Big Data and Grocery Shopping?

One may not commonly think of Big Data and Grocery shopping in the same sentence, but Big Data is everywhere. It is a part of your devices, your T.V., and your weekly trip to the super market. Big Data is now being used to predict the future of products and hopefully ensure the quality of what we see on our store shelves.

Data was not always Big, in fact it started out very small. As creatures of habit, most people shop in patterns, buying the products they like and trust. These patterns are the type of thing shop owners would keep track of, allowing them to provide specific products for their clientele. Once this idea took on a larger scale it slowly transformed into Big Data, studying millions of consumers and products across the nation.

Recently a group of marketing scholars put together a study on consumers of a chain selling consumer packaged good over the course of two years. The data produced from this study allowed them to see a pattern between the consumers of a product and its success. Usually a product’s success is determined by the rate of its early sales, but what this group has found is that it is more telling to look at who is buying rather that how many are being bought. They discovered certain consumers have a knack for buying products that fail within a few years. These consumers happened to be well off individuals with larger families, people with the kind of financial safety to risk trying a new product on the shelf. This study birthed the idea to take this experiment to a larger scale.

These marketing scholars are now researching their theory on six major grocery stores across the nation, collecting mass amounts of data and searching for a pattern to support their previous findings. With this larger data set the researchers now believe they have a better chance at discovering the set of consumers who determine a product’s success. The more data collected from these types pf studies, the more we can use it to predict future success or failures of a product. With this type of future knowledge producers will be able to pull their product from the market more quickly if they see the patterns for failure, saving both the producers and consumers time and money.

As researchers continue to discover useful patterns in this marketing world, they hope to expand to other areas such as movies and movie theaters. To learn more about using big data to predict the future success of a product or how it can help companies save money, click here!

Taming The Big Data Beast

The future of big data has to do with the “Big Variety” problem or what Stonebraker likes to call “the 800-pound gorilla in the corner.” The problem dates back to the emergence of data warehouses in the 1990s and the need to “clean” and integrate the data coming from a number of data sources, making sure it conforms to a global data dictionary (e.g., “salary” in one data source is a synonym for “wages” in another). The process of data integration invented then, Extract-Transform-Load (ETL), is still used today.  But it doesn’t scale, argues Stonebraker, failing when you try to integrate data from thousands of data sources, increasingly a “business as usual” reality for many enterprises trying to tap the abundance of public sources now available on the Web, to say nothing of what’s to come with the emergence of the Internet of Things and the yet-to-emerge new-data-generating technology.

“The trouble with doing global upfront data models is that no one has figured out how to make them work,” says Stonebraker. “The only thing you can do is put the data together after the fact.” The solution is a mix of automated machine learning and the crowd sourcing of domain experts and the resultant startup, Tamr, was launched in 2013.

Despite businesses being told for years to abolish their data in order to thrive, award winner, Stonebraker says that we must instead preserve the “data silos”.  Stonebraker and his collaborators came up with a way to mask the data silos, super-imposing on them a layer of software that adapts to the constantly changing semantic environment of the organization, based on a human-computer collaborative process.

Preserving data silos is also about the future of the business. “Agility is going to be crucial to successful enterprises,” says Stonebraker, “and I don’t see a way to do that realistically without decomposing into independent business units. The minute you do that you either anoint a Chief Data Officer to keep everybody from diverging or you say, ‘look, run as fast as you can.’ I would err on the side of agility rather than standardization.”

Tamr is his “fourth attempt at doing data integration,” Stonebraker says, “and I think we finally got it right.” Not getting it right happens when you make it happen.  All of Stonebraker’s solutions involve some innovative take on known technological tradeoffs, all balanced against the cost of not just the technology but also the people and processes around it. The solution may not get one or more of the components right or will incur unforeseen costs when it is implemented in the real world. Or the timing could be off. “If you are too late, you are toast, if you are too early you are toast,” says Stonebraker. “There’s a lot of serendipity involved. You have to guess the market and lead it.”

Is there a future beyond the future defined by the three startups Stonebraker is currently involved with? “Right now I’m not interested in starting any more companies,” Stonebraker says flatly. But then he adds: “If I had more bandwidth, it would be what I’m working on at MIT right now, what we call Polystores.”

Again, this is an age-old problem, tackled before with the not-too-successful concept of “federated” databases. Today, it’s an extension and expansion (in my opinion) of the Big Variety problem, what happens after the data has been “curated” (cleaned and integrated). Following his strong convictions about the advantages of special-purpose databases and given the proliferation of not just sources of data but also data types, Stonebraker suggests that “it makes sense to load the curated data into multiple DBMSs. For example, the structured data into an RDBMS, the real-time data into a stream processing engine, the historical archive into an array engine, the text into Lucene, and the semi-structured data into a JSON system.”

Big Data’s future is really about simplifying the applications that are deployed over multiple, special-purpose database engines. “If your application is managing what you want to think of as a single database which is in fact spread over multiple engines,” says Stonebraker, “with different data models, different transaction systems, different everything, than you want a next-generation federation mechanism to make it as simple as possible to program.”

With Stonebraker’s “make it happen” attitude, we may just be one step closer to turning Big Data into Smart Data.

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New Procedures Reducing Installation Times and “No Shows” Result in Excess of $10 Million in Savings

Reliable Reports and Metrics Improve Customer Service

In the initial phases of the telephony over Hybrid Fiber Coax, one of the largest Multi-System Operators (MSO) in the broadband industry knew they had issues with both customer installations and customer satisfaction, but lacked the ability to identify the extent of the problems or the reasons behind them. The organization called upon Cliintel to develop a system to capture reliable, actionable data and to assist them with interpretation of that data.

The Business Issue:

The corporate telephony field operations group at the MSO needed a better understanding of the total installation process. This group was receiving conflicting information around the daily installs from disparate markets across the United States, each of which were performing thousands of installs per day. Reporting was not standardized, and the accuracy of information was very much in doubt.

To manage the situation, the MSO needed to:

• Identify which data was important to capture
• Design a reliable means to obtain the data
• Determine how to interpret the data

Management wanted to know the reasons for procedural problems during an installation, how long the installs were taking, and set a reasonable baseline a true time per task. Additionally, they wanted to find out the causes of the number of “no shows” for service appointments

As new procedures were adopted, installation times and “no shows” were reduced resulting in revenue generation in excess of $10M.

The Solution:

Cliintel worked with the MSO to identify and source all of the critical data points. This included creating Reason Codes to describe why an appointment was missed, cancelled or rescheduled. Additionally Cliintel resources created business rules for allocating technician drive time. Once the critical data elements were identified, an automated reporting system was developed and deployed. This system greatly reduced the “human error” element that had confounded earlier attempts at manually gathering data. Meetings were facilitated between the corporate and individual market groups to define the standards against which the data would be measured, such as: How long each type of job should take? The meetings were continued as reports were made available to the organization on a daily, weekly, monthly and quarterly basis. Charts, tables and graphs were utilized to help the organization understand the data. The meetings with the corporate and market groups continued to aid the organization in understanding what it was seeing and to develop strategies to deal with the identified problems.

The Results:
Trends were uncovered highlighting problems with provisioning efficiencies, installation times and customer satisfaction levels. These trends were identified in the reports and provided decision support and agnostic intelligence, actionable at the various levels within the organization. The publication of the results enabled the global installation standards team to identify new procedures to address the trends. As new procedures were adopted, installation times and “no shows” were reduced resulting in revenue generation in excess of $10M. A concurrent rise in customer satisfaction levels confirmed that the team had identified the important variables. This was a two-year project that left the MSO with a reporting tool that worked to help the organization understand and improve the daily installation process for the telephony product line across the enterprise.

We’re proud to help our clients solve tough problems and achieve stunning results. To see what kind of results Cliintel can deliver for you, please visit www.cliintel.com or e-mail askcliintel@cliintel.com.

Business Slide Show – Tips On How To Get Sponsorship For Your Business or Idea

Business Slide Show – How Do You Get A Sponsor? from Bill Decker

This won’t answer all your questions, but it is a good start for business development. Click Here for Business Talk Radio

Is Your Data Biased?

Leaders in business are handed extremely large amounts of data on their customer’s personal information. How do these business leaders decide what is good data. How do you determine that your data is unbiased? Here are some tips for how to identify the best possible data to inform your business decisions.

Be A Good Steward

Many business leaders invest in data governance, which designates staff to ensure quality and credibility of data. Whether it’s a chief data officer who leads an entire team, or a few dedicated employees, every organization needs at least one effective data steward to make sure data are being collected and handled properly.

Data collection conducted under stringent oversight enables business leaders to catch errors before that information is used to substantiate important decisions.

Data stewards can guard against misreading of data by emphasizing the importance of metadata—background information that defines the characteristics of data elements, said Manav Misra, chief science officer at CenturyLink Cognilytics.

“It’s not just a one-time thing,” he added. “Every time specific data is moved or touched, you have to ensure that the quality of the data is not compromised.”
Scrutinize Data Vendors

It’s one thing for an organization to rely on data that it has collected. But what about data generated by outside sources? Misra recommends applying the same level of scrutiny and control to both internal and external sources.

Ask third-party vendors if they can certify the data they’re providing, he advised. Does the vendor have a data governance program in place? What about logs that record how data is modified? Can the vendor see how the data originated, what path it took to get to your organization, and who touched it along the way?

Don’t be afraid to hold the bar as high for outside vendors as you do for your own business, he said.

Ask The Right Questions

Whether a business leader relies on internal or external sources of data, it’s critical to ask the right questions about how the information was collected, Misra said.

There are many biases that can impact data sets. Confirmation bias occurs when the person who does the analysis selects data that support a certain hypothesis or belief, he said.

Selection bias can occur when data are skewed because of the way that it’s collected, such as when a particular group is either excluded or over-represented in a survey.

To better understand how data are collected, business leaders should ask for details about the data model, or the framework used to organize the data. When a statistical model is too complex, it does a poor job of “generalizing,” or predicting future outcomes, Misra added.

Watch For Red Flags
Even when business leaders do everything they can to ensure that their data are accurate and unbiased, errors can still occur. That’s why it’s important to watch for red flags, including fluctuations in new data that is collected, Misra advised.

If data results vary widely from one report to the next, it could indicate that something is wrong in either the underlying data or in the analysis that was performed, he said.

Business leaders should also lean on their business knowledge to ask questions, Misra added. That’s what one credit card company business leader did when an analyst presented him with results that seemed to imply that the average customer had about 100 checking accounts. The business leader immediately disputed the conclusion and decided that the rest of the data was suspect as well.

Don’t be shy about investigating the quality of the data presented, or the analysis that was done, when the information defies experience and common sense, Misra said.

If businesses take the time to become trained in the basic understanding of what constitutes good data, they will reap the many benefits it will produce. To be a data driven business you must ensure the data you are receiving is the good data you can transform into solutions.

To read the full article click here.

Streamlined Reports Save Time and Money – Save With Data

Reducing Reporting Redundancies, Targeting and Consolidation Save 250 Hours per Month

Broadband operators rely on the billing systems to provide them with accurate and timely reports. These reports are crucial to day-to-day operations, and are increasingly important for both strategic planning and the execution of business goals.

The Client:

A region in one of America’s biggest Multi System Operators responsible for 250,000 customers.

The Business Issue:

The client was using time intensive manual processes to develop reports required to support ongoing business. Various queries were used to retrieve data from the billing systems, often times delivering inconsistent results across differing reports. The standard practice was to run and merge multiple reports from these queries, then copy the results from these queries and other sources into spreadsheets for further manipulation, all to arrive at questionable data. Coordination of reports between departments and groups was non-existent and there were no standardized Methods and Procedures (M&Ps) for developing these reports. The reporting group was stretched beyond capacity resulting in a multi-week backlog for the generation of new reports. The client retained Cliintel to help streamline and document the reporting process.

By identifying redundancies and targeting inefficient processes Cliintel achieved a reduction in internal resource workload by 250 hours/month, improved report accuracy, increased customer satisfaction and a return on the investment in less than 4 months.

The Approach:

Cliintel takes a holistic approach to every business issue presented for resolution. Our project professionals evaluate the situation, design a solution that fits, gain adoption and optimize performance. Cliintel’s focus was on increasing productivity and reducing costs by examining and evaluating reports for each department – independently and thoroughly. Using this holistic approach, Cliintel interviewed and met with end users in 8 departments to assess their reporting needs and to identify redundancy. Cliintel performed a gap analysis and inventoried and performed an audit of many of the crucial reports needed for day to day business operations. Labor intensive and inefficient manual processes were targeted and re-engineered. Consolidation opportunities were identified and redesigned.

The Solution:

Cliintel designed and developed new queries extracting only the relevant data necessary for each report. Database clean-up tools were created to ensure the accuracy of the data and work processes were streamlined to consolidate redundant reports.

Additionally Cliintel:

• Identified and re-designed current reports and procedures
• Implemented a strategic plan that included process re-engineering and system enhancements
• Implemented a KPI plan and provided ongoing KPI analysis framework
• Provided recommendations for further enhancements
• Provided a base for future reporting development

The Results:

By identifying redundancies and targeting inefficient processes Cliintel achieved a reduction in internal resource workload by 250 hours/month, improved report accuracy, increased customer satisfaction and a return on the investment in less than 4 months.

We’re proud to help our clients solve tough problems and achieve stunning results. To see what kind of results Cliintel can deliver for you, please visit www.cliintel.com or e-mail askcliintel@cliintel.com.

3D Printing, Sensors and Data Science Coming to America’s Factories

A new study from consulting giant McKinsey says factories are the next fertile ground for the “Internet of things.”

While the current trend toward automation and reduction of standard factory floor staff will continue, Kaas added that “any skill set which truly requires handling of data and analytics” will be highly in demand for manufacturers in the next decade.

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Bringing Life to Design: Data Science in 3D – Autodesk‘s Mike Haley

Want to solve your tough problems and achieve stunning results with big data?

Cliintel is a data analytics company that helps you make your business strategy happen. Their business systems and insights work hand in hand with your business strategies extracting the actionable intelligence that will help you accomplish your goals.

Evaluation and Replacement of Subscriber Management System Enables Rapid Growth

For the burgeoning satellite radio industry, competition drove the market. Improving service delivery meant the difference between continued growth or a quick decline. To address this, the client, one of the world’s most aggressive providers of satellite radio, chose Cliintel to align its billing and operational support systems. The success of this project enabled the satellite radio provider to achieve their aggressive implementation objectives and advance their competitive position.

The Client:

The client, one of the largest satellite radio service providers offering a digital radio service that transmits 100 streams of digital-quality music and entertainment from its broadcast studios.

Through the utilization of Cliintel’s evaluation framework, the client was able to select the new billing system, configure, implement, convert the old data and scale the new system to 4x its original size in less than 7 months.

The Business Issue:

For this industry, the Subscriber Management System (SMS) holds the key to service delivery, facilitating gains in market share and ultimately shareholder returns. The client knew that their current SMS had functional shortcomings that were directly impacting its ability to collect revenue as well as provide the desired level of customer service. The system needed evaluation, and the client was prepared to implement a replacement if necessary. The client needed an aggressive assessment and plan that would work within operational and financial constraints.

The focus of the project was to evaluate the current billing system, define desired functionality and select a replacement subscriber management system if necessary.

The SMS needed to:

• Capture and make available timely, accurate, customer and partner data
• Enable testing and timely implementation of new services, marketing programs, and strategies to leverage continued growth
• Contribute to the growth and retention of customers, as well as partners, with cost-effective, reliable technologies.

A system strategy would also be developed to enable the client to grow the business aggressively, accommodate new business models, and respond to changing business conditions, without undue expense or over-reliance on manual processes and procedures.

Through the utilization of Cliintel’s evaluation framework, the client was able to select the new billing system, configure, implement, convert the old data and scale the new system to 4x its original size in less than 7 months.

The Solution:

Cliintel broke down the work structure into smaller, more manageable processes, which ensured the capture of all business-critical requirements. The methodology allowed for the collection, documentation and prioritization of system requirements without disrupting the ongoing operations of the client, or placing an undue burden on the team members who represented the functional areas. From this foundation, a requirements matrix was developed that enabled the client’s executive steering committee to highlight current critical business needs as well as identify areas requiring enhanced scalability.

Cliintel performed an SMS Gap Analysis on the current system, focusing on the best-practice constructs of features and functionality, adaptability, vendor risk, architecture and scalability, deployability and economics. As a result of this analysis the steering committee concluded that their current SMS provider lacked the stability and scalability the client would require. Cliintel was further engaged to help find a more suitable replacement solution.

This process involved an initial request for information (RFI) from 45 SMS service providers. Cliintel tailored the information requests to the clients business and system requirements and the same six constructs that were used to evaluate the legacy system. Analysis of the responses to the RFI led to the identification of the top five SMS providers, which were sent requests for proposals (RFPs).

Cliintel reviewed the RFPs and created executive “wrappers” for the steering committee, highlighting their evaluations. Invitations for product demonstrations were sent to the best candidates from this group. Cliintel created scenarios to test the extent of product functionality provided by the vendors. Cliintel also created scorecards to assist the client in ranking vendor performance during the demos.

Based upon the demonstrations, requested documentation, and interviews with the potential provider’s customers, Cliintel worked with the client in the selection of their new SMS provider. In addition, Cliintel created a high-level implementation plan and cost-estimates for the implementation, integration and management of the recommended solution.

The Project Results

Cliintel’s SMS evaluation allowed the client to select a system more suitable for their expanding business needs while keeping their focus on their core business. By prioritizing the requirements, the gap analysis enabled functional departments to more fully understand their business and establish a common goal. Through the utilization of Cliintel’s evaluation framework, the client was able to select the new billing system, configure, implement, convert the old data and scale the new system to 4x its original size in less than 7 months.

We’re proud to help our clients solve tough problems and achieve stunning results. To see what kind of results Cliintel can deliver for you, please visit www.cliintel.com or e-mail askcliintel@cliintel.com.

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Displaying a framed Broadway playbill, is the perfect way to treasure a special memory. My Forever Treasures is pleased, to offer our most iconic playbills.  They bring alive, those great theater experiences. Every show was declared, the event of that Broadway season.  This new home decorating rage, allows you to share, each great show with everyone. Framed on your wall, Judy Garland’s Two-A-Day at the R.K.O. Palace Theater Playbill will put a smile on everyone’s face. Just as Garland did, in the “Event of 1951.” She sang all of her classics, for 9 S.R.O. months. Critics and fans celebrated every song. CLICK HERE: 1951 JUDY GARLAND 2-A-DAY AT THE PALACE PROGRAM       Barbra Streisand, in 1964’s “Funny Girl” playbill, will have everyone remember the 2 songs, “People” and “Don’t Rain On My Parade.” They made Streisand a superstar. CLICK HERE: VINTAGE 1964 BARBARA STREISAND FUNNY GIRL BROADWAY PLAYBILL       1960’S  “An Evening With Mike Nichols and Elaine May“ playbill,  offers their Grammy Award winning comedy show. Incredible improvisational skills and world class wit,  had them revered, as the best comedy duo of any year. Long before winning, an Academy Award for Directing “The Graduate,” Mike Nichols was […]

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Stretching Myths, Types of Stretching and Stretching Exercises

Stretching, in its most basic form, is a natural and an instinctive activity. Stretching results in a feeling of increased muscle control, flexibility, and range of motion.

There are four different types of stretching: ballistic, dynamic, proprioceptive neuromuscular facilitation, and static stretching.

By performing slow controlled stretches through full range of motion, a person reduces risk of injury.

5 Stretching Myths
To stretch or not to stretch? That is the age old question. Here’s everything you need to forget about stretching, and everything you should know instead.

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Stretching: What To Do and When To Do It
There are several variations of stretches to improve your range of motion. Why? Better range of motion means improved strength, which leads to speed and power.

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Stretching Exercises
Stretching exercises and workouts. Learn from experts using this stretching exercise database filled with detailed instructions and video.

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Big Data Video Show – What Shouldn’t You Do With Your Big Data?

Here is a quick slide show about what Big Data does and what you should never do with your data! It takes a minute and can save you a lot of time and hassle.

Where is Big Data Going Next?

With Big Data dipping its toe in just about every field it can, we must wonder, where will it go next?  Almost everything from health to sales and marketing has been positively affected by Big Data and data analysis, but there has to be more areas that can benefit from this service.  This great Podcast on Big Data predicts that the next big field for Data Analysis is 3D Printing. What do you think? Will 3D printing benefit from Big Data or will the next big thing be something else?

Take a few minutes to listen to this new and exciting news and decide for yourself!

Global Business and Big Data – You Are In The Big Data Business

Big data is becoming one of those overused buzz words. You can’t turn on a website or look at a social media app without reading about big data. However, like many overused buzzwords, most people don’t know what it means.

Rich Batenburg Jr, of Cliintel in Denver has been involved in what we call big data for 20 years. He refers to his firm as “data scientists.” Batenburg defines big data as “having many facts across many dimensions of your business. Data Science allows you to pivot to understand what is going on now and let you forecast what will be going on in the future.”

In other words, big data is multiple data sources which are created by many systems.

Big data can also refer to big websites with big user groups and big amounts of information collected.
Just about everyone has big data. This is due to the facts that .processing has become so cheap. Companies have many applications, many businesses units. This gives firms more facts than they can possible digest. More and more administration systems create more and more data.

Inexpensive processing means we can collect and store and share more data. As an example, today’s Iphone has more processing power than all the computer power on the spacecraft NASA launched in the 1960’s. Just for fun and a slightly different bend…what’s on board for free on a Mac has more tools to record music than the Beatles ever had!

The trend is that everyone is harvesting everything. In another example, a 1 terabyte hard drive now costs $80 and you can be bought off the shelf at any retail electronics store. Batenburg compares this to spending $1 million for same storage space 10 years ago.

So is it logical that big data can be the next big global industry? Both Batenburg and I say: “It already is!”
Batenburg argues that is has been a large global industry since 2008. Every time someone logs into a website, they are giving out information. It may be their name and address, their credit card information or simply their search behavior. We know that Google knows what you initially looked for, what you looked for additionally, how long you spent on its site, what time of day it is, where you are, what you searched for in the past and whether or not you searched for same thing more than once, among many other “data bytes.”

Are Facebook likes and page rankings from Mexico useful to us? Can U.S. firms harness this data to understand Mexican buying habits better? Will we get any insight as to how to manage our own Mexican employees? Can we sell that data right back to companies in Mexico? Are there any other companies out there that might want this user-generated insight to understand Mexican markets?

In a simple example, if we knew Mexicans didn’t spend any time on sites that look purple, and didn’t search for purple things and didn’t buy purple goods it might help us a pick a color for our new line of sportswear. It could certainly help us rule out purple! And that is only a small part of what we might learn with a few million Google searches..

When Egyptian children can bring the Egyptian government down with data, it shows the changing landscape and importance of this tool. A Harvard dropout creates a website with 1 billion users. Kids with smart phones topple a totalitarian regime.

If you want to hear Batenburg and I speak, tune into this International Business Podcast on big data.

Whether you like it or not, you are in the big data business.

3D Printing Video Shows 13 Cool Things To Make With a 3D Printer

Here are some fun things you can make with a 3D Printer. This is a good way to show the capabilities of 3D Printing.

Good Luck to All Our Players This Week! – ProWorld Tennis Academy

Good luck this week for our players!!!
G.Mina in Tampere 42,5K
N.Osaka in Granby 50K
A.Mannarino in Bogota ATP 250
M.Osaka in Sacramento 50K

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If Big Data Can Help Save The Planet, So Can You!

With Climate Change becoming an ever increasing threat to our planet, Big Data is joining the fight against it! These five Big Data projects are arming environmental researchers with new and informative tools to combat the our planet’s almost certain doom.

Google Earth Engine

Google earth’s satellites have been able to capture images of our earth for decades. Data analysts are compiling these images from previous years and tracking how the climate has transformed the earth. Through this data we can see patterns and alert trouble areas so that environmentalists can focus on the areas in most need. Even though this sort of intelligence is new to many researchers, it is beginning to become known the scope of opportunity here. Researchers can now have an analysis for the entire continent dating back at least 40 years!

Microsoft Research’s Madingley Model 

Microsoft has created an early prototype graph that simulates all life on earth. Through this technology Microsoft hopes to be able to see how climate changes affect different animals across the continent. This will allow scientists to predict the security of our main food sources such as fish.

Data.gov’s Climate 

Data.gov is like a warehouse for climate data. Ranging from earthquakes to temperature changes, this database hold all of the information for the earth’s climate. Data.gov has housed all of this data in one library making it an excellent resource for researchers. The more information we can find and give to researchers, the closer we will become to a cure for climate control.

Global Forest Watch

Since the 90’s Global Forest  Watch has been trying to provide up to date information on the status of our forests. It wasn’t until recently that they were able to launch a satellite to collect this data and maintain a current update on forests around the world. Through this data feed we will be able to keep a close watch on the status of the forest and be more aware of trouble areas.

Opower

Opower works with consumer companies to analyze the energy consumption of individual homes and create a personalized report that they then publish to the community. Once a consumer discovers their neighbor is conserving more energy than they are, the consumer is naturally more inclined to up their saving. We are a competitive species and through the use of this data, Opower is able to motivate households to fight to be more conservative.

Through these five Big Data projects researchers are taking huge leaps in their fight against climate control.

Update on the Latest Colorado Court Cases and Immigration News

Colorado: Immigrant Leaves Sanctuary After 9 Months A Mexican immigrant who lived for nine months in the basement of the First Unitarian Church in Denver to avoid deportation left the sanctuary Tuesday and returned to his home nearby, after immigration…

Congrats to Adrian Mannarino Reaching Quarterfinals in Newport ATP 250

Congratulations to Adrian Mannarino who reached the quarterfinals in Newport ATP 250 after beating Tommy Haas and E. Roger Vasselin. Next week Bogota ATP 250. ‪#‎atp‬, ‪#‎adrianmannarino‬, ‪#‎proworld‬ #proworldtennis

Okay, Okay, We need to go vertical. Now what?

Lots of our customers have come to us after reading our most recent report, To Be or Not To Be an ISV?, and are saying, “we agree that we need to focus on one or more verticals, but which ones?” It sounds like a simple question, but is it? Do you go for ones you are good at? Ones that are easy? Ones that are really big? Traditional or not? How do you decide?

The most successful of our customers take a very focused approach to answer this question. It’s an important decision that requires some work, but it’s very possible to do a compact and clear analysis to come up with one or more verticals on which to focus, and be all but certain they are right for you.

Whether you decide to embark on this yourself, or to seek help from an outside party, here are the key questions we think should be answered:

• What are the top verticals in my portfolio by merchant count and by business volume?
• What verticals am I selling the most of (this may be different from my overall portfolio due to changes over time)?
• Which verticals make me the most money?
• In which verticals do I have core competencies and/or competitive advantage?
• What’s a really good opportunity for me based on my competencies and advantage, the size of the segment, competition, and potential margin?
• What products do I need to maximize that opportunity? What compelling value propositions can I offer?
• What channels do I need to penetrate that opportunity? How can I activate those channels?
• What partners can I enlist? What’s in it for them?
• What competitors will I have? How can I differentiate my offerings from theirs?

I hope this is helpful as you work to refine your market focus. If you have questions, please feel free to email me, or we can set up a call. We can discuss ideas, I can answer questions, or if you are interested, we could frame up a project where the Double Diamond Group experts can help you answer these questions and get your strategy jump-started.

Contact The Author

Todd Ablowitz

President of Double Diamond Group

todd@doublediamondgroup.com

(303) 916-9997

About Double Diamond Group

Denver-based Double Diamond Group LLC provides expert consulting services to the global electronic payments industry. Founded by industry veteran Todd Ablowitz, a former ViVOtech and First Data senior executive, Double Diamond Group helps payments industry clients solve their most critical business challenges with a unique blend of experience, connections and know-how. From venerable leaders to promising start-ups, Double Diamond Group works with companies of all sizes from around the world, including processors, acquirers, ISOs, agents, vendors, suppliers, service providers and merchants.

Denver Top 10 Destination for People Relocating – Is There A Housing Bubble in Denver?

The top 10 moving destinations for 2014 in the report are:

Atlanta (No. 1 for five years running).
Tampa/Sarasota (No. 2 in 2013).
Dallas/Fort Worth (No. 3 in 2013).
Phoenix (up from No. 5 in 2013).
Orlando (down from No. 4 in 2013).
Seattle (up from No. 7 in 2013).
Denver (up from No. 9 in 2013).
Houston (down from No. 6 in 2013).
Chicago (down from No. 8 in 2013).
Las Vegas (No. 10 in 2013).

READ MORE

Is there a housing bubble in Denver?

Many people in the Denver area are wondering whether the rising home prices we’re seeing are indicative of a bubble. Today, we discuss what recent trends mean for our market and whether they are anything worth worrying about. The answer might surprise you

Why Wait To Save Money?

By now most people know that there is a surge of companies jumping on the Big  Data train but, why? Some companies are skeptical of what Data Analytics  can really do for them.

Does our company gather enough data? How can we solve our problems if we are receiving our data too late? Aren’t Data Analytics expensive? How do I know I will make my money back?

These questions are the reason why companies are dragging their feet. A solution to problems such as receiving data too late is Predictive Analytics. Predictive Analytics is a system in which data analysts study the trends and patterns to identify key opportunities for improvement. By analyzing mass amounts of data and standardizing it in a way that can be understood, data scientists allow the company to make quicker, more informed decisions. Through becoming more efficient, companies save more money and often greatly exceed the original cost of analytics.

Some companies may question the accuracy of prediction, but it is better to make decisions with predictive insight rather than blindly guessing. Predictive analysis gives companies the opportunity to see trends in their history so that they may change certain elements and become more efficient. It is the companies who choose to blindly move forward who will be doomed to repeat the failures of their past.

For more information on how Data Analytics can save your company money CLICK HERE to check out this great site!

3D Printing Classes and 3D Printing News From the 3D Printing Online Course

Check out the 3D Printing MBA. It will keep companies from spending way too much on unnecessary expenses and teaching the business side of 3D Printing. In coordination with the Association of 3D Printing, the course promises to keep entrepreneurs and executives on track for the fundamentals of running any 3D Printing business.

3D Printing Companies – Which 3D Printing Firms Will Succeed? from Bill Decker

Flameproofing Fabrics, Upholstery Fire Safety and Flame Retardant Fabrics Testing on Sofas

A video showing the difference between untreated fabrics and ones that are flame retardant.

Improved Utilization of the Ticketing System Results in Savings of $75,000 per Year – Save With Data

Redesign and Tuning of Business Systems Optimizes Growth

Growing the business is the goal for most organizations. Managing that growth becomes difficult while managing and meeting the day-to-day business goals. Cliintel provides real world experience to facilitate operational improvements, create best practices and take businesses to their next level of success.

The Client:

A leading provider of insurance for new housing construction as well as appliance and home warranty services had experienced exponential growth. This growth began taxing internal systems, specifically the IT department’s trouble-ticketing system.

The Business Issue:

When organizations experience extreme business surges, much of their time, money, focus and resources are spent upgrading and adding customer facing applications while internal systems are pushed to their limits, or even neglected. The client’s IT department found itself needing to support both a myriad of new tools on multiple platforms, as well as an onslaught of new employees. The rudimentary trouble ticketing system they had been using for years was not capable of responding to the rapid growth. The increased utilization of the ticketing system soon revealed that the system and associated processes did not support adequate problem identification, timely resolution or proactive trend reporting. Furthermore, established and ‘rightsized’ Service Level Agreements had not been baselined or followed and resulting in longer than necessary system outages and downtime.

The new and improved utilization of the ticketing system resulted in a cost savings of $75,000 per year and created an enterprise repository and improved management of resources.

The Approach:

Utilizing Cliintel’s INSIGHT methodology, the team took a holistic view of the client’s business operations, and through a series of end-user interviews and operational observations, gathered system and user requirements. Existing contractual commitments required that the client continue to use the existing trouble-ticketing system. Cliintel examined the existing system and identified features and functionality not being used and presented a plan to modify and upgrade current versions to meet the growing needs of the client.

The Solution:

Cliintel worked with the trouble-ticketing vendor to complete system reinstallation and improved report development. The trouble-ticketing system was redeployed with appropriate support, documentation and procedures. Cliintel established modified procedures and standards to facilitate disciplined ticket management.

The Results:
The reimplementation of the trouble ticketing system enabled the client to reduce system outages and proactively prevent future outages from occurring. The new and improved utilization of the ticketing system resulted in a cost savings of $75,000 per year and created an enterprise repository and improved management of resources.

We’re proud to help our clients solve tough problems and achieve stunning results. To see what kind of results Cliintel can deliver for you, please visit www.cliintel.com or e-mail askcliintel@cliintel.com.

Accurate Forecasting of Technician Availability Provides Customers with a True Appointment Promise

Across the Telecommunications industry, the belief in “fixing quota allocations” is pervasive. This belief stems from the desire to create efficient service delivery. The issue is that there is no simple fix, no “silver bullet” to deliver on this belief. Over the past 15 years broadband service providers have consolidated operations and added multiple product lines to consumer choices. Over the same period however, back office tools and associated processes have not been enhanced to efficiently match the new complexity and scale of the business. As a result, business applications that are tied to the billing systems, which have become default Customer Relationship Management tools are ill suited to modern business requirements.

By strategically implementing the best practice recommendations, the MSO has recognized reduced costs associated with repeat truck rolls, improved completion rates and decreased customer churn.

The Client:

One of America’s largest Multi System Operators (MSOs) has been acquiring new systems and adding advanced services. The MSO was reliant on incumbent cable billing systems and quota management tools for scheduling installation and service appointments. This condition was not going to change near-term so they needed a way to improve current operations to more accurately reflect technician availability as well as forecast future appointment needs.

The Business Issue:

Because of inaccurate forecasting, technicians were consistently arriving late or missing appointments; repeat truck rolls were increasing and customer satisfaction was decreasing. Manual processes were prevalent and subject to manipulation based primarily on the instinct of the quota management resource, not by set business rules. The MSO needed to implement new processes and practices to enable quota to be more accurately calculated and forecasted.

The Approach:

Cliintel takes a holistic approach to every business issue presented for resolution by designing and implementing solutions that cross traditional silos. This holistic approach was used to complete the discovery process while observing current quota management methods. Cliintel focused on procedures and operational practices that impact the creation and utilization of quota. Questionnaires were used to collect pertinent data prior to the site visits. While on site, current process discussions were held with key system personnel.

Cliintel completed first-hand observations of the quota management process and its impacts upon operations. Relationships were developed with the essential system personnel, ensuring anonymity to increase the level of honesty and data integrity. During the site visits, specific attention was placed on the identification and documentation of activities of quota influencers and impactors. Each area is identified in the diagram to the below.

The Solution:

Cliintel developed implementation plans for 86 best practices for managing, calculating and maintaining responsive quota systems. These best practices involved process and procedure changes across all departments that influence and impact quota. The ability to accurately forecast and allocate field resources required significant procedural and cultural changes affecting multiple departments.

The Results:

Upon completion, Cliintel presented the top issues relating to quota to management, assigning each an ROI estimate, identifying the most important tasks that needed to be addressed to help solve the “quota question”. This presentation included tasks that could be completed in-house, as well as those that required further assistance from outside. By strategically implementing the best practice recommendations, the MSO has recognized reduced costs associated with repeat truck rolls, improved completion rates and decreased customer churn. Possibly the most remarkable result, was a marked improvement in customer satisfaction due to the company’s ability to deliver
on service promises.

We’re proud to help our clients solve tough problems and achieve stunning results. To see what kind of results Cliintel can deliver for you, please visit www.cliintel.com or e-mail askcliintel@cliintel.com.

Beatles 1965 Shea Stadium New York and 1966 Candlestick Park San Francisco Souvenir Keychains

The August, 1965 Beatles Shea Stadium show, is the most celebrated, in rock and roll history. It was the first concert,  ever performed, in a stadium, with 56,000 people attending.  This was the height of Beatlemania. “Help” had just been released. They taped the Ed Sullivan television show, the night before. Their 11 song, 30 minute show, including “Can’t Buy Me Love,”  “A Hard Day’s Night” and “Help,”  could not be heard above the hysteria.  An armored truck took the band,  to and from the stage.  Ed Sullivan introduced them, “Honored by their country,  decorated by their Queen and loved here in America. Here are the Beatles.” Women screamed,  cried,  and fainted  their entire show.  John Lennon said, “The Shea Stadium concert,  was the highlight of his career. He felt, he’d seen the top of the mountain.” The August, 1966 show,  at Candlestick Park, in San Francisco, was their most historical show. It marked, the last time, they’d ever perform live, as the Beatles.  The conversation, before the show had a surreal quality. They never thought about,  where or when,  their last show  would take place.  Beatles fans offered, the same hysteria as always. The Beatles 11 song, 30 minute […]

Introducing Dr. Laura Balda Board-Certified Family Medicine Physician – BeautySmart, M.D.

YOU DESERVE EXCEPTIONAL CARE, WITHOUT EXCEPTION

Dr. Laura Balda is a board-certified family medicine physician. She received her medical degree at the University of Florida College of Medicine and performed her family medicine residency at Halifax Health in Daytona Beach, Florida.

Dr. Balda is a top-ranked concierge physician at Inova 360 in Northern Virginia. Finding that many of her patients reside in Palm Beach County part of the year, it was a natural fit for Dr. Balda to expand her practice and return to her Florida roots.

She recently relocated to Palm Beach and opened Balda Health, a concierge practice providing the highest level of comprehensive medical care.

More than a physician, Dr. Balda is a passionate patient advocate whose success with helping patients lose weight, live well and minimize the need for medications has earned her a Patient’s Choice Award.

She treats every patient as a unique individual and seeks to understand how physical, genetic, psychosocial and spiritual factors affect the overall state of wellness. Utilizing this philosophy, she develops deeply personalized prevention plans that directly impact her patients’ health and longevity.

When Dr. Balda is not practicing medicine, she is an active mother of three and avid long distance runner.

Feel Great, Look Great, Be Great… Call (561) 330-7579

What Is Machine Learning from Big Data and What Does Deep Learning Do?

Big Data is So Exciting!

There’s nothing exciting about big data until you have a methodology to make use of it. How we use computers to transcend human limits…

A machine learning approach inspired by the human brain, Deep Learning is taking many industries by storm. Empowered by the latest generation of commodity computing, Deep Learning begins to derive significant value from Big Data. It has already radically improved the computer’s ability to recognize speech and identify objects in images, two fundamental hallmarks of human intelligence.

“Any product that excites you over the next five years probably uses this…”
– Steve Jurvetson, Partner, DFJ Ventures

What Does Machine Learning Do?

“We can’t really talk about deep learning without talking about data. There’s really two kinds of data: data that’s recorded from the physical world [images, sound recordings, etc.], and then there’s data that humans produce [e.g., meta data, tagging via data entry, transcriptions, written words, etc…]. Now we’re getting to a world where we can take measurements of the physical world and turn that into symbols that we can search and sort.”
– Adam Berenzweig, Co-founder and CTO, Clarifai

READ MORE

We Turn Data Into Actionable Information. Click Here for More Info.

Big Data Health Care – Now Is The Time For Personalized Medicine

Big Data Means Big Discovery

Eric Dishman shares his personal story of how his 25 year struggle with kidney cancer was finally resolved through Big Data and personalized medicine.

Dishman’s doctors were able to treat him successfully after sequencing his complete genome. For personalized medicine, only 50,000 people on earth have had their entire genome sequenced.

“The National Human Genome Research Institute, (NHGRI) has tracked the costs associated with DNA sequencing performed at the sequencing centers funded by the Institute. This information has served as an important benchmark for assessing improvements in DNA sequencing technologies and for establishing the DNA sequencing capacity of the NHGRI Genome Sequencing Program (GSP). Here, NHGRI provides an analysis of these data, which gives one view of the remarkable improvements in DNA sequencing technologies and data-production pipelines in recent years.”

The Cure for Healthcare Is Personalization

Being able to crunch massive amounts of data using real-time, in-memory computing solutions means that hospitals all over the world can start accessing and analyzing numerous sources of information, from genomes, to electronic medical records (EMR), to clinical trials – bringing them together to create personalized treatments for patients.

READ MORE

Proven Insights. We turn data into actionable information.

CLICK HERE TO LEARN MORE.

Have You Ever Really Been In Love?

Well, July 4th has come and gone, and the summer is almost half over. Can you believe it? What about your dreams all winter long, enduring the cold and the snow, thinking about that great summer vacation that lies ahead. Hoping to meet that special someone during that long hot and sultry summer, you devise the most intricate of plans in your head, knowing it will be a July full of romance and lust that will outshine any firework display!

SCREEEEECCHHHHHH!!!!! Ok, now back to reality. It is the middle of the summer, and your one true love has not yet appeared! Egad! What on earth, no it can’t be, not another bummer of a summer with no fantastic love story to report upon return to earth and your fellow co-workers!

So then, what of this fantasy that most of us have had once or twice in our lives, to fall madly in love with that one unique and fantastic, handsome/beautiful person that walks on water and floats through the air?

The one that you’ve created in your mind a thousand times over, that will love you like you’ve never been loved before and can do no wrong. The one guy or gal that reminds you of good old mom’s apple pie and dad’s aftershave when you were 6 years old.

It’s a bird, it’s a plane, NO….or is it merely a myth as intangible as Superman’s ability to fly?

You tell me. I’d love to hear from my readers first. Then I’d love to respond to most all of you as to whether or not I truly believe that “REAL LOVE” does indeed exist!!

Individual counseling provides an opportunity for you to openly talk about your thoughts and feelings in a safe environment. Together, we can discuss your issues and concerns with sex, love and relationships. CLICK HERE.

4 Reasons Why your MPOS Strategy is Failing

Are you tired of hearing that MPOS is the future of payments while your business is incapable of scaling its MPOS offering? Or are you seeing that your MPOS portfolio is made up of nothing but inactive or low volume merchants? Here’s 4 reasons why, and some things you can do about them.

Reason for Failure	Explanation	What you can do
Because you have an MPOS strategy.	Good product strategies end with solutions, they don’t start with them. If you are merely adding products to your portfolio as a reaction to Square and others, you have short circuited the entire product management process. It’s a prescription for product failure.	Get to know your customers, prospects and competitors. Stop focusing on reactive strategies and get back to the 4 Ps.
Because you don’t really know your customers or prospects.	If you are listening to your customers, understanding their problems and offering solutions, you might have a chance. Keep in mind that not all customers have the same problems, and not all problems have viable solutions.	Segment your customers and prospects by vertical, by size, by profitability, and by your organizational expertise. Identify the segments where financial opportunity and core competencies overlap, and focus there.
Because you don’t really know your competitors.	Few financially valuable ideas are new, so don’t think of yourself as a genius for having an idea. The magic will be in execution and in differentiation. You must know your competitors and offer a more valuable solution, and continue to stay ahead over time.	Reinvent your competitive outlook. POS is not a payment product, it’s much more than that. If your list of competitors includes a bunch of payment companies you need a new list. Once you have that list, get to know the companies on it, and their products, extremely well.
Because your products and channels don’t fit.	Products and channels need to go together like peanut butter and jelly. If you’re mixing peanut butter and tuna, you won’t get far.	Create an MPOS channel strategy. Assuming that payment channels will suffice is a pipe dream. They need to be either transformed or replaced.

Payments is a universal merchant need and a commodity, MPOS is neither of those things, so it shouldn’t be a surprise that payment companies are struggling with it. POS is a highly differentiated, value-added service, so a whole new set of rules apply. It will be product teams, not distribution teams, that will make or break the payments companies of the future. Is your business ready?

This blog post was inspired by a recent report by Double Diamond Payments Research. For more information about the report please visit To Be or Not To Be an ISV? Integrated Payments Strategies for Merchant Solutions Providers, or email research@doublediamondgroup.com.

ETA Transaction Trends, July 14, 2015
READ FULL ARTICLE

Big Data Slide Show – 5 Things Every Executive Needs To Know About Big Data

Here is a quick 30 second glance at the top 5 things every executive needs to know about Big Data and what is going to happen.

What You Might Not Know About Big Data

As a  so called “newb” to the Data World, I am finding some interesting elements of Big Data that I believe the average person does not know about. Most of us see Big Data in the headlines, but do we know what it really is or how it works? After reading an article on consumers paying for data, I am beginning to see both the pros and cons to Big Data.

This article explains how consumers of products such as Fitbits or GPS systems are paying for the data they produce. Consumers are not actually sending in a check each month but are paying through what economists would call “barter”. Once the product is purchased, the personal data it produces is used by big companies such as Apple or Yahoo! to advertise more efficiently. These companies learn from the data to create ads personalized to your interests or hobbies. It is a brilliant marketing scheme, but is it ethical?

I have always been slightly creeped out by how the internet adapts its advertising to my interests at the time. For example, in my teens all the advertisements I received were about volleyball and dating apps, but now they are almost exclusively about wedding apps. The personal information these mega companies obtain through our data is making them mass amounts of money. Some might ask “Where is my share?” but this is where we get into the “barter” part.

Even though the sharing of data might seem like an invasion of privacy we must remember, nothing is free. We buy products like Fitbits and expect to receive continuous feedback on our health and sleep habits without paying for a subscription. The sharing of our data with big companies and advertising agencies is our payment.

So really it is up to you to decide if it is morally right or wrong.  Are big companies stealing your private information or is it worth the trade off to use these products that give us valuable information and feedback?

Click Here for some more insight into Big Data!

3D Printing Advice For Market Entry Into the USA

Marketing into the USA? Here is a point made quickly for firms wishing to market into the USA. Check out the Association of 3D Printing as a way to learn more about the 3D Printing Industry and how to penetrate it.

Also, take a peek at Market Entry Partners.

Big Data? What About Smart Data?

Big data is the new ‘it’ word, the new hot topic, and quite frankly, the term can be somewhat overused. There are a few different reasons why I dislike the term “big data”. The big data word came around and data is big, just by nature. As the world continues to grow, data will also continue to grow. The word is completely relative; what terabytes is considered big data to Comcast, 100 lines on an Excel sheet may be considered big data to a small ma & pa shop. The other factor that needs to be taken into consideration here is that not all data is relevant. Today, many people are getting caught in this cycle of “it happened, so we better record it. You never know, we might need that someday”. Sometimes we tend to lose the forest for the trees. Taking in so much data can lead to fascinating academic results, but not always relevance from a business point of view. There is a lot of time, energy, and money spent chasing down this big data because it’s the new buzzword, but it’s not put into perspective. Big data can truly mean different things to each and every person.

So, how about smart data? Rather than looking at the amount of data one can collect and hold onto, why don’t we begin to draw our attention to what the data can tell us and what changes we can make based on the power of analytics? Why not focus in on the actionable insights rather than this giant species of nothing but numbers? I challenge you to alter this perspective that you have had engrained in your mind. Big just takes up space, but smart can change the space.

Big Data: Shaping the Future of Sales and Marketing

With the era of Big Data upon us, it is time to change our thinking. Big data and predictive analytics technologies represent the opportunity to turn the table on the house. In other words, sales and marketing can finally become more about math than magic.

Let’s get specific and talk about the five ways I believe big data will rock our world in 2015 and beyond.

1. Large enterprises will be the first to widely adopt big data and predictive analytics technologies, but small and medium businesses will get on board soon thereafter and will benefit even more.
2. Marketing spend will become significantly more precise by leveraging insights from big data to accurately target prospects and deploy
   account-based marketing strategies.
3. Salespeople will gradually adopt data-driven methodologies to target high-value prospects, keep existing customers on board, and expand existing opportunities.
4. Sales forecasting accuracy will improve dramatically as sophisticated algorithms supplant “gut feel” as the weapon of choice for predicting sales.
5. Real-time sales data visualization technologies will emerge, empowering sales managers to adjust battlefield tactics based on live data feeds.

I guess in the end, if you are a sales or marketing professional in any industry I’d suggest that you get smart about what’s happening in big data and predictive analytics. A tsunami of data and potentially powerful business insights is heading your way. It is time to decide, will you jump on board or be swept away?

Read the Full Article Here

3D Printing Expo in Santa Clara – Use The 3D Printing Channel Code

Inside 3D Printing Conference & Expo – West Coast’s Largest 3D Printing Show!

Inside 3D Printing is returning to Santa Clara on October 20-22! Since its inception in 2013, the Inside 3D Printing Conference and Expo has quickly grown to become the largest professional 3D printing event worldwide.

Inside 3D Printing Santa Clara will feature a full day of tutorials plus two days of conference sessions led by industry experts and demonstrations of the latest 3D printers and services.

Whatever your role, Inside 3D Printing has a focused track with in-depth analysis and takeaways tailored to your priorities. The expo hall allows networking opportunities with colleagues from 40 countries and 41 states (based on statistics from 2014 events) as well as 70+ exhibits from around the world. 80 + speakers provide coverage of industrial and consumer topics and strategies.

Inside 3D Printing covers arts, business, manufacturing, medical, metal, scanners, and more.

EXHIBIT HALL HOURS: OCT. 21, 10:00AM-6:30PM AND OCT. 22, 10:00AM-3:45PM

Use the discount code CHANNEL for 10% off Inside 3D Printing Santa Clara. CLICK HERE!

The Next Great Payments Opportunity: Commoditization

Investopedia defines “commodity” as:

A basic good used in commerce that is interchangeable with other commodities of the same type. Commodities are most often used as inputs in the production of other goods or services. The quality of a given commodity may differ slightly, but it is essentially uniform across producers.

Payment processing has been a commodity since its inception, but it hasn’t always been used as raw materials in the production of other products. Now, however, the fastest growing processors are the ones that facilitate the use of payments as an input, completing the commoditization cycle and creating the next great payments opportunities.

A variety of banks created Visa and MasterCard in order to enable financial institutions to offer payment instruments that could be accepted at any merchant, anywhere in the world. To do so, they created standardized authorization, clearing, and settlement frameworks that merchant acquirers could use to offer payment acceptance to merchants in a way that provided global coverage and interoperability to bankcard issuers. It’s important to also understand that this standardization was the most important thing that ever happened in the payment industry, it offered thousands of companies to enable electronic payment acceptance around the world, and to benefit by earning a percentage of the many trillions of dollars in transaction volume that would follow.

There’s another important implication. By creating standards, the payment networks not only made payment cards globally interoperable, they also commoditized the industry. By definition payment acceptance offerings had to meet network rules, and these rules forced a convergence of diverse offerings into a single standardized product, so payment acceptance has been a commodity since day 1. Payment processors and terminal manufacturers followed the networks’ lead, deploying multi-network processing solutions and for-purpose payment acceptance hardware that enabled any card to be accepted by any merchant in an out-of-the-box, yet highly commoditized product.

Integrated software vendors (ISVs) have been using payments as an input into the production of their POS systems for decades, but primarily for just the largest of merchants. However cloud computing has reduced the cost of software delivery, making integrated payment solutions more accessible to smaller merchants, thereby making payments as an input far more popular. This trend has gathered momentum to the point that companies that specialize in helping ISVs include payments in their applications, such as Accelerated Payment Technologies, Element Payment Services, PayPros, and Mercury Payment Systems were growing a rate that outpaced the rest of the acquiring industry by a 3X multiple until they were swallowed up by Vantiv and Global Payments. Other integrated payment firms such as Stripe and Braintree continue to be some of the fastest growing firms in payments.

It’s important to note that facilitating the use of payments as an input to the products of other firms is a pure commodity play. Integrated payments firms like those mentioned above continue to make it easier and easier to use payments as an input, speeding the process of payments devaluation into raw-material status. Integrated payment is the next big commodity play that will be dominated by scale-driven firms, strategies, and pricing. In short, the integrated payments player is the payments processor of the future: large, untargeted, undifferentiated, and facing ongoing pricing compression. So as Vantiv and Global duke it out to be the largest commodity distributors, what is the rest of the world’s merchant services providers to do?

We believe that there are 6 options, each one requiring a specific set of competencies. Payments firms should be deeply involved in self assessments to determine the option that best fits their business, and they should be aggressively investing to close any gaps and to maximize their growth potential. To learn about the six options, contact us about our most recent report: To Be or Not To Be an ISV?

For more information about the report, To Be or Not To Be an ISV? Integrated Payments Strategies for Merchant Solutions Providers, email research@doublediamondgroup.com.

How Big is Big Data?

It is amazing how many different fields Big Data Analytics can be used in. Currently Big Data Analytics is being used in everything from 3D printing to understanding why certain people sleep better than others. This short video on Big Data shows how analytics can help you understand your data, leading you to big solutions.

Big Data Joins 3D Printing

Interested in Big Data and 3D Printing? This great Podcast shows how the two can come together. Listen to this short podcast and quickly educate yourself on the up and coming trends of both Big Data and 3D Printing.

Big Data 3D Printing and What’s The Big Secret?

This podcast is from the Data Talk Show and discusses the marriage of 3D Printing and Big Data Analytics.

Kevin Bacon and Big Data?

Kevin Bacon and Big data have more in common than you think. The way people connect Kevin Bacon to other celebrities in the Six Degrees Of Kevin Bacon Game is the same way companies use Big Data analytics to connect people, products, businesses, etc.

Through Data analytics we can start to understand the mass network that connects all of us ordinary people.

This video explains the importance of Data Anaytics and how it can benefit us all.

Big Data and 3D Printing – What is the Secret to Protecting Yourself With Data?

We have a top Big Data scientist on this Big Data Podcast.  Here we speak about 3D Printing and how Big Data can make 3D Printing Companies win or lose.

Call Center Solution Design Increases Customer Loyalty and Retention – Big Data Case Study

The key to success for any company comes from excellent customer service. A financial services firm with a long history of world class customer service suddenly found themselves with a new challenge: high attrition in the new-tofirm customer segment. In an effort to meet even more customer needs, the company had created a level of complexity that was not well received by the marketplace.

The Client:

The client is a leading financial services firm serving over 7 million customers with assets in excess of $1.4 trillion. Customers access services through 300 branch offices, a call center network and online.

The Business Issue:

The client has an established culture built upon the belief that meeting and exceeding the customer’s needs drives the decisions. The firm developed both products and services designed to serve previously unmet customer needs. This development became a double-edged sword for the customer; products were now available to meet a wide variety of needs, but in doing so the systems became more complicated and confusing. For existing customers the client resources were both known and readily available to address this issue. However, for new customers this complexity led to attrition as they struggled to find their way through the maze of products and services. The client needed a way to simplify their new customer experience and stop the attrition.

The Challenge:

The client has extensive customer data, which has been used to segment the customer base to provide need specific services. The Call Center Network was segmented according to service expertise. Due to the reactive approach to customer service the company did not possess strong sales skills in their phone teams. Extensive work would be required to build and develop teams, which possessed both universal service/product knowledge and needs-based sales skills. Additionally, infrastructure, technology and data challenges abounded.

The Solution:

Cliintel took a structural and skills based approach to the solution design. This entailed the design of phone teams which melded inbound, outbound and email channels to facilitate an introductory relationship with each new-to-firm customer. Training to build consultative sales skills, construction of feedback loops with the target client, creation of marketing collateral to support the relationship and technology support to develop new tools were all employed.

This resulted in a 40% increase in Net Promoter Score (client loyalty), a 26% reduction in customer attrition and increased service and product adoption by new customers.

The Results:

By implementing this solution, Cliintel developed a new service delivery model, leveraging existing data capabilities, creating custom workflow tools and developing collaborative sales skills within the phone reps. This resulted in a 40% increase in Net Promoter Score (client loyalty), a 26% reduction in customer attrition and increased service and product adoption by new customers. Employee satisfaction also increased as the role provided opportunities for skill development and career growth.

To learn how we can help you solve your problems and achieve stunning results with customer retention, visit www.cliintel.com or email askcliintel@cliintel.com.

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Using Data Analysis To Examine Business Processes

Where do we start the change efforts to fix the processes? First, we have to identify the problem with some analysis––careful, considerate, objective, dispassionate analysis. The only way to accomplish this is to be self-reflective; avoid reflexively and aggressively going after your internal supplier on the front end or your internal customer on the back end. Most everyone in any company is accustomed to working within their silo or department and looking for efficiencies within their area. You will rarely find that managers and operational people are looking for efficiencies that relate to their internal supplier or internal customer—the departments on either side of their silo. They are not typically attuned to how the particular processes within their silo or department impact the end result. In other words, mangers within a silo are simply looking to drive out costs or to make things move faster within their own particular purview.

Only after we examine intention to retention within our own silo will we have any chance to understand how we might change the activities within a specific silo and determine appropriate suggestions for our internal supplier or customer. This is the point at which an outside consultant may be useful to you, someone not deterred by politics and agenda, and who can democratically and sympathetically look at the SIPOC within each silo and communicate ideas in a nonthreatening way. The problem in proceeding without outside assistance is that as soon as you confront somebody in another silo about what they are doing, they are going to get defensive. It is just a natural human reaction. I’m not saying it is impossible to do without an outside consultant, but it does require a little more creativity and a willingness to slow down, to spend time building a relationship and a decent level of trust. Otherwise, your efforts will be counterproductive, and you just put the other silo on the defensive.

A consultant is not the magic pill; any time a consultant comes in, some people will automatically get defensive. Typically, when there’s a consultant hired, it is interpreted to mean that someone higher up the in the company believes there is a need for change, and obviously they are serious about it because they have brought people in from outside. That is a bit threatening, but if you hire the right consultant, it doesn’t need to be.

The next step is to engage in a purposeful conversation with clearly outlined goals for the betterment of everyone, meaning the company in general, which will also impact the company’s external customers. Next, conduct an analysis of all stakeholders in the target silo. This is where a consultant can come in and assess, in a nonjudgmental way, the stakeholder group and see who is going to be receptive, who is going to be protective or defensive, and who is going to be an obstructionist.

It has often been observed that there are three levels of personality types: those that watch things happen, those that make things happen, and those who wonder what’s happening. This last group doesn’t seek to understand what’s going on but will do their best to shut everything down because they don’t like change. They don’t spend the time to evaluate whether it is good, bad, or indifferent. The attitude is, “That’s how we’ve always done it.” Everybody will deny they ever had that thought, but they’re kidding themselves. It is just basic human nature—“new and different” is scary.

Pick your partners and your battles: Who is going to be easiest to work with? It is not usually who you think. If you are doing this internally, you might assume, “I’ve known Lynne over in my supplier silo for a long time. We’ve gone to conferences, and we have a good relationship.” That might be a good place to start, but do not assume this new interaction will be more fruitful because of that relationship. The change effort that we’re talking about here may require less of a social awareness of one another and more a business respect level, along with a congruence around the idea of change for the betterment of the two silos and, ultimately, the external customer. If you can find the later, professional alignment, as well as personal alignment, you can make magic, we have all been on or seen what a great team can accomplish—regardless of talent.

-Richard M. Batenburg Jr.