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Marketers: What’s Your Fastball? What’s Your Curve Ball?

With Opening Day at Fenway Park just days away, I want to share a great blog article with a great baseball story that has stuck with me for a long time. That story also nicely complements some very good marketing advice from a friend of mine.

Steve Dalkowski. Source: SportsHollywood.com
Steve Dalkowski. Source: SportsHollywood

Writing for the Kalido (Magnitude Software) blog, Mike Wheeler introduced readers to Steve Dalkowski, probably the fastest pitcher in baseball history, whose fastball was routinely well over 100MPH, with top speed estimates as high as 125MPH. Dalkowski struck out 1,396 batters in just 995 minor league games in the late 50’s and early 60’s.

Unfortunately, Dalkowski’s incredible fastball was also incredibly unpredictable: He also walked 1,354 batters and won only 46 of the 236 games he started.

Mike Wheeler’s key point was that focusing on raw speed at the expense of reliability is a bad combination, whether you’re talking about a super-fast pitcher with no ball control, or super-fast data delivery without any data governance controls.

But there’s much more to Steve Dalkowski’s story – with a related marketing lesson as well.

Steve Dalkowski’s performance improved dramatically in the early 60’s while playing for Earl Weaver, then manager for the Baltimore Orioles’ double-A affiliate. In 1962, Dalkowski had the best year of his career, giving up less than one walk per inning for the first time, and a 52-inning stretch with an amazing 104 strikeouts and only 11 walks. During 1963 Spring Training, after pitching six straight hitless innings in relief, Dalkowski was told by the Orioles that he had finally made the team.

How did Steve Dalkowski finally improve his performance? Earl Weaver discovered Dalkowski had a low IQ; he’d merely get confused and distracted when coaches tried to teach him how to throw a change-up, hold a base runner, execute a pitch-out or other unfamiliar plays. Weaver concluded if the team was to ever capitalize on Dalkowski’s potential, he would have to keep things very simple. So Weaver had Dalkowski focus on nothing but throwing his fastball and an occasional slider. Two pitches. Just throw strikes. Earl Weaver probably didn’t think of this plan in business terms, but his coaching decision was certainly a wise application of the good old 80/20 Rule.

Keeping it simple is game-winning advice for marketers as well. No, not because your prospects have a low IQ! – very funny😉 Seriously, buyers are smarter than ever, but they are also very unlikely to bother trying to figure out on their own what your technology does. If they get confused or distracted by your message, they’ll simply move on.

Source: iStockphoto

Which leads me to that advice from my marketing friend. He was good friends with a rock star technology sales manager who explained his success by saying, “I know my fastball and I know my curve ball.” His ‘fastball’ was the #1 product of interest to the vast majority of his prospects; his ‘curve ball’ was his second product. Whether he opted for the fastball or curve ball depended on the needs of his prospect.

The company had other products, of course; and while he didn’t totally ignore those products, he knew his ultimate success depended on his ability to deliver a clear, compelling sales pitch for his top two products – his fastball and curve ball. So he focused right away on practicing those two sales pitches and made sure they were strikes.

While my friend’s rock star sales friend described his fastball and curve ball as being two different products, the logic still holds for other scenarios. If, for example, a company offers a single technology platform or solution as opposed to multiple products, then the “fastball” could be an engaging value proposition to answer the question, “What is it?” The “curve ball” could in turn succinctly answer, “How does it work?”

Marketing’s single most important responsibility is to define the company’s fastball and curve ball and then clearly communicate it – internally and externally – to set up your marketing campaigns and sales team for success.

In a cruel twist of fate, Steve Dalkowski severely strained a tendon in his elbow while pitching relief in the Orioles’ final 1963 pre-season game. With his post-injury fastball topping out at only 90MPH, Dalkowski never made it to the major leagues again and was out of baseball for good in 1966. One can only wonder what his pitching career might have been had he not languished for years, no doubt being constantly told to “try harder” before Earl Weaver’s wise leadership guidance.

Similarly, if current marketing messaging is not working, “trying harder” in a multitude of ways and directions with the same overall messaging will not help and instead merely waste time. The future is now. Business circumstances and technologies all change without advance notice. Marketing leaders must be willing to allow trying something new, starting with, I suggest, focusing on answering two simple but critical questions…

What’s your fastball?

What’s your curve ball?

 

 

“Begin with the Beginning in Mind” for Content Creation

Many people are familiar with Stephen R. Covey’s “7 Habits” (although I much prefer Dale Carnegie), one of which is to “begin with the end in mind.” But when crafting product messaging, I suggest you “begin with the beginning in mind.”

When writing a datasheet, web copy, case study or other collateral piece, I start by thinking about what the first paragraph should say that will make the reader want to keep reading and learn more. For a new website, I think first about what the home page splash screen should say and what graphic should accompany it.

If that first impression message is not compelling, your audience will most likely tune out rather than bother to continue paying attention.

For a presentation deck, I like to define a really good “icebreaker” slide first before anything else. It might be a compelling – even alarming – stat with a strong supporting graphic. It can be a quick story or interactive game, as long as it is directly relevant to your presentation. I once attended a breakout in which the presenter led off with an awkward “tell to your neighbor something interesting about yourself” exercise that had nothing to do with his chosen topic. It merely distracted the audience from his presentation.

My friends and colleagues know I generally like to go with humor; for example, I recently led a presentation on replacing expensive commercial software with reliable, supported open source technology. My icebreaker slide was this excerpt of a classic Calvin & Hobbes comic strip. I wanted to convey, in an engaging way, the core message that no one likes to feel like they’re being ripped off, forced to pay too much for something, and not being treated fairly… and that includes paying too much for commercial licenses with pricing accelerants and legalese intended to lock in their customers. Notice too how Moe, the bully shaking Calvin down for a quarter, is now in the minds of the audience as a symbol for their unrepentantly high-cost commercial software vendor taking too much of their money.

From that intro, slides presenting the proof points for smart and substantial open source savings and how to get started flowed naturally from that icebreaker.

“Begin with the beginning in mind” also applies to demand generation emails. Even before the intro paragraph, come up with the subject line. I have received three emails in a row from a vendor, each with the same bland subject line of “[Company Name] Newsletter — New e-Book”. I can’t imagine the open rate for these emails is anywhere near acceptable. I don’t accept the notion that email marketing is dead; only that poor email marketing is dead. During the company’s recent Boston World Tour stop, Salesforce.com agreed. Going beyond A/B testing, SFDC proceeded to present new features to make it easier to personalize email subject lines to optimize engagement as soon as the email hits the inbox. Begin with the beginning in mind.

As frustrating as it is, if the beginning of your message is not engaging, the end and middle of your collateral, no matter how fine, scarcely matters. But if you spend the extra time up front by beginning with a great beginning, a great introduction, you’ll find the rest of your message will flow from there much more easily – and your target audience will be much more willing to receive it and act on it.

Intuitive Reasoning, Effective Analytics, Success: Lessons from Dr. Jonas Salk

Jonas-Salk-MemeApril 14, 2015 marks the 60th anniversary of the Salk Polio Vaccine. On that day in 1955, it was publicly announced that human trials confirmed Dr. Jonas Salk’s vaccine provided effective protection from the polio virus. By 1957, new polio cases fell by 90% from epidemic levels just five years earlier.

A fascinating interview with Dr. Salk on the Academy of Achievement website sheds light on his key personal attributes and values, which are vitally important for success in any line of work. And the best analytic tools will play a leading role in fostering that success.

1. The most successful people practice intuitive reasoning.

Dr. Salk explained how he could identify and solve problems more easily and effectively than others by following his intuition (perceptions, spontaneous creative thought), guided by reason (hard data).

Reason alone will not serve. Intuition alone can be improved by reason, but reason alone without intuition can easily lead the wrong way… both are necessary. For myself, that’s how my mind works, and that’s how I work… It’s this combination that must be recognized and acknowledged and valued.

In fact, it was Salk’s intuitive reasoning that ultimately led him to his polio vaccine research. Several years prior, as a second year medical student, Salk realized statements from two lectures on immunization techniques contradicted each other. He never got a straight answer as to why, which he (thankfully) could not accept:

It didn’t make sense and that question persisted in my mind… I just questioned the logic of it… I just didn’t accept what appeared to me to be a dogmatic assertion in view of the fact that there was a [medical] reason to think otherwise.

Intuitive reasoning requires not taking “because it is!” as an answer, and “actively pursuing a question and seeing where it leads.”

2. Emotional Intelligence is more important for intuitive reasoning than traditional skills or knowledge.

To view any problem or challenge from a different perspective can be a lonely task. It takes a high EQ to be willing to be a contrarian. Check out this clip from Brain Games (National Geographic TV) on peer pressure. It’s amazing how people are so willing to go along to get along:

To perceive something differently or even to know something as being true is of little or no value if you’re not willing to stand apart from the crowd.

It’s very clear from his interview this was never an issue for Dr. Salk. He was extraordinarily thick-skinned, and had an exceptionally healthy attitude regarding criticism and rejection. And yet, he was fully willing to follow the hard road necessary for a new truth to be recognized and accepted. People lacking these high-EQ attributes are unfortunately likely to keep intuitive reasoning to themselves or just give up.

3. The best analytic tools will directly empower those with high intuitive reasoning, who probably will not have formal data science skills.

Dr. Jonas Salk was not a scientist. Wait, what?  He explains (emphasis added):

I entered medicine with the idea of bringing science into medicine… I was not trained as a scientist. I was trained in medicine. And, so my functioning… as a medical scientist came through being self-taught through the experience of investigating the questions that were of interest to me.

Combined with his strong sense of intuitive reasoning, Salk’s unique background as a self-styled medical researcher contributed greatly to his ability to dramatically advance viral research beyond what other scientists could see:

Instantly I saw that there were more efficient ways of typing viruses than were proposed by those who set forth the protocol that I was supposed to follow… I saw the world differently, [and so] I could make things work more efficiently and effectively… It became obvious to me that we had the ways and means for moving ahead toward [polio] vaccine development.

One conclusion I draw from Dr. Salk’s experience is that the greatest insights, advances and innovations using big data will come from people with unique subject matter expertise and high intuitive reasoning skills – enabling them to “see” challenges very differently. And they will probably not be formally trained in data science or programming.

There’s evidence of this trend already: The New York Times recently reported how genetic scientists have turned to Daniel Kohn, a Brooklyn-based painter and conceptual artist, to help them rethink how to render their data to discover patterns that would otherwise remain hidden.

And a recent MIT Sloan Management Review article noted that while analytical techniques are becoming commoditized, the ability to identify new ways to put analytics to actionable use will become increasingly valuable. As an example, the article mentioned a research analyst with a library science degree who went back to school, not for data science, but rather to learn sufficient analytical skills to empower her to leverage her SME.

The best technology tools, therefore, will be those that empower subject matter experts to quickly apply intuitive reasoning:

  • Data visualization and advanced analytics that do not require programming or advanced technical skills
  • Data integration and workflow tools to rapidly infuse existing data sets with new, untapped data sources that enable a more complete analytic picture – again with no programming required
  • Agile application development tools that shield the user from coding, data connectivity and other programming challenges
  • Tools for predictive analytics that support intuitive reasoning as to what data attributes and other conditions will impact future performance

I’d like to end here by giving Dr. Salk the last word. His comments on the need for discovering wisdom from huge volumes of knowledge is truer now than when he said them in 1991:

At one time we had wisdom, but little knowledge. Now we have a great deal of knowledge, but do we have enough wisdom to deal with that knowledge? I define wisdom as the capacity to make retrospective judgments prospectively. I think these are human qualities, human attributes that need to be brought out, need to be drawn upon, need to be valued.

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You Do Not Need Permission to Innovate

Bootleggers K turnA recent blog post by Brooke Allen described a meeting he had with an ex-Prohibition era bootlegger, who explained the “bootlegger’s K-turn,” a driving tactic used by bootleggers to escape hot pursuit by police.

Brooke’s encounter with that ex-bootlegger also included a key life lesson that served him well throughout his business career.

When FDR brought an end to Prohibition, that bootlegger – Allen called him “Jeb” – had to find new work. Jeb finally found a mundane job working as a factory drill press operator. To deal with the monotony, he’d think of different ways to improve the drill press. Finally he mustered up the courage to ask the factory owner if he could share his ideas:

After a few years he screwed up the courage to ask the owner, “May I ask a question?”

The owner laughed, “You don’t need permission to ask a question.”

… It turned out Jeb’s idea made the drill-press much more efficient. Jeb was about to go back to work when the owner said, “Why don’t I put you on another machine and let’s see what you come up with.”

In short order he’d invented all kinds of better ways of making things and soon he was even inventing whole new things to make. The owner gave him piles of money and Jeb was very happy.

“I never asked for permission to be a bootlegger because I knew it was the wrong thing to do,” Jeb told Allen. “But, I didn’t become inventive until I learned that I don’t need permission to do the right thing.”

Brooke Allen took away this key life lesson: You do not need permission to do the right thing. Knowing this simple fact is essential for any true innovation to take place. Innovation, by definition, is an act of “intelligent disobedience.” It is unafraid to question the status quo; it unashamedly asks, “What if…?”

I’d also add a big thumbs-up for the factory owner who had the sense to not only listen to Jeb’s idea, but to also encourage Jeb to discover new ideas and share the financial rewards with him. The owner demonstrated business sense that is lacking in too many corporate “leaders” today.

An empty suit of a “leader” probably would just used Jeb’s first idea to make or save money without even a thank you (just like this example); or simply shooed Jeb back to his drill press with a “We don’t pay you to think!” or some other jerk statement.

Poor leaders can go a very long way to discourage innovation; however, that doesn’t change the fact that you don’t need permission to innovate. Lousy leaders who think nothing upsets the status quo without their blessing are kidding themselves. Under their noses, innovations are taking place in the form of secret skunkworks projects, workarounds and hacks that enable workers to sidestep red tape and self-important gatekeepers while also keeping their personal sanity!

Gatekeepers and Workarounds

Now imagine how well such a company could perform if innovation wasn’t driven underground by its own “leaders.”

Bottom line, you do not need permission to freely assess the way things are and envision the way things could be. Recognizing this universal truth might be the bootlegger K-turn you need to make a clean getaway from an innovation-hostile, “potted plant” organization and towards organizations and true leaders that actively encourage and reward innovation.

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When All You Have is an Analytic Hammer, Does Every Business Problem Look Like a Nail?

I found the wording of this tweet and article summary interesting: What HR “problems” and “organizational changes” will IBM “solve” with analytic software?

From the Washington Post article (emphasis added):

[IBM] unveiled several new technology services that would apply big data and analytics processes to human resources problems. 

One service, predictive hiring, would use large volumes of behavioral assessments and other employee data to better understand the traits that are characteristic of top performers, and then comb through candidates to identify potential hires. A predictive retention service would analyze workforce data — exit interviews, for instance — to identify those employees most likely to leave.

What strikes me here is the apparent assumption that job applicants bring high-performance traits with them through the door, or they don’t. Period. Color me skeptical of that assumption – and whether big data analytics is even the right tool here.

It sounds like an example of Maslow’s law: If all you have is a [analytic] hammer, every problem will look like a nail.

"We need more people like... us!" Mad Men photo via CNET
Confirmation bias: “We need more people just like us!Mad Men photo via CNET

First, the analytics themselves described in the article seem logically flawed, based on a read of David McRaney’s blog-turned-book You Are Not So Smart.

For example, since existing leaders will largely decide what the attributes of top performers are, they might well end up defining the ideal employee profile in their own image (confirmation bias)!

And analyzing the traits of perceived top performers who have a long history with the company runs afoul of survivorship bias:

You must remind yourself that when you start to pick apart winners and losers, successes and failures, the living and dead, that by paying attention to one side of that equation you are always neglecting the other…

[For example,] when a company performs a survey about job satisfaction the only people who can fill out that survey are people who still work at the company. Everyone who might have quit out of dissatisfaction is no longer around to explain why. Such data mining fails to capture the only thing it is designed to measure…

The reality is that workers’ attitudes in the workplace can and do change significantly over time in response to the organization’s own traits, for better or for worse, depending on whether the work environment is proactive or risk averse, collaborative or politically charged, collective or exclusive. And employees don’t need big data or predictive analytics to draw those conclusions.

Liz Ryan, former HR VP and founder of Human Workplace, hit that nail right on the head (bad hammering pun intended, sorry) in this article:

In order to hit our goals in any organization, we need to build positive energy in the workplace. We need people to be excited about their work… Anyone in your organization will be able to tell when the excitement level is high… low, or nonexistent…

Physicists proved a hundred years ago that energy moves in waves, and we see waves around us in the air and water. Still, we pretend that the workplace is a linear place made only of easy-to-measure particles… as though the waves aren’t there.

To her credit, Liz Ryan doesn’t pull any punches sharing her disdain for technocratic measurement of employee engagement (and by extension, performance). She calls for other much more effective ‘low tech’ methods:

If we really care what our employees think, it’s easy enough to find out… We could ask them how they’re doing… We all have enough creativity and intelligence to move our organizations without unnecessary, fear-fueled micro-management practices…

The more formal, rigid and hierarchical an organization, the less easily waves of energy and trust will flow… Give up the Employee Engagement survey, drop the junk-science patina on stupid HR practices and learn how to be human at work. You’ll be amazed how the team’s energy will power your success once you let it start flowing.

Business intelligence, when created and used appropriately, can be a powerful force for success. But analytics are not the only arrow in the technology quiver. New tools such as gamification platforms actively engage employees and helps cultivate employee positivity and productivity. For just one example right here in Boston, the WeSpire platform engages and energizes employees around company sustainability and social responsibility programs.

Making a conscious, personal effort to build an energetic, collaborative work culture should yield much better employee outcomes than passively poring over predictive analytics based on past history and potentially flawed assumptions. “The best way to predict the future is to create it” is an old saw, but one that still rings true when considering the right actions and technologies to improve employee performance and successful hiring.

Five Years On: Innovation as a Driver of Good Business and Social Good

I recently revisited this article, among the first I wrote for this blog back in early 2009. America and the world was still reeling from an unconscionably cratered economy; and yet, there was substantial optimism that the global economy – as well as global society and well-being at large – would recover and become stronger. That optimism has since been proven to have been on the mark.

Now more than ever five years later, the advancement of global business and global civilization are increasingly viewed as intertwined and no longer commonly regarded as mutually exclusive. With that in mind, it is even more gratifying to look back at this write-up (which I have since refreshed and updated just a bit) on Bentley University’s 2009 Leadership Forum: The Business of Healing Our World – a special event to promote and encourage business initiatives and innovation, to quote Gloria Larson, Bentley University president, “that are both good for business and the broader social good.”

Read the complete article.

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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”!

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Not Every Picture Tells a Story: Keys to 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 storytellingPanorama Software has just recently launched Necto 14, the newest version of its business intelligence software. In addition to many other new features, the company describes Necto 14 as being “visual, using infographics, graphic visual representations of information, to present complex information quickly and clearly; creating business stories that every business person can understand” (emphasis added).

I find this messaging to be exciting as well as timely, as I believe BI systems have not done nearly enough to enable business storytelling. But that should change in 2014, as BI author and thought leader Cindi Howson recently wrote:

The concept of storytelling is increasingly appearing in BI products whereby information and analyses are presented to support a decision-making process, a bit like PowerPoint.

Watching the Necto 14 online demo, I found some of the sample infographics told stories better than others. For example, does the following infographic-style chart quickly convey its intended business story(ies) more effectively than a more common variety of chart or data visualization? What do you think?

necto-demo

Regardless of your BI presentation solution of choice, it’s important to note that “business storytelling” is not synonymous with “infographics” or “data visualization”. BI tools can slice and dice data in a multitude of ways, but may not necessarily reveal any sort of causality. (More on this in a moment…)

Also, improving your 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 C. Redman recently wrote: “As Edward Tufte advises, label the axes, don’t distort the data, and keep chart-junk to a minimum.”

The next step Redman recommends is also very simple: annotate your charts. “While annotations do not replace a well-told story [told by a speaker in a live meeting], they do give the reader some inkling of what’s involved.”

Consider the “before” and “after” charts (below) cited by Redman in his article. The annotations in the second “after” chart go a long way to tell a story how the company’s efforts to improve customer data quality were successful, while still in the form of a basic chart:

Image

Image

Looking at Redman’s “after” chart annotations more closely, they 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 (in this case) a happy ending: a once-severe and pervasive customer data quality problem has been solved.

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

Perhaps you have seen Charles Joseph Minard’s incredible 1869 data visualization of Napoleon’s army in the Russian campaign of 1812. Minard was given the well-deserved contemporary recognition for this work by Edward Tufte in his acclaimed 1983 book, The Visual Display of Quantitative Information, noting “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, including the movements of Napoleon’s army over time across a map – 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 reaching -30⁰ F/-38⁰ C. Minard’s data sources are brought together in a very moving visualization that tells the tragic story of the total futility of Napoleon’s Russian campaign and the misery of his soldiers culminating in overwhelming casualties that wiped out the Grande Armee.

Fast forward to today: Big data infrastructures and analytics hold huge potential to not only visualize and tell the story of the loss of life from violent conflict in hindsight, but also develop narratives that prevent global violence in the first place. This vital global goal was outlined in a recent Foreign Policy article: Can Big Data Stop Wars Before They Happen? Author Sheldon Himelfarb cites three key trends justifying optimism that the answer will 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 his third observed trend may well be the most critical to developing a clear story based on the root human causes that fan the flames of world 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, storytelling that moves a business forward demands the same utilization of as many varieties of data as possible – structured and unstructured, internal and external. Doing so will require rapid, powerful data integration capabilities. This wider spectrum of highly diverse data sources must then be combined with clear, user-friendly data visualizations that convey understanding, empathy and a sense of urgency to take timely, opportunistic, successful action.