A Field Guide to Digital Transformation, by Thomas Erl and Roger Stoffers, Pearson 2022

A hot and growing topic area for manufacturing and supply management, everything about IT systems, or digital transformation has the opportunity to integrate key data systems while it phases out awkward and past generation stand-alone approaches. The re-creation of manufacturing IT could not come fast enough, and we are, at least in many US plants, long overdue for the kind of integration that will supersede legacy systems.

The two best features about this Field Guide are the graphics - read it and see it - and the authors' treatment of each systems piece, from data and data intelligence, down through Block Chain, AI, Robotics, Machine Learning, the Internet of Things (IoT).  While you may not foresee Block Chain, for instance, as an integrated part of your system, its important to understand what this system can actually do, and what it can't.  Because there are islands of IT in the manufacturing landscape, many of which have been experimented with some time ago - AI for instance -  their time has come and we need to appreciate their capabilities.  

Remember, the term Digital Transformation is a very big basket that's been around for awhile; some gurus roll their eyes at the term, but it remains the best umbrella for this transformation we are journeying through.  And of course we are now seeing that these digital systems do in fact have great impact on humanoid workers.  The question of when to apply a specific digital tool has in some areas now been superseded by the question of how fast we can achieve implementation. The Field Guide and its case study will help readers think through their priorities and visualize The Plan.

Key chapters:

Chapter 4 - Why undergo a digital transformation?  The answer is, Its not only about the money.  The authors take readers through key contributors, covering why this strategy facilitates market growth.

Chapter 5 - Pitfalls - Common Risks and Challenges - Here the authors point out what happens with bad data, but they also cover the risk of over-automation.  Hand assembly of some components happens for a reason, and until our engineers design for automation, and generate connected flows, over-automation will continue to be a distant scary point.

Chapter 11 -  Introduction to Digital Transformation Data Science Technologies - in a word, here the authors cover Big Data and Analytics the most exciting and challenging chapter in this basic guide.

Mill Girl Verdict - Essential guide for manufacturing leaders and planners, especially those whose geekish abilities are infrequently explored.