Data Gamification: No, not Angry Birds

Are you spending a lot of your time gaming your life away?  Maybe a little Angry Birds, FarmVille, World of Warcraft, or even Half Life.  Lets shift that energy over to your enterprise information management practice.  Whatever it is that makes gaming so enticing is what we should be bringing to the table to govern data. This is where gamification comes in to play.  For those that do not know what gamification is, gamification involves applying game design mechanic to applications to make them more fun and engaging.  

So Alan, how do we accomplish that?  Well, it is actually pretty easy.  

Step 1 - Monitoring

When shopping for an enterprise information management platform, you need to make sure you have the full package.  More often than not, organizations procure tools for profiling, cleaning, and mastering data but forget to make sure that the tool includes monitoring the data governance cycle.  How would you know that your data is improving if you are not monitoring?  

Step 2 - KPI and Goals

Now that you are monitoring your data, you need to think hard and fast at what your KPIs and goals really are.  The impact of your data quality must be quantifiable.  Don't fall in to the trap of cleaning your data for the sake of cleaning your data.  Look at your business processes and analyze where the true data management cost centers are.  Prioritize these cost centers and you will have your KPI and goals for the enterprise information management practice.

Step 3 - Gamification

Now that the KPIs and goals are established, let’s make this fun.  Look at the goals and cut them in to bite sized milestones.  For each milestone, make sure you provide a reward.  You might think this can be costly, but that is just not true.  You don't have to throw a lot of money in.  As a matter of fact, money doesn't always make us happy.  A badge or a leader board (playing on the human ego) can actually make us happier.  All we are really asking for is some street cred.

Autonomous Data Quality - Are we there yet?

Are you sick of making the same data quality decisions over and over again?  (Rhetorical)  Just like data, decisions should be viewed as capital, decision capital.  Decisions should be summarized and understood in a fashion so that future situations of similar nature can be autonomously resolved.  As new decisions are made, the data platform should evolve without the need to pull in a team of developers to add in more rules.  Come to think of it, why do we even need a team of developers to setup initial rules?  Plug, play, and learn.  Isn't that what we all want? Autonomous data quality.

What are you doing to make your data quality platform smarter?

Target Marketing without Data Quality - aka Shotgun Marketing

The retail social space has been buzzing about target marketing, but are retailers getting the result that they want?  More importantly, are consumers satisfied with how retailers are reaching out to them?  The answer is "not exactly".  Why you ask me?  Elementary my dear Watson.  Data Quality is missing.

More often than not, when retailers think of target marketing, they think about how they can better understand their consumer in terms of their historical actions.  If you buy x, you will likely need or want to buy y.  If you do a, you will likely do b.  This is indeed helpful; however, are retailers getting the complete picture of the consumer?  I recently bought an iPad online and then bought an iPad HDMI output cable from a brick and mortar store at the same retailer.   Guess what, a week later, they sent me a email asking me to buy an iPad HDMI cable.  WTF.  How could they not know I already bought an HDMI cable?  I used the same credit card so it was an easy layup to correlate the two transactions to me.  Super lame.  How can you target market to me if you do not even know who I am or what I have done?  Not very targeted.  Hence, target marketing without data quality is also known as shotgun marketing.  Shotgun marketing is not going to generate many happy customers nor will retailers prosper from it.

I would highly advise retailers (especially multi-channel retailers) to not only look at my history to target market to me, but also invest in making sure they have the full picture of their customer.   To have a true target marketing platform, you need data quality as the foundation.

Globalization of Data - Translation vs Transliteration - What does this mean to OUR world?

My professional life revolves around customer data, (not my customers) but the data of the customers of my prospects. Kinda like my friend's sister's husband's dog, except the data that I speak about is extremely important to me, because I can help the prospect make smarter business decisions... quickly and accurately. Think... in REAL time CLEAN & ACCURATE business analytics. The question that I'm about to pose is a challenge that I believe most in the data quality industry will have at some point, considering e-commerce internationalization and the global marketplace that has evolved over the past umpteen years... and not one vendor (to my knowledge) has addressed data internationalization in it's entirety.

For the past couple of months, I've been working on one of the largest projects of my career. The organization that I am servicing is extremely global in nature. Instead of listing the 196 or so countries around the world, picture the entire globe or world map to depict the area that this organization resides in. Did you know that there is over 6500 languages across the world? How do you match, merge, and dedup this data across every language in the world? This poses a challenge for some of the organizations that I'm currently working with, as well as any other global or international organization that cares about their customer data. Who cares about their customer data?! EVERYONE. So, how do you keep a single customer record up-to-date with a confident degree of accuracy?

What makes up a "typical" generic customer record?

Name
Address
Phone #
Email Address
Some sort of customer #

Address formats vary around the world. If you have a subset of data residing in a Japanese database or a French database, can you translate or transliterate this data to your headquarters in the US?

To be clear, I've included the definitions below:
Translate: turn words into different language: to reproduce a written or spoken text in a different language while retaining the original meaning.
Transliterate: transcribe something into another alphabet: to represent letters or words written in one alphabet using the corresponding letters of another.

So why would you want to transliterate the text of an address? Ultimately it wouldn't be valid, right?? No.

Languages such as Japanese, Cantonese, and Mandarin use characters such as "東京都" It's common in many Asian cultures to not be able to say/pronounce a word that has been translated. This is where transliteration comes into play, especially for First/Last Names.

Address standardization, translation, and transliteration is commonplace. There's a number of tools that link the USPS database and other international address databases across the world and provide a service "out of the box." Read this address: "Japan, 東京都中央区築地４丁目７－５" Can this be translated to English? Yes. But is the direct translation how you communicate it through words? I have no idea, and I'm sure your customer service rep, your marketing applications, or your central master data hub can't read it aloud either. Hence, the importance of both translation and transliteration.

Another concept to think about... Does your customer service application recognize when your CSR enters in William as Bill or Will? There are many answers to this question that result in a YES. I'll bore you with this piece another time. Actually, if you'd like to know the answer, I'll facilitate a meeting with you and my esse, Alan. He's the man.

I could also bore you with the common challenges of the internationalization of data as it relates to one common organization, however, if you're reading this you're probably familiar.

Back to transliteration...AND the challenge... I haven't found an organization, a library, or a service that will transliterate every language; or even a large subset for that matter as it relates to NAMES. It's 2011 people!!! How has this not yet been addressed? Or, has it?

-tc

P.S. Did you know? There are still places in the world that an address may be, 3rd building from the second sign after (fill in landmark) with the green door...

the esse and the account executive

Alan is one of the smartest people that I have ever worked with, and I have the blessing on a daily basis to work side by side with him. We are a team that will take the data industry by storm. Think Snoop Dogg and Dr. Dre in the Hip Hop world. Alan is my Solution Architect (SA, a.k.a. my "esse", as I'll refer to him for now on) and I am his partner in crime, enter... Thera, Enterprise Software Sales Professional--writing to you from the greater Los Angeles Area.

I believe that exposing my job title in my first blog post is essential to our success; the authenticity of our conversations moving forward. Sales is my job, and it pays the bills, however... keeping up to date (or ahead) of the data governance and enterprise information management industry including listening, reading, and subscribing to every source possible is essential to our success. My goal is to understand what's top of mind, what's relevant, what's changing today, and where are we going?

A differentiator between Alan and I, and the "typical" software sales team is that we're Gen Ys, and don't take sh*t. We are on the TOP of our game, we sip gin and juice, drop it like it's hot, and leaaaan back.

Kidding aside, Alan is a professional student. Although he graduated from Berkeley a decade ago, I have to believe that he still sleeps with his nose in between book pages, most likely on topics like MDM or data integration. Alan's drive and interest in everything IT, has motivated me to switch to the dark side. The geeky, nerdy... darkside.

We plan to continue to blog a consolidated view of the most relevant topics in the data industry. Follow along, (take naps as needed), as we discuss roadblocks, data internationalization, verticalized business rules, data quality, MDM, data integration, data governance, etc.

-tc

The big question - WHY?

The big question is why?  Why, Alan, are you starting a blog about data quality, master data, enterprise information management, and other dataphiliac topics?  Well, here you go...

Reason #1 - I heart data.
Having spent the last 49 dog years in the e-business space, I have learned the true power of data and can't seem to live without it anymore.  It is like coffee in the morning.

Reason #2 - Can I interest you in <somthing relevant>?
Whether it is selling to my wife to spend the rest of her life with me or selling my son that he should eat his vegetables, I have been a salesmen all my life.  To sell effectively, I have to understand what people really want, in other words, to be relevant.  One of the reasons I started this blog is to stay relevant so that I can create/sell products that people are actually looking for.  Social media turns out to be the best way to stay relevant in a timely manner.  Yes, "selling" sounds bad, but we all have to pay bills. :)

Reason #3 - Boneless chicken wings, anyone?
As many of you are aware, social media is full of noise.  While I am spending time listening to the social space with respect to data, I run in to lot of jibber jabber that isn't relevant.   I wish someone would filter out the bone and just give me the meat on a weekly basis.  Well, instead of wishing, I might as well just do it.

So here I am, writing a weekly curated consolidation of social chit chat on data quality, master data, enterprise information management, and other dataphiliac topics.