data means business
November 13, 2021

How all leaders can learn that data means business

By Paul Laughlin

A new book, Data Means Business from Jason Foster and Barry Green fills an important gap in the market. That is for a book that is both practical advice for data leaders & accessible to other business leaders. One that advances both the success of data strategies in practice and the data literacy education of the wider organisation.

I picked up a copy of this book when speaking at Big Data London and I’m glad that I did. At only 260 pages including titles & appendices it is a shorter and easier read than so many CDO playbooks. It also aims at a different audience. Rather than focussing on the CDO profession, this encouraging book is focussed on making a difference in your business.

Whilst reading it, I was reminded of a term used by Roberto Maranca during our podcast interview. He talked about the need for Business Empathy. This book helps reveal what that looks like in practice for data leaders. So, if you are more concerned about delivering lasting change in your organisation (than joining the CDO speaker circuit), I recommend reading it.

How you can get started with “Data Means Business”

To start, let me give you an overview of the structure of this book and the style of those sections. After a foreword by Prof Philip Tetlow (who also praises this focus & book), the content is divided into four parts.

Part 1, is titled Thinking Differently and includes one chapter on a new approach to business. This would be an ideal read for non-technical leaders wanting to get their heads around the potential of data for businesses. It covers the need & potential of thinking in terms of a data ecosystem & data value chain. Plus, the authors simply explain the cultural changes needed, including considering ethics, diversity & the power of data products. As a key foundation for the rest of the book, the authors also introduce a start-up philosophy & their level-up framework.

Part 2, is about Getting Off the Ground. This covers the first two stages of that level-up framework, Establish & Prove Value. The former provides practical advice on creating a data strategy & engaging stakeholders (including a segmentation of stakeholders). It is also wise in the advice provided on hiring a small starter team & communicating a scoped investment case for a pilot.

The chapter on Prove Value guides data leaders on how to gain credibility by delivering value from a well chosen pilot. This includes aspects like more rapid provision of initial insights, whilst also implementing foundational capabilities. Other important sections here cover how to implement agile working practices & make initial technology selections that will scale as you grow. Closing with communication advice for your pitch deck.

Harnessing the momentum of initial success communicated well

Part 3 of the book focusses on Growth and Impact by sharing advice for the remaining phases of their level-up framework. These are Scale, Accelerate & Optimise. Reading these and other parts of their framework, I was reminded of the guiding model in “Why Digital Transformations Fail“. Much of the practical wisdom reads across. Which probably reflects the need for this approach to data strategy to also be central to digital transformation programmes.

Scale is the longest chapter in this book, reflecting how much there is to think about at this stage. Once again there is learning from a start-up mindset. Plus the authors tackle the frequent business trade-off between in-house capability build & outsourcing development for speed. They share plenty of cultural tips for data leaders. These cover topics including cooperation, collaboration, roles when scaling & org design options. There is also more technical advice on building the elements of an adaptable data platform & how to build reusable components. Finally, they provide guidance on both achieving data ownership & adaptive data management as a service.

Chapters 5 & 6 on Accelerate and Optimise are shorter, which also reflects that fewer organisations are at these stages. But here too there is practical advice for data leaders in more mature organisations. Topics covered include DataOps, automation, wider culture change, federated data knowledge & monetising your data. The Optimise chapter brings to life how to sustain such change through two ‘Data Native‘ case studies. SportPursuit and Gousto are good examples to share. I recall my podcast interview with Rob Barham and the lessons he shared there too.

What next? How can you show data means business?

The final part of this book is focussed on helping data leaders set themselves up for success in defining and executing a data strategy. It is a helpful guide to what too include in scope (see their 6 pillars model)& how to retain business strategy alignment. It also focusses on planning and tracking your progress. Foster & Green offer an example of a data vision, how to use the level-up framework as a planning tool & tracking metrics to consider. They also include a useful final section on handling legacy technology, a challenge for most data leaders.

I hope this review has encouraged you to seriously consider getting this book. I could see it as a useful purchase for boards or executive teams. It can easily be dipped into for relevant sections. It would also provide leadership teams with a common language for their data journey. The book achieves further credibility through including useful quotes from interviews with data leaders whom I respect. Ryan den Rooijen, Graeme McDermott & Rob Barham (all podcast guests) are quoted at length.

So, what will you do? How could you help your organisation see that data means business? Perhaps reading this book might be great place to start. But , if you have other resources that have helped guide you as a data leader, please let me know. Finally, to all data leaders leet me join Jason & Barry in saying, “enjoy the ride“.