Driving Digital Transformation through Data and AI

A Practical Guide to Delivering Data Science and Machine Learning Products

Alexander Borek, Nadine Prill

• Publisher: Kogan Page
• Year: 2020
• Print ISBN: 9781789665390
• eBook ISBN: 9781789665406
• Edition: 1
• Topic: Computer Science
• Subtopic: Business Strategy
• Index: Computer Science

Leading tech companies such as Netflix, Amazon and Uber use data science and machine learning at scale in their core business processes, whereas most traditional companies struggle to expand their machine learning projects beyond a small pilot scope. This book enables organizations to truly embrace the benefits of digital transformation by anchoring data and AI products at the core of their business.

It provides executives with the essential tools and concepts to establish a data and AI portfolio strategy as well as the organizational setup and agile processes that are required to deliver machine learning products at scale. Key consideration is given to advancing the data architecture and governance, balancing stakeholder needs and breaking organizational silos through new ways of working.

Each chapter includes templates, common pitfalls and global case studies covering industries such as insurance, fashion, consumer goods, finance, manufacturing and automotive. Covering a holistic perspective on strategy, technology, product and company culture, Driving Digital Transformation through Data and AI guides the organizational transformation required to get ahead in the age of AI.

02

Strategy and vision for data and AI

LEARNING OBJECTIVES FOR THIS CHAPTER

• Learn why a new strategy and vision are essential.
• Learn how to rethink the current corporate strategy and business vision.
• Learn how to create a data product strategy.
• Learn how to define a capability strategy.
• Learn how to build a transformation strategy.
• Learn how to combine all four into a joint transformation roadmap.
• Learn how to secure enough funding for your initiative.
• Learn how to close the gap between strategy and reality.

Key principles for creating the strategy and vision

The previous chapter outlined the fundamental changes driven through data and AI. Digital transformation through data and AI has already started to shift the current industrial landscape. Data and AI make up an innovative, complex and cross-functional discipline. It is an absolute necessity to align managers and employees across the business to foster a joint and orchestrated effort to implement the data and AI transformation effectively. A joint strategy and vision for data and AI that is shared across the organization is the basis for change. It is a massive task to create a new strategy and vision for driving digital transformation through data and AI and requires a strong willingness among the company’s leadership to truly reinvent the company.

The new strategy and vision determine how an organization plans to benefit from data and AI, positions itself in the new competitive landscape and how it wants to get there. As the strategy and vision forms the core of the transformation, it lays out how the business model is supposed to evolve, which data products and capabilities will be of strategic importance and how the transformation change will be managed. The strategy and vision should be executable with sufficient resources planned and a feasible roadmap. Without it, there is a risk of missing out on the new business opportunities created by data and AI in your industry, slowing down the digital transformation progress, allocating resources ineffectively, quickly losing the board’s attention and making change management far more difficult to achieve.

Based on the authors’ collective experience, an effective strategy and vision can be designed in four phases addressing the different perspectives of data and AI: reinventing the corporate strategy and business vision; creating the data product strategy; deriving the capability strategy; and developing the transformation strategy.

A strategy and vision for driving digital transformation through data and AI revises the current strategy and vision of the company and readjusts it to the new realities in the industry. It addresses the four distinct perspectives of strategy, product, capabilities and transformation.

Figure 2.1 The four phases of developing a strategy and vision for data and AI

Figure 2.1 details

The details of the process are as follows:

• Reinvent corporate strategy and vision.
• Create the data product strategy.
• Derive the capability strategy.
• Develop the transformation strategy.

Strategy and vision can be approached in four phases:

1. Reinventing the corporate strategy and business vision: How is your industry affected through data and AI? Do your current business model and corporate strategy need to be adapted? What should the business vision and corporate strategy be for the age of AI?
2. Creating the data product strategy: In which business areas and for which purposes should data products be designed and developed to best support the vision and strategy?
3. Deriving the capability strategy: Which capabilities and technologies are needed to deliver the vision and strategy? Which competences have to be built and how should the organization be designed?
4. Developing the transformation strategy: What are the change management activities needed to implement the strategy and vision? How can the transformation of the company be managed?

The strategy and vision provide the company’s orientation for how it plans to reinvent itself and invest resources in the short, medium and long term. This is not a one-time exercise, but an evolving plan for the future and it needs periodical inspection and revision to incorporate learning from the transformation process.

Key principles for reinventing the corporate strategy and business vision

The first phase is concerned with the fundamental changes that are brought by data and AI to the corporate strategy and business vision for your company. A good starting point is to investigate how your industry will be...

Table of contents

• List of figures
• List of tables
• 01 Introduction
• 02 Strategy and vision for data and AI
• 03 Data product design
• 04 Data product delivery
• 05 Capabilities and agile organization
• 06 Technology and governance
• 07 Transformation and culture
• Index