Big Data Helps Reduce Medicaid Fraud

The state of North Carolina has 2 million medicaid patients and pays out $12 billion in Medicaid each year. Due to these high numbers, in 2010 governor Beverly Purdue announced a program to analyze medicaid claims. To do this, IBM was asked to step in to aid with healthcare analytics tools.

Since using the IBM Healthcare analytics there has been a 90% reduction in medicaid fraud. This software allows healthcare providers to see the patterns in medicaid claims and identify faulty claims against true claims. The great part about the use of Big Data analytics is that the IBM software can take the data collected from medicaid claims and put it into a visual format that is easy to understand. This allows for doctors and nurses to identify the fraudulent claims rather that rely on data scientists.

The use of big data analytics in the healthcare system not only aids in picking out the patterns that discover fraud, but it is also showing the population that there are people watching them and that they will be caught.

Thanks to Big Data analytics the state of North Carolina has decreased the rate of medicaid fraud and continues to search for those who dare to commit it.

When Chinese Money is Worth Less What Does Your Business Do?

Everyone has seen the news that China has devalued its currency. This means the Yuan Renminbi is weaker. When you exchange currency, you can now buy more Yuan for each dollar spent. If China is really the world’s second largest economy, than the Renminbi (People’s Currency) effects world markets.

After all, if Chinese money is weaker, that means that US products sold into China become more expensive. Take the example of Mandarin Oranges for sale in China, but imported from the USA. An 8 kg box costs between $20 and $30. With the weaker Chinese currency, this could cost 25 percent more this year. Thus, the imported oranges are more expensive and the Chinese will buy less of them from the USA, critics say.

On the flip side, items we buy from China will cost less. Importers of (e.g.) Chinese toys will pay less. If the US importers keep the price constant, then the importers will benefit and make more money. So why is everyone complaining?

If your firm is selling a price-based commodity to Chinese buyers (rice, soy, oil, hogs, corn, cotton, etc.) your sales may suffer because your price is too high.

But if you are selling iPhones or BMW’s, the higher price may not matter. Higher prices may even work as an advantage, because the products are more expensive and hence more prestigious.

What advantages do BMW and Apple enjoy that cotton growers and soy farmers don’t?

It comes down to branding and positioning. The successful firms plow back profits into building and protecting a brand. They have made it clear that an iPhone costs more, but is worth it. A BMW costs much more than almost anything Chevrolet makes and their argument is that “price doesn’t matter.”

U.S. firms can often be lazy when it comes to branding overseas. My work in this area points to many firms that relinquish overseas branding to local “partners.” If U.S. firms remember their marketing muscle, they can expand overseas and not be as sensitive to price fluctuations. If we can remember that Starbucks is a lifestyle (not a coffee) we can export that concept (as Starbucks does well).

For those businesses that deal in commodities, there has to be a way to differentiate other than price. Last week I asked a firm (who wishes to deal abroad) if they had bank accounts set up in overseas markets. When they explained that they wanted to be paid in US dollars via wire, one has to wonder if they really intend to service the markets. Better service would be a differentiator.

This firm picked China as a target market. I asked these questions of this firm:

Did they have anyone on staff that speaks Chinese?
Are they interested in going to China regularly?

Do they have relationships in China?

Can they help the Chinese with their own businesses?

Do the Chinese clients need help where the U.S. firm is better connected?

Did they read anything about the region?

Do they eat Chinese food?

All of these points can be differentiators.

All of these questions point to ways in which the Americans can enhance customer intimacy.

When Will the Federal Reserve Raise Interest Rates?

The likelihood of the Fed moving to raise its benchmark rate next month for the first time in 10 years seems “less compelling,” said one Reserve official Wednesday.

The global selloff, brought on by weak Chinese economic data, threatens to crimp global growth and create financial conditions unsuitable for a initial policy tightening in the United States, he said.

The volatility has tightened financial conditions and widened credit spreads, he said, adding inflation remains “well below” the Fed’s 2 percent target due to falling oil prices and the strength of the dollar, “which we expect to be transitory.”

“It’s important not to overreact to short-term market developments because it’s unclear whether this will just be a temporary adjustment or something more persistent that will have implications for U.S. growth and the inflation outlook,” Dudley said.

READ FULL ARTICLE

Two regional Federal Reserve presidents who will vote on policy next year said that while they are mindful of market volatility, they consider the U.S. economy strong enough to justify raising interest rates.

“Inflation expectations have been relatively stable, we have growth, above-trend growth, we have labor-market improvements continuing,” the Cleveland Fed’s Loretta Mester told Bloomberg Television Friday at the Kansas City Fed’s annual conference in Jackson Hole, Wyoming. “My view so far in looking at all of the factors is that the economy can sustain an increase in interest rates.”

“The key question for the committee is — how much would you want to change the outlook based on the volatility that we’ve seen over the last 10 days, and I think the answer to that is going to be: not very much,” Bullard said.

Their remarks came two days after New York Fed President William C. Dudley said market turbulence made the case for a September liftoff “less compelling to me than it was a few weeks ago.”

READ FULL ARTICLE

FiberCare Dallas – Customer Review

Thank you for being so responsive to our request to have the bed steamed at Curtis on Monday.

The guys who worked on it did an excellent job.

After the bed was delivered, the designer reported back to us that it looked “amazing”.

Please relay our thanks and appreciation to them. They saved the day for us.

– Diane Wood

Smart Marketing: Targeting Millennials in the Automotive Sector With Big Data

Targeting Millennials in the Automotive Sector with Big Data

As technology marches on, so do the aspirations of automobile manufacturers to be the first to tap into the “next big thing.” The next big thing is Big Data.

Although it is a healthy industry, there are still challenges facing the industry players. Competition for market share, rising costs to promote product differentiation, and a flourishing frontier of digital advertising has left automobile manufacturers and dealers alike searching for ways to gain competitive advantage in a crowded atmosphere.

With this shift, a considerable amount of focus is being directed towards reaching today’s must have demographic.

Using Big Data to Acquire New Millennial Customers

A report published earlier this year drove home (pun intended) speculations that the automotive market share of Millennials was predicted to blossom.  The report projected that millennial consumers, those born between 1980-late 1990’s, will purchase roughly 4.24 million cars and light trucks in 2015. Thus, producing $135 billion in total revenue.  Furthermore, 35% of millennials (compared to 25% of U.S. adults) indicated that they are likely to purchase a car within 12 months.

Because of this immense buying power, auto manufactures have been gearing campaigns to this particular generation. They have visibly rebranded vehicles in attempts to appeal to the younger audience. But behind the scenes, they have been using a very important tool to aid their success in attracting the new market: Big Data. It is proving to be far more powerful and successful than the rebranding flare and advertising gimmicks.

Big Data is especially useful because of the context and target market. As the most digitally interconnected generation, Millennials are constantly leaving behind a virtual trail, leading straight to their next purchase. All auto marketers have to do is find it.

Data service providers comb the internet for verified indicators that imply imminent purchase. These indicators could be anything from searches of competitor vehicle brands to social media statuses expressing interest in or inquiring about purchasing a car. Many Millennials are still nursing their 10 to 20 year-old college cars and every trip to the shop leaves a trail of data that indicates how much closer they are to taking the next step in purchasing a new vehicle.

By pulling information from various sources, businesses can access prospect lists of in-market, millennial consumers who, whether or not they are even aware of it, are already virtually primed for the purchase. Data mining is used to trace the vehicle purchasing process, beginning from the first search term, all the way to pulling up to the dealer lot. Studies show that more than 50% of consumers across all generations base their final purchasing decision off of digital channels such as web research, reviews, social media, and community forums, and each digital interaction leaves a footprint of the purchaser’s journey. Therefore, utilizing this as an information, marketing and sales source is vital.

Increasing Brand Loyalty with Customer Data

Once a prospect has transitioned into a customer, auto dealers leverage quality data to increase customer retention with personalized campaigns that solidify customer relationships and ensure that they are positive relationships. For example, a customer who purchased a sports car has now begun leaving a purchasing and social data trail that now indicated he or she is a soon to be parent. This would certainly be a good time for a sales team member to give the customer a call and see if they’re interested in trading the sports car in for a safety conscious minivan.

The good news is that not only is this information available, consumers are becoming more accustomed to their information being used to construct personalized outreach. A recent study shows that the majority of consumers are more likely to engage in a personalized ad than a general ad. In the case of Millennials, a personalized ad is expect.

With data intelligence services, businesses can maintain and utilize customer data to create the custom, personalized experience that Millennials require. This provides the framework for a positive experience that can ultimately lead to brand loyalty; this is the ultimate gold mine for customer retention. Although Millennials aren’t very loyal when it comes to employment, nearly all appreciate when brands actively reach out to them and the great majority practice brand loyalty.

The saying rings true that the easiest customer to sell to is one you have already sold to. Data services are being used to create comprehensive customer profiles giving insight to unprecedented aspects of buying behavior.

Big Data Is The New College Acceptance Factor

Now that we are fully submerged into the digital age of social media and technology, the rules are changing. Our lives are no longer recorded in journals, but through our tweets and Instagram posts. It is because of this change that even colleges are moving towards social media.

Remember when your mom used to tell you “Don’t make that face or it will stick like that” ? Moms were right, just not in the way we all thought. No your silly face won’t actually freeze into place, but whatever face you post to social media is stuck there forever.

Colleges are now looking into applicants’ social media profiles to decide whether the student fits a certain stereotype that has been known to be more successful in school. This means that colleges have looked at the Data and put together a type of student most likely to not drop out. Colleges are even creating their own media sites similar to Facebook to better gather this data.

Although this may be a beneficial tool for colleges to recruit more successful graduation rates, is it ethical? It does not seem right to accept or deny someone based on their social media profile rather that test scores or grades. Bringing social media into the admissions process is opening a Pandora’s box of potential issues such as biased recruiting because of attractiveness or wealth.

What do you think?  We would love to hear your thoughts on this issue. Is it ethical to use the data from social media in College Admissions?

Big Data Questions – 5 Things You Need To Ask About Big Data

5 Questions About Big Data from Bill Decker

Here is a quick slide show about Big Data and the questions you should be asking.

SIM

Outline

Intro

Quick intro about self and change – What was meant by the Sequoia tree?

Who are “The Hated 5?”

Resistance to change is about loss.

Change is inevitable and ongoing – as illustrated buy the slice of the tree.

Information 100 years vs. 2 weeks New York Times – Data in one year.

Difficulty with change is politics.

Optimist – Pessimist – Politico.

Change and the silos – Silo’s figure 1 then Silo’s & LOAmbiv.

Change and the organizational hierarchy – Marie Story.

Did We Accomplish?

Some Tools

You are more persuasive than you think! For the Harvard Business Review article, HBR.

Email Us

Big Data Videos!

Data Newsletter!

Big Data Isn’t The Money Maker- You Are

If someone handed you a shovel and asked you to dig a hole, who would get credit for the hole? Did the shovel create the hole? No, you did, the shovel was a tool that allowed you to dig the hole more efficiently.

This is what Big Data is to businesses.

Many people believe that big data is the key to making money, and it is….just not necessarily in the way you may think. Instead of starting up your own Big Data company to make the big bucks, try using Big data instead. Companies who use Big Data to make more informed decisions are the ones who succeed, companies who produce Big Data software are the ones who get passed up by the newest model.

Don’t be a tool, be the person who uses the tool. 

Back to the shovel analogy, your job is to dig a hole and though the shovel seems like your best friend in that moment, what if someone handed you an excavator? Now you can dig holes three times the size, all while sitting down! Even though the shovel seemed better than digging with your hands, the excavator now does the work for you. Businesses are the brains and Big Data is the tool, as long as the brains know what they are doing, the tool aids them wonderfully.

This is where the trouble comes in, even if you have a fancy complex program that does all the work, it still isn’t saving the business money if they don’t know how to run it. Many Big Data applications have made their money by providing a product that then requires a hired team of experts to manage it.

The way to make money in Big Data is to produce an application that is simple enough for the average business’s IT team to handle. The way to save money is to implement these applications into your business to gain much needed insight that allows the company to be more efficient and make smarter decisions.

The successful businesses are the ones who have figured out how to use Big Data to set themselves apart, rather than let it steal the spotlight.

Let us know what you think, is Big Data just a tool or are Big Data companies worthy of a higher name?

3D Printing Time Lapse Demonstration – 3D Printing in Action

It all starts with making a virtual design of the object you want to create. This virtual design is made in a CAD (Computer Aided Design) file using a 3D modeling program (for the creation of a totally new object) or with the use of a 3D scanner (to copy an existing object). A 3D scanner makes a 3D digital copy of an object. This time lapse video shows 3D Printing in action!

FTL

August 25, 2015

Future Tax Leaders Presentation;How to Enter Cultures; international and otherwise

Participants should leave the session knowing:

– The largest stumbling block when working in different corporations.
– The 5 questions each person should be asking when confronted with any new culture.
– Common mistakes made in interacting with different cultures.

What we will cover:

– Interactive exercise – Bridges and Umbrellas

How we size up a new situation

– Defining culture; visible and invisible
Strategies and tactics for cross generational and international work

– A primer for global cultures
International Business defined with 3 drawings

Task Specific vs. Relationship Specific
Short Term vs. Long Term
Individual vs. Collective (think of Bush vs. Saddam)

War stories

Refrigerator
How to fire employees in Womza
What is profit?
Chinese Balance Sheet

10 Questions To Ask Yourself!

This is how we do it our way. What is is their way
What is public, what is private?
How do you know when you are in?
Do they respect my authority?
What assumptions might be underlying their actions?
Have I heard this correctly?
Does the other person understand what I have asked them to do?
Who does my “employee” work for?
Is there more than what I am seeing?
How can I “bridge?”

International Business Podcast! (free)
International business videos
International business book

email me

IBM’s Thoughts on Big Data – 1 Minute Video

Here an executive gives some thoughts in a 1 minute video on Big Data.

Sim

Intro
Quick intro about self and change – What was meant by the Sequoia tree?

Who are “the Hated 5?”

Resistance to change is about loss

Change is inevitable and ongoing – as illustrated buy the slice of the tree

Information 100 years vs. 2 weeks New York Times – Data in one year

Difficulty with change is politics

Optimist – Pessimist – Politico

Change and the silos – Silo’s figure 1 then Silo’s & LOAmbiv

Change and the organizational hierarchy – Marie Story

Did We Accomplish?

Some Tools

You are more persuasive than you think! For the Harvard Business Review article, HBR.

Email us

Big Data Videos!

Data Newsletter!

Requirements For Landing A Big Data Job

As one of the hottest careers in 2015, it is no surprise Big Data job applicants are getting snatched up by companies like candy out of a pinata. Want to work in this up and coming industry? These are the skill sets that will land you a job in Data Analytics.

Hadoop

• In non data scientist terms, Hadoop is a complex platform that allows data to be BIG DATA. Hadoop removes storage contraints and makes processing data a billion times easier.

General Purpose Programming Languages

• Ability to program applications in Java, C, Python, and Scala is an important skill set many companies working with Big Data are interested in.

Structured Query Language

• SQL is an older data-centric language, but is still commonly used alongside programs such as Hadoop.

Machine Learning and Data Mining 

• Ability to use machine learning technology to create predictive analysis apps consisting of classification, recommendation, and personalization systems.

NoSQL

• A database that works hand in hand with Hadoop to make necessary application changes based on insights found by Hadoop.

Apache Spark

• The stepsister of Hadoop, this program is faster and more simple making anyone who knows how to program and run it, a much valued employee.

Statistic and Quantitative Analysis

• As the foundation of Big Data, this skill is fundamental to working in the field. Must have experience with statistical analysis and quantitative reasoning. If you are proficient in tools such as R, SAS or Stata, you are set.

Data Visualization

• Knowing how to use visualization tools is huge, as sometimes repetitive logistic regression analysis doesn’t make the cut. This is a dynamic way to look at data and problem solve.

Creativity and Problem Solving

• Speaking of problem solving, creativity and problem solving are two very strong characteristics of successful employees in any job posses.

Do you posses all of these skills? Look into this rising Data Analytics Company!

Big Data Is A Big Deal

The article, “Why ‘Big Data’ is a Big Deal,” written by Jonathan Shaw gives its readers an idea of just how “Big,” big data is. It is transforming the world around us, and helping us make sense of things that were once mind-boggling. Big data is changing the world we live in.

Following his article, there are a series of comments and arguments in response to Shaw’s words. Many of those comments seem to be about how big data can influence matters of security and privacy. While this may be true, I believe the benefits of utilizing big data science outweigh the costs. In order to understand why, we must understand how “Big,” big data really is.

We can gather and access data from just about everything we use; our mobile phones we use daily, our televisions, our iPads and tablets, the trains we take to work, and the airplanes we fly in to go home for Thanksgiving. We have access to so much data…everywhere. This is truly amazing, and the thought of how much data this is, is mind-boggling.

However, as noted in this article, it is not the quantity of data that is revolutionary but the fact that we can now actually do something with the data. In his article, “Why ‘Big Data’ is a Big Deal,” Jonothan Shaw explains to his readers that what once took a $2-million computer to analyze, we can now do the same on merely our personal laptops.

Shaw explains the “Big” roles big data science plays in our great big society, as a whole. Big data science is applicable to nearly every academic discipline and industry: astronomy, physics, energy, medicine, business, government, design, policing and human evolution.

It is also applicable to our daily lives. For example, credit card companies mine data to help evaluate our risk of default. Target used an algorithm to decide what types of coupons to send out. Netflix and Amazon use recommendation engines to show us what we might like to buy, and what we might like to watch; and usually (at least according to my own experience), they are right.

Perhaps the most astounding way we can use big data is to analyze the human race… through social media. There are roughly 2 billion posts each day. This is the greatest increase in the capacity of humans to express themselves in all of human history. We have now developed tools to help us analyze these texts… even in Chinese.

Even though so much data exists, this does not mean we can make sense of it. Shaw gives the example: you can’t just throw it all against the wall and only analyze what sticks. Right now data mining is often considered an industry of its own. It takes data scientists, with specific skill sets to make sense of all this data.

They enable the understanding of data sets using visualization. They aggregate, filter and cluster the data so a person can make sense of it. It cannot be denied that humans are better at seeing patterns than humans are. Therefore, we can combine what humans are good at (asking the right questions and interpreting results) with what the computers are good at (computation, analyzation, and statistics using large datasets). For now, however, it is only the data scientists that are trained and able to do this. Yet big data has a transformative impact on nearly every aspect of our lives.

For this reason, there are new data tools being implemented in higher education. Last fall, there was a Harvard course in data science that attracted more than 400 students (I hope they had a big lecture hall). Student projects included the distribution of tweets for competitive product analysis, predicting the stock market, and the performance of NHL hockey teams.

It certainly will be interesting to see where the rise in big data science takes us in the future. It is proven that data science, analyzation and consulting can and does improve all aspects of life, and especially all businesses. If you are interested in reading the full article, you can do so by clicking Here.

If you are interested in learning how big data tools and big data science can help your company, contact us at Cliintel, by clicking Here.

Can You Use Your Data To Tell A Story?

At this point, you may have heard it time and time again- big data means nothing without some form of actionable analytics. However, contrary to many beliefs, analytics is not just about data. In fact, getting too caught up in the data can obscure what the data means. And what it means is what matters in business.

Many data scientists today are getting too involved in the raw data, feeling like they have to talk about their data and their process. Instead, they should focus on telling the business story their data shows. Ask yourself this- can you use your data to tell a 60-second story about your business? If the answer is no, then you simply need to shift your focus. Keep points short, talk in dollar terms, and don’t overdo the details. Focus in on what it is that interests your audience, and remember that they are the ones with the power to act on your insights.

So many data scientists lack the ability to communicate their findings in a way anybody could understand, as they are taught to speak in complex terms. What we really need to focus in on here however, is big picture, big picture, picture! You can be talking about dry numbers and algorithms that may be beyond your audience, but as long as the data frames a story, people will be likely to pay attention — and learn something, which is the point of communication.

Data visualizations are a great tool to aid in your telling of the story – but be careful. Although a complex graph may look appealing, overcomplicated visualizations may actually end up confusing the audience even more. Use them as an aid, and just that. Don’t get too fancy.

If anything remember this- a story about what your data means to your business means so much more than any number presented.

Click here to let us help you tell a story with your data.

Is Data Management The Key?

Many organizations today struggle to get their cards in order and turn data into dollars.

“The more data you have, the more crucial it is to better manage your master data and improve the maturity of your master data management (MDM) program,” said Saul Judah, research director at Gartner. “Existing approaches to data management are, in many cases, insufficient to accommodate big data sources on an enterprise scale. Collecting data without managing it properly also creates ongoing costs as well as regulatory and compliance risks.”

In order to save money, CIOs and Chief Data Officers who oversee big data initiatives need to consider the following steps:

Update Information Strategy and Architecture
Many organizations have had success leveraging big data insight around specific business operations, but typically it’s limited to a single business unit or use case. Few firms have explored how to make big data insights actionable across the entire organization, by linking big data sources with trusted master data.

For example, many marketing organizations use data from social sources — such as Twitter and Facebook — to inform their campaigns, but they don’t reconcile this with trusted data in customer/prospect repositories that are used by customer services or sales. This can lead to incoherent customer communication that can actually undermine the sales or customer service process.

Become More Agile
Effective use of big data requires a mixture of old and new technologies and practices. This necessitates an agile approach that applies a bimodal IT framework to information governance (see “Why Digital Business Needs Bimodal IT”). MDM traditionally uses a Mode 1 approach which is policy-driven and approval-based. Big data typically uses a Mode 2 approach with little or no predefined processes or controls. Tactical and exploratory initiatives are much better suited to the “faster” Mode 2.

Move to Limit Risk Exposure
When an organization executes actions based on information sources outside the curation of MDM — as is the case in many big data implementations — exposure to certain types of business risk increases. Factors such as poor data quality, loss of critical information, and access to unauthorized information become more likely. Gartner recommends appointing a lead information steward role in relevant business units to assist in creating and executing risk controls with regards to data use in business operations.

All of the above steps to help manage your data can quickly turn around and save or make your firm money. You have the data- now just unlock the value of it with master data management.

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.

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

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 e-mail info@explainyourdata.com.

Banks Begin Turning To Data Consultants To Play Catch Up

Major banks are sitting on mounds of big data, and most of them have no clue what to do with it.  While banks are willing to invest, and understand that data analytics can save them money, they simply don’t know what the next steps to take are.

“Banks Have A Long Big Data Journey To Catch Up With Google and Facebook”

Large financial institutions have between 50-100 petabytes of data. However, less than 10 percent of this data is readily accessible. Furthermore, less than 1 percent is actually used for analytics.

These financial institutions should begin by addressing the business problems that big data helps solve in a way that older methods don’t. Examples include: marketing, fraud prevention and risk management. Then, it is important to look for the technologies that will best serve those purposes.

Some companies are beginning to launch analytics platforms that utilize advanced analytics englines. One company has launched the Tresata Analytics Platform.

According to this company, it has automated the process of creating data assets from its clients’ vast troves of existing data across all customers, geographies, markets and products.

“We are having tremendous success and showing banks the benefit of applying a data approach to solving massive business problems is a game changer — we can do it better, faster and cheaper,” said Mehta.

The company’s customers are using it for many things such as: payments flow analysis, trade flow analysis, automated risk scoring and regulatory reporting.

If you need assistance identifying your big data solutions, you can Click Here to learn more about business solutions using big data. Or Click Here to directly contact us at Cliintel. We can help!

Process Redesign and Software Enhancements Reduces Operating Expenses

Customer service is critical for the success of most companies. But it comes at a cost. For a leading provider of industrial-strength hardware, software and services this cost had become inordinately high due to a business decision to “give service” or support to customers regardless of entitlement. Cliintel was asked to assess the situation, create new processes to correct the problems in the software which had been developed for the European/Middle East and Asian (EMEA) markets, and then to oversee its deployment in the Americas.

The Client:

The Client is a leading provider of industrial-strength hardware, software and services that power the internet with installations in more than 100 countries.

The Business Issue:

The client had reached an impassable situation. During a period of quick expansion, both the database available to the call center representatives and the tools needed to verify customer entitlement for services contained significant inaccuracies. In an attempt to address these issues, the client created a policy of providing unnecessary service to assuage customers and attempt to maintain customer retention. The customers soon became accustomed to contacting the call center and simply demanding service which often resulted in a technician being dispatched to their location to resolve issues. This practice was barely maintaining customer satisfaction levels, but was creating unnecessary costs in excess of $4 million per quarter. The company needed a solution to the systemic problems of inaccurate customer information. In other words, the client needed a tool that would quickly and accurately determine the entitlement status for any given customer 24×7, 365 days a year as well as provide an action plan for correcting, uplifting or abandoning customers who were out of their warrantee or support period.

The project was completed under budget, within the 45 day schedule, with the client realizing a savings of $4 million in the 1st quarter, eliminating the unnecessary costs previously being incurred.

The Challenge:

The client database mining algorithm had been developed in the EMEA markets for the purpose of handling such a problem. The challenge was to deploy this tool in the Americas, where the customer base was 25 times the size of the EMEA markets currently using the tool, with a deadline looming in 45 days.

The Solution:

The solution was to gather stakeholders, agree upon a level of service and negotiate with the Sales and Service Delivery organizations on an acceptable response time for corrective action. Then they could proceed to development to rapidly enhance the EMEA product for the Americas and deploy it in 45 days.

Due to the incredibly short deadline Cliintel employed a strategy to break down the processes into manageable units. A Rational Unified Process (RUP) model was used to complete the development of the enhanced software, followed by a Change Acceptance Process (CAP) developed with the stakeholders to ensure a smooth and efficient transition to deployment.

The Project Results:

The project was completed under budget, within the 45 day schedule, with the client realizing a savings of $4 million in the 1st quarter, eliminating the unnecessary costs previously being incurred.

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 Cliintel.com.

Diverse Expertise Opens Up New Markets

Many companies come up with a great ideas that they know will help a particular industry, but then struggle to formulate a plan to access and acquire customers in the new market. Cliintel is comprised of experts with diverse expertise in a wide variety of fields that can be quickly leveraged by our clients to ensure their successful entry into new markets and industries.

The Client:

A leading innovator in the Radio Frequency Identification (RFID) business had been working with a diverse client base that ranged from aerospace to the medical industry. They had recently identified the retail vertical as a potential new market for their products.

The Business Issue:

The primary use of RFID technology is for inventory tracking. The client wanted to broaden their reach by using their software solution to solve issues within the retail space. They had built a solution to track the relationships of products within a store location, providing real-time data on customer behavior and interaction with the products. The problem was trying to identify a client who would be willing to “beta-test” to validate the benefits from the solution and provide references.

Cliintel’s research enabled the client to complete product development ahead of schedule and successfully enter the retail market by successfully implementing their solution in record time while simultaneously acquiring new, referenceable customers.

The Approach:

Cliintel took a broad view of the retail industry, looking for beta-test candidates with needs that aligned with the primary uses of the RFID technology and who would realize value from the innovation. The industry was examined collectively and objectively to identify specific candidates who prioritized relationship marketing performance metrics, had large supply-chains and were targeting both internal and external loss-preventions programs.

Cliintel’s research enabled the client to complete product development ahead of schedule and successfully enter the retail market by successfully implementing their solution in record time while simultaneously acquiring new, referenceable customers.

The Solution:

Cliintel presented three key retail venues that they felt would benefit most from the client’s solution. Specific requirements for the solution were identified for each venue – ranging from pure inventory tracking to relationship marketing. After quickly conducting extensive market research, Cliintel identified specific companies that needed an inventory solution and possessed the willingness to participate in the beta-test.

The Project Results:

Cliintel’s research enabled the client to complete product development ahead of schedule and successfully enter the retail market by successfully implementing their solution in record time while simultaneously acquiring new, referenceable customers.

We’re proud to help our clients solve tough problems and achieve stunning results. To see what kind of big data results Cliintel.com can deliver for you, please Call 720-200-3001.

How To Save Money With Big Data

Often times when the next big thing hits the market, people jump into it without careful consideration. Don’t be the company that dumps all your money on Big Data without first knowing how to use it. These three steps describe how to use Big Data smartly, allowing it to make you money.

Test and Learn                                                                                                                                                                                                                                                                                                          

• Make sure your IT team includes someone who’s responsible for testing your Big Data Model. Use the Test and Learn strategy to conduct quick, cheap tests frequently. This will enable you to expose variability, uncover needs and ultimately improve overall performance with fast insights.

Manage Data Processing Wisely                                                                                                                                                                                                                                                            

• Those who have been successful in the Big Data industry are the ones who are most clever about how their data is processes Knowing how to ask the right questions allows data models to process and store the data more efficiently. When possible apply low cost methods to first, using cheap IT tools to fun queries.

Use New Data Types                                                                                                                                                                                                                                                                              

• Integrating new types of relevant data allows for more dynamic information. Companies who rely only on internal data collected will outperformed by companies who include other factors such as weather or traffic. The more relevant data collected, the better the information which allows us to analyze and make decisions more accurately.

Interested in how these methods save companies money? Learn More!

Customized Application and Deployment Improve Technician Availability

For one of the largest Multi-System Operators (MSO) in the broadband industry, the importance of higher standards of customer care could not be underestimated given the fierce competition the company faced. With more than a thousand telephony/cable/HSD providers active in the United States, the MSO needed to improve customer satisfaction. To achieve this the client needed assistance deploying a new workforce management tool in the Florida market.

The Client

A leader of global broadband products in the United States, the client had more than 15 million subscribers. The client offered telephony, video, and high-speed data services for the lower 48 contiguous states from Key West, Florida to Seattle, Washington.

The Business Issue

Prior to implementing CSG’s Workforce automation solution, a number of high-prioritized specific market issues had to be taken into account. Two of these issues in the Florida Keys were: 1) The annual “Snowbird Effect” and 2) The high number of multiple dwelling units (MDUs) These issues caused major operational challenges in the delivery of service due to the large number of voluntary disconnects in the spring, and similarly large number of reconnects in the fall, as well as an inordinate number of per capita “bulk accounts.” The incumbent billing system was not designed for maintaining either bulk accounts or greater than 50% yearly churn. In order to meet the special needs of the “Snowbird” and MDU customers, the client turned to Cliintel to design a process that would adapt the enterprise solution into the local processes and coordinate the implementation efforts.

The Solution

Cliintel completed a needs analysis of the operations. The analysis identified that the technical operation centers throughout the Keys could not individually meet the needs of each of their markets. The solution involved a process adjustment so that during times of greatest needs service could be delivered in the “Keys” markets by combining the technical resources. The analysis pointed to CSG’s Workforce Express solution to coordinate the activities of the entire Florida Keys workforce. The MSO was then able to service all the voluntary disconnects in the spring, reconnects in the fall and service the bulk account work orders, without negatively effecting uninvolved customers as had been an issue in the past. Cliintel led the implementation of the Workforce Express product by defining the needs of the markets and illustrating to the end-users how the product would address their issues.

Cliintel recognized that the CSG implementation teams knew how to set-up the product, but their focus was not on how to use the product. Cliintel helped shift the focus to the user thus obtaining a proper level of buy-in and improving customer service.

The Project Results

Cliintel reduced the learning curve for new end-users. Alignment of goals and operational procedures allowed the Keys markets to meet the needs of the customers. By focusing on historical data and current workforce capabilities, the management group was able to allocate the appropriate number of technicians to specific needs. The MSO was then able to service all the voluntary disconnects in the spring, reconnects in the fall and service the bulk account work orders without negatively effecting uninvolved customers as had been an issue in the past.

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 contact us.

Want To Make Your Data Matter?

Looking for a reputable company to help you with your Big Data? Cliintel is one of the leading sources for Big Data Analytics. Let us explain your data and help you find the insights that add up to results!

Learn What Your Business Should Not Do With Your Data

While many times using big data can help you make and save money, there are some things you should not do with your data.

Watch this quick video to learn 5 things you should NOT do with your data. For example, you should never leave your data with someone you do not trust or someone who does not know how to properly analyze your data.

Saving Money With Big Data – On The Federal and State Level

From the government offices, Federal IT officials say real-time analytics of big data can help reduce the federal budget by at least 10 percent annually, or about $1,200 per citizen, by detecting improper health care payments before they occur, according to the TechAmerica survey. If we can save that money, we can also save sickness and lives!

Yet, despite all the real and potential benefits of big data analytics, federal and state IT officials also cite several barriers to adoption, including privacy concerns, the expense of new tools, lack of clarity about big data’s return on investment, and the time it can take to extract queries from traditional databases in a timely manner. There are data podcasts which discuss this more deeply.

Parents, Have a Date Night and Enjoy Restaurant Week

Westport Parent's Night Out Sign up by TH at 10am

Parents, Have a date Night Enjoy Restaurant Week Let us play with your kids for the evening!! Friday July 24th 5:30-9pm Drop your kids off with us from 5:30-9pm for tennis, swimming, pizza & games ages 3-12* *children that cannot swim the length of the pool must wear a floatation device during swimming. Space is limited call or email now to reserve your child's spot westportclub@att.net or 704-489-2227 Cost includes 3 1/2 hours of childcare and dinner Kids will play tennis for an hour, eat dinner, swim & end with games in the yoga room drop off at 5:30pm pick up by 9pm 1 Child $28 2 children in same family $38 3 children in same family $48

Saving Money With Data – Data Video On Things You Need to Know About Big Data

Can big data be a money saving tool? Well, if you look at this data video, you can see some quick easy tips on data and how to save money.

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Big Data is Fundamental in the Hospitality and Travel Industry

Big Data in the Hospitality and Travel Industry

It is vital for all players in the travel industry to effectively manage the millions of records about travel behavior that the industry generates daily.

Travel is ripe for the use of big data; Take the photos being posted on Facebook or Instagram. Would the traveler that shares snaps from a trip to Ireland be interested in information about Scotland?

If shown on a mountain bike, would that individual want to know more about local biking destinations or biking clubs?

If shown standing in front of a car with a bicycle roof rack, wouldn’t a trunk rack be easier to use and avoid back problems down the road?

Big data and data analytics suggest that the future may belong to those firms best able to shape and deliver the consumer travel experience.

Personalization

In a series of interviews within the travel industry, the authors of the study from the Society of Consumer Affairs are intent to show how Big Data can be used to increase impact and reduce friction across disciplines, both within a company and the industry.

Personalization is a key tenant of Big Data; there is a plethora of information about particular consumers, transactions or destinations, the reality is one of detailed, accurate personalization.

However, in order to most effectively win at true personalization, large travel companies must work across silos to gather the myriad data points created by a consumer at different points, as the study emphasizes:

Information systems can be quite fragmented and even territorial, with records pertaining to a single customer showing up in reservation, post sales complaint, survey, loyalty and other systems, with little or no ability to weave together and form a complete customer profile.

Combining data from different in-house systems can help companies achieve new insights.

Call centers must interface with online consumer reviews; loyalty programs must link with booking histories; on-property preferences need to be combined with social media chatter. It’s a giant firehose that first must be segmented and then packaged in a useful way for employees at each stage of the consumer lifecycle.

The customer should be at the center of all Big Data efforts. If the data gathering is seen as creepy or invasive, the consumer will not be pleased and loyalty will be lost. However, all signs point to consumers willing to accept vast intrusions into their behaviors if the resulting product is more targeted and able to anticipate their needs throughout.

SOCAP names the following distinct areas that companies need to master in order to succeed at a Big Data-fueled consumer experience:

1. Align company offerings and customer needs.

2. Build internal consensus.

3. Collapse data silos.

4. Create unified, logical data views.

5. Elevate the customer care role in customer experiences.

6. Collect and use data responsibly.

Internal buy-in comes not only from active consensus building, but also by ensuring that the company’s offerings are addressing customer needs, and thus making it easier to train employees to be active in solving these needs, and understanding the value they are providing.

Aligning the company with customers also assists in the elimination of silos and fiefdoms.  It also allows for the integration of an open sharing of data and information company-wide. This also helps foster a collaborative environment focused externally on the customer and not internally on politics.

Finally, privacy is a paramount concern when it comes to Big Data. Avoiding a privacy snafu is an essential component of successful Big Data implementation, and also ensures trust among customers.

Need help utilizing big data in your company. Contact us, and tell us about your problems, and see how we can help!

CIO Conference – Big Data and Change Discussed In Denver

Can Big Data be the catalyst for change? The CIO’s will be discussing this at the SIM Women Annual Summer Conference.  There is still time to get there for the August 28th meeting.  We will have this topic on hand.

Register Here

International Business Videos – Does The Best Product Get The International Business Deal?

This one minute video on global business asks if business deals are done because the product is better. Does the best mousetrap mean we got an international customer?

Here are 5 Top false assumptions in doing international business

We see it repeatedly, from the low-level trainee right up to the CEO. Americans often start with the wrong assumptions when entering a foreign market

The assumption set used when marketing, selling, hiring and buying from foreign countries is critical to our eventual success.

When devising an international strategy for a corporation, the presumptions are the first thing to address.

—- There is an “international market.”

Ghana, Greece or Malaysia? This first assumption divides the world into two pieces: us and them. And the danger is apparent: We think of the “rest of the world” as one entity. Intellectually, we know there are several entities, each with their own language, culture and business practices.

—- “Business is business” (the world is getting smaller).

The shrinking of the planet forces us to make less, not more, suppositions about how our counterparts conduct business. Thirty-five years ago, a $50 million manufacturer didn’t worry about Chinese offshoring, Indian software or Italian design. Today’s CEOs must think globally, initially by recognizing the differences, not the similarities.

—- Our technical skills will transfer abroad.

A CFO is a CFO. An XML programmer is the same anywhere in the world. This attitude costs money, reputation and time to market. The CFO who is an expert in financial modeling needs to interact with locals who may not respect his authority or knowledge, and may organize finances differently.

—- A contract comes at the end of the process; a deal is a deal.

The “holy contract” (as Dutch often call U.S. contracts) comes at the end of U.S. negotiations. Contracts often serve as “outlines” in Southeast Asia, the Middle East, and Central and Eastern Europe. The rule to think about is “first a contract, then a negotiation.”

Global Business Video – What Gets The Best International Deal?

3D Printing Video – React To 3D Printing Technology With Copper

At Virginia Polytechnic Institute and State University (VT), Christopher Williams heads the effort to further advance 3-D printing–known among engineers as additive manufacturing–with copper, a widely used conductor in electronics. Williams is using a process called binder jetting in which an inkjet printer selectively jets glue into a bed of copper powder, layer-by-layer. The printed copper product is then taken to a furnace to fuse the particles together

With support from the National Science Foundation (NSF), Williams is addressing a major challenge in the 3-D copper printing process, which is to eliminate the porosity that develops in the part during the process. These microscopic pockets of air weaken the finished product. Is it time to move from 3D Printing Plastics to metal?

Data Scientists Wanted

Data scientists are a new name for the very intelligent people who analyze data. The have been referred to in the past as data analysts and are great demand. As companies continue to integrate the use of Big Data in their business, the more they need Data scientists to analyze the data and find the patterns that will help these companies make faster, more informed decisions.

Banks are the new kids on the block and are desperately seeking Big Data Scientists to help them understand all of the data that is flooding their databases. Although the majority of companies use Big Data for the same thing; to analyze patterns and predict future trends, banks are going down two different paths.

Banks like Capitol One are hiring Data Scientists to apply technology that will help point out the big opportunities to help customers save time and money. Goldman Sachs is using Big Data Scientists as security guards. Goldman Sachs has a surveillance program that searches for insider trading and market manipulations. They want Data Scientists to screen their program for any potential dangerous behaviors their program is missing.

No matter which path banks take, the commitment to use Big Data will change the way banks interact with their customers. There will be more strategic advertising geared towards individuals and more fine print explaining what the banks will do with their customers’ very personal information.

Banks are not the first to mass hire data scientists, they are actually pretty late in the game. With the rise in demand for data scientists, we can only hope companies are hiring people who know what they are doing.

Talking About Change?

Here is a conference in Denver Colorado on August 28th in Denver. Listen to Rich Batenburg , Author of “Change Is Great, Be The First”

In his operations he has also streamlined technology infrastructure, business processes, and practices as well as established strategies to maximize profitability while reducing costs. Batenburg excels at “end-to-end” processes to help front line employees deliver products and services to customer.

Sign Up for the conference Conference

Big Data Questions – 5 Questions You Should Be Asking About Your Data

Here are the top 5 Big Data questions you should be asking right away. Enjoy the Big Data video!

Big Data Tip – 5 Questions You Need To Ask About Big Data

Here are the 5 questions you need to ask your self and your firm about Big Data. If you can’t answer them, there is still good news. We can help!

Big Data Podcast –

Here is a quick radio show discussing the upcoming CIO conference in Denver, Colorado later in August.

register here

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World Class Coaches and Players at ProWorld Tennis Academy in Delray Beach Florida

Glad to have at the ProWorld Tennis Academy such nice people and such world-renowned coaches as Emmanuel Planque, Jean Marc Leboscq and former Gustavo “Guga” Kuerten coach Larry Pasos.

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Brandon Marinoff Knows the Justice System From The Inside – Colorado Criminal Defense Attorney

If you have been accused of a crime, arrested or even investigated, contact an attorney right away. Criminal defense attorney Brandon Marinoff will help protect your rights, explain the consequences of the charges and defend you to protect your freedom…

Cliintel CEO to Speak at CIO Conference

Hear Richard Batenburg, Jr. the CEO of Cliintel speak on his upcoming book “Change Is Great… Be First!” at the upcoming SIM Women Annual Summer Conference in Denver.

SIM Women Annual Summer Conference 2015

Join us at the 1st Annual Summer Conference for SIM Women, held on Friday, August 28 from 8AM-5PM in Denver, CO.

This day-long conference for professional women will focus on thought-leadership, innovation & collaboration. Presented by the Colorado Society for Information Management (SIM), the event will be held at the Wellshire Inn, 3333 South Colorado Blvd, Denver, CO 80222.

Click Here to Register.

Big Data, What Is It Good For?

Many people believe “Big Data” is just a hype. It is the cool new fad that will last a few years and then plateau. Some even believe that Big Data has reached its limit, it is worn out and useless.

I beg to differ. To understand how important Big Data is we need to first explain what Big Data is, in the simplest form.

Data= information

Big Data= information on a very large scale or A LOT of INFORMATION.

Now, Data doesn’t mean much if you cant understand it. If someone gave you a paper with a bunch of numbers on it, you would think “what the heck is this?”, but if someone then explained to you that those numbers represent the statistics on cancer in the US. Well then, this paper would no longer be meaningless numbers but valuable insight into the patients who survived and what medications they were taking.

According to the surveillance research conducted by the American Cancer Society, it is predicted that 1,658,370 Americans will be diagnosed with cancer in 2015. This leads me to believe that there could not possibly be one American who doesn’t know someone affected by cancer. This is a Big problem.

With every problem comes an opportunity to find a solution. This is where Big Data steps in, Gaurdant Health is using Big Data to aid in cancer research. They have created a blood screening product called Gaurdant360. This product is revolutionizing cancer research by collecting patient data in a much more efficient and cost effective way.

The only way to access genomic information about a tumor is to do a very painful and expensive biopsy, but now with the Gaurdant360 we can simply collect blood samples from patients and have them screened for genetic tissue unique to tumors. Through this technology researchers around the world can more easily access a vast amount of patient data and learn more about the patterns of cancer and how to combat it.

The more information researchers have access to, the higher the likelihood of discovering a cure.

Now, if the majority of the population still feels that Big Data is useless and that  “the internet of things” is more important, then so be it. But I am rooting for people to continue to invest in information, invest in knowledge and research, not a car that drives itself.

Let us know what you think! Leave a comment on our Facebook Page!

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 info@explainyourdata.com.

Database Consolidation Aids in Business Decisions

In a very short time following its IPO, a national restaurant chain had successfully increased their number of restaurants to over 630 stores throughout the nation despite the highly-competitive nature of the fast-food industry. This may sound like a recipe for success, however the burgeoning growth brought with it unexpected technological challenges such as outgrowing their back office operations.

The Client

The restaurant chain is a wholly-owned subsidiary of McDonald’s Corporation with 630 companyowned restaurants nationwide in 28 states and employing over 14,000 employees nationwide.

The Business Issue

By meeting their very aggressive growth goals, the client experienced the creation of a number of legacy database systems that were either redundant or no longer relevant. The client realized that to actively meet the changing demands of the continually evolving operational support systems, steps would need to be taken to improve interactions and business intelligence. The business consisted of a number of distinct areas of activity including: sales, customer service, legal, and product delivery. Prior to the consolidation project, the client could only monitor business performance on a month-end basis. This was a time-consuming process making month-end reporting slow and inadequate.

The client needed to analyze its supporting processes and information requirements across the organization. They expressed a desire to consolidate all of their legacy databases into one system that would enable the sharing of all business and customer facing information. In addition, once the databases were converted to the new system, the old records would need to be stored in a manner to allow access to the history they contained. The client made an executive decision to implement PeopleSoft Enterprise Customer Relationship Management (CRM) and retained Cliintel to manage the consolidation.

The Approach

Cliintel applied proven Project Management Institute (PMI) methodologies to manage this consolidation project. PMI standardized documentation offered complex content in a simple to use format, enabling comprehension of the multifaceted project’s direction and status. This was accomplished in less than 90 days, under budget, caused no disruption to the resources and improved overall back-office efficiency In crafting the solution for the client, Cliintel’s primary objective was to analyze the client interactions, processes, and data requirements in their current state and devise a future state that took advantage of existing commonalities in the process steps, data elements and business rules. One of the success factors of the engagement was to clearly hear the voice of the end users and work with them to identify pain points and ways to support their existing work habits when interfacing with clients. By decomposing the process steps and requirements, the team developed a catalog of data elements, entities, and aggregates, as well as the associated business rules. The analysis resulted in the consolidation of numerous data needs into a core profile. Equally important to the analysis was the ability to capture future state business requirements and to create traceability across the processes, elements and rules requirements.

The Solution

Cliintel utilized their proprietary INSIGHT methodology that captures and documents business requirements, business rules, data elements and values. The method then creates traceability and extensibility across these requirements, as well as the test plan and system requirements that allows for consolidation into the PeopleSoft CRM. The solution provided the steps necessary for converting the required databases to the PeopleSoft CRM by redesigning the processes and information requirements that support the back office. A roadmap was generated to guide the detailed decomposition and automation of the new business requirements. Throughout the engagement, all decisions were mapped to a balanced scorecard that clearly defined the value propositions to Boston Market to assure vision attainment. Lastly, Cliintel coordinated the efforts of the conversion team to leverage the existing knowledgebase on the legacy systems to be decommissioned.

The Results

The 19 legacy databases were successfully converted to the new PeopleSoft CRM platform that enabled the improvement of business processes. This was accomplished in less than 90 days, under budget, caused no disruption to the resources and improved overall back-office efficiency.

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 contact us.