I recently had the opportunity to read Data Crush: How the Information Tidal Wave is Driving New Business Opportunities  by Christopher Surdak.  The book was published this year by the American Management Association and is 288 pages long.

For a quick observation, while reading the book,I felt at times like I was reading a book in the vein of Freakonomics in some ways (especially on page 169, for example).  If you liked that book or like that type of book, then this book may well be a great read for you! If you wonder what “Data Crush” means, consider that “four primary drivers of data growth are caused by mobility: pervasiveness, connectedness, data enablement, and context” (12).  Christopher Surdak writes about his own book, that “this book was intended to stimulate your imagination and hopefully help you set a course for your own work” (235).  I believe it does that. 

The book is divided into three parts, with each part consisting of six chapters.  Part 1 looks at the history and context leading to the “Data Crush” by asking “What’s Driving the Data Crush?” Part 2 considers “The Impact of Business” and offers a series of models and strategies to unpack and consider the business impacts and potential impacts of the exponentially increasing data.  Part 3 offers recommends and ideas of “How Successful Businesses Will Respond.” Particularly helpful within part 3 are the inclusion “six recommendations for how to manage all of this information and how to put it to use in driving your business forward (171). Following part 3 is what I think is the best chapter in the book. In fact, I would argue that the best part of the book is the last chapter, “Summary:  A Few Days in Life, Circa 2020,” which puts together all of the ideas and topics covered in the book into practical and understandable demonstration through five fictitious but very believable scenarios. In this chapter all the ideas and perspectives offered up to that point are now given possibility, legs, and life. 

As I do with my reviews, I will not offer a thumbs up/thumbs down, or a ranking of stars, or things like that.  Rather for my processing, and hopefully for your benefit, I will share what I found that I loved, what I liked, what I might have done differently, and what I felt raised questions for myself.  What I value in a book is that it makes me think and not just shake my head in automatic agreement or in hasty disagreement.  I want to be challenged when I read, sometimes affirmed, but most importantly I want to be able to think, learn, and grow.

What I Loved:  I loved how seminal the text felt when reading it. Perhaps it has more to do with my lack of familiarity with the topic, but the way the book covered the various themes related to “Big Data” it was intriguing and made me aware of just how important an understanding of this is.  Some of the details that greatly caught my attention included the estimation that almost 90% of humanity has mobile phones, meaning that they are no longer a luxury (Data Crush, 10).  Or consider this, “‘Facebooking'” is the second most popular web-based activity by click rate; the first is searching on Google. Facebook is the number one online activity by minutes spent, capturing around nine percent of all time spent online by all users” (24).  That’s a fairly amazing thing to think about, since Facebook has only been around about ten years.  There was also the learning piece from the data, greatly exemplified about how Target accurately discerned and predicted someone was pregnant before their family even knew based simply on their purchases (75).  There were plenty of other illustrations which I loved how they made the points well and convincingly. Because of my involvement with a start-up organization, I also appreciated some of the perspectives about start-ups that were shared included a reflection about the relationship of cloud computing and start-ups (62). 

In terms of structure, I greatly appreciated that at the end of each chapter, chapter summaries with key points were provided. This was very helpful, particularly in digesting some of the denser topic chapters.

In terms of the writing itself, a few particular lines stood out.  I loved the claim that “we will have to be open to revealing more about ourselves than we desire, but the benefits will make us more likely to opt in to this datafied world rather than become digital luddites living at the fringe of the information age” (5).  This is compelling and I believe proves to be a good thesis for the book.  It’s later expanded upon by the observation that “younger users of mobile and social technologies appear to be dramatically less concerned about their privacy than older users” (84).  

There was a number of good illustrations too which were appreciated in helping lighten the mood in reading this text.  One that stands out,  the comparison of the storage of data off-line to the way the ark was stored in way at the end of the movie “Raiders of the Lost Ark” (200).

What I Liked:  I found that the graphics and graphs were helpful for unpacking some of the models and ideas that Surdak proposed.  These include the:  Contextification Maturity Model (89); Socialification Maturity Model (106); Quantafication Maturity Model (121); Appification Maturity Model (135); Cloud Computing and Cloudification Maturity Model (150); and Thingification Maturity Model (161). 

Again, there were a number of observations which I found compelling and helpful.  Within the beginning of the book, is the basic belief and observation that ” far too few organizations have systems and strategies for managing their most important assets in a digital world- their information assets” (viii). This fact becomes readily apparent within the text.  For example, “early adopters are finding dramatic improvements in their operational efficiency, customer satisfaction, and profitability” (4). Or, consider this observation, “One  theme that is evident from the explosive growth of YouTube is that consumers want to play a more proactive role in their entertainment” (54). 

The Peter Drucker questions and focus on who is your customer and what does your customer value came to mind in some of the discussion about data.  Surdak writes, “If you really want to keep up, you need to be able to predict customer needs and to fulfill them before anyone else does” (46).  I would add that if a company wants to keep up, it probably needs to be able to predict and name and meet the customer’s needs before the customer even knows that they are needs.  Related, “through comprehensive data analysis, businesses can develop a new level of understanding about what drives customer behavior” (76).  Also, there was some good discussion about the need to engage customers’ feedback and comments, especially the negative ones as learning opportunities to respond and turn a negative into a positive (221).  In fact, “many companies are hiring professional ‘tweeters’ – people whose sole job is to monitor sites such as Facebook and Twitter for negative comments and to then respond as quickly as possible to each customer’s complaint” (101). 

Taking a step back, I appreciated the recognition by the author that “Big Data is receiving enormous amounts of press these days, and yet there’s a complete lack of consensus on what exactly constitutes ‘Big Data'” (69). Surdak followed this up throughout the book to try and help provide some definition about “Big Data,”and particularly its implications, but the fact that there is no general consensus means that there is much larger societal discovery left to be done about what it is. 

What I Might Have Done Differently:  Overall, I enjoyed this book.  But, I have to be honest, Part 2 is kind of dense. I do think that a lot of this has to do with its content, but the writing in this section didn’t necessarily help either as it often felt highly technical and may be a bit disengaging for the non-technical data reader.  As I said previously, the graphs and charts though were helpful to slog through the ideas.  Further, the final summary chapter did a great job of synthesizing some of the deeper technical ideas expressed in part 2 in ways that were approachable, relatable and more understandable for lesser technical experiences and understandings. 

What Raised Questions for Myself: A number of questions did come to mind based on this text.   Some of these questions were raised by the text itself, like “How could a company that provides a free service to its customers be worth so much money? To answer this question, I look to my favorite quotation from a venture capitalist: ‘If you aren’t paying for it, then YOU are the product!'” (30).  Others, were implied.  For example, how are you embracing your customer’s contexts?  “Fail to embrace the power of customer context, and your business will continue to erode in the face of data-enabled competition” (40).

In its best form I believe that Big Data provides an opportunity to ask questions, to learn, and then to take that learning and to act on it.  Surdak writes, “Big Data really consists of two things. First, it is the joint analysis of structured and unstructured data from within a company. Second, it is the joint analysis of internal data sources and external sources, both structured and unstructured” (70).  This reality will only increase as “the demand for people who are data literate will grow dramatically over the coming decade…These people will command a significant premium for their skills for the foreseeable future; hire yours while you still can!” (74).

In terms of how to approach the data, Surdak provides a number of helpful comments.  He writes, “Your business strategy should drive what data you seek to obtain and analyze in order to grow your business” (178).  Without some strategy, the sheer amount of data would overwhelm.  Further, in terms of dealing with the data, “if you can then you must.  This predictive imperative is going to be the eventual result of joining massive quantities of contextual data with the advancing capabilities of Big Data analytics and machine learning” (189).  To get past the amount, there is great opportunity for learning, growth, and meeting needs. “The data created through business operations will represent a potential gold mine for companies that learn to properly manage and use it and will become a digital albatross for those who don’t” (196). To this end, “meaningful metrics for every business process in the company must be identified and captured” (202). These comments help wade through the questions, but they also create their own questions. 

Other questions raised by the text include what does it mean that social media’s  impact overtime “may eclipse that of the Internet itself?” Surdak writes,  “Social media is affecting every aspect of our lives and the advancing application of social media into our lives, our Socialification, will define the next few decades of our society’s evolution” (99).  What might this mean? 

In terms of claims and observation, there are quite a few which raise questions. For example, Surdak writes “the App Store might very well go down in history as Steve Jobs’ single greatest innovation” (129). I probably agree with this. What do you think?  If you want another claim to think about, contemplate this:  “To survive and thrive in the near future, all companies involved in the sale of physical goods must prepare themselves for this torrent of incoming customer data, and realign their business models to maximize the value that they derive from this information” (169). What do you think? 

The text includes a number of ideas with large implications.  Being as I have a foot in a few different contexts and sectors of society, I couldn’t help but think and wonder about some of the implications.  For example, what are the possibilities for contextification for congregations? (89-95) Or, what does it mean about humanity, if people are becoming “process stewards?” Surdak writes, “People have become process stewards, who monitor the performance of automated processes rather than execute the processes themselves” (118).  Perhaps this is related to the observation that “entire layers of middle-class, middle-management jobs have been cut, largely due to the process automation that has occurred over the last 25 years” (145).  In which case, that is a whole part of our economy that is not going to return, and have we really begun to comprehend what this might mean in the way we train and prepare (and re-train) people? What new opportunities might this create?  Related, the explosion of automation of business and the connection with increasing of minimum wage (147-148) makes for a rather timely discussion.

The book is a great read, and an important read to think about the ever increasing amount and role of data.  This presents challenges and opportunities.  Surdak writes, “today’s opportunity becomes tomorrow’s imperative. And tomorrow’s imperative becomes the following day’s obituary for those who don’t act” (204).  According to the author, there are two options for engaging the data.  I entrust this book to you, and believe it will be a good read for you to contemplate data and the many questions and possibilities raised by the ever increasing amount of data and ways we engage and create it.

Source:  Christopher Surdak, Data Crush: How the Information Tidal Wave is Driving New Business Opportunities, (New York, NY:  American Management Association, 2014).