Business Transformation Requires Transformational Leaders

Adapting to the changing business environment of a digital business is about much more than implementing new technologies like analytics, the IoT, and so on. Rather, business managers from the boardroom down must drive the adoption and skilled use of data-based decision making. Ultimately, middle managers are critical to digital business — making data-based decisions and selecting tasks that provide the necessary capabilities to deliver on a digital transformation vision and strategy.

Starting from a data warehouse just makes sense. Of course, the architectural thinking and technology offer valuable intellectual capital to IT. But the real value comes from the decades of experience in information/data governance and management, as well as the interpersonal and organizational skills that DW imple­menters have gathered. As you will see from the articles in this issue, the contributors are on the same path.

In this, the final Advisor in a four-part series, we explore the third lens of organizational behavior — capability: We “have the ability” to do it. We also examine the importance of language and its impact on culture in the digital transformation transformation.

Compared to software, industrial delivery takes longer, is more complex, and requires a broader set of skills. This series on industrial Agile opens with an overview of a framework for industrial agility, and considers these questions:

• What is new in industry when Agile principles are applied?

• How do the different frameworks of Lean, Agile, Scrum, and Six Sigma fit together?

In this Advisor, the authors explore how two fundamentally different paradigms — Agile architecture and architectural agility — can reinforce one another. Based on a real-world case study from a US technology company, the authors describe how one organization has combined architecture with Agile thinking and methods to break through the anti-patterns and improve its results.

Cutter Consortium is conducting a survey on how organizations are adopting, or planning to adopt, artificial intelligence (AI) technologies. We also seek to identify important issues and other considerations they are encountering or foresee encountering in their efforts. In addition to gathering and analyzing survey data, I have been interviewing leaders and practitioners from different organizations implementing or working to implement AI appli­cations. Here, in Part VI, we jump right into where we left off and continue examining industries that AI is expected to disrupt.

In this Advisor, we examine the organizational behavior lens called pathway: We know “how” we need to do it. We also explore the importance of applying Agile to manage day-to-day activities, and transition states to manage the longer term and ensure delivery of the broader transformation objective.

There are more people who work on improving organizational agility than people who know why this should be required. How can you work on something when you do not know why you should do it? So, before working on transforming our organizations to become more agile, maybe we should discuss the business environment and make sure everybody in the organization sees the same one. Then we should look at our internal organizational environment and make sure everyone has the same expectations and the same perceptions of it.