L.A. Lakers Visualization: R Code Plus Illustrator for the Win

I am a huge Los Angeles Lakers fan since I grew up on the West Coast; I lived in Los Angeles for a year and Las Vegas for many years as a kid. Magic Johnson and the “Showtime” squad of the 80’s will always be the best team dynasty in NBA history in my rather biased opinion. I wanted to make a visualization using base R code to plot a bar chart of Lakers wins by season and then use Adobe Illustrator to complete the effort. Using a .csv data file from Basketball-Reference.com I was able to tell the story of the franchise in an easy to comprehend visualization. I love bringing data to life and making it tell a story!

Laker Wins By Season

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Lessons from the Japanese Auto Industry

I spent seven years working at Saturn Corporation which was a truly innovative automotive company. Unfortunately, to the chagrin of Saturn-philes, the subsidiary suffered from a lack of sufficient investment from its parent entity, General Motors. Sadly, the defunct Oldsmobile brand was the recipient of funding that should have been allocated to Saturn but I digress. As an automotive industry veteran (albeit on the I.T. and data side of the house), I enjoyed discussions during my days in business school that focused upon the strategy of companies operating within the industry. In an MBA class titled Managing the Resources of Technological Firms (offered at Georgia Tech), our readings concentrated on the challenges associated with managing a firm’s resource capabilities for long-term competitive advantage.

On such article typifying the aforementioned concentration was written by business historian Michael A. Cusumano. In his article Manufacturing Innovation: Lessons from the Japanese Auto Industry which appeared in the MIT Sloan Management Review, Cusumano sets out to debunk the fact that higher productivity amongst Japanese auto firms is a result of the employment of Japanese workers. He aims to illustrate that the merits of innovative processes are the cause for higher productivity emanating from Japanese owned firms.

The article is in essence a summarization of major findings from a five year study of the Japanese auto industry focusing particularly on Toyota and Nissan. It states that some observers of Japan have assumed that Japanese firms copied US manufacturing techniques and then benefited from a better educated and more cooperative workforce. Cusumano attacks this perception by commenting that Japanese run factories located in the United States have demonstrated higher levels of productivity, quality and process flexibility than their domestic counterparts.

Japanese firms who shunned US or European production techniques were able to innovate and improve upon their native processes. Toyota in particular avoided conventional production techniques and decided to focus on developing a tailored system that met the needs of the Japanese market. Other Japanese firms such as Hino, Daihatsu, Mazda and Nissan started to leverage the techniques employed by Toyota and moved away from the US/European traditional process. Toyota and Nissan appeared to have matched or surpassed US productivity levels by the late 1960’s even though their production levels were far less than US automakers.

Cusumano does not share the Boston Consulting Group’s assessment that Japanese management’s emphasis on long term growth in market shares led to an accumulation of experience. He believes that that the emphasis on the accumulation of experience and innovation led to the rise in market share.

Toyota’s legendary Taiichi Ohno realized that firms needed to be flexible when producing small volumes. Three basic policies were introduced during post war Japan’s auto manufacturing era. Just in time manufacturing reduced buffer stocks of extra components and this small lot philosophy tended to improve quality since workers could not rely on extra parts or rework piles if they made mistakes. The second policy was to reduce unnecessary complexity in product designs and manufacturing processes. Nissan and Toyota standardized components across model lines. The third policy involved a Vertical “De-Integration”. In essence, automakers began to build up a network of suppliers for outsourced component production.

US companies stopped innovating by the early 1960’s as they perceived the domestic auto market as mature. The “American Paradigm” from an automotive production standpoint meant large production runs, worker specialization and statistical sampling. The unique market conditions of Japan after WW2 presented an opportunity for Toyota and other producers to challenge convention and become more efficient at much lower levels of production.

Image courtesy of winnond at FreeDigitalPhotos.net

Visualizations with R and Adobe Illustrator

I’ve been reading Visualize This by Nathan Yau to better understand visualization concepts. The book provides some direction regarding how to begin graphing data in R and then touching up the graphics in Adobe Illustrator. Here are a few visualizations I was able to create with some basic knowledge of R code and Adobe Illustrator. Nathan’s book provides most of the R code but the Illustrator portion took some work to get just right.

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Billboard Hip Hop Chart Visualized 1989-2015


I enjoy a great work of visualization and this interactive data graph by Polygraph charting the top 10 Billboard hip hop hits from 1989-2015 is phenomenal. The number one song in the list plays until it is supplanted by the next number one chart-topping song.

For someone like me who grew up in the 90’s and listened to the golden age of rap music, this graph is a very enjoyable walk down memory lane conjuring up mental images of high school, college and enjoyable times thereafter.  I can pinpoint where I surrendered my knowledge of mainstream hip hop as it ceded to the tastes of a younger generation (around 2011). Enjoy the link:


Enterprise Architecture Best Practice: Communicating & Quantifying Value

One of the common threads that I have come across while researching Enterprise Architecture with respect to its rollout and adoption within organizations is the importance of communication and value quantification.

Many cases studies have hammered home a common theme that communication is a critical success factor in EA engagements. Particular EA challenges include working with a wide assortment of stakeholders who are unfamiliar with EA and how it adds value. A successful EA implementation and adoption depends upon stakeholders having an understanding of how EA adds value.

Bernard, (2012) asserts that translating value to the bottom line is a major concern for key executives and line of business managers with respect to an EA program.  I believe that his list of quantifiable benefits would shore up any “marketing” plan for EA implementation. Blosch (2012) states that EA is quite frequently new to many business executives and that these executives often need help to understand the value that EA is adding. Articulating the value proposition of EA is paramount and the ten benefits as paraphrased from Bernard (2012, pgs. 72-74) are as listed below:

Shortening Planning Cycles: The EA repository provides a wealth of information that is already preassembled for strategic planning or BPI (Business Process Improvement) activities.

More Effective Planning Meetings: EA can help reduce uncertainties by providing a common baseline.

Shorter Decision Making Cycles: A majority of strategy, business and technology information is already pre-vetted and assembled thereby abbreviating the decision making process.

Improved Reference Information: Reference data is gathered using a standardized methodology that lends itself to practicable storage on the EA repository; thus data mining and business analysis capabilities are enhanced.

Reduction of Duplicative Resources: EA enables current enterprise resources to be inventoried and then subsequently analyzed for value overlap and performance gaps.

Reduced Re-work: Greatly reduces potential for individual program level initiatives, which typically involve duplicative processes and implementations if not crafted in sync with an overarching strategy.

Improved Resource Integration and Performance: Resources are planned and utilized on an enterprise-wide basis thus promoting enterprise wide integration. Future state requirements are compared to current state requirements to identify performance gaps.

Fewer People in a Process: EA supports BPR (Business Process Reengineering) and BPI (Business Process Improvement), which can lead to streamlined processes.

Improved Communication: An EA approach helps to reduce misunderstandings and potential rework via a common language of the business.

Reduction in Cycle Time: EA facilitates the capturing of “Lessons learned” from completed projects. These lessons can then be reapplied to future projects making implementation more effective and efficient.

With these ten quantifiable benefits of EA in hand, EA practitioners should work to communicate the benefits of EA to the organization as a whole. Concentrating on gathering executive level support is another key to initial organizational or line of business adoption.  In turn, executives must remain actively engaged in showing their support. They should also communicate expectations that the business should participate in the burgeoning EA or any other process improvement initiative.

Doucet et al (2009 pgs. 460 – 465) describe the AIDA (Attention, Interest, Desire, Action) method that is commonly used in advertising to sway behavior. A marketing communications model is used to push the EA from a level of Unawareness to full Adoption. The full six communications objectives are as follows: Unaware, Awareness, Interest, Desire, Action and Adoption.

At differing stages of the objectives, different communication approaches are employed. In the earlier Unaware states, more broad based statements about EA benefits and effectiveness are communicated. As the objectives move closer to the adoption stage, the details on EA become more focused until actual benchmarks, touchstones and guidelines are shared for full adoption.

In a similar manner, the “Coherency Management State” of an organization ranging from Level 0 (Absent) to Level 5 (Innovating) will dictate communication objectives (Doucet et al., 2009. Pg. 465).

  • Level 0 (Absent): Recognize the importance and create awareness of EA.
  • Level 1 (Introduced): Find an isolated application of EA and encourage use elsewhere in the organization
  • Level 2 (Encouraged): Reinforce and promote values and practices
  • Level 3 (Instituted): Widen the adoption
  • Level 4 (Optimized): Communicate results and organizational wins achieved through EA
  • Level 5 (Innovating): Maintain sustained interest in continuous improvement

Blosch (2012, pg. 10) promotes the idea of recognizing and measuring the impact of a communications strategy to make sure that it is having the desired effect.

Quantitative Measures:

·      Timeliness of communications

·      Production to plan

·      Readership statistics

·      Amount of feedback

·      Number of communications sent out by channel

·      Access and use of EA artifacts


Qualitative Measures

·      Feedback from stakeholders

·      Assessment of stakeholders perception of EA

·      Adoption of EA, where and how widely it is being use

Marketing the EA program with a credible list of quantifiable benefits and paring that list with a robust, well thought out communications strategy should greatly support adoption and diffusion of EA throughout the organization.


Bernard, Scott A. (2012). Linking Strategy, Business and Technology. EA3 An Introduction to Enterprise Architecture (3rd ed.). Bloomington, IN: Author House.

Blosch, M (2012, August 16). Best Practices: Communicating the Value of Enterprise Architecture. Retrieved from Gartner.

Doucet, G., Gotze, J., Saha, P., & Bernard, S. (Eds.). (2009) Coherency Management (1st Ed.). Bloomington, IN: Author House.

Image courtesy of Stuart Miles at FreeDigitalPhotos.net