Recently Read: March 22, 2010

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.

• The Data Quality Herald Magazine – Dylan Jones, the founder and community manager of Data Quality Pro, recently released the first edition of a unique new magazine focused squarely on the needs of the data quality community.

• Defining Master Data for Your Organization – Loraine Lawson recaps a recent David Loshin MDM vendor panel discussion, and looks at both the simple answer and the complex, but more useful, answer to the question “what is master data?”

• What is Data Quality anyway? – Henrik Liliendahl Sørensen asks two excellent questions in this blog post (which also received great comments): “is data quality an independent discipline?” and “is data quality an independent technology?”

• Business logic – Peter Thomas provides a hilarious adapted comic strip.

• Police Untelligence – from IQTrainwrecks.com, which is provided by the IAIDQ, read the story about the home of an elderly Brooklyn couple that has been raided by the New York City Police Department 50 times over the last 4 years.

• Julian Schwarzenbach on Implementation Challenges – in his Technology Today podcast, Phil Simon discusses implementation challenges with Julian Schwarzenbach, including the relationship between data quality and technology.

• Metadata and 3-D Glasses – David Loshin explains the data governance, data stewardship, and metadata/harmonization albatross hanging around the neck of the common question “what is the definition of ‘customer’?”

• No Enterprise wide Data Model – Ken O’Connor continues his excellent series about common enterprise wide data governance issues with this entry about the impact of not having an enterprise wide data model.

• Putting data on the web – Rich Murnane shares an excellent recent TED video by Tim Berners-Lee showing some of the benefits of shared data on the web.

• How Are You Creating a Pull for Data Quality in Your Organization? – Dylan Jones provides two brief case studies contrasting the “push” and “pull” approaches to getting the organization engaged in a data quality improvement initiative.

• Building your Data Governance Board – Marty Moseley continues his overview of agile data governance by discussing how you select a data governance board, and how you establish data governance priorities.

• Staring at the Lights: Your Data Warehouse Isn’t a Commodity – Evan Levy explains how far too many data warehouse development teams have completely lost sight of their success metrics—and have become entirely focused on loading data.

• The Change Paradox – Carol Newcomb examines the “change is good, but change is bad” paradox often encountered in consulting when recommended new technology or new methodology conflicts with your client's corporate culture.  

• Data Quality Non-Believers – Phil Simon takes on the data quality non-believers making “dataless decisions” by relying on gut instincts to explain such things as customer churn, employee turnover, and intelligent spending of corporate funds. 

• Data Cleansing to Achieve Information Quality – Jackie Roberts raises some interesting questions regarding the efforts needed to cleanse data though multiple stages of analytics and processes to achieve appropriate information quality.

• Data Quality Principles within the PMO – Phil Wright provides a list of six excellent principles that must be met in order to help embed a culture of data quality, data assurance, and data governance within each new project.

• Reduce Business Intelligence cost through better data migration – James Standen examines the challenges of cost control on business intelligence initiatives—and as usual, his blog post includes some great satirical cartoons.

• Is computer analysis accurate? – Julian Schwarzenbach considers the accuracy of computer analysis in decision making, especially automated decision making that attempts to mimic human logic, intuition, and insight.

Related Posts

Recently Read: March 6, 2010

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

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

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

Wordless Wednesday: March 17, 2010

Photo via Flickr (Creative Commons License) by: Stéfan

Social Karma (Part 8)

This post is the conclusion of a series about the art of effectively using social media in business, which is an essential strategy for organizations as well as individual professionals.

Using social media effectively can definitely help promote you, your expertise, your company, and its products and services.

However, too many businesses and professionals have a selfish social media strategy.

You should not use social media to exclusively promote only yourself or your business.

You need to view social media as Social Karma.

Social Karma: The Art of Effectively Using Social Media in Business

If you are having trouble viewing this video, then you can watch it on Vimeo by clicking on this link: Social Karma Video

To download the presentation as an Adobe Acrobat Document (.pdf file) click on this link: Social Karma Presentation 

The Complete Series

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 6) – Social Media Books

Social Karma (Part 7) – Twitter 

Social Karma (Part 7)

In Part 6 of this series:  We discussed some of the books that have been the most helpful to my social media education.

In Part 7, we will discuss some recommended best practices and general guidelines for using Twitter.

Frosted Cheerios are Yummy

In social media, one of the most common features is some form of microblogging or short message service (SMS) that allows users to share brief status updates.  Twitter is currently built on only this feature and uses status updates (referred to as tweets) that are limited to a maximum of 140 characters, which at first glance may appear to indicate an obvious limitation. 

Twitter is a rather pithy platform that many people argue is incompatible with meaningful communication, especially of a professional nature.  Most people who have never (as well as some who have) tried it, assume Twitter is a source of nothing but inane babble such as what its users are eating for breakfast.  I must admit that this was my opinion as well—at least at first.

However, Twitter is not only one of the most popular microblogging and social networking services, but if used effectively, it can easily become one of the most powerful weapons in your social media arsenal.

Twitter as Research

In addition to a listening station and an outpost (concepts discussed in Part 2 and Part 3), I use Twitter as a research tool.

Twitter provides near real-time updates about my online community and my areas of professional interest.  For example, the above tweet alerted me to an excellent LinkedIn discussion about the business benefits of master data management (MDM).

I chose this particular tweet in order to clarify an important distinction about Twitter.

Unlike other social networking services, you do not need an account on Twitter for read-only access to its content, which means that anyone could have seen this tweet.  (Of course, Twitter does provide privacy options for both tweets and accounts).

However, in order to click on the URL in this tweet and read the discussion from the Master Data Management Interest Group, you would require both an account on LinkedIn and need your group membership request approved by the group's owner.

Therefore, because it's not a “walled garden” you could leverage Twitter as a listening station only without creating an account.

With or without an account, Twitter Search provides the ability to search for relevant content.  Tweets often include embedded search terms called “hashtags” since they are prefaced with the hash (#) symbol.  You can also save search queries as RSS feeds.

If you are not familiar with how to use it, then check out my video tutorial by following this link:  Twitter Search Tutorial

Twitter as Social Networking

As we discussed in Part 5, the difference between connection and engagement is going beyond simply establishing a presence and achieving active participation within the online community.

Active participation can take on many different forms.  However, as we also discussed, “social media is not about you.”

A focus on helping others is what separates social networking from (especially shameless) self-promotion. 

In the example above, I was helping a fellow Twitter user promote his new blog.  However, conversations are better examples of social networking—and not just on Twitter.  Tweets between users can be public or private (referred to as direct messages). 

As with any public conversation, you should use extreme caution and avoid sharing any sensitive or confidential information.

The Art of the Re-Tweet

Re-tweeting is the act of “forwarding” another user's tweet.  Many bloggers use Twitter to promote their content by tweeting links to their new blog posts.  Therefore, many re-tweets are attempts to share this content with your online community.

A simple re-tweet is easy to do.  However, a few recommended best practices include the following:

• Make your re-tweets (and tweets) re-tweetable by leaving enough unused characters to prevent truncation on re-tweet, which is important since a link is usually at or near the end of the message and truncation would send a broken link
• If you are re-tweeting a link, verify that the link is neither broken nor spam—and if you're not sure, then don't re-tweet it
• If the tweet uses a URL shortener (e.g., a bit.ly link), then reuse it since the user may be relying on its associated analytics
• Space permitting, add relevant hashtags to the re-tweet to make it more compatible with related Twitter searches
• Prove that you're not a robot by providing a meaningful description of what you're re-tweeting (as in the above example)

Following, Followers, and Lists

The Twitter term for connecting with other users is “following.”  Unlike other social networking services, Twitter is not permission based, which means connections do not have to be first requested and then approved.

This creates two different perspectives on your Twitter world—those following you and those you are following.

Unless you only follow a few people, it is a tremendous challenge to actually follow every user you follow.  Twitter Search as well as tools and services (see below) can help with making following a more manageable activity.  Twitter also has a list feature that helps organize the users you are following—and you can follow the lists created by other users.

However, as we discussed in Part 5, social media is not a popularity contest.  Therefore, Twitter is not about the quantity of followers you are able to collect and count, but instead the quality of relationships you are able to form and maintain.

Twitter Tools and Services

Twitter tools and services that I personally use (listed in no particular order):

• TweetDeck – Connecting you with your contacts across Twitter, Facebook, and LinkedIn
• Digsby – Digsby = Instant Messaging (IM) + E-mail + Social Networks
• HootSuite – The professional Twitter client
• Twitterfeed – Feed your blog to Twitter
• TweetMeme – Add a Retweet Button to your blog
• Ping.fm – Update all of your social networks at once 

“Thanks”

I haven't performed the actual analysis, but I am willing to bet the word that appears most often in my tweets is: “Thanks”

I named this series Social Karma for a reason—beyond simply being a cute pun for social media.

I view the “Social” in Social Karma as the technical variable in the social media equation.  Social is the strategy for accomplishing our goals, the creation of our own content, the effective use of the tools—the technology. 

I view the “Karma” in Social Karma as the human variable in the social media equation.  Karma is the transparency of our intentions, the appreciation of the content created by others, the sharing of ourselves—our humanity.

The most important variable in the social media equation is the human variable. 

In other words, I want to say thanks to all of you for being the most important aspect of my social media experience.

In Part 8 of this series:  The series concludes with my Social Karma presentation for Enterprise Data World 2010.

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 6) – Social Media Books

The Wisdom of the Social Media Crowd

The Twitter Clockwork is NOT Orange

Video: Twitter Search Tutorial

Live-Tweeting: Data Governance

Brevity is the Soul of Social Media

If you tweet away, I will follow

Wordless Wednesday: March 10, 2010

Photo via Flickr (Creative Commons License) by: Skip The Budgie

Data Quality Mad Libs (Part 2)

Data Quality Mad Libs is an ongoing OCDQ series.

For the uninitiated, Mad Libs are sentences with several of their key words or phrases left intentionally blank.

Next to each blank is indicated what type of word should be entered, but you get to choose the actual words.

The completed sentence can be as thought-provoking, comical, or nonsensical as you want to make it.

Data Quality Mad Lib

“If you want to

_______________ (verb or phrase)

your

_______________ (noun or phrase)

initiative, then

_______________ (verb)

your

_______________ (noun or phrase)

that

_______________ (phrase)

is highly recommended.”

My Version

“If you want to doom your data quality initiative, then advise your technical stakeholders that ignoring the business context is highly recommended.”

Share Your Version

Post a comment below and share your completed version of this Data Quality Mad Lib.

Related Posts

Data Quality Mad Libs (Part 1)

Recently Read: March 6, 2010

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.

• Applying “Lateral Thinking” to Data Quality – Ken O’Connor applies some Edward De Bono wisdom to data quality using the analogy of water quality where a factory's water inflow pipes are downstream from its outflow pipes.

• Traditional Methods for Estimating Business Benefits of MDM – Larry Dubov of Initiate Systems examines calculating the return on investment for MDM using a simple business case scenario, and also provides links to several useful articles.

• 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. 

• The Battle for the (Master Data) Item Code Is In Full Swing – Andrew White examines the challenge of making MDM work with existing business applications, which often have their own custom business rules for governing master data.

• 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.

• Referential Treatment - The Open Source Reference Data Trend – Steve Sarsfield shares his excitement about the growing trend of open source reference data and its positive impact on the future of data quality and data enrichment processes.

• 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.

• Bridging the Gap between Data Governance and Technology – Marty Moseley of Initiate Systems bridges the “great divide” in data governance with CRUD—meaning Create, Read, Update and Delete—to create active online documentation.

• 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.

• Why Are Marketers So Bad At Measuring Social Media? (And How Can They Get Better?) – Nate Elliott of Forrester examines the challenges of measuring social media ROI, and recommends a three-step approach.

• 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.

• Nine Scientifically Proven Ways to Get Retweeted on Twitter – Dan Macsai of Fast Company shares with us some of what viral marketing scientist Dan Zarrella shared in his report about The Science of ReTweets.

• 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.

• The 6 Dangerous Fallacies of Social Media – Jay Baer examines six of the most common beliefs and expectations about social media and explains why they are all false.

• How to Measure Return on Investment in Social Media – Brian Solis explains that 2010 begins a new era of marketing, one based on information, rationalization, resolve, and the need to truly measure your return on investment in social media.

• Social Networking Starts the Relationship, Face to Face Clinches It – Terri Rylander reminds us although social networking allows us to interact with more people, it is always best to be able to follow-up the on-line greet with an in-person meet.

Book Quotes

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

• From Why New Systems Fail: An Insider's Guide to Successful IT Projects by Phil Simon – “It's all about the people making the decisions, using the applications, and running the projects.  No technology, regardless of moniker, implements itself.”

• From Pull: The Power of the Semantic Web to Transform Your Business by David Siegel – “Another word for semantic is unambiguous.  In the semantic web, we declare what we mean in precise, standardized terms.  Data that is semantic means exactly the same thing to any system or person who uses it.”

• 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

Adventures in Data Profiling

Data profiling is a critical step in a variety of information management projects, including data quality initiatives, MDM implementations, data migration and consolidation, building a data warehouse, and many others.

Understanding your data is essential to using it effectively and improving its quality – and to achieve these goals, there is simply no substitute for data analysis.

Webinar

In this vendor-neutral eLearningCurve webinar, I discuss the common functionality provided by data profiling tools, which can help automate some of the work needed to begin your preliminary data analysis.

You can download (no registration required) the webinar (.wmv file) using this link: Adventures in Data Profiling Webinar

Presentation

You can download the presentation (no registration required) used in the webinar as an Adobe Acrobat Document (.pdf file) using this link: Adventures in Data Profiling Presentation

Complete Blog Series

You can read (no registration required) the complete OCDQ blog series Adventures in Data Profiling by following these links:

• Adventures in Data Profiling (Part 1) – Series Introduction 
• Adventures in Data Profiling (Part 2) – Customer ID and Gender Code
• Adventures in Data Profiling (Part 3) – Birth Date, Telephone Number and E-mail Address
• Adventures in Data Profiling (Part 4) – City Name, State Abbreviation, Zip Code and Country Code
• Adventures in Data Profiling (Part 5) – Postal Address Line 1 and Postal Address Line 2
• Adventures in Data Profiling (Part 6) – Account Number and Tax ID
• Adventures in Data Profiling (Part 7) – Customer Name 1 and Customer Name 2
• Adventures in Data Profiling (Part 8) – Series Conclusion

Wordless Wednesday: March 3, 2010

Photo via Flickr (Creative Commons License) by: kmevans

The Circle of Quality

Explaining why data quality is so vitally important to an organization's success that it needs to be viewed as a corporate asset is unfortunately not an easy task to accomplish. 

A common mistake made during such attempts is failing to frame data quality issues in a business context, which leads the organization's business stakeholders to understandably mistake data quality for a purely technical issue apparently lacking any tangible impact on their daily business decisions.

An organization's success is measured by the quality of the results it produces.  The results are dependent on the quality of its business decisions.  Those decisions rely on the quality of its information.  That information is based on the quality of its data. 

Therefore, data must be viewed as a corporate asset because high quality data serves as a solid foundation for business success.

As the above diagram illustrates, quality is a fundamental requirement and success criterion all throughout the interconnected Data–>Information–>Decision–>Result business context continuum, which I refer to as The Circle of Quality.

The Circle of Quality

Peter Benson of the ECCMA explains that data is intrinsically simple and can be divided into one of two categories:

1. Master Data – data that identifies and describes things
2. Transaction Data – data that describes events

In other words, master data is an abstract description of the real-world entities with which the organization conducts business (e.g., customers and vendors).  Transaction data is an abstract description of the real-world interactions that the organization has with those entities (e.g., sales and purchases).

Although a common definition for data quality is fitness for the purpose of use, the common challenge is that all data has multiple uses—and each specific use has its own specific fitness requirements. 

Viewing each specific use as the information that is derived from data, I define information as data in use or data in action.

Although data's quality can be objectively measured separate from its many uses (i.e., data can be fit to serve as at least the basis for each and every purpose), information's quality can only be subjectively measured according to its specific use.

Therefore, information is being customized to meet the subjective needs of a particular business unit and/or a particular tactical or strategic initiative.  In other words, the information is being used as the basis for making a critical business decision.

The quality of the decision is measured by the business result that it produces.  Of course, the reality is that the result is often not immediate and also contingent upon a complex interplay of multiple business decisions.

The result can also produce more data, which could come in the form of new transaction data associated with either existing master data (e.g., sales to existing customers) or new master data (e.g., purchases from new vendors). 

Either way, with the arrival of this new data, yet another spin around The Circle of Quality begins all over again . . .

Conclusion

The Circle of Quality illustrates the interconnected business context continuum formed by data, information, decisions, and results.  Additionally, it demonstrates the need for a sustained enterprise-wide program of data governance and data quality, which is necessary for managing data as a corporate asset.

The Circle of Quality also helps illustrate the true challenge of root cause analysis, where poor quality could be occurring in one or more places within the business context continuum. 

And of course, even total quality management is no guarantee of success since it is certainly possible to have high quality data, derive high quality information from it, and then make high quality business decisions based upon it—but still get poor results.

However, it's also easy to imagine the highly questionable results produced when data quality is not considered vital to an organization's success.  Therefore, not managing data as a corporate asset is nothing less than extremely risky business.

Related Posts

Beyond a “Single Version of the Truth”

Poor Data Quality is a Virus

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

The Only Thing Necessary for Poor Data Quality

Hyperactive Data Quality (Second Edition)

The General Theory of Data Quality

Data Governance and Data Quality

The Data-Information Continuum

Social Karma (Part 6)

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.

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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

Wordless Wednesday: February 24, 2010

The Game of Darts – An Allegory

Photo via Flickr (Creative Commons License) by: Mike Burns

The Game of Darts – An Allegory

“Other than the people involved, what else do you need in order to play the game of darts?”

With this question, so began another one of grandfather’s life lessons. 

“Darts . . . a dartboard . . . and a scorecard,” I said slowly.

“Very good,” grandfather responded.  “Why do you need each one of them?”

“You throw the darts at the dartboard in order to score points and the scorecard keeps track of who’s winning,” I said.

“Excellent,” said grandfather.  “Now which do you think is more fun, keeping score or throwing darts?”

“Since I’m still too young to throw darts, I guess I’m supposed to say keeping score,” I sarcastically replied.

Grandfather gave me an icy stare.  He wasn’t a fan of sarcasm.

“Sorry,” I said quietly while looking down at my scuffling feet.  “But throwing darts is obviously more fun.”

“Yes, obviously throwing darts is more fun,” grandfather continued, “but keeping score is important as we previously established.  Now, which do you think is more fun, throwing darts or being the dartboard?”

“Huh? I . . . um . . . I’m sorry,” I stammered.  “I don't understand the question.”

“Do you think it would be fun being the dartboard?” repeated grandfather.  “Obviously, I do not mean you or any person for that matter, and I want to be very clear on this—especially if your parents ask—NEVER actually throw darts at anyone!  I am asking you to use your imagination and think about what the game of darts feels like from the perspective of the dartboard.”

I quietly stared at the dartboard while my eight-year-old mind struggled to make sense of the question.

“Don’t hurt yourself by thinking too hard,” grandfather joked.

“I don’t think it would be any fun at all to be the dartboard,” I answered in a soft and serious tone.  “I bet the dartboard doesn’t like this game at all.  I bet the dartboard thinks this game sucks—er, I mean—stinks.”

“Yes, the dartboard probably thinks the game is cruel,” grandfather replied.  “After all, it’s not like the dartboard ever gets to take a turn . . . and throw itself at the darts.”

Grandfather gave me a goofy grin and then he laughed out loud.  He was a big fan of laughter.

I giggled uncontrollably while my eight-year-old mind played a cartoon-like image of the dartboard throwing itself at the darts.

As we both slowly regained our composure, grandfather continued.  “Now, let’s imagine that the game of darts is an allegory, another way of thinking about something, such as three people having a conversation.  For example, you, me, and your brother.”

“Um, okay,” I replied.

“Let’s say your brother is upset and yelling at me about something,” started grandfather.

“Ha!  That’s easy to imagine,” I interrupted.  “Sorry, you were saying?”

“Your brother is upset—yes, easy to imagine but not the point—of the three required things necessary in order to play the game, which one is your brother?” asked grandfather.

“The darts!” I replied.

“And if he is yelling at me, which one of the three things am I?” asked grandfather.

“The dartboard—and that makes me the scorecard—why I am always the scorecard?” I whined.

“Settle down, I’m trying to make a point here,” grandfather retorted.

“You can’t make a point—you’re the dartboard—not the darts,” I mumbled.

“Very good smart ass—er, I mean smart aleck—yes, I am the dartboard and being the dartboard isn’t any fun, remember?” grandfather replied.

I quietly nodded my head, knowing not to push my luck with another sarcastic remark.

“But if nobody’s the dartboard,” grandfather resumed, “then your brother and I couldn’t be playing the game of darts, could we?”

I had previously been through enough lessons with grandfather that I knew what was coming next.

“So, what’s my p—what am I trying to say?” asked grandfather.

“Um, that when three people are having a conversation,” I slowly responded, “and one of them starts yelling at another, the one who is yelling is the darts, the one being yelled at is the dartboard, it’s no fun being the dartboard, no one likes getting yelled at, but . . . everyone needs someone to yell at . . . and needs someone else to keep score?”

“That’s pretty close,” grandfather replied.  “In most conversations, everyone is simply waiting for their turn to speak—their turn to throw the word-darts.  When it’s not their turn, they become the scorecard in order to track how the conversation is going.  The dartboard is usually the topic of the conversation—what they’re taking turns throwing the word-darts at.  However, when the conversation turns into an argument . . .”

“Then they start throwing word-darts at each other,” I interjected on cue, “taking turns turning each other into the dartboard, and nobody likes being the dartboard!”

“Correct!” said grandfather.

“But you also said that if nobody is the dartboard, then you can’t play the game.  I’m a little confused,” I responded.

“Yes, that is the most challenging thing about effective communication,” continued grandfather.  “Although no one likes being the dartboard, sometimes a dartboard is exactly what the other person needs you to be.  Other times, a scorecard is exactly what the other person needs you to be . . .”

“When they need to be the only one throwing all of the word-darts?” I asked.

“Correct!” said grandfather.

“Therefore, what you’re saying is that,” I thoughtfully concluded, “sometimes you’re the darts, sometimes you’re the scorecard, and sometimes you’re the dartboard.  You can’t play the game of darts unless you have all three.  Therefore, you can’t have effective communication unless you’re willing to sometimes talk, sometimes listen, and sometimes be willing to get yelled at.”

“That’s my boy!” said grandfather.  “You know, you’re pretty smart for your age.”

“That’s because I take after grandmother.”

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Wordless Wednesday: February 17, 2010

Data Quality Mad Libs (Part 1)

Data Quality Mad Libs is a new OCDQ series.

For the uninitiated, Mad Libs are sentences with several of their key words or phrases left intentionally blank. 

Next to each blank is indicated what type of word should be entered, but you get to choose the actual words. 

The completed sentence can be as thought-provoking, comical, or nonsensical as you want to make it.

Data Quality Mad Lib

“The most

_______________ (adjective)

thing about

_______________ (noun or phrase)

is that it

_______________ (verb)

your

_______________ (noun or phrase)

by essentially

_______________ (phrase)

your enterprise systems.”

My Version

“The most surprising thing about master data management is that it improves your customer data quality by essentially deleting every customer record from your enterprise systems.”

Share Your Version

Post a comment below and share your completed version of this Data Quality Mad Lib.