Organizational Intelligence

ib-book_coverThis book is about the history of a business technology. Specifically, it traces the emergence and evolution of analytics software. More specifically, it is the story of the growth and success of one of the leading companies in the field – Information Builders (IB), as written by one of its co-founders and CEO, Gerald Cohen, and Dr. Rado Kotorov, the company’s chief innovation officer and VP of global product marketing. The authors are co-holders of patents on key inventions underlying IB’s success, and are clearly evangelists for analytics.

The structure of the book is conventional: the first half is a brief history of information technology with a drill-down into data science and analytics, and the second half consists of a half-dozen case studies across as many industries describing successful implementations of Information Builders’ products.

It’s not easy to write gripping history, and the history of info-tech is no exception. The authors are not professional writers composing for the general reader, and so the elements of story and drama are missing from the first half of the book – the first human is not mentioned until page 39, the second on page 70. But they do paint a chronological picture of the evolution of the information application – from different platforms, database structures, operating systems, metadata and the internet, to the cloud and mobile that is of interest to the IT literati. And they make, and explain, a statement that at first glance appears counter-intuitive: “as the demand for information for decision-making grows, the level of technical and mathematical skill of those who need information decreases.” The explanation derives from their analysis of present-day information users: 1% are “data scientists”, 8% are “business analysts”, and the remaining 91% are non-technical users textrequiring a “self-service application.” This is their holy grail – their paragon is the Expedia application for travellers – democratizing information assets by putting analytics in the hands of workers throughout the organization.

Another belief of the authors is that data is an asset, and that it can and should be monetized. Selling data outright is an obvious example, but they spend more time on two other use cases – first, using data analysis to make processes more efficient, and second, communicating data to workers as a tool to incent them to higher performance.

I had a phone interview recently with co-author Dr. Kotorov, while he attended an analytics conference in the Netherlands. I asked him why all six case studies (covering wealth management, automobile manufacturing, international shipping, banking, food production, and healthcare) were American? He said there were many more overseas case studies in the pipeline (for use in the second edition of the book) and he described the difficulties encountered in obtaining the sign-off of clients who fear disclosing competitive information.

Two case studies in this book stand out. One references nVision Global, an international shipping company that moves $5.2 billion in freight, and processes 100 million invoices annually. CEO Luther Brown wanted to provide clients with the ability to track shipments on the move, and to increase efficiency and effectiveness of their shipping activities. He commissioned the creation of an InfoApp called iFocus Supply Chain Analytics which minimizes transportation costs by analysing invoice data. Transportation providers can click on a digital map to determine the best worldwide shipping lanes, and customers can save from 3 to 10% using the InfoApp. Luther Brown summarized its impact: “It’s one of the top reasons why clients select us.”

Another revealing case study comes from the Ford Motor Company. Jim Lollar is business systems manager for Ford’s Global Warranty Operations. A 34-year veteran of the company, Lollar had seen Ford dealers wade through lengthy tables to determine how their warranty-claim practices compared to those of other Ford dealers. Lollar and Information Builders partnered to create an InfoApp called GWMS-EZ that provides intuitive charts and graphs which empower dealers to visualize and interact with warranty data that spans 15 years of history. Use of the system is not mandated, but enhancements to the app make it more attractive each year – new features such as ability to predict what each type of repair will cost before vehicles are brought in for service.

Dr. Rado Kotorov, VP product marketing, Information Builders
Dr. Rado Kotorov, chief innovation officer and VP global product marketing, Information Builders

I also asked Dr. Kotorov what he believed the leading inhibitors to growth are for analytics in general and Information Builders in particular. First in his view is organizational reluctance to wholeheartedly embrace data analysis: business intelligence and analytics has only a 22% penetration in most organizations. The second barrier is closely related: the shortage of skilled people, particularly in the first two categories referred to above.

In an interview run in industry magazine Dashboard Insight several years back, Dr. Kotorov was optimistic about where business intelligence was going. “There will be a drive for adoption as we begin to see a generational shift in the workplace.” He described the younger generation (Gen X, Y, millennials) as much more receptive to business intelligence, and as their influence has grown, so too has adoption. A Harvard Business Review article from 2012 by Davenport and Patil described “Data Scientist” as “The Sexiest job of the 21st Century”. Today, market watchers and forecasters typically include analytics within a group of technologies – cloud, security, mobile, cognitive computing – that are leading the growth charts.

The authors have aimed this book at their customers and prospects, but students and prospective IB employees will also acquire important information from its reading. With all the hiring that is anticipated for the analytics arena, I urge HR and recruiting professionals to consult this book for a clear explanation of what analytics specialists actually do, and do not do.

I am pleased to hear that the authors are already thinking about the second edition of this book. One improvement will be the inclusion of more case studies, from across more industries and more geographies, which outline more applications of analytics. Two other topics, not covered in this first edition but which the authors are knowledgeable on, would be worthy of more detail: dashboards, the dynamic visual representations of the application of analytics, and the certification of data scientists and analysts, the basis for a consistent education and accreditation program to advance the field of analytics.


(There will be a virtual launch of the book on Thursday, October 6 at 10 am EST. Anyone interested in joining in can go to and sign in to the Analytics stream and search the calendar.)