with an agility-infused Digital Operating Model, and touches on Enterprise Architecture, continuous learning, security vs. User Experience, Responsible AI and transforming the way we develop solutions — using a model-based, cross-functional approach.

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Welcome to The Digital Formula podcast. This week we are speaking with Craig Barbakow about DevOps as a better way of implementing and operating digital products for your customers.

We spoke about three main topics:

Introduction to DevOps

- DevOps combines development and operations, aiming to improve collaboration and efficiency in IT organizations

- The podcast guest, Craig, is an IT expert with extensive experience in IT strategy, architecture, and service management

Key Concepts of DevOps

- DevOps involves cultural shifts, organizational changes, new skills, and integrated tools to enable faster and more reliable software delivery

- The CALMS model (Culture, Automation, Lean flow, Measurement, and Recovery) provides a holistic approach to implementing DevOps

- Integrating tools like Jira, Jenkins, and ServiceNow is crucial for streamlining the development and operations processes

Challenges and Best Practices

- Organizations often struggle with bureaucratic obstacles like change advisory boards, which can significantly delay software releases

- Involving security and risk management teams early in the development process is essential for successful DevOps implementation

- Creating a culture that encourages collaboration, balances risk, and attracts the right talent is fundamental to DevOps success

This week's episode is the second part of our conversation about Process Intelligence.

Based on the foundation of what Process Intelligence is (Episode 8), we are now looking at one technique and how you can implement it in your organization: Process Mining.

There are a lot of myths around what Process Mining can and cannot do (depending on who you ask), there is still the need to follow a certain train of thought/process to do a successful Process Mining project, independent of which software you use.

The approach that we recommend has six steps as follows:

1. Define (Process Mining) strategy
2. Extract system logs
3. Create data model
4. Create reference process
5. Analyze process
6. Identify improvement opportunities

Soon you will find the content of the six steps, including graphics, on our blog, so that you have a written reference. However, here are a few books/resources that I recommend having a look at:

• the book “Successful Process Improvement: A Practice-Based Method To Embed Process Mining In Enterprises”: https://www.amazon.com/gp/product/B096XJ8CK7/ref=ppx_yo_dt_b_d_asin_title_351_o01?ie=UTF8&psc=1
• the book “Process Mining: Data Science in Action”: https://www.amazon.com/gp/product/B01EUYVU6Y/ref=ppx_yo_dt_b_d_asin_title_351_o05?ie=UTF8&psc=1
• there is also a course on coursera available that uses this book as text book: https://www.coursera.org/learn/process-mining