Welcome!

Industrial IoT Authors: Pat Romanski, Derek Weeks, AppDynamics Blog, Elizabeth White, Liz McMillan

Related Topics: Microservices Expo, Industrial IoT

Microservices Expo: Article

$3 Trillion Problem: Three Best Practices for Today's Dirty Data Pandemic

Maybe your software is healthy, but is your data terminally ill?

In survey after survey, about half of IT executives consistently agree that data quality and data consistency is one of the biggest roadblocks to them getting full value from their data.

This has been consistently true all since the Chinese invented the abacus. I suspect it will be true long after quantum computing has solved every other problem that humanity faces.

 

Incorrect, inconsistent, fraudulent and redundant data cost the U.S. economy over $3 Trillion a year - an astounding figure that is over twice the amount of the 2011 Federal Deficit.

Similarly, many experts estimate that HALF the money spent on developers goes towards "software repair". So we're living in a world of sick software and dirty data. And the cost of all this is staggering.

 

I've long been a proponent of healthy software - but healthy software can only function properly in the presence of healthy data. Does quality software even matter if the underlying data are defective? Agreed - that's pushing the point to the extreme.

The rapid, iterative, continuous testing model has measurably improved the quality of software development. Evangelists such as Kent Beck have had a huge impact on this. I recently posted a freely downloadable white paper on this topic. But where are the evangelists for data quality? Where is an open source "JUnit for Data" and if it's out there, why isn't everyone using it?

The Cost of Bad Data
Anyone care to make a guess at how much money is wasted every year due to dirty or duplicate / redundant data? I'll start by presenting one common user story - one you probably have also recently experienced. And then expand on it.

Recently, I went to my mailbox and waiting for me was yet another invitation from a major bank to join their credit card program.

This shouldn't come as a surprise, as people everywhere are deluged by credit card offers. Except that I already have the particular card in question. Not only that, but because the particular bank in question has managed to acquire a number of other banks and credit card lines of business, between my personal and my corporation, I believe I now have five Visa cards from this particular bank.

I also occasionally get mail from them offering me cash bonuses to open up a checking account at their bank. Probably wasted postage, as I already have two checking accounts there. I suppose I could open up a third, just to get the $100.

Every month, I get a significant number of expensive looking direct mail offers from this bank, often with slightly different variations on my name, which I promptly throw away. Aside from the impact on the environment and the wasted direct mail expense, it's a bit irritating to me. I hate junk mail, and I feel compelled to shred things like credit card offers. So they've burdened me (an existing customer) with yet another "thing to do". So they've spent money, hurt the environment, irritated an existing customer, and now I get to make fun of them online. Bad investment on their part.

QAS (an Experian company) estimates that the average company wastes $180,000 per year simply on direct mail that does not reach the intended recipient because of inaccurate data. But this is just one miniscule slice of the data quality issue. In fact it's only one small part of the "direct mail" data quality issue. A lot more money is wasted in "inappropriate offers" and "duplicate offers" such as the ones my bank sends. I also get offers from several companies that are convinced that I'm married to the previous owner of my house. Those offers reach me, yet are immediately shredded. No sense opening them. So the "big picture" just for direct mail is much larger than what QAS shows.

None of this accounts for the "irritation" factor - what is the cost of annoying existing customers (or potential customers) with badly targeted offers?

Yet direct mail and all other forms of advertising together add up to a tiny slice of the bad-data pie.

Fraud Is a Bad Data Problem
Some time back, the US Attorney General's office stated that they believed that 14 percent of health care dollars are wasted in fraud or inaccurate billing.

Why do I lump fraud in with "bad data"? Bad data comes in two forms - accidentally created bad data and intentionally created bad data (for example, fraudulent billing). Either way, it's bad data. It doesn't matter how it got there, it's defective. And a lot of it could be detected and remediated "at the point of entry".

Healthcare accounts for over 16% of the U.S. GDP (Canada is 10%, Australia is 9% as a comparison). The U.S. GDP is currently approximately $14 Trillion - therefore healthcare spending in the U.S. amounts to $2.25 trillion. And the cost of bad data in Healthcare- $314 Billion.

That's just for fraud or inaccurate billing. What about other areas in healthcare (e.g. lost data, "bad patient outcomes", duplicate patient testing, manual rework, etc.)?  Even if we round down, we're still taking about $500 Billion for one industry alone.  If I extrapolate that out to the entire U.S. economy, we're talking about a $3.1 Trillion problem.  No matter how far off my estimate is (on the high side or the low side), it's a problem of astonishing proportions.

Cost of Bad Data to Business and IT
A classic but very worthwhile book from information governance expert Larry English posits that the business cost of nonquality data may be as high as 10-25% of an organization's revenue, and that as much as 50% of the typical IT budget may be spent in "information scrap and rework".  If that is the case, then my $3.1 estimate is not out of line.

In the introduction to his book, English states "With this proliferation of information, the challenge of managing data and providing quality information has never been more important or complex."

That was in 1999. With so much more data today, and a surprising lack of attention to the data quality issue, I can only imagine the total economic impact of things today. I do not doubt that the cost of bad data has risen.

Dealing with bad data at the I.T. level is expensive. But if I.T. doesn't deal with the bad data problem, then the cost gets pushed downstream to the "business", where the business costs are geometrically higher. The model is not that different from that of "healthy software", where it costs $1 to uncover a defect during developer/unit testing, but $100 to fix that defect if the software is released to the end-users.

"Low Hanging Fruit" - Best Practices for Bad Data Avoidance
I am not saying that there are any easy fixes to the bad data problem. Even something as relatively simple as cleaning, standardizing and de-duping a mailing list with 10,000,000 entries is essentially impossible to get completely right no matter how much effort is put into it. Yet there are some relatively easy things that can be done to substantially improve the quality of our data.  As with so many other problems in life, the some version of the 80/20 rule applies to this as well.

Best Practice #1: When integrating data, fix the quality problem during integration
As data are added or integrated, data should be tested. Profiling is a simple, fast, relatively easily implemented and highly effective way for eliminating significant volumes of defective data.

When developers write a new application for the input of some new data, it's normal for input fields to be "validated" - a simple "hard coded" form of profiling. Month number needs to be between 1-12. 13 is never correct.  Not rocket science. And it's universally done.

Yet people have far fewer reservations about integrating data from here, there and everywhere - often not checking for even the most egregious data errors, and thereby polluting the organizational drinking water (i.e. all the data and applications downstream).

I strongly suspect that's why I get so many offers from my current mega-bank. Since the banking implosion, this particular bank has purchased every other bank around. And their credit card businesses. And their marketing databases. And (apparently) smashed them together. So I get offers for Hollis Tibbetts, Hollis W. Tibbetts, Hollis Winslow Tibbetts, Hollis Tibbets, Hollis Tibbitts and so on.

Integration of data isn't necessarily just a "big bang" event - like when one company acquires another and smashes all the data together, or when two divisional customer applications get merged. It can be more insidious and more when you have "trickle" integration - the slow feed of new data from one system into another (either within the organization or from customers/suppliers/partners).  This is the class of integration that is causing a lot of the problems previously discussed with healthcare fraud.

Either way, FIX IT before integrating it. Once the poison enters the corporate drinking water, it's a lot harder to get out (not just technically, but especially politically/organizationally).

Best Practice #2: When migrating data, fix the data problem as PART of the migration project
Spending $1 billion to upgrade your Seibel system like the US Government is doing? Sounds like a great time to fix your data quality problem.

If you're doing something like migrating your customer data from Seibel to Netsuite or Salesforce.com, data quality should be a major element in your project plan (and budget). Fixing the problems during the migration are easier than fixing them later:

  1. You probably already possess a lot of knowledge about the existing legacy systems, the types of problems in the data. But your new system is relatively unknown to you. So it's likely to be easier to fix data issues from a technical perspective BEFORE they get loaded into the new system.
  2. As part of the data migration process, you can export the data to a staging platform (On Prem or Cloud), leverage any number of data quality tools/engines, and then import the data into the the application platform.  This approach may partially pay for itself in an easier/smoother upgrade to the new application, but that's a rounding error in the overall scheme of things.
  3. Organizationally and politically, companies are much more likely to spend money to clean data if it's part of a project like "upgrade the CRM system". I'd hate to be the CIO that spends a mountain of money to upgrade the CRM system and then goes back to the board asking for another mountain of money to fix all the bad data that just got loaded into the CRM system. That's how CIO's become ex-CIOs.

Best Practice #3: Data profiling and data de-duplication engines
Data profiling engines are a great technology for quickly improving the quality of data as it is integrated from one system into another. At the highest level, they are an engine that scans data, and applies certain easily definable rules to data elements, such as formats, ranges, allowable values and can evaluate relationships between different fields.

Furthermore, these engines can also be used to analyze existing data stores very rapidly and generate "exceptions files" for manual, or semi-automated remediation (if anyone can find a totally automated data remediation system, I'd love to know about it). So they can be used in "continuous testing" or "batch testing" mode.  In batch mode, they're ideal for application migrations or big-bang integrations, as they're easiest to use them if you have your data in something like a staging database.  But they can also be used to test data as it is "trickle integrated" into production systems.

De-duping engines generally fit into the same category. I haven't seen them be as effective as data profiling engines, yet I believe they're essential. The technology for de-duping is considerably more sophisticated - with a large number of different algorithms and tunable thresholds and such. It's a harder class of technology to implement. More manual effort is involved. And, unlike profiling (where there is NEVER a month "13"), de-duping can "get it wrong", so the technology needs to be applied more selectively.

Conclusion
I've never understood why these engines haven't been more popular. There is no "JUnit for data" as far as I know. But commercial solutions are available - they're not terribly expensive and rapidly pay for themselves.

On the other hand, I've never understood why organizations are so tolerant of bad, dirty data. They waste millions and millions directly because of it (and untold quantities of money in "wasted opportunities"), but are reluctant to spend $15,000 on a data quality engine to help fix a significant portion of the problem.

More Stories By Hollis Tibbetts

Hollis Tibbetts, or @SoftwareHollis as his 50,000+ followers know him on Twitter, is listed on various “top 100 expert lists” for a variety of topics – ranging from Cloud to Technology Marketing, Hollis is by day Evangelist & Software Technology Director at Dell Software. By night and weekends he is a commentator, speaker and all-round communicator about Software, Data and Cloud in their myriad aspects. You can also reach Hollis on LinkedIn – linkedin.com/in/SoftwareHollis. His latest online venture is OnlineBackupNews - a free reference site to help organizations protect their data, applications and systems from threats. Every year IT Downtime Costs $26.5 Billion In Lost Revenue. Even with such high costs, 56% of enterprises in North America and 30% in Europe don’t have a good disaster recovery plan. Online Backup News aims to make sure you all have the news and tips needed to keep your IT Costs down and your information safe by providing best practices, technology insights, strategies, real-world examples and various tips and techniques from a variety of industry experts.

Hollis is a regularly featured blogger at ebizQ, a venue focused on enterprise technologies, with over 100,000 subscribers. He is also an author on Social Media Today "The World's Best Thinkers on Social Media", and maintains a blog focused on protecting data: Online Backup News.
He tweets actively as @SoftwareHollis

Additional information is available at HollisTibbetts.com

All opinions expressed in the author's articles are his own personal opinions vs. those of his employer.

@ThingsExpo Stories
So, you bought into the current machine learning craze and went on to collect millions/billions of records from this promising new data source. Now, what do you do with them? Too often, the abundance of data quickly turns into an abundance of problems. How do you extract that "magic essence" from your data without falling into the common pitfalls? In her session at @ThingsExpo, Natalia Ponomareva, Software Engineer at Google, provided tips on how to be successful in large scale machine learning...
If you had a chance to enter on the ground level of the largest e-commerce market in the world – would you? China is the world’s most populated country with the second largest economy and the world’s fastest growing market. It is estimated that by 2018 the Chinese market will be reaching over $30 billion in gaming revenue alone. Admittedly for a foreign company, doing business in China can be challenging. Often changing laws, administrative regulations and the often inscrutable Chinese Interne...
Why do your mobile transformations need to happen today? Mobile is the strategy that enterprise transformation centers on to drive customer engagement. In his general session at @ThingsExpo, Roger Woods, Director, Mobile Product & Strategy – Adobe Marketing Cloud, covered key IoT and mobile trends that are forcing mobile transformation, key components of a solid mobile strategy and explored how brands are effectively driving mobile change throughout the enterprise.
In his session at @ThingsExpo, Kausik Sridharabalan, founder and CTO of Pulzze Systems, Inc., will focus on key challenges in building an Internet of Things solution infrastructure. He will shed light on efficient ways of defining interactions within IoT solutions, leading to cost and time reduction. He will also introduce ways to handle data and how one can develop IoT solutions that are lean, flexible and configurable, thus making IoT infrastructure agile and scalable.
Data is an unusual currency; it is not restricted by the same transactional limitations as money or people. In fact, the more that you leverage your data across multiple business use cases, the more valuable it becomes to the organization. And the same can be said about the organization’s analytics. In his session at 19th Cloud Expo, Bill Schmarzo, CTO for the Big Data Practice at EMC, will introduce a methodology for capturing, enriching and sharing data (and analytics) across the organizati...
SYS-CON Events announced today that Bsquare has been named “Silver Sponsor” of SYS-CON's @ThingsExpo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. For more than two decades, Bsquare has helped its customers extract business value from a broad array of physical assets by making them intelligent, connecting them, and using the data they generate to optimize business processes.
Internet of @ThingsExpo has announced today that Chris Matthieu has been named tech chair of Internet of @ThingsExpo 2016 Silicon Valley. The 6thInternet of @ThingsExpo will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
Video experiences should be unique and exciting! But that doesn’t mean you need to patch all the pieces yourself. Users demand rich and engaging experiences and new ways to connect with you. But creating robust video applications at scale can be complicated, time-consuming and expensive. In his session at @ThingsExpo, Zohar Babin, Vice President of Platform, Ecosystem and Community at Kaltura, will discuss how VPaaS enables you to move fast, creating scalable video experiences that reach your...
A strange thing is happening along the way to the Internet of Things, namely far too many devices to work with and manage. It has become clear that we'll need much higher efficiency user experiences that can allow us to more easily and scalably work with the thousands of devices that will soon be in each of our lives. Enter the conversational interface revolution, combining bots we can literally talk with, gesture to, and even direct with our thoughts, with embedded artificial intelligence, wh...
In his keynote at 18th Cloud Expo, Andrew Keys, Co-Founder of ConsenSys Enterprise, provided an overview of the evolution of the Internet and the Database and the future of their combination – the Blockchain. Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life sett...
Cloud computing is being adopted in one form or another by 94% of enterprises today. Tens of billions of new devices are being connected to The Internet of Things. And Big Data is driving this bus. An exponential increase is expected in the amount of information being processed, managed, analyzed, and acted upon by enterprise IT. This amazing is not part of some distant future - it is happening today. One report shows a 650% increase in enterprise data by 2020. Other estimates are even higher....
SYS-CON Events announced today that SoftLayer, an IBM Company, has been named “Gold Sponsor” of SYS-CON's 18th Cloud Expo, which will take place on June 7-9, 2016, at the Javits Center in New York, New York. SoftLayer, an IBM Company, provides cloud infrastructure as a service from a growing number of data centers and network points of presence around the world. SoftLayer’s customers range from Web startups to global enterprises.
19th Cloud Expo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, will feature technical sessions from a rock star conference faculty and the leading industry players in the world. Cloud computing is now being embraced by a majority of enterprises of all sizes. Yesterday's debate about public vs. private has transformed into the reality of hybrid cloud: a recent survey shows that 74% of enterprises have a hybrid cloud strategy. Meanwhile, 94% of enterpri...
Businesses are struggling to manage the information flow and interactions between all of these new devices and things jumping on their network, and the apps and IT systems they control. The data businesses gather is only helpful if they can do something with it. In his session at @ThingsExpo, Chris Witeck, Principal Technology Strategist at Citrix, will discuss how different the impact of IoT will be for large businesses, expanding how IoT will allow large organizations to make their legacy ap...
In his general session at 18th Cloud Expo, Lee Atchison, Principal Cloud Architect and Advocate at New Relic, discussed cloud as a ‘better data center’ and how it adds new capacity (faster) and improves application availability (redundancy). The cloud is a ‘Dynamic Tool for Dynamic Apps’ and resource allocation is an integral part of your application architecture, so use only the resources you need and allocate /de-allocate resources on the fly.
SYS-CON Events announced today the Enterprise IoT Bootcamp, being held November 1-2, 2016, in conjunction with 19th Cloud Expo | @ThingsExpo at the Santa Clara Convention Center in Santa Clara, CA. Combined with real-world scenarios and use cases, the Enterprise IoT Bootcamp is not just based on presentations but with hands-on demos and detailed walkthroughs. We will introduce you to a variety of real world use cases prototyped using Arduino, Raspberry Pi, BeagleBone, Spark, and Intel Edison. Y...
The vision of a connected smart home is becoming reality with the application of integrated wireless technologies in devices and appliances. The use of standardized and TCP/IP networked wireless technologies in line-powered and battery operated sensors and controls has led to the adoption of radios in the 2.4GHz band, including Wi-Fi, BT/BLE and 802.15.4 applied ZigBee and Thread. This is driving the need for robust wireless coexistence for multiple radios to ensure throughput performance and th...
Internet of @ThingsExpo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 19th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago. All major researchers estimate there will be tens of billions devices - comp...
The many IoT deployments around the world are busy integrating smart devices and sensors into their enterprise IT infrastructures. Yet all of this technology – and there are an amazing number of choices – is of no use without the software to gather, communicate, and analyze the new data flows. Without software, there is no IT. In this power panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists will look at the protocols that communicate data and the emerging data analy...
According to Forrester Research, every business will become either a digital predator or digital prey by 2020. To avoid demise, organizations must rapidly create new sources of value in their end-to-end customer experiences. True digital predators also must break down information and process silos and extend digital transformation initiatives to empower employees with the digital resources needed to win, serve, and retain customers.