Jack Bauer and Enforcing Data Governance Policies

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Jack Bauer

In my recent blog post Red Flag or Red Herring?, I explained that the primary focus of data governance is the strategic alignment of people throughout the organization through the definition, and enforcement, of policies in relation to data access, data sharing, data quality, and effective data usage, all for the purposes of supporting critical business decisions and enabling optimal business performance.

Simply establishing these internal data governance policies is often no easy task to accomplish.

However, without enforcement, data governance policies are powerless to affect the real changes necessary.

(Pictured: Jack Bauer enforcing a data governance policy.)

 

Jack Bauer and Data Governance

Jill Wanless commented that “sometimes organizations have the best of intentions.  They establish strategic alignment and governing policies (no small feat!) only to fail at the enforcement and compliance.  I believe some of this behavior is due to the fact that they may not know how to enforce effectively, without risking the very alignment they have established.  I would really like to see a follow up post on what effective enforcement looks like.”

As I began drafting this requested blog post, the first image that came to my mind for what effective enforcement looks like was Jack Bauer, the protagonist of the popular (but somewhat controversial) television series 24.

Well-known for his willingness to do whatever it takes, you can almost imagine Jack explaining to executive management:

“The difference between success and failure for your data governance program is the ability to enforce your policies.  But the business processes, technology, data, and people that I deal with, don’t care about your policies.  Every day I will regret looking into the eyes of men and women, knowing that at any moment, their jobs—or even their lives—may be deemed expendable, in order to protect the greater corporate good. 

I will regret every decision and mistake I have to make, which results in the loss of an innocent employee.  But you know what I will regret the most?  I will regret that data governance even needs people like me.”

Although definitely dramatic and somewhat cathartic, I don’t think it would be the right message for this blog post.  Sorry, Jack.

 

Enforcing Data Governance Policies

So if hiring Jack Bauer isn’t the answer, what is?  I recommend the following five steps for enforcing data governance policies, which I have summarized into the following simple list and explain in slightly more detail in the corresponding sections below:

  1. Documentation – Use straightforward, natural language to document your policies in a way everyone can understand.
  2. Communication – Effective communication requires that you encourage open discussion and debate of all viewpoints.
  3. Metrics – Truly meaningful metrics can be effectively measured, and represent the business impact of data governance.
  4. Remediation – Correcting any combination of business process, technology, data, and people—and sometimes, all four. 
  5. Refinement – You must dynamically evolve and adapt your data governance policies—as well as their associated metrics.

 

Documentation

The first step in enforcing data governance policies is effectively documenting the defined policies.  As stated above, the definition process itself can be quite laborious.  However, before you can expect anyone to comply with the new policies, you first have to make sure that they can understand exactly what they mean. 

This requires documenting your polices using a straightforward and natural language.  I am not just talking about avoiding the use of techno-mumbo-jumbo.  Even business-speak can sound more like business-babbling—and not just to the technical folks.  Perhaps most important, avoid using acronyms and other lexicons of terminology—unless you can unambiguously define them.

For additional information on aspects related to documentation, please refer to these blog posts:

 

Communication

The second step is the effective communication of the defined and documented data governance policies.  Consider using a wiki in order to facilitate easy distribution, promote open discussion, and encourage feedback—as well as track all changes.

I always emphasize the importance of communication since it’s a crucial component of the collaboration that data governance truly requires in order to be successful. 

Your data governance policies reflect a shared business understanding.  The enforcement of these policies has as much to do with enterprise-wide collaboration as it does with supporting critical business decisions and enabling optimal business performance.

Never underestimate the potential negative impacts that the point of view paradox can have on communication.  For example, the perspectives of the business and technical stakeholders can often appear to be diametrically opposed. 

At the other end of the communication spectrum, you must also watch out for what Jill Dyché calls the tyranny of consensus, where the path of least resistance is taken, and justifiable objections either remain silent or are silenced by management. 

The tyranny of consensus is indeed the antithesis of the wisdom of crowds.  As James Surowiecki explains in his excellent book, the best collective decisions are the product of disagreement and contest, not consensus or compromise.

Data Governance lives on the two-way Street named Communication (which, of course, intersects with Collaboration Road).

For additional information on aspects related to communication, please refer to these blog posts:

 

Metrics

The third step in enforcing data governance policies is the creation of metrics with tangible business relevance.  These metrics must be capable of being effectively measured, and must also meaningfully represent the business impact of data governance.

The common challenge is that the easiest ones to create and monitor are low-level technical metrics, such as those provided by data profiling.  However, elevating these technical metrics to a level representing business relevance can often, and far too easily, merely establish their correlation with business performance.  Of course, correlation does not imply causation. 

This doesn’t mean that creating metrics to track compliance with your data governance policies is impossible, it simply means you must be as careful with the definition of the metrics as you were with the definition of the policies themselves. 

In his blog post Metrics, The Trap We All Fall Into, Thomas Murphy of Gartner discussed a few aspects of this challenge.

Truly meaningful metrics always align your data governance policies with your business performance.  Lacking this alignment, you could provide the comforting, but false, impression that all is well, or you could raise red flags that are really red herrings.

For additional information on aspects related to metrics, please refer to these blog posts:

 

Remediation

Effective metrics will let you know when something has gone wrong.  Francis Bacon taught us that “knowledge is power.”  However, Jackson Beck also taught us that “knowing is half the battle.”  Therefore, the fourth step in enforcing data governance policies is taking the necessary corrective actions when non-compliance and other problems inevitably arise. 

Remediation can involve any combination of business processes, technology, data, and people—and sometimes, all four. 

The most common is data remediation, which includes both reactive and proactive approaches to data quality. 

Proactive defect prevention is the superior approach.  Although it is impossible to truly prevent every problem before it happens, the more control that can be enforced where data originates, the better the overall quality will be for enterprise information.

However, and most often driven by a business triage for critical data problems, reactive data cleansing will be necessary. 

After the root causes of the data remediation are identified—and they should always be identified—then additional remediation may involve a combination of business processes, technology, or people—and sometimes, all three.

Effective metrics also help identify business-driven priorities that determine the necessary corrective actions to be implemented.

For additional information on aspects related to remediation, please refer to these blog posts:

 

Refinement

The fifth and final step is the ongoing refinement of your data governance policies, which, as explained above, you are enforcing for the purposes of supporting critical business decisions and enabling optimal business performance.

As such, your data governance policies—as well as their associated metrics—can never remain static, but instead, they must dynamically evolve and adapt, all in order to protect and serve the enterprise’s continuing mission to survive and thrive in today’s highly competitive and rapidly changing marketplace.  

For additional information on aspects related to refinement, please refer to these blog posts:

 

Conclusion

Obviously, the high-level framework I described for enforcing your data governance policies has omitted some important details, such as when you should create your data governance board, and what the responsibilities of the data stewardship function are, as well as how data governance relates to specific enterprise information initiatives, such as master data management (MDM). 

However, if you are looking to follow a step-by-step, paint-by-numbers, only color inside the lines, guaranteed fool-proof plan, then you are going to fail before you even begin—because there are simply NO universal frameworks for data governance.

This is only the beginning of a more detailed discussion, the specifics of which will vary based on your particular circumstances, especially the unique corporate culture of your organization. 

Most important, you must be brutally honest about where your organization currently is in terms of data governance maturity, as this, more than anything else, dictates what your realistic capabilities are during every phase of a data governance program.

Please share your thoughts about enforcing data governance policies, as well as your overall perspectives on data governance.

 

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Red Flag or Red Herring?

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A few weeks ago, David Loshin, whose new book The Practitioner's Guide to Data Quality Improvement will soon be released, wrote the excellent blog post First Cuts at Compliance, which examines a challenging aspect of regulatory compliance.

David uses a theoretical, but nonetheless very realistic, example of a new government regulation that requires companies to submit a report in order to be compliant.  An associated government agency can fine companies that do not accurately report. 

Therefore, it’s in the company’s best interest to submit a report because not doing so would raise a red flag, since it would make the company implicitly non-compliant.  For the same reason, it’s in the government agency’s best interest to focus their attention on those companies that have not yet reported—since no checks for accuracy need to be performed on non-submitted reports.

David then raises the excellent question about the quality of that reported, but unverified, data, and shares a link to a real-world example where the verification was actually performed by an investigative reporter—who discovered significant discrepancies.

This blog post made me view the submitted report as a red herring, which is a literacy device, quite common in mystery fiction, where the reader is intentionally misled by the author in order to build suspense or divert attention from important information.

Therefore, when faced with regulatory compliance, companies might conveniently choose a red herring over a red flag.

After all, it is definitely easier to submit an inaccurate report on time, which feigns compliance, than it is to submit an accurate report that might actually prove non-compliance.  Even if the inaccuracies are detected—which is a big IF—then the company could claim that it was simply poor data quality—not actual non-compliance—and promise to resubmit an accurate report.

(Or as is apparently the case in the real-world example linked to in David's blog post, the company could provide the report data in a format not necessarily amenable to a straightforward verification of accuracy.)

The primary focus of data governance is the strategic alignment of people throughout the organization through the definition, and enforcement, of policies in relation to data access, data sharing, data quality, and effective data usage, all for the purposes of supporting critical business decisions and enabling optimal business performance.

Simply establishing these internal data governance policies is often no easy task to accomplish.  Just as passing a law creating new government regulations can also be extremely challenging. 

However, without enforcement and compliance, policies and regulations are powerless to affect the real changes necessary.

This is where I have personally witnessed many data governance programs and regulatory compliance initiatives fail.

 

Red Flag or Red Herring?

Are you implementing data governance policies that raise red flags, not only for implicit, but also for explicit non-compliance? 

Or are you instead establishing a system that will simply encourage the submission of unverified—or unverifiable—red herrings?

 

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The Point of View Paradox

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One of my all-time favorite non-fiction books is The 7 Habits of Highly Effective People by Stephen Covey. 

One of the book’s key points is that we need to carefully examine our point of view, the way we “see” the world—not in terms of our sense of sight, but instead in terms of the way we perceive, interpret, and ultimately understand the world around us.

As Covey explains early in the book, our point of view can be divided into two main categories, the ways things are (realities) and the ways things should be (values).  We interpret our experiences from these two perspectives, rarely questioning their accuracy. 

In other words, we simply assume that the way we see things is the way they really are or the way they should be.  Our attitudes and behaviors are based on these assumptions.  Therefore, our point of view influences the way we think and the way we act.

A famous experiment that Covey shares in the book, which he first encountered at the Harvard Business School, is intended to demonstrate how two people can see the same thing, disagree—and yet both be right.  Although not logical, it is psychological.

This experiment is reproduced below using the illustrations that I scanned from the book.  Please scroll down slowly.

 

Illustrations of a Young Woman

Look closely at the following illustrations, focusing first on the one on the left—and then slowly shift over to the one on the right:

Can you see the young woman with the petite nose, wearing a necklace, and looking away from you in both illustrations? 

 

 

Illustrations of an Old Lady

Look closely at the following illustrations, focusing first on the one on the left—and then slowly shift over to the one on the right:

Can you see the old lady with the large nose, sad smile, and looking down in both illustrations?

 

 

Illustrations of a Paradox

Look closely at the following illustrations, focusing first on the one on the far left—and then on the one in the middle—and then shift your focus to the one on the far right—and then back to the one in the middle:

Can you now see both the young lady and the old woman in the middle illustration?

 

The Point of View Paradox

The above experiment is usually performed without using the secondary illustration (the one shown on the right of the first two and in the middle of the final one).  Typically in a classroom setting, half of the room has their perception “seeded” utilizing the illustration of the young woman, and the other half with the illustration of the old lady.  When the secondary illustration is then revealed to the entire classroom, arguments commence over whether a young woman or an old lady is being represented.

This experiment demonstrates how our point of view powerfully conditions us and affects the way we interact with other people.

In the world of data quality and its related disciplines, the point of view paradox often negatively impacts the communication and collaboration necessary for success. 

Business and technical perspectives often appear diametrically opposed.  Objective and subjective definitions of data quality seemingly contradict one another.  And of course, the deeply polarized camps contrasting the reactive and proactive approaches to data quality often can’t even agree to disagree.

However, as Data Quality Expert and Jedi Master Obi-Wan Kenobi taught me a long time ago:

“You’re going to find that many of the truths we cling to depend greatly on our own point of view.” 

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Mind the Gap

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Photo via Flickr (Creative Commons License) by: futureshape

For many people, the phrase “mind the gap” conjures up images of a train platform, and perhaps most notably one used by the London Underground.  I’ll even admit to buying the T-shirt during my first business trip to England more than a decade ago.

However, lately I have been thinking about this phrase in a completely different context, specifically in relation to a recurring thought that was provoked by two blog posts, one written by James Chartrand in February, the other by Scott Berkun in May.

The gap I have in mind is the need to coordinate our acquisition of new information with its timely and practical application.

 

Information Acquisition

The Internet, and even more so, The Great Untethering (borrowing a phrase from Mitch Joel) provided by mobile technology, has created a 24 hours a day, 7 days a week, 365 days a year, world wide whirlwind of constant information flow, where the very air we breath is literally teeming with digital data streams—continually inundating us with new information. 

Of course, until they start embedding the computer chips directly into our brains at birth (otherwise known as the top secret iBaby experiment at Apple), we always have the choice of turning off all the devices and giving our full undivided attention to a single source of new information—such as a printed book or, even better, an in-person conversation with another human being.

However, when we are confronted by information overload, its accompanying stress is often caused by the sense that we have some obligation to acquire this new information—as if we were constantly cramming for a perpetually looming pop quiz. 

Contrast this perspective with Albert Einstein, who was known for not remembering even some of the most basic equations.  He argued why would he waste time memorizing something he could just look up in a book—when he needed it. 

This allowed Einstein to focus on problems nobody else could solve, as well as problems nobody had even thought of before, instead of learning what everyone else already knew.  He acquired more of his new information from his thought experiments than he did from books or other sources.

 

Filter Failure

As Clay Shirky famously stated, “it’s not information overload, it’s filter failure.”  I agree, but setting our filters is no easy task. 

Defending ourselves against information overload has become more difficult precisely because we now have greater individual responsibility for our own filters.  Not only are there more published books than ever before, but blogs, and other online sources of new information, have virtually eliminated the “built-in filter” that was provided by publishers, editors, and other gatekeepers. 

Please don’t misunderstand me—I am the complete opposite of Andrew Keen—I believe that this is a truly great thing. 

However, our time is a zero-sum game, meaning for every book, blog, or other new information source that we choose, others are excluded.  There’s no way to acquire all available information.  Additionally, cognitive load, a scientific theory that, in part, examines the limitations of our memory, explains why we often don’t remember much of the new information we do acquire.

Limiting ourselves to the few books and blogs we currently have the time to read, still requires filtering a much larger selection in order to make those choices—or we could simply choose to read only bestselling books and the blogs with the highest PageRank. 

However, can that approach guarantee access to the most valuable sources of new information?  Can any approach do this?

 

Information Application

Although acquiring new information is always potentially useful, it is when—and if—we can put it to use that makes it valuable. 

The distinction between useful and useless information is largely one of applicability.  If the gap in time between the acquisition and application of information is too great, then we would need to reacquire it, rendering the previous acquisition a wasted effort.

Perhaps the key point could be differentiating the type of potential knowledge provided by the information.  At a very high level, there are two broad categories of knowledge—explicit and tacit.

 

Explicit Knowledge

Explicit knowledge is relatively easily to acquire from either verbal or written information, and is often easily understood without extensive explanation.  Explicit knowledge can be based on a straightforward set of facts, or a specific set of instructions to follow, which after being repeatedly put to practical use just a few times, becomes easy to internalize and later recall when necessary. 

The information required for explicit knowledge is often best coordinated around when the knowledge gained would be used. 

One example is software training classes.  As an instructor, I always recommend minimizing the gap in time between when a training class is taken, and when the students would actually start using the software.  Additionally, an introductory class should focus on the most commonly used software features so students can master the basics before approaching advanced concepts.

 

Tacit Knowledge

Tacit knowledge is not only more difficult to acquire, but it is often not even easily recognizable.  Some lessons can simply not be taught, they can only be learned from experience, which is why tacit knowledge is sometimes alternatively defined as wisdom.

One of my favorite quotes about wisdom is from Marcel Proust:

“We do not receive wisdom, we must discover it for ourselves, after a journey through the wilderness, which no one can make for us, which no one can spare us, for our wisdom is the point of view from which we come at last to regard the world.”

Thought-provoking or paradigm-shifting information is often required to get us started on our journey through the wilderness of tacit knowledge, but we can easily lose sight of the deep forest it represents because we are far more immediately concerned with the explicit knowledge provided by the trees.

Whereas explicit knowledge is often more tactical in nature, tacit knowledge is often more strategic.  In general, we tend to prioritize short-term tactics over long-term strategy, thereby developing a preference for explicit, and not tacit, knowledge.

With tacit knowledge, the gap in time between information acquisition and application is much wider.  You require this time to assess the information before attempting to apply it.  You also need to realize that you will fail far more often when applying this type of information—which is to be expected since failure is a natural and necessary aspect of developing tacit knowledge.

 

Mind the Gap

As the growing stack of unread books on my nightstand, as well as the expanding list of unread blog posts in my Google Reader, can both easily attest, neither filtering nor acquiring new information is an easy task.

I have read many books—and considerably more blog posts—containing new information, which in retrospect, I can not recall. 

Obviously, in some cases, their information was neither valuable nor applicable.  However, in many cases, their information was both valuable and applicable, but I didn’t find—or more precisely, I didn’t make—the time to either put it to an immediate use, or to use it as inspiration for my own thought experiments.

I am not trying to tell you how to manage your time, or what new information sources to read, or even when to read them.

I simply encourage you to mind the gap between your acquisition of new information and its timely and practical application.

As always, your commendable comments are one of my most valuable new information sources, so please share your thoughts.

 

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The Acronymicon

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Image created under a Creative Commons Attribution License using: Wordle

“The beginning of wisdom is the definition of terms.” – Socrates

“The end of wisdom is the definition of acronyms.” – Jim Harris

The Acronymicon

The Necronomicon

The Necronomicon is a fictional grimoire (i.e., a textbook containing instructions on how to perform magic), which first appeared in the classic horror stories written by H. P. Lovecraft, and later appeared in other works, including some films, such as Army of Darkness, starring Bruce Campbell, which is one of my favorites—it’s a comedy and it’s highly recommended.

Therefore, the explanation for the rather unusual title of this blog post is that I could think of no better term to describe the fictional textbook containing instructions on how to discuss enterprise information initiatives by using acronyms, and only acronyms, other than:

The Acronymicon

 

Acronyms Gone Wild

For whatever reason, enterprise information initiatives (EIIs?)  have a great fondness for TLAs (two or three letter acronyms): ERP (Enterprise Resource Planning), DW (Data Warehousing), BI (Business Intelligence), MDM (Master Data Management), DG (Data Governance), DQ (Data Quality), CDI (Customer Data Integration), CRM (Customer Relationship Management), PIM (Product Information Management), BPM (Business Process Management), and so many more—truly too many to list.

Additionally, we have apparently become so accustomed to TLAs, that we needed to take it to the next level with Acronyms 2.0 by starting the fun new trend of FLAs (four letter acronyms) such as software as a service (SaaS), platform as a service (PaaS), data as a service (DaaS), service oriented development of applications (SODA), and so many frakking more four letter acronyms.

I also have it on very good authority that by the end of this decade, the Semantic Web will deliver Acronyms 3.0 by creating an Ontology of Unambiguous Acronyms (OOUA), which will be written using a RDFS (Resource Description Framework Schema), in the FOAF (Friend of a Friend) vocabulary, which we will obviously query using SPARQL, which is itself a recursive acronym for SPARQL Protocol and RDF Query Language.

 

WTF?

Now, don’t get me wrong.  I do appreciate how acronyms and other lexicons of terminology can be used as a convenient way of more efficiently discussing the complex concepts often underlying enterprise information initiatives. 

However, too often acronyms are used without ever being defined, which can lead to conversations like that scene in the movie Good Morning, Vietnam where Adrian Cronauer (played by Robin Williams) responds to the overuse of military acronyms used by an officer in charge to describe an upcoming press conference by then former Vice President Richard Nixon with the question:

“Excuse me, sir.  Seeing as how the VP is such a VIP, shouldn’t we keep the PC on the QT?  Because if it leaks to the VC, he could end up MIA, and then we’d all be put out in KP.”

An even worse offense than not defining what the acronym stands for, is only providing what it stands for as the definition. 

For example, when someone asks you the question “what is MDM?” and you respond by stating “Master Data Management,” that really doesn’t help all that much, does it?

Even when you use a better definition, such as the following one from the book Master Data Management by David Loshin:

“Master Data Management (MDM) incorporates business applications, information management methods, and data management tools to implement the policies, procedures, and infrastructures that support the capture, integration, and subsequent shared use of accurate, timely, consistent, and complete master data.”

This is only the beginning of a more detailed discussion, the specifics of which will vary based on your particular circumstances, including the unique corporate culture of your organization, which will greatly influence such things as how exactly the “policies, procedures, and infrastructures” are defined, and what “accurate, timely, consistent, and complete” actually mean.

For that matter, you shouldn’t even assume that everyone knows what you are referring to when you say “master data.”

My point is that you should always make sure that the key concepts of your enterprise information initiatives are clearly defined and in a language that everyone can understand.  I am not just talking about translating the techno-mumbojumbo, because even business-speak can sound more like business-babbling—and not just to the technical folks.

Additionally, don’t be afraid to ask questions or admit when you don’t know the answers.  Many costly mistakes can be made when people assume that others know (or pretend to know themselves) what acronyms and other terminology actually mean.

 

Instructions for using The Acronymicon

If you absolutely insist on using The Acronymicon to discuss enterprise information initiatives at your organization, please just remember that before you even open the book, you must first carefully recite the following words:

“Clatto Verata Nicto!”

No, wait—that’s not quite right.  I think it’s something more like, you must first carefully recite the following words:

“Klaatu Barada Nikto!” 

No, that doesn’t sound right either.  Somebody should just create an acronym for it—they’re much easier to recite and remember.

 

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Oh, the Data You’ll Show!

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Congratulations!
Today is your day.
You’re off to make your data presentations!
You’re off and away!

You have brains in your head.
You have pretty charts and graphs in your slides.
With data transparency, you’ll show you have nothing to hide.
You’re on your own, and you know what you know.

But your Data Quality may decide, where it is you may go.

You looked up and down columns, then across every row, with patience and care.
About some data you said, “I think that we need better quality here.”
With your head full of brains, and data under your supervision, 
You’re too smart to advise a not-so-good business decision.

Oh! the Data You’ll Show!

You’ll be on your way up!
You’ll be providing great business insights!
You’ll join the high fliers who soar to high heights.

You won’t lag behind, because you have parallel processing speed.
You’ll analyze the whole database, and you’ll soon take the lead.
Wherever you fly, you’ll be the best of the best.
Wherever you go, your data analysis will help you top all the rest.

Except when you don’t.
Because, sometimes, you won’t.

I’m sorry to say so but, sadly, it’s true.
Poor Data Quality and Bad Business Decisions can happen—yes, even to you.

You will discover data sources without any meta-mark. 
Nothing is labeled, leaving all business context in the dark. 
Data that could cause quite a chagrin!  Do you dare to stay out?  Do you dare to go in?
How much could you lose?  How much could you win?

And if you go in, should you JOIN LEFT or JOIN RIGHT—or JOIN LEFT-and-three-quarters?
With this data, you will feel like you are SQL querying blind.
Simple it’s not, I’m afraid you will find,
For a fine mind-maker-upper to make up their mind.

You can get so confused that you’ll start racing down long winding rows at a break-necking pace,
Grinding on for gigabytes across a weirdish and wild tablespace, headed, I fear, toward a most useless place.

The Analysis Paralysis Place—for people just analyzing.

Analyzing and analyzing, with no end in sight,
Analyzing and analyzing, with no way to know what’s wrong or what’s right.
Analyzing and analyzing, until three in the morning, and until the Nth degree,
Analyzing and analyzing, refusing to seek help from any business or data SME.

No!  That’s not for you!

Somehow you’ll escape all that Analysis Paralysis,
And hopefully without any of that costly psychoanalysis.
You’ll discover a way out of that place, so dismal and so dark,
Because when it comes to clear thinking, you’re a bright little spark.

Oh! the Data You’ll Show!

There is fun to be done!  And work too, that’s for sure.  But even work feels like a game you have already won.
The magical things that you can do with data, will make you the winning-est winner of all.
Among your co-workers and friends, everyone and all, you will truly stand the tallest of the tall.
You’ll be famous as famous can be, with the whole World Wide Web watching you win on YouTube and Google TV.

Except when they don’t.
Because, sometimes, they won’t.

I’m afraid that sometimes you’ll play lonely games too.
Games you can’t win because you’ll play against you.

All Alone!  Whether you like it or not,
Alone will be something you’ll be quite a lot.

And when you’re alone, there’s a very good chance you will meet, 
Data that scares you and convinces you it’s time to retreat.
There are some operational source systems that regularly do spawn,
Data that can scare you so very much, you won’t want to go on.

But on you will go though the data quality be most foul.
On you will go though the hidden data defects do prowl.
On you will go though it might take quite awhile, and leave quite a scar, 
You’ll overcome your data’s problems, whatever they are.

Oh! the Data You’ll Show!

Proceed with great care and with great tact, always remembering that,
Data Quality is a Great Balancing Act.
Just never forget to be dexterous and deft,
And never mix up your RIGHT JOIN with your LEFT.

Kid, you’ll move data mountains!
Today is your day!
Your data analysis is waiting.
So you had better get underway!

And will you succeed?
Yes!  You will, indeed!
(99.999 percent guaranteed.)

 

* * *

As you probably already do know,
Since it really does quite easily show,
This blog post was inspired by Oh, the Places You'll Go!


Persistence

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In a recent eLearningCurve MDM and Data Governance webinar, Dan Power quoted former U.S. President Calvin Coolidge:

“Nothing in the world can take the place of persistence.  Talent will not; nothing is more common than unsuccessful men with talent.  Genius will not; unrewarded genius is almost a proverb.  Education will not; the world is full of educated derelicts.  Persistence and determination are omnipotent.  The slogan ‘press on’ has solved and always will solve the problems of the human race.”

Although I had heard this excellent quote many times, it perhaps resonated with me more this particular time because I recently finished reading the latest Daniel Pink book Drive: The Surprising Truth About What Motivates Us.

In one of the many case studies cited in the book, Pink recounts the findings of an academic study performed to determine why some (approximately one in twenty) prospective cadets at the U.S. Military Academy at West Point, drop out before completing the mandatory seven weeks of basic training during the summer before what would be their first year at the academy.

The study tried to isolate the personal attributes that made the difference, such as physical strength, athleticism, intelligence, leadership ability, or perhaps a well-balanced combination of these factors traditionally considered to be crucial characteristics.

However, what the research discovered was that although all of the traditional characteristics were important, not one of them was the best predictor of success.  Instead, it was the prospective cadets’ rating on a non-cognitive, non-physical trait known as grit, defined as “perseverance and passion for long-term goals,” which truly made all the difference.

In related research examining the most accurate predictor of the academic performance of West Point Cadets, grit was once again found to be the determining factor in success.  As the researchers thoughtfully concluded:

“Whereas the importance of working harder is easily apprehended, the importance of working longer without switching objectives may be less perceptible.

In every field, grit may be as essential as talent to high accomplishment.”

This conclusion is similar to the “10,000-Hour Rule” explained by Malcolm Gladwell in his book Outliers: The Story of Success, where he claims the key to success in any field is largely a matter of practicing its primary task for approximately 10,000 hours.  However, Gladwell also acknowledges that success is far more complicated, and often relies on variables beyond our control.

I have written many times before about the common misperception of experts and their apparently easy success. 

Experts are often misunderstood as being somehow more naturally talented, more intelligent, or better educated than the rest of us.  When in truth, expertise is largely about experience, which as Oscar Wilde wrote “is simply the name we give our mistakes.”

Experts are simply those among us who have made the most mistakes, but persevered and persisted in spite of those failures, because experts see mistakes, as James Joyce wonderfully wrote, as our personal “portals of discovery.”

One of our most difficult challenges in life is the need to acknowledge the favor that our faults do for us.  Although experience is the path that separates knowledge from wisdom, the true wisdom of experience is the wisdom gained from failure.

However, expertise in any discipline is more than an accumulation of mistakes, birthdays, and 10,000 hours.  Expertise is not a static state that once achieved, signifies a comforting conclusion to all that grueling effort, which required so much perseverance.

All of this returns me to the misperceived connection between expertise and success.

Just as talent, intelligence, and education are no guarantee of success, neither are experience, perseverance, and expertise.  As much as we would like to believe that our personal success is dependent solely upon ourselves alone, the harsh reality is more often that not, variables beyond our control, such as luck, timing, and circumstance, will control our destiny as much as we do.

Please don’t misunderstand—I agree with President Coolidge that “persistence and determination are omnipotent” because we do have complete control over the effort we choose to expend. 

However, the most challenging mistake for us to overcome is when we choose entitlement over persistence.

Talent, intelligence, education, experience, and (perhaps paradoxically) expertise can all bring a sense of entitlement.  In other words, we can feel that we possess the necessary attributes and/or have completed the necessary steps required to be successful.

Therefore, we must ultimately accept that there is absolutely nothing that can guarantee our success—but far more important, we must also accept that the only guarantee of our failure would be to abandon our persistence.

 

Related Posts

The Once and Future Data Quality Expert

Mistake Driven Learning

The Fragility of Knowledge

The Wisdom of Failure

A Portrait of the Data Quality Expert as a Young Idiot

Podcast: Business Technology and Human-Speak

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An excellent recent Marty Moseley blog post called for every one of us, regardless of where we sit within our organization chart, to learn conversational business-speak. 

This common call to action, perhaps first sounded by the George Colony blog post in August of 2006, rightfully emphasizes that “business is technology and technology is business” and therefore traditional IT needs to be renamed BT (Business Technology) and techies need to learn how to “engage in a discussion of process, customers, and operations, not esoteric references to SOA, Web services, and storage management.” 

Therefore, we need to always frame enterprise information initiatives (such as data governance and master data management) in a business context by using business language such as mitigated risks, reduced costs, or increased revenue, in order to help executives understand, as the highly recommended Tony Fisher book details, the need to view data as a strategic corporate asset.

While I do not disagree with any of these viewpoints, as I was reading the latest remarkable Daniel Pink book, I couldn’t help but wonder if what we really need to do is emphasize both Business Technology and (for lack of a better term) Human-Speak.

In this brief (approximately 9 minutes) OCDQ Podcast, I share some of my thoughts on this subject:

You can also download this podcast (MP3 file) by clicking on this link: Business Technology and Human-Speak

 

Related Posts

Not So Strange Case of Dr. Technology and Mr. Business

Podcast: Open Your Ears

Shut Your Mouth

Hailing Frequencies Open

The Game of Darts – An Allegory

 

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The Challenging Gift of Social Media

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I recently finished reading (and also highly recommend) the excellent book Linchpin: Are You Indispensable? by Seth Godin. 

Although it’s not the subject of the book, in this blog post I’ll focus on one of its concepts that is very applicable to social media. 

 

The Circles of the Gift System

Godin uses the term “Gift Culture” to describe an emerging ethos facilitated by (but not limited to) the Internet and social media, which involves what he calls “The Circles of the Gift System” that I have attempted to represent in the above diagram.

In the first circle are your true real-world friends and family, the people that you would never interact with on the basis of trying to make money (i.e., the people you freely give “true gifts” while expecting nothing in return).

In the second circle are your customers and clients, the people that you conduct commerce with and who must pay you for your time, products, and services (i.e., the people and organizations you don’t give gifts because you need them to help pay your bills).

In the third circle is the social media and extended (nowadays mostly online) community, where following the freemium model, you give freely so that you can reach as many people as possible.  It is in the third circle that you assemble your tribe comprised of blog readers, Twitter followers, Facebook fans, and other “friendlies” — the term Godin uses for our social media connections.

It is the third circle that many (if not most) people struggle with and often either resist or ignore.  However, as Godin explains:

“This circle is new.  It’s huge and it’s important, because it enables you to enlarge the second circle and make more money, and because it enables you to affect more people and improve more lives.” 

However, dedicating the necessary time and effort to enlarge the third circle doesn’t guarantee you will enlarge the second circle, which risks turning freemium into simply free.  It is on this particular aspect that I will focus the remainder of my blog post.

 

The Intriguing Opportunity of Social Media

It is difficult to imagine a business topic generating more widespread discussion these days than social media.  That’s not to say that it is (or that it even should be) considered the most important topic.  However, almost every organization as well as most individual professionals have at the very least considered getting involved with social media in a business context.

The intriguing opportunity of social media is difficult to ignore—even after you ignore most of the hype (which is no easy task).

But as I wrote in the Social Karma series, if we are truly honest, then we all have to admit that we have the same question:

“What’s in this for me?”

Using social media effectively can definitely help promote you, your expertise, your company, and its products and services.  The primary reason I started blogging was to demonstrate my expertise and establish my authority with regards to data quality and its related disciplines.  As an independent consultant, I am trying to help sell my consulting, speaking, and writing services.

 

The Sobering Reality of Social Media

A social media strategy focused entirely on your own self-promotion will be easily detected by the online community, and could therefore easily result in doing far more harm than good.  Effectively using social media for business requires true participation, sustained engagement, and making meaningful contributions to the community’s goals—and not just your own.

The sobering reality of social media is that it’s not something you can simply do whenever it’s convenient for you.

Using social media effectively, more than anything else, requires a commitment that is mostly measured in time.  It requires a long-term investment in the community, and the truth is you must be patient because any returns on this investment will take a long time to materialize. 

If you are planning on a quick get in, get out, short-term marketing campaign requiring little effort, then don’t waste your time, but much more importantly, don’t waste the community’s time.

 

The Challenging Gift of Social Media

Godin opens his chapter on “The Powerful Culture of Gifts” by joking that he must have been absent the day they taught the power of unreciprocated gifts at Stanford business school. 

In fact, it’s probably a safe bet that the curriculum at most business schools conveniently ignores the fifty thousand year tradition of human tribal economies based on mutual support and generosity, when power used to be about giving, not getting.

Although we maintain some semblance of this tribal spirit in our personal lives with respect to the first circle, when it comes to our professional lives in the second circle, we want money for our time, product, or service—and we usually don’t come cheap.

Therefore, by far the most common question that I get asked (and that I often ask myself) about social media is:

“Is it really worth all that time and effort, especially when you aren’t getting paid for it?”

Although I honestly believe that it is, truthfully there have been many times when I have doubted it.  But those were usually times when I allowed myself to give in to the natural tendency we all have to become hyper-focused on our own goals. 

The paradox is that the best way to accomplish our selfish goals is—first and foremost—to focus on helping others. 

Of course, helping others doesn’t guarantee they’ll reciprocate, especially with financial returns on our social media investment.  Returning to Godin’s analogy, enlarging (or even just maintaining) the third circle doesn’t guarantee enlarging the second circle.

However, true service to the social media community requires giving true gifts to the third circle. 

Godin explains that these gifts—which do not demand reciprocation—turn the third circle into your tribe.  Giving gifts fulfills your tribal obligation.  Recipients pay it forward by also giving gifts—but perhaps to another tribal member—and not back to you.

And this is the challenging gift of social media—it is a gift that you may keep on giving without ever getting anything in return.

 

Related Posts

Freemium is the future – and the future is now

Social Karma

True Service

 

Recently Read: March 6, 2010

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Recently Read is an OCDQ regular segment.  Each entry provides links to blog posts, articles, books, and other material I found interesting enough to share.  Please note “recently read” is literal – therefore what I share wasn't necessarily recently published.

 

Data Quality

For simplicity, “Data Quality” also includes Data Governance, Master Data Management, and Business Intelligence.

  • Let the Data Geeks Play – Rob Paller is hosting a contest on his blog challenging all data geeks to submit an original song (or parody of an existing one) related to MDM, Data Governance, or Data Quality.  Deadline for submissions is March 20.
  • The First Step on your Data Quality Roadmap – Phil Wright describes how to learn lessons from what has happened before, and use this historical analysis as a basis for planning a successful strategy for your data quality initiative.
  • Bad word?: Data Owner – Henrik Liliendahl Sørensen examines how the common data quality terms “data owner” and “data ownership” are used and whether they are truly useful.  Excellent commentary was also received on this blog post.
  • Data as a smoke screen – Charles Blyth discusses how to get to the point where your consumers trust the data that you are providing to them.  This post includes a great graphic and received considerable commentary.
  • MDM Streamlines the Supply Chain – Evan Levy ruminates on the change management challenge for MDM—where change truly is constant—and how the supply chain can become incredibly flexible and streamlined as a result of MDM.
  • MDM as a Vendor Fight to Own Enterprise Data – Loraine Lawson (with help from actor Peter Boyle) looks at another angle of the recent MDM vendor consolidation, based on the recent remark “MDM is the new ERP” made by Jill Dyché. 
  • Data Quality Open Issues and Questions? – Jackie Roberts of DATAForge issues the blogosphere challenge of discussing real-world best practices for MDM, data governance, and data quality.  This blog post received some great comments.
  • Noise and Signal – David Loshin examines the implications of the rising volumes of unstructured data (especially from social media sources) and the related need for data (and metadata) quality to help filter out the signal from the noise.  
  • A gold DQ team! – Daniel Gent, inspired by the recent Winter Olympics and his country's success in ice hockey, discusses the skills and characteristics necessary for assembling a golden data quality team. 
  • Unpredictable Inaccuracy – Henrik Liliendahl Sørensen incites another thought-provoking discussion in the comments section of his blog with this post about the impact on data quality initiatives caused by the challenging reality of time.
  • Does your data quality help customers succeed? – Dylan Jones searches for the holy grail of data quality—providing your customers with great information quality that enables them to achieve their goals as quickly and simply as possible.
  • Charm School: It’s Not Just for IT Anymore – Jill Dyché reminds the business that it’s their business, too—and illustrates the need for a sustained hand-off cycle between IT and the business—and the days of the IT-business mind-meld are over.
  • Data Quality Lip Service – Phil Simon examines why leaders at many organizations merely pay lip service to data quality, and makes some recommendations for getting data quality its due.  Simon Says: “Read this blog post!”
  • What is the name of that block? – Rich Murnane provides a fascinating discussion about looking at things differently by sharing a TED video with Derek Sivers, who explains the different way locations are identified in Japan.
  • Aphorism of the week – Peter Thomas recently (and thankfully) returned to active blogging.  This blog post is a great signature piece representative of his excellent writing style, which proves that long blog posts can be worth reading.
  • How tasty is your data quality cheese? – Julian Schwarzenbach explains data quality using a cheese analogy, where cheese represents a corporate data set, mold represents poor data quality, which causes indigestion—and poor business decisions.
  • Wild stuff: Nines complement date format – Thorsten Radde provides a great example of the unique data quality challenges presented by legacy applications by explaining the date format known as Nine’s complement. 

 

Social Media

For simplicity, “Social Media” also includes Blogging, Writing, Social Networking, and Online Marketing.

  • Ten Things Social Media Can't Do – B.L. Ochman provides a healthy reminder for properly setting realistic expectations about social media, and provides a great list of ten things you should not expect from social media.
  • A Manifesto for Social Business – Graham Hill discusses how the nature of business is inexorably changing into a new kind of Social Business that is driven by social relationships, and lists fifteen themes (the Manifesto) of this change.
  • Framing Your Social Media Efforts – Chris Brogan explains there are three fundamental areas of practice for social media: (1) Listening, (2) Connecting, and (3) Publishing.
  • Minding the Gap – Tara Hunt examines the gap between the underlying values of business and the underlying human values that drive community.  This blog post also includes an excellent SlideShare presentation that I highly recommend.
  • The Albert Einstein Guide to Social Media – Amber Naslund channels the wisdom of Albert Einstein by using some of his most insightful quotes to frame a practical guide to a better understanding of social media.

 

Book Quotes

An eclectic list of quotes from some recently read (and/or simply my favorite) books.

  • From Linchpin: Are You Indispensable? by Seth Godin – “You don't become indispensable merely because you are different.  But the only way to be indispensable is to be different.  That's because if you're the same, so are plenty of other people.  The only way to get what you're worth is to stand out, to exert emotional labor, to be seen as indispensable, and to produce interactions that organizations and people care deeply about.”

 

Related Posts

Recently Read: January 23, 2010

Recently Read: December 21, 2009

Recently Read: December 7, 2009

Recently Read: November 28, 2009

 

Recently Read Resources

Data Quality via My Google Reader

Social Media via My Google Reader

Books about Data Quality, Data Governance, Master Data Management, and Business Intelligence

Blogs about Data Quality, Data Governance, Master Data Management, and Business Intelligence

Books about Social Media, Blogging, Social Networking, and Online Marketing

Blogs and Websites about Social Media, Social Networking, and Online Marketing

Social Karma (Part 6)

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In Part 5 of this series:  We continued discussing the basics of developing your social media strategy by reviewing some recommended best practices and general guidelines for engaging your community, as well as the basics of social media ROI.

In Part 6, we will discuss some of the books that have been the most helpful to my social media education. 

The following list (in no particular order) includes links to and quotes from five of my favorite social media books.  The last book is actually about social networking in the social scientific sense, but does contain useful material for social media discussions.

 

The Whuffie Factor

The Whuffie Factor: Using the Power of Social Networks to Build Your Business by Tara Hunt.

  • “Whuffie is the residual outcome—the currency—of your reputation.  You lose or gain it based on positive or negative actions, your contributions to the community, and what people think of you.”
  • “Whuffie flows from the trust, reciprocity, information, and cooperation that moves quickly within social networks.”
  • “Turn the bullhorn around: Stop talking and start listening.”
  • “Become part of the community you serve and figure out who it is you are serving.  It isn't everyone.”
  • “To truly become part of the community you serve, you must add value.”
  • “Instead of being concerned with quantity, you need to become more concerned with quality of relationships.  This doesn't mean that quantitative measurements disappear, it just means they aren't your most dominant measurement.”

 

Crush It!

Crush It!: Why NOW Is the Time to Cash In on Your Passion by Gary Vaynerchuk.

  • “Your business and your personal brand need to be one and the same.  Your latest tweet and comment on Facebook and most recent blog post—that's your résumé now.  It's a whole new world, build your personal brand and get ready for it.”
  • “Can you think of any business that isn't in some way dependent on human interaction?”
  • “If you're not using Twitter because you're in the camp that believes it's stupid, you're going to lose out.  It doesn't matter if you think it's stupid, it's free communication.  That in and of itself has value, and you should take advantage of it.”
  • “You're in business to serve your community.  Don't ever forget it.  Don't betray their trust.”
  • “The other thing you're going to do is accept that just having good content and Internet access is not enough to take your business to the top.  Someone with less passion and talent and poorer content can totally beat you if they're willing to work longer and harder than you are.”
  • “Creating community—that's where the bulk of your hustle is going to go and where the bulk of your success will be determined.  Creating community is about starting conversations.”
  • “Building and sustaining community is a never-ending part of doing business.”
  • “Don't get obsessed with how many friends or fans are following you—the stats are only marginally important.  What's important is the intensity of your community's engagement and interaction with you.  The quality of the conversation is much more revealing than the number of people having it.”
  • “Making connections, creating and continuing meaningful interaction with other people, whether in person or in the digital domain, is the only reason we're here.”

 

Trust Agents

Trust Agents: Using the Web to Build Influence, Improve Reputation, and Earn Trust by Chris Brogan and Julien Smith.

  • “Focus on connecting with the people—the human stuff is far more important than the software.”
  • “The Web and social media give you the opportunity to reveal the human side of your business.”
  • “Building any kind of following online is difficult enough.  It requires solid leadership skills, the ability to create a sense of belonging, a gracious attitude, transparency about who you are, and empowering the community to feel important.”
  • “Trust agents build networks almost reflexively by being helpful, by promoting the good work that others do, by sharing even their best stuff without hesitation, and by finding ways to deliver even more value on top of all that without asking for anything in return.”
  • “Attention is and will continue to be our scarcest resource.”
  • “Social networking is not about getting attention for attention's sake, but rather about being a part of the network, making other people aware that you are there—and that you'll be there in the future, too.”
  • “If you are to learn how to be a trust agent, the skill of being a Human Artist—someone who understands how to communicate with people in a real and thoughtful way—is very important to what you're doing.”

 

Six Pixels of Separation

Six Pixels of Separation: Everyone Is Connected. Connect Your Business to Everyone. by Mitch Joel.

  • “It's no longer about how much budget you dump into advertising and PR in hopes that people will see and respond to your messaging.  The new online channels will work for you as long as you are working for them by adding value, your voice, and the ability for your consumers to connect, engage, and take part.” 
  • “This new economy is driven by your time vested—and not by your money invested.”
  • “Networking online is core to success because it's not blatant sales and marketing.”
  • “You can't have a strong business without a strong community.”
  • “The digital social spaces are built on trust and trust alone.”
  • “Your ability to leverage true ROI is going to come from the level of trust you have built and the community you serve.”
  • “Nothing stinks of insincerity more than using these new digital channels and not listening to the other conversations.”
  • “The more human, honest, and transparent you are, the quicker you will be able to build trust and leverage it to build community and your business.”
  • “You're not looking for sheer mass numbers of people for the sake of traffic.  Traffic has levels of quality that only you can measure.  Focus on building community and not traffic.”
  • “The long-term game of sustainability in the online channels is one of quality versus quantity.”

 

Connected

Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives by Nicholas A. Christakis, MD, PhD and James H. Fowler, PhD.

  • “Six Degrees of Separation: We are all connected to everyone else by an average of six degrees of separation (your friend is one degree from you, your friends' friend is two degrees, and so on).” 
  • “Three Degrees of Influence: Everything we do or say tends to ripple through our network, having an impact on our friends (one degree), our friends' friends (two degrees), and even our friends' friends' friends (three degrees).  Our influence gradually dissipates and ceases to have a noticeable effect on people beyond the social frontier that lies at three degrees of separation.  Likewise, we are influenced by friends within three degrees but generally not those beyond.”
  • “Just as brains can do things that no single neuron can do, so can social networks do things that no single person can do.”
  • “Social networks have value precisely because they can help us achieve what we could not achieve on our own.”
  • “Since information flows freely within a close circle of friends, it is likely that people know more or less everything that their close friends know. We might trust socially distant people less, but the information and contacts they have may be intrinsically more valuable because we cannot access them ourselves.”
  • “Networks with a mix of weak and strong ties allow easy communication but also foster greater creativity because of the ideas of new members of the group and the synergies they create.”
  • “Although social networks may help us do what we could not do on our own, they also often give more power to people who are well connected.  As a result, those with the most connections often reap the highest rewards.”
  • “Social networking fosters strong ties with groups that optimize trust and then connects them via weaker ties to members of other groups to optimize their ability to find creative solutions when problems arise.”
  • “For thousands of years, social interactions were built solely on face-to-face communication.  The invention of each new method of communication has contributed to a debate stretching back centuries about how technology affects community.  Yet, new technologies just realize our ancient propensity to connect to other humans, albeit with electrons flowing through cyberspace rather than conversations drifting through air.”
  • “The recent surge in mobile phones, the Internet, and social networking sites has shifted our ability to stay in touch with one another into overdrive, causing us to become hyperconnected.”

 

In Part 7 of this series:  We will discuss some recommended best practices and general guidelines for using Twitter.

 

Related Posts

Social Karma (Part 1) – Series Introduction

Social Karma (Part 2) – Social Media Preparation

Social Karma (Part 3) – Listening Stations, Home Base, and Outposts

Social Karma (Part 4) – Blogging Best Practices

Social Karma (Part 5) – Connection, Engagement, and ROI Basics

Social Karma (Part 7) – Twitter

The Wisdom of the Social Media Crowd

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In his blog post A Story Culture, Michael Lopp, author of Managing Humans (check out the book's great promotional website), used the intriguing phrase “connective information tissue” to describe the value of tweets (status messages sent via Twitter).

 

Information Hierarchy

Challenged by his editor to better understand what information is, Lopp starts with the definition of the Information Hierarchy provided by Ray R. Larson at Berkeley:

  • Data – The raw material of information
  • Information – Data organized and presented by someone
  • Knowledge – Information read, heard or seen and understood
  • Wisdom – Distilled and integrated knowledge and understanding

Lopp then examines how information ascends this hierarchy using the perennial vehicle designed for its transmission—the story.

 

Shattered bits of narrative

“The traditional narrative,” explains Lopp, “has been shattered into bits of well-indexed information.  Google wasn’t the first indexing tool, but it’s certainly the best.  Still, Google is powerfully dumb.  Yes, I can find whatever piece of information I’m looking for, but what’s more interesting are all the related pieces of information.  How do you query for knowledge via Google?  How about wisdom?”

Constructing (or reconstructing) a meaningful narrative from shattered bits of information requires a human storyteller.

“There’s no replacing,” explains Lopp, “a human being combing through seemingly disparate pieces of information to evaluate, interpret, and combine it into something unexpected; into a new work.  Into a story.”

 

What tale can tattered tweets truly tell?

With their 140 character limit, tweets are certainly capable of being classified as shattered bits of narrative.

However, according to Lopp, “the point of Twitter isn’t knowledge or understanding, it’s merely connective information tissue.  It’s small bits of information carefully selected by those you’ve chosen to follow and its value isn’t in what they send, it’s how it fits into the story in your head.  There are great stories to be found on Twitter, but you have to do the work.”

Case in point—it was the tweet sent by Rob Paller that lead me to the blog post I am trying to write a great story about now.

Of course, as Lopp acknowledges, Twitter is not an isolated example. 

Information continues to be shared in smaller and smaller bits in accordance with our shorter and shorter attention spans. 

“Paradoxically, it’s never been easier to share or meaningfully interact with more people with less physical, in-person effort,” explains Lopp.  “Your ability to compose and convey information as well as express yourself through your fingertips is a skill that is only going to increase—and increase in value—as people become more comfortable with their place in communities that span the planet, and as the tools to connect them become more commonplace.” 

As social media's conversation medium continues to supplant traditional media's broadcast medium, it is enabling a world that fulfills James Joyce's vision in Finnegans Wake: “my consumers, are they not my producers?”

In other words, we are both consuming and producing the connective information tissue that forms our collective intelligence.

 

We are all storytellers

Even before the evolution of written language, storytelling played an integral role in every human culture.  Listening to stories and retelling them to others continues to be the predominant means of expressing our emotions and ideas.  Writing (and reading) greatly improves our ability to communicate, educate, record our history, and thereby pass on our information, knowledge, and wisdom to future generations.

We are now living in an amazing age where the very air we breath is literally teeming with information.  Digital data streams are continuously transmitted across the globe at near instantaneous speeds.  We need storytellers now more than ever. 

However, storytelling is neither an esoteric skill possessed by only a select few, nor is it the sole providence of writers. 

“The construction of a story,” explains Lopp, “has very little to do with writing.  It has to do with the semi-magical process of you taking disparate pieces of information, combining them into something new, which includes your experience and understanding, and then giving them to someone else.”

In a story culture, we are all storytellers. 

Storytelling may not be as simple (or as fun) as playing a game of Mad Libs.  However, it is important to realize that the very act of thinking is a form of storytelling.  The thought process is your brain collecting the shattered bits of information whirling around in your head and weaving them together into a narrative that, at least at first, might not make sense—even to you. 

The thought process isn't always simple and it isn't always fast.  Especially when all those voices in your head talk at once. 

My own thinking often feels like I am herding cats or—thanks to the “semi-magical process” makes me describe it—as if I am “full of broken thoughts I could not repair” (from the song Hurt originally by Nine Inch Nails and covered by Johnny Cash).

Eventually, you assemble a tale actually worth telling.  But even though you may be certain that the force is strong with this one, your tale is not a story yet. 

“Just like information isn’t knowledge until it’s understood,” as Lopp thoughtfully explains, “your tale isn’t a story until you give it to someone else—until they have a chance to see what they think about your inspiration.”

 

The Wisdom of the Social Media Crowd

One of my favorite books is The Wisdom of Crowds by James Surowiecki, which was originally published in 2004 (i.e., 2 B.T.E., two years “Before the Twitter Era”) before the real rise to prominence of social media.  Aspects of social media (such as blogging) were already prevalent at the time, but most of today's leading social networking tools were still in their nascent phase.

However, I believe many of Surowiecki's insights are very applicable to social media.  Take for example the four conditions that characterize wise crowds:

  1. Diversity of opinion
  2. Independence
  3. Decentralization
  4. Aggregation

Returning to Lopp's concept, it is social media's small bits of connective information tissue, gathered from diverse digital sources, acting as independent agents, lacking any centralized information authority, aggregated with your own knowledge, which you then construct into a story and share with others—that is The Wisdom of the Social Media Crowd.

 

Related Posts

The War of Word Craft

Will people still read in the future?

Brevity is the Soul of Social Media

 

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Recently Read: January 23, 2010

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Recently Read is an OCDQ regular segment.  Each entry provides links to blog posts, articles, books, and other material I found interesting enough to share.  Please note “recently read” is literal – therefore what I share wasn't necessarily recently published.

 

Data Quality

For simplicity, “Data Quality” also includes Data Governance, Master Data Management, and Business Intelligence.

  • Data Quality Blog Roundup - December 2009 Edition – Data Quality Pro always provides a great collection of the previous month's best blog posts, this particular entry covers my data quality “recently reads” from before the start of the new year.

     

  • Hostile Environment Data Harassment – Phil Simon discusses the common tendency for an organization's culture to not only compartmentalize data issues, but also tolerate “data carelessness” and irresponsibility.

     

  • Data Profiling For All The Right Reasons, Part 1 – In this Hub Designs Blog guest post, Rob DuMoulin begins a tool-agnostic five-part series about data profiling using psychology and Jungian word association analysis.

     

  • Personal Data – an Asset we hold on Trust – Daragh O Brien shares an intriguing case study about data protection, and discusses the key stages and data protection principles in the Information Asset Life Cycle.

     

  • Standardizing Data Migration – Evan Levy uses a motion picture industry analogy to suggest establishing a separate functional team that’s responsible for data packaging and distribution.

     

  • A Data Quality Riot Act – Rob Paller shares a great real-world example of data quality challenges even when an enterprise system is well-designed with protocols specifically put in place to ensure proper data management and data quality.

     

  • What is a MDM Strategy – Charles Blyth channels the ancient wisdom of Sun Tzu to explain that an MDM strategy is the overarching governance that defines the goals, reasons, approach and standards of its individual initiatives.

     

  • Data Quality issue in my new database - or so we thought... – Rich Murnane shares an interesting real-world example of how not every apparent data problem turns out to be an actual data quality issue.

     

  • Diversity in City Names – Henrik Liliendahl Sørensen explains the challenges inherit in global data quality using the example of the many ways that the city of Copenhagen, Denmark can be represented due to linguistic variations.

     

  • How data quality derives from meta data – Rayk Fenske examines the relationship between data quality management and metadata management by discussing directed functional dependency as well as a hierarchy in requirements.

     

  • The Quality Gap: Why Being On-Time Isn’t Enough – Jill Dyché discusses the all-too-common tendency to emphasize efficiency over effectiveness in enterprise project management, where everything is date-driven and not quality-driven.

     

  • Name Patterns and Parsing – David Loshin explains that personal names, although conceptually straightforward, are beset by many interesting pattern variations, making them a very daunting data quality challenge. 

     

  • A true story of how data quality issues can cripple a business – Graham Rhind shares a remarkable real-world example that illustrates very well the effect poor data quality (and lack of information quality) can have at every level of an organization.

     

  • WANTED: Data Quality Change Agents – Dylan Jones explains the key traits required of all data quality change agents, including a positive attitude, a willingness to ask questions, innovation advocating, and persuasive evangelism.

     

  • The Power of Slow - Paul Boal begins an excellent series about slow by explaining that a proper understanding of slow truly reveals it is the far more efficient approach—and not just for data quality. 

     

  • Data vs. Facts, Illustrated - Mark Graban discusses the common problem of relying too much on reports and dashboards without verification of the underlying data—and shares a hilarious picture to illustrate the point.   

     

  • The Value of Data – Marty Moseley discusses the core issue that most businesses still do not understand the value of data to their organizations, and shares some findings from a recent data governance survey.

     

  • ETL, Data Quality and MDM for Mid-sized Business – Steve Sarsfield on challenges of investing in enterprise software faced by small to medium sized businesses, and opportunities in the freemium model of open source alternatives such as Talend.

     

  • Beyond Data Ownership to Information Sharing – Joe Andrieu provides an interesting look at the often polarizing topics of data ownership, data privacy, and information sharing, explaining that we want to share our information, on our terms, protect our interests, and enable service providers to do truly amazing things for us and on our behalf. 

     

  • The Great Expectations of BI – Promising new blogger Phil Wright provides an excellent Dickensian inspired explanation of why, in many organizations, business intelligence doesn't live up to its great expectations.   

 

Social Media

For simplicity, “Social Media” also includes Blogging, Writing, Social Networking, and Online Marketing.

 

Book Quotes

An eclectic list of quotes from some recently read (and/or simply my favorite) books.

  • From Confessions of a Public Speaker by Scott Berkun – “Expressing ideas is often the only way to fully understand what ideas are, and to know what it is you really think.  Expression makes learning from the criticism of others possible, and I'm happy to look like a fool if in return I learn something I wouldn't have learned any other way.”

     

  • From The Dip: A Little Book That Teaches You When to Quit (and When to Stick) by Seth Godin – “The opportunity cost of investing your life in something that's not going to get better is just too high.”

     

  • From Six Pixels of Separation: Everyone Is Connected. Connect Your Business to Everyone. by Mitch Joel – “It's no longer about how much budget you dump into advertising and PR in hopes that people will see and respond to your messaging.  The new online channels will work for you as long as you are working for them by adding value, your voice, and the ability for your consumers to connect, engage, and take part.  This new economy is driven by your time vested—and not by your money invested.”

DQ-Tip: “Start where you are...”

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Data Quality (DQ) Tips is an OCDQ regular segment.  Each DQ-Tip is a clear and concise data quality pearl of wisdom.

“Start where you are

Use what you have

Do what you can.”

This DQ-Tip is actually a wonderful quote from Arthur Ashe, which serves as the opening of the final chapter of the fantastic data quality book: Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information by Danette McGilvray.

“I truly believe,” explains McGilvray, “that no matter where you are, there is something you can do to help your organization.  I also recognize the fact that true sustainability of any data quality effort requires management support.  But don't be discouraged if you don't have the ear of the CEO (of course that would be nice, but don't let it stop you if you don't).”

McGilvray then suggests the following excellent list of dos and don'ts:

  • You DON'T have to have the CEO's support to begin, but . . .
  • You DO have to have the appropriate level of management support to get started while continuing to obtain additional support from as high up the chain as possible.

     

  • You DON'T have to have all the answers, but . . .
  • You DO need to do your homework and be willing to ask questions.

     

  • You DON'T need to do everything all at once, but . . .
  • You DO need to have a plan of action and get started!

“So what are you waiting for?” asks McGilvray. 

“Get going: build on your experience, continue to learn, bring value to your organization, have fun, and enjoy the journey!”

 

Related Posts

DQ-Tip: “Data quality is about more than just improving your data...”

DQ-Tip: “...Go talk with the people using the data”

DQ-Tip: “Data quality is primarily about context not accuracy...”

DQ-Tip: “Don't pass bad data on to the next person...”

 

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Freemium is the future – and the future is now

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Earlier this week, two excellent blog posts—Three Ways to Start a Revolution by James Chartrand on Men with Pens, and Your Dream is Under Attack by Nathan Hangen on Copyblogger—discussed the somewhat polarizing debate about making money from blogging, which is one of many examples of the so-called “freemium” business model, which was first articulated in 2006 by venture capitalist Fred Wilson:

“Give your service away for free, acquire a lot of customers very efficiently through word of mouth and referral networks, then offer premium priced, value added services or an enhanced version of your service to your customer base.”

In 2009, Chris Anderson published the book Free: The Future of a Radical Price, which among numerous other coverage, was critically reviewed in the article Priced to Sell by Malcolm Gladwell, and discussed in an interview conducted by Charlie Rose.

 

Isn't everything on the Internet supposed to be free?

The freemium model, as well as the concept expressed in Anderson's book, is not entirely about the Internet.  However, it is most often at the center of polarized debates because more and more businesses, in varying degrees, are becoming online businesses.

General public perception is that the Internet is free—getting on the Internet does have a cost (sometimes conveniently ignored), in terms of electricity, ISPs, and the various computer and mobile devices used to access it.  However, once you are connected, the content on the Internet is either free or is supposed to be free—according to the “logic” of a very common perspective.

To be fair, this is somewhat understandable, especially given the fact that many of the most popular online services, such as Twitter, Facebook, and YouTube, to name but three examples from countless others, are in fact, free – and their users often defiantly claim that they would never pay any amount of money for such a service.

 

So how does the Internet make money?

The Internet has traditionally made money the same way broadcast television (also “free” when you conveniently ignore the cost of electricity, cable and satellite providers, and the various devices used to access it) has traditionally made money – advertising.

Paraphrasing (and oversimplifying) the words of Chris Anderson, the three generations of making money on the Internet:

  1. Pop-Up Ads – in the beginning was the Pop-up Ad—and it was not good.  Do you still remember (or are you old enough to remember) the early days of the Internet?  Nearly every website you visited brought the seemingly random attack of pop-up ads.  Even after the invention of pop-up blockers and the advent of alternatives to pop-up ads, online advertising was not very context sensitive and not only annoying, but also largely ineffective.

     

  2. Google AdSense – the next generation of advertising was basically pioneered by Google (or companies they now own).  Exemplified by the now somewhat ubiquitous Google AdSense, ads specific to website content provided online advertising that is both less annoying and seemingly far more effective.

     

  3. Freemium – we are just entering the third generation of making money on the Internet, and the first one not ruled by advertising—at least not advertising in the “traditional” sense.  Under this new model, free online content is made available to everyone—providing the opportunity to “up-sell” premium content to a (typically small) percentage of your audience.

 

Freemium is NOT a new concept

Although many Internet users become seemingly outraged by the very notion of the option to purchase premium content, the idea of giving away something for free in order to facilitate a potential purchase is by no means a new concept.

Just a few simple examples include:

  • Samples at the mall food court are free, but you have to pay to eat a full meal
  • Movie previews are free, but you have to pay to watch an entire movie
  • Broadcast television shows are free, but you have to pay for the DVD box sets

The Internet, however, has seemingly always been viewed as a special case.

I believe this is mostly due to the ratio of free to premium.  Food samples, movie previews, and an individual episode of a television show, are small compared to the size of a full meal, a full-length movie, and a full season (or series) of episodes.

In other words, what we get for free isn't much, so paying for the rest makes more sense.  On the Internet, this ratio is reversed. 

Since almost everything on the Internet is free (again, after the cost of connection), we are genuinely, and perhaps really quite understandably, surprised or even annoyed when we encounter something that we are asked to pay for.

In other words, since we get so much for free, paying just to get a little more simply doesn't seem to make sense. 

After all, if the full meals at the mall food court were free, we certainly wouldn't pay just to eat samples.

(And yes—I do realize that was a terrible analogy on so many levels—so please stop yelling at me.)

 

Isn't freemium the end of the world as we know it?

Obviously, the real issue is not the ratio of free to premium, or how much you should (or should not) expect to get for free. 

The fundamental argument is that anything you pay for should be worth the price.

Historically, price has been the indicator of value, meaning something has value only if people are willing to pay for it.  Higher prices, in theory at least, indicate higher value, especially if people are willing to purchase at the higher price.

So, if people are willing to pay for it, then this indicates there is a demand for it, for which a supply of it must be produced. 

(And yes—I do realize that was a huge oversimplification of economic theory—so yet again, please stop yelling at me.)

One of the most common counter-arguments to the freemium model is that if price is allowed to essentially drop to zero, then there will be no way to accurately measure demand, which means there will be no way for content producers to determine what to supply.  Furthermore, if almost everything is free, then why would content consumers be willing to pay for anything at all.

If nobody is willing to pay, then nobody can possibly get paid, and all online content will be completely user-generated, and following Andrew Keen's argument in The Cult of the Amateur, a cultural apocalypse occurs, which results in not only the Internet, but the entirety of human expression, being reduced to us hurling our feces at each other just like our primate cousins.

(You may feel free to resume yelling at me now.)

 

Freemium is the future—and the future is now

Obviously, the freemium business model doesn't only apply to blogging.  By the way, it is totally understandable if you had forgotten that my lunatic fringe was ignited by the debate over making money from blogging.

Freemium is the future of most of the business world—and the harsh reality is—the future has already arrived.

In my opinion, too many people, companies, and in some cases, entire industries, are wasting their time, effort, and money trying to fight the unrelenting reality of freemium.  Instead of refusing to accept that the price of what you are now offering may be falling essentially to zero—focus on creating something new that people would be willing to pay for.

Once again, to paraphrase Chris Anderson, “free” is only one of many markets—and only one of many additional pricing levels. 

Don't stop at thinking about just two versions of each individual product or service—one free version and one premium version.  You should be thinking about one free version and multiple tiers of premium.  Value still drives price.  Therefore, if you can truly add more value at each tier, then you can successfully demand a higher price.

Freemium works as a viable model because people will always be willing to pay a premium for something worth its price.

If you can't (or can no longer) produce something your customers are willing to pay for—that's your problem, not theirs.