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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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

Image

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.

Why the Question “Is Your Product a Vitamin or a Painkiller?” is a False Choice

I recently read an article posing the well-known sales question, Is Your Product a Vitamin or a Painkiller? by George Deeb. It’s a good reminder that it’s better to be selling a “painkiller” technology product that relieves acutely-felt, pervasive business problems, rather than a “vitamin” product that offers some lesser, more specialized value.

I agree with Deeb that it’s much harder to build a large, scalable business around vitamin products than painkiller products, but a product-as-painkiller is not the ultimate or best product offering either.

In other words, the question “Is your product a vitamin or a painkiller?” is a false choice – and businesses that rely on painkiller product revenue are at more risk than they might realize.

The issues of trying to sell a vitamin product are described quite well in Deeb’s article. But painkiller products have their own issues. For example, one of the most frequent and frustrating “competitors” to a painkiller product sale is “none of the above”. Much to many a sales manager’s chagrin, prospects often decide that while the business pain is real, alleviating it simply isn’t worth the effort, like Norm in this classic scene from Cheers:

Meanwhile, new enabling technologies march on: painkiller products that once required a huge capex for on-premise enterprise software, servers and services (CRM, marketing automation, legacy BI) are now offered inexpensively on a SaaS basis (SFDC, Marketo, GoodData) with more to come. More and more painkiller products are becoming available at lower “vitamin-level” cost and simplicity!

Another issue I have with painkiller products is they implicitly assume a business status quo. Consider Polaroid in the mid 90’s. Like so many other large companies, Polaroid jumped in with both feet into ERP, the ultimate painkiller technology of its time. Polaroid even won major awards for its SAP implementation. While Polaroid’s ERP no doubt lightened many operational pains by optimizing inventory, purchasing, quality control and such, meanwhile the company was failing miserably with new products and all but ignoring the deterioration of its instant photography market to digital cameras.

I recall reading a Polaroid executive praising the company’s new operational efficiency of its instant photography “core business.” Not long after, in 2001, Polaroid filed for bankruptcy, with most of that “core business” long gone.

Clearly, while reducing business “pain” is important, such efforts are no substitute for the ultimate purpose of a business, as memorably described by Peter Drucker:

There is only one valid definition of a business purpose: to create a customer… Because the purpose of business is to create a customer, the business enterprise has two – and only two – basic functions: marketing and innovation.

And for decades, business technology has focused on operational efficiencies instead of serving as new platforms for innovation. Again, quoting Peter Drucker:

For top management, information technology has been a producer of data [for operational tasks]… Business success is based on something totally different: the creation of value and wealth.

This requires risk-taking decisions… on business strategy, on abandoning the old and innovating the new… the balance between the short term and the long term… These decisions are the true top management tasks.

The technology products that will reap the greatest financial rewards will be those that address those “true top management tasks”: innovation that creates new business value and wealth; such as

  • Advanced analytic platforms that reveal all-new insights into markets, products, customers and competitors
  • Gamefication platforms that motivate employees, customers and partners to want to take actions that mutually benefit the organization, themselves and other stakeholders
  • Customer/prospect engagement technologies that personalize and optimize every experience with your organization, whether online or in-person, across all channels (particularly mobile)

Artwork by: BTimony (click to see original)These and other new technologies designed to enable innovation make up a third category of products that go far beyond painkiller or vitamin products.

So what should we call this third product category? Maybe… “steroids”? Nah, don’t think so…

Perhaps “miracle drug”? No…

What about… “Popeye’s Spinach”?!

What do you think?

How KM & Enterprise Search Help Collective-We Firms Eat Exclusive-We Competitors for Lunch

Poorly managed organizations are likely to function – or, I should say, malfunction – with frequent use of a divisive verbal tactic called the exclusive “we”. I suspect most business people can recall being on the receiving end of remark like this:

We don’t do things that way here.”
“Will you stop asking so many questions? We don’t tolerate ‘fishing expeditions’ around here!”

“I’ve been saying ‘We don’t do things that way’ so long, I’ve forgotten what we DO do.”
Image by HikingArtist.com (CC)

The speaker is clearly excluding the person being addressed from the pronoun “we” to stifle communication. This kind of non-communication is also a sign of a dysfunctional exclusive-we culture, in which information sharing is discouraged in favor of information hoarding. Exclusive-we organizations will struggle to so much as acknowledge business problems before they become undeniable crises, leaving managers in constant ‘fire-fighting’ mode. Hardly a recipe for business success.

Successful companies use the word “we” a lot, too – but in an opposite, winning manner:

“What should we be doing that we aren’t doing now?”
“These questions are important. We need to be able to answer them.”

What a difference! This time the speaker is invoking the collective “we” to equally include the person being addressed along with everyone else in the room, as well as everyone throughout the entire organization.

Leaders in highly successful organizations naturally speak and act from a collective-we perspective. Even better, they build a collective-we culture, actively encouraging and supporting information sharing and collaboration. Doing so transforms a company’s collective-we into a powerful company asset capable not only of quickly solving problems, but also proactively finding them – and, in the process, leaving the exclusive-we competitors in the dust.

Know What You Don't Know by Michael RobertoMichael Roberto, a leading business leadership authority whose excellent book Know What You Don’t Know I have written about previously, strongly urges organizations to develop problem finding skills. Roberto recently commented about new technologies that enable internal crowdsourcing, aka the collective-we:

Crowd sourcing can work inside of a company too, and we’re seeing more and more companies doing that; particularly global companies that have people spread out around the world. They’re using [new] tools to get people sharing [information] across different silos.

Eliminating information silos is a key prerequisite to becoming a collective-we organization capable of effective problem finding. In an interview with management consulting firm Linkage, Michael Roberto shared some valuable insights into the three major ways unified enterprise information management enables the organization’s collective-we:

Organizations must frankly answer, “Why did we fail?”

Take a look at a failure that took place in the organization. Ask yourself, “Could we have seen it coming… were there some signals we missed? Why did we miss them?”

Organizations that have undertaken such “candid self-assessment” have discovered that they had been acting based on an incomplete informational picture that was indeed missing critical business signals. Such signals reside within trends in KPIs and metrics drawn from data warehouses and databases, as well as unstructured content (free-flowing text residing in document repositories, SharePoint, wikis, file servers and external websites).

Boil large quantities of information down to what really matters.

[In the] old-school way, you built a big report, you put it in a binder and it collected dust… the answer is not a big report. The [real] answer is three bullets… the couple of takeaways – and technology can play a role in helping to share those. But the most important thing is boiling it down… If you (have) a 100-page report… no one is going to read it.

Good organizations are already adept at boiling down large volumes of data into KPIs that can be trended over time, but that’s not enough. It is also important to mine “those key takeaways” from every “100-page report no one is going to read” through natural language processing (NLP) and text analytics, including extraction of entities (names, products, places), key phrase extraction, entity normalization, content classification and more.

It’s also important to note a unified knowledge management (KM)/enterprise information management (EIM) system will also utilize advanced enterprise search to present the most relevant information instead of a long laundry list of documents to sort through. As a result, “those key takeaways” from every “100-page report no one is going to read” will be discovered by users whenever they are needed to help directly address any given matter at hand.

In a real world example, a level 1 IT support rep for a leading financial services firm resolved a serious enterprise application failure incident with no known workaround in the first call. The company’s service knowledge management solution surfaced an ideal resolution buried within a 100-plus page application development transitional document, written by one of the original programmers located in India.

Few people probably ever read the entire document, or even knew it existed; and yet, the company’s unified information architecture empowered the company’s collective-we from halfway around the world to solve a serious problem, by presenting that document when it was needed.

“You can’t chase down everything”… so let KM/EIM technology chase it down for you.

You can’t chase down everything [yourself]. I think part of the job of the leader is to be able to prioritize… [and] recognize that you have talent around you that can help you.

The same financial services firm also integrated key information about their own employees, particularly areas of subject matter expertise and current areas of research. Through such “expert finder” capabilities, a worker within a global organization can find and reach out to fellow co-workers for help down the hall or anywhere in the world – once again, empowering the organization’s collective-we to cross international boundaries.

A collective-we organization fully leverages the power of the collective intelligence, the collective knowledge of the entire organization to find business problems before they become serious issues, as well as seize new business opportunities before the competition even knows they exist.

Big Data Wisdom, Courtesy of Monty Python

Monty Python and the Holy GrailNote: This article was co-written by Mike Urbonas and Rik Tamm-Daniels.

One of our favorite parts of the hilarious 1975 King Arthur parody, Monty Python and the Holy Grail is the “Bridge of Death” scene: If a knight answered the bridge keeper’s three questions, he could safely cross the bridge; if not, he would be catapulted into… the Gorge of Eternal Peril!

Unfortunately, that’s exactly what happened to most of King Arthur’s knights…

The knights were either stumped by a surprise trivia question like, “What is the capital of Assyria?” – or responded too indecisively when asked, “What is your favorite color?”

Fortunately when King Arthur was asked, “What is the airspeed velocity of an unladen swallow?” he wisely sought further details: “What do you mean – an African or European swallow?” The stunned bridge keeper said, “Uh, I don’t know that… AAAGH!” Breaking his own rule, the bridge keeper was thrown over into the gorge, freeing King Arthur to continue his quest for the Holy Grail.

Many organizations are on “Big Data Holy Grail” quests of their own, looking to deliver game-changing analytics, only to find themselves in a “boil-the-ocean” Big Data project that “after 24 months of building… has no real value.” Unfortunately, many organizations have rushed into hasty Hadoop implementations, fueled by a need to ‘respond’ to Big Data and ‘not fall behind.’

Read the rest of this article on SmartData Collective.

Big Data Analytics, Business Intelligence and the Mind of Sherlock Holmes

My name is Sherlock Holmes. It is my business to know what other people do not know. — The Adventure of the Blue Carbuncle

Sherlock-Holmes-Big-Data-Analytics-and-BI-133x134Sherlock Holmes turned 125 years old last year, and he’s never been more alive and well. The world seems more captivated by Sir Arthur Conan Doyle’s legendary London detective than ever before. Much of this excitement has been driven recently by the smash BBC One TV series Sherlock, drawing rave reviews for its update of Holmes and Dr. Watson as present-day Londoners fighting 21st-century crime. (Similarly, the U.S. version of the series, Elementary, is also a major new hit.)

Pop culture critic and author John Powers cleverly explains Holmes’ enduring appeal as a literary hero and cultural icon:

Sherlock Holmes “possesses no superpowers — his parents weren’t wizards, no radioactive spider bit him — [and yet] his gifts are cool enough to be superhuman. Playing to our fantasies of being smarter than everyone else, Holmes performs jaw-dropping feats of perception.

It’s no coincidence that heightened interest in Sherlock Holmes coincides with the rapidly accelerating, proliferating sources of information around us: databases, documents/text, big data, social media, web content and more. Like Sherlock Holmes, we all want to make sense of seemingly unrelated information and “be smarter than everyone else” — or at least outsmart the competition, outsmart criminals and fraudsters, outsmart seemingly intractable business problems.

A quick review of Conan Doyle’s novels and short stories reveals Sherlock Holmes shared useful advice on effectively accessing, analyzing, and unifying information. His advice rings truer than ever in today’s increasingly information-rich but insight-deficient world.

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