Les Paul’s Electric Guitar & Unified Information Access: Two Platforms of Innovation

Les Paul. Source: Rock & Roll Hall of Fame

Without Les Paul (1915-2009), it’s safe to say that rock and roll as we know it would not exist. Inducted into the Rock and Roll Hall of Fame in 1988, Les Paul was a virtuoso guitarist and pioneer in the development of the solid-body electric guitar. His innovations helped make the unforgettable sound of rock and roll possible.

There are some interesting analogies between Les Paul’s modern electric guitar, which ushered in a new era of modern music, and unified information access, modern technology enabling a new era of deeper analytic insights well beyond what traditional tools can offer.

Early in his musical career, Les Paul found his acoustic guitar was drowned out by the other instruments in a band. The acoustic guitar was simply too quiet. In its own way, text-based unstructured information (documents, wikis, email, social media) has also been too “quiet.” Quickly drowned out by more easily accessible structured databases, unstructured content was largely ignored by data analysts for decades.

Early efforts to use a microphone or an amplifier with a hollow-body acoustic guitar in Les Paul’s day resulted in poor sound quality and feedback. Similarly, unstructured content also defied initial efforts to integrate it with other information sources, such as trying to store it within relational databases. Unfortunately, most database methods do not perform full-text searching of content, and those that do require the content to be stored and organized in database tables. Effective textual searching requires linguistics and text analytics is commonly found not in relational databases, but in enterprise search technologies.

The methods for accessing unstructured content and structured data remained divided for decades: enterprise search engines being used for finding unstructured content and relational database systems for retrieving structured data.

Applying his musical talent and inventor’s mind, Les Paul built one of the very first solid-body electric guitars, culminating in 1952 with the classic Gibson Les Paul guitar. Thanks in large part to Les Paul, the guitar was definitely no longer the quietest instrument in the ensemble!

Les Paul with his Gibson Les Paul solid body electric guitar and 8-track tape recorder. Source: les-paul.com

Between his electric guitar and breakthroughs in multi-track sound recording, Les Paul created a platform of innovation that enabled entirely new types of musical expression that were previously impossible. Indeed, the Rock and Roll Hall of Fame rightly honored Les Paul as an architect of rock music.

Similarly in the business world, we have seen unified information access – a new technology platform of innovation – enable new ways to inform, educate and entertain people, through a single interface, portal, website or device, replacing what used to be dozens of individual products or standalone software packages.

UIA is helping transform businesses by freely integrating, joining and presenting all related enterprise information – structured and unstructured, internal and external alike – and building amazing new business applications no one has ever seen before.

Breaking the “Curse of Too Much Knowledge”

A great passage from Jeffrey Fox’s best selling first book How to Become CEO has stuck with me over the years. Fox recounted how one of the U.S. automakers, desperate to improve gas mileage during the 1970s energy crisis, called on its engineers to redesign its cars to be less heavy. But veteran engineers insisted that just couldn’t be done. Doing so, they said, would be unsafe, impractical and impossible. Of course, they were wrong.

The automaker brought in recent engineering grads with less experience, who proceeded to shed hundreds of pounds off the cars with no adverse safety impact. The new engineers were successful because they were not constrained by preconceptions; they didn’t “know enough” to conclude the task was impossible!

The Man Who Knew Too Much (classic 1956 Alfred Hitchcock film)This story is a great example of what my business friend and colleague Neil Baron calls “the curse of too much knowledge.”

Neil Baron is managing director of Baron Strategic Partners, a business management consulting firm with experience in developing value propositions. I have known Neil for a few years now and have enjoyed many of his presentations at past ProductCamp Boston and Boston Product Management Association (BPMA) events.

At his recent Creating Compelling Value Propositions workshop, Neil said the ‘curse of too much knowledge’ is a major inhibitor to successfully creating a value prop that resonates with prospective customers:

A big challenge is that we assume that our customers know as much as we do about the product. Our own knowledge gets in the way. Companies have an advanced understanding of the technology because they live with it every day. Customers, even those with PhDs, are not at the same level of expertise. This makes it hard for vendors to relate to their customers. It is nobody’s fault. It is just how our brains are wired.

Neil then offers a solution which happens to coincide very closely with how that US automaker lightened the weight of their cars:

Often the problem of too much knowledge can best be addressed by bringing in an someone who does not have the same level of knowledge as your team… The key is that they have the ability to question your assumptions about your product and your customer. (emphasis added)

This is very similar to advice from Michael Roberto’s book Know What You Don’t Know (a longtime favorite of mine that I happened to recently turn Neil on to as well!). In his book, Michael Roberto agrees with Neil that managers need to “seek out the youngest and the brightest inside and outside the organization” to “gain access to a different worldview” about your products and markets. And these two additional suggestions to get unfiltered points of view appear particularly relevant to breaking the curse of too much knowledge:

  • Seek-out-unfiltered-information-go-out-to-peripheryGo to the periphery. Communicate with co-workers in distant geographic regions, units exploring new technology and groups or ventures outside of the firm’s core market. Focus on the disconnects between what people living your products every day versus the “periphery” of the business.
  • Talk to the “nons”, as in speaking with non-customers, non-employees and non-suppliers; those who do not interact with the company, whether for a particular reason (why?) or simply being unaware of your organization. What are their reactions to your product and value prop? Do they “get it” and express some interest in it? If not, why not?

Neil Baron offers a very thorough process in his value proposition workshop to overcome the curse of too much knowledge using tools and techniques based on cutting-edge brain science from MIT. Similarly, Michael Roberto’s book also addresses the root causes of barriers to getting fresh, unvarnished perspectives on products and customers, some of which also involve brain science (confirmation bias) and others rooted in the unfortunate reality of “palace politics” (pressure to conform; advocating for one’s own best interests).

A clear first step forward is to simply accept the paradoxical notion that we as product marketers and product managers just might not “know what we don’t know,” while at the same time “knowing too much”!

If you liked this article, you may also like:

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Product Managers & Marketers Should be “Intelligently Disobedient”

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Using Business Intelligence for Effective Business Storytelling

An appropriately told story has the power to do what rigorous analysis couldn’t: to communicate a strange new idea and move people to enthusiastic action.

~  Steve Denning, “The Leader’s Guide to Storytelling”

Business storytelling, campfire optional

“…And my phone log analysis proved the calls were coming from INSIDE THE HOUSE!!”

The most successful business intelligence professionals are also great storytellers. Regardless of your BI tools of choice, it’s important to note that “business storytelling” is not synonymous with infographics or data visualization. Every analytic tool can slice and dice data in a multitude of ways, but, of course, correlation is not causation. (More on this in a moment…)

Also, effective business storytelling does not necessarily require advanced data visualization tools. Any organization can take a the first step towards better storytelling by following universal best practices when creating even the most simple chart. Data consultant and author Thomas Redman recently wrote: “As Edward Tufte advises, label the axes, don’t distort the data, and keep chart-junk to a minimum.”

Redman’s next recommendation is also very simple: annotate your charts. “While annotations do not replace a well-told story, they do give the reader some inkling of what’s involved.”

Take a look at the “before” and “after” charts cited by Redman in his article. The annotations in the “after” chart tell a story how the company successfully improved customer data quality were successful, all in a very simple line chart:

Image

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The chart annotations (above) are not just helpful notes; they also comprise a second set of data (the key milestones of the company’s data quality program – by month), correlated with the monthly data quality measures. As a result of this data correlation, a time series cause-and-effect story emerges, complete with a beginning, middle, and a happy ending.

This leads to a key point: the most compelling business stories present strong correlation-causation relationships using many disparate yet complimentary sets of data.

Perhaps you have seen Charles Joseph Minard’s 1869 data visualization of Napoleon’s army in the Russian campaign of 1812. It was deservingly praised by Edward Tufte in his classic book The Visual Display of Quantitative Information: “It may well be the best statistical graphic ever drawn.”

Charles Josepn Minard's Chart of Napoleon's 1812 March to Russia (1861).

Source: Scimaps.org. Click map to view/enlarge image. See also: http://www.edwardtufte.com/tufte/posters

Minard painstakingly correlated multiple data sources: the movements of Napoleon’s army over time, their geographical location – marching to Moscow and then retreating from it – with the (rapidly narrowing) thickness of the line representing the number of Napoleon’s men, falling in battle as well as from deadly subzero temperatures that hit a low of -30⁰ F/-38⁰ C.

Minard then brought his many datasets together to very effectively tell the story of Napoleon’s futile Russian campaign and the misery of his soldiers, resulting in massive casualties that wiped out the Grande Armee.

Fast forward to today: Big data infrastructures and analytics hold huge potential to not only tell the story of the loss of life from violent conflicts of past history, but also in the future – by piecing together stories that help prevent global violence before it actually happens.

This critical world goal was covered in a Foreign Policy magazine article, Can Big Data Stop Wars Before They Happen? Author Sheldon Himelfarb cites three key trends justifying optimism that the answer will soon become a clear “Yes”.

First, Himelfarb points out the increasing amounts of data being generated by more and more people through digital devices; and second, our expanded capacity to collect and crunch data like never before. But the third trend he notes is the most critical to developing a clear story of human sentiment that can forewarn us of future violence:

When it comes to conflict prevention and peace-building, progress is not simply a question of “more” data, but also different data. For the first time, digital media – user-generated content and online social networks in particular – tell us not just what is going on, but also what people think about the things that are going on.

Excitement in the peace-building field centers on the possibility that we can tap into data sets to understand, and preempt, the human sentiment that underlies violent conflict.

Thankfully, the stories we want and need to tell in our respective organizations don’t fall into this same literal life-or-death category. However, all effective business storytelling requires the same two core elements:

  • Not just “more” data… Different data. Integrate of as many varieties of complimentary data as possible on the backend – structured and unstructured, internal and external. Doing so lets you present what has happened with strong correlation/causation, as well as enabling deeper advanced analytics (e.g., location-based, sentiment, predictive).
  • Clear, annotated, “junk-free” data visualizations. Combine and present your data on the front end as a compelling story that conveys understanding, empathy and a sense of urgency to take action.