Annual Gartner Predictions

Posted on

Gartner recently completed its Symposium ITXpo where it makes predictions on how technologies will evolve and how they will be used. Curtis Franklin provides a summary on Information Week of these predictions. Let’s take a look:

  • Artificial intelligence (AI) will positively impact the behavior of more than 1 billion workers around the world by 2020
  • As the number of commercial transactions continues to grow, Blockchain, although in the early stages, is showing promise to reduce transaction “friction”
  • Gartner believes the infrastructure is there to support new data and increased data from IoT. Gartner expects that by 2020 IoT storage demand will be less than 3%
  • Industrial IoT will bring more predictability to maintenance, benefiting the bottom line by reducing costs
  • In the coming years every $1 of innovation will also require $7 for deployment and operational costs
  • Company investment in fitness trackers will play a role in reducing employee health care costs, but there will be a need to address privacy and security
  • As augmented reality continues to gain traction through gaming, Gartner expects by  2020 that it will also be commonly used for shopping assistance by consumers

What technology trends is your IT team seeing take hold?

Big Data Predicts

Posted on

Big data analytics is providing many new insights for companies around the world.  Bernard Marr reports for Forbes that predictions from big data analytics are being made every day by some of the most well-known companies in the world – buying habits on amazon.com, Netflix movies and even dating sites.  There are many other situations that big data is being applied to that you might not realize.  Mr. Marr points out several:

  • Weather. Always a topic of conversation in Minnesota, weather affects not just our weekend plans but also the operations of many businesses.  More accurate weather reports, especially in rural areas, are now possible due to the multitude of sensors and increase in mobile devices. More data allows for better weather predictions down the road
  • Health and disease.  From diabetes to cancer, big data analytics is being utilized to identify risk factors and early signs.  Big data analytics is being used to improve patient outcomes as well as find ways to combat rising healthcare costs
  • High school dropouts. Mr. Marr reports that nearly one in five students in the U.S. do not complete high school on time.   Many states and even districts have their own programs in place to increase graduation rates, but what if a larger approach could be taken using big data methods. The Center for Data Science and Public Policy at the University of Chicago is doing just that – applying data discipline to identify dropout risk factors to help more youth complete high school
  • Cyber attacks. A timely topic in recent news, big data analytics tools can actually be utilized to help detect and predict security threats

Big data analytics has many applications. From consumer buying behavior, patient symptoms, public policy and even the weather, the insights it can provide are on track to make long lasting impacts.

MN Perspective: Big Data & Healthcare

Posted on

A recent article on the Star Tribune by Joe Carlson brought the conversation about healthcare and big data analytics close to home. Several Minnesota-connected companies led discussions on working across the industry to utilize data from insurance, hospital, pharma and medical device sources to drive better patient outcomes and manage rising costs.  Working with big data analytics tools has been key to making this possible.

The first example comes from Medtronic and UnitedHealth. Many might think medical device and insurance companies might not always have the same goals in mind but not true.  The two companies partnered together to discover the value of the features of a Medtronic insulin pump vs. other pumps on the market.  Mr. Carlson reports they discovered that there was a decrease in hospitalizations due to complications from diabetes when the Medtronic pump was used, thus decreasing overall insurance costs.  This led to a change of thinking.  Dr. Richard Migliori, chief medical officer of UnitedHealth explains in the article, “It caused us to stop looking at line-item cost figures and start looking at, what is the total value? Because we saw a total value, we then began to wonder; shouldn’t we be (paying) on the basis of total value?” In 2016, UnitedHealth announced that Metronic would be its preferred insulin pump provider.

In Mr. Carlson’s article, he also gains insight from Mayo CEO John Noseworthy.  Mr. Noseworthy adds that the industry has changed in the last five years and the atmosphere is one of “partnership, trust and transparency” in order to work together to bring down rising costs and improve patient outcomes.

Finally, St Jude Medical is working on a solution to reduce chronic pain by using a medical device versus pain medications. According to Mr. Carlson’s article prescription opioid painkillers are not only addicting but they lead to 15,000 deaths per year.  Using big data analytics, St. Jude is looking to make the case for using its device which has a larger upfront cost but may reduce overall costs long term.

The power of big data analytics and a great spirit of partnership has helped make these connections possible.

Early Adopters Report Cognitive Benefits

Posted on

IBM explains cognitive computing as follows, “cognitive technology augments human expertise to unlock new intelligence from vast quantities of data and to develop deep, predictive insights at scale.”  Cognitive computing is opening up more real-time opportunities  for many businesses across many industries. In fact, analysts expect investment in cognitive technology to grow from $2.5 billion in 2014 to $12.5 billion in 2019. IBM recently surveyed over 600 decision makers who are early adopters and asked about the benefits they are experiencing.

First, who are the early adopters?  Below is a great graphic from IBM outlining where these early adopters fall within their cognitive uses:

The cognitive early adopters

Here are also some of the reasons why they are investing in cognitive:

  • 65% of early adopters view cognitive technology as very important to their organization’s strategy
  • 58% feel that cognitive is essential for digital transformation
  • 58% reported that they feel strongly that cognitive will become a “must have” in just a few short years

62% of cognitive users are already reporting that their projects have exceeded expectations.  For the most part these early adopters are finding success in three categories: customer engagement, productivity and efficiency and business growth. Here is a break down from the survey:

  • 49% report more personalized customer/user experiences
  • 42% said they have been enabled to respond faster to customer/market demands
  • 46% have seen improved decision making and planning
  • 46% report improved security and compliance
  • 41% have used cognitive to expand the company into new markets
  • 45% report a reduction in costs due to productivity and efficiency gains

Business growth - IBM Cognitive Graphic

The road to adoption isn’t always easy. Many of the decision makers surveyed sited data management and an employee skills gap as challenges. Turning to outside expertise has been key to helping them overcome both challenges.

Cognitive computing is helping many early adopters unlock new opportunities. As more practical use cases develop, we can expect more companies to put cognitive technology to work for them.

Industry Spotlight: Manufacturing & Big Data

Posted on

68% of manufacturers are currently investing in big data analytics in the next twelve months and 67% are moving forward with these investments even as they cut in other areas. Mr. Louis Columbus of Forbes breaks down for us a recent analytics/IoT Honeywell survey of 200 North American manufacturing executives.

According to the survey, 46% of respondents no longer see big data analytics as “optional.”  Instead, the benefits of big data analytics are clear to many in the industry:

  • Equipment performance.  Unscheduled downtime was sited as a top threat to revenue.  51% of respondents agree that the combination of the Industrial Internet of Things (IIoT) and big data analytics will help to predict equipment downtime, maintenance needs and breaks/repairs
  •  Supply chain management. 46% of the executives surveyed agree that big data analytics will help with supply chain performance by allowing them to better plan for and use resources more efficiently
  • Safety. 47% of respondents agree that access to better equipment and operational data through big data analytics could help detect possible safety issues
Big Data Benefits - Forbes
Source: Forbes.com

Mr. Columbus reports most executives are fairly confident on the analytics path they are on. In fact, 65% report being on the “right track” or “above the curve” when it comes to their use of big data analytics. In summary, the results of this survey show that big data analytics will be key to allowing those in the manufacturing industry to improve revenue and operations for their companies.

Modernize Your Data Warehouse

Posted on

Entrepreneur reports that by 2020 every person online will create 1.7 megabytes of new data every second, and according to a study on  Computerworld, by that same year $72 billion will be spent on big data hardware, software and professional services. Data is growing and its coming in many forms both structured and unstructured, and companies are looking for the tools to help them manage and utilize it.

Big data can provide a more complete picture of your customer, marketplace or product/service. But before you can take advantage of big data, you must first have the right systems and tools in place.  Now is the time to consider your own infrastructure to make sure the right workloads are working on the right technologies.  In fact, it may be time for your company to take a deep look into how your data warehouse architecture can be modernized, so you are ready to move ahead with big data analytics projects.

Modernizing your data warehouse can increase your ability to deploy new workloads and handle new data sources.  You can also simplify your operations. Modern appliances can be integrated with your data warehouse, filling service gaps and making deployment and management of data easier.  Finally, a whole new set of tools for big data analysis are available. These analytics tools can integrate into your system allowing you to crunch massive amounts of data to form actionable insights.

So how do you get started on the right path? A trusted partner can help you develop a plan for the changes needed to modernize your data warehouse architecture and can help identify the right big data analytics tools for your company. Evolving Solutions takes the time to fully assess your data and business objectives, develop customized software solutions based on your needs, and we provide ongoing support.  We take the time to understand your goals and help you to accomplish them. Contact us today to start discussing how to modernize your data warehouse.

Industry Spotlight: Banking & Big Data

Posted on

Big data use has been expanding across a variety of industries. Today let’s focus on the banking industry and how it is using big data.

Business Insider reports that some of the biggest banks in the world hope to use the information found on social media channels like Facebook, Twitter and Instagram as part of a customer’s credit history or in place of one when none is available.  Of course, developing a system to handle this type of data does not only bring technology and system challenges but also regulation and privacy challenges. Still, many feel tapping into social media would allow the industry to get amore complete picture of the consumer’s financial status and credit.

Bernard Marr spotlights Citibank’s use of big data in a Forbes article.  Citibank is taking a “data-led” approach to its decision making and using big data analytics across areas such as customer retention and acquisition, customer service and compliance and fraud. Citibank has over 200 million customer accounts and operates in hundreds of countries which all equates to a lot of data to handle and store. Adopting big data tools and processes has also helped Citibank to utilize data better and manage and store data more effectively. Mr. Marr writes, “At Citi, model testing allows for a holistic understanding of innovative use cases by deconstructing data at its most granular level as well as synthesizing structured and unstructured data sources.”

The banking industry is making inroads with big data to better serve its customers. It continues to look for solutions that strike a balance between regulations and privacy and solutions that support the vast amounts of transactional and customer data it already has with new data sources.

Cognitive Computing: Improving X-Rays

Posted on

“What if your X-ray could predict a potential disease months in advance,” writes Laura Lorenzetti for Fortune. This past summer IBM Watson Health created a new partnership with leading medical providers and imaging tech companies to see if cognitive computing can take medical imaging one step further to actually predict the chance of diseases like cancer and heart failure.

Ms. Lorenzetti’s article points out that much of the data gathered from an x-ray or MRI is “unstructured.” It can be difficult for computers to connect the information to patient records in a meaningful way. IBM Watson Health is trying to change that and utilizing its power to connect unstructured data with its massive databases of patient medical history.  Ms. Lorenzetti writes, “the goal is to provide new offerings across various medical environments (a hospital ER or an everyday physician’s office) that can connect systems (medical records, picture archiving, lab results) and deliver cognitive insights to doctors on the spot for better diagnoses.”

One example from the article is the use of mammograms. Not only could Watson connect the image results to the patient’s medical history but it could also “cross-reference against the similar patients within the Watson database.”  These connections could improve a doctor’s  ability to identify early warning signs or risks.

Another example is the use of cognitive computing to help doctors predict which patients are more likely to have a heart attack after reporting chest pain.  Ms. Lorenzetti reports that 2% of patients who visit an ER with chest pain have the early signs of a heart attack missed. By connecting the data dots IBM Watson Health could help doctors identify these signs better.

IBM Watson Health’s shear power to process unstructured data such as medical imaging while also consuming vast amounts of patient data allows for it to draw cognitive insights that will one day improve patient diagnoses and treatments.

Industries Exceling with Big Data

Posted on

“Two and a half quintillion bytes or 2,500,000,000,000,000,000 bytes. That’s how much data humanity generates every single day. And the amount is increasing; we’ve created 90% of the world’s data in the last two years alone,” writes Michael Belfiore for IBM’s Watson Blog.

Many businesses struggle with this ever increasing data, especially growing unstructured data, but other businesses in an assortment of industries are succeeding by using cognitive computing technology to turn big data into big insights.  Mr. Beliofe provides a summary of several industries succeeding with big data:

Telecommunications – cognitive computing tools are being used to index documents, images and manuals giving call center agents access to more actionable data to better solve customer issues. Every second saved in call time is $1 in cost savings.

Finance – an auto finance firm is using big data to develop better customer insights that not only allow them to serve customers better but also to improve data security.

Healthcare – by being able to better capture and analyze unstructured data, one health system is using this data to help identify patients with risks for chronic diseases to improve treatments and reduce readmission.

Fitness – the rise of mobile and wearables has led to a fitness app that tracks your performance and progress and coaches you through your workouts to meet fitness goals.

Retail – a clothing retailer has used big data to drive a better in-store experience using sensors and Wi-Fi data to track customer behavior while in the store.

Travel – one airline is using mobile to access customer preferences, travel history and even allergies to provide more personalized service in-flight.

In each of these examples, cognitive computing technology allows companies to harness big data to create better customer service experiences.

AI – Practical Applications

Posted on

Last week’s blog post featured information on what augmented intelligence (AI) means and the industries using the technology from IBM Research.  Today, let’s review a couple real life examples of AI applications.

First, a quick definition, IBM prefers to refer to AI as augmented intelligence.  Their approach is to use cognitive computing capabilities, such as machine learning, reasoning and decision tech, language, speech and visual tech and human interface tech, to create practical applications that enhance and scale human expertise.

IBM’s Watson Health – Partnering with New York’s Memorial Sloan Kettering Cancer Center (MSK), IBM’s application helps to consume and process the massive amounts of medical research while also “learning” from cancer experts, working to ultimately expand access to cancer treatment options and expertise. Laura Lorenzetti of Fortune explains, “Some MSK oncologists have a highly specific expertise in certain cancers. By training Watson to think like they do, that knowledge expands from one specialist to any doctor who is querying Watson. That means that a patient can get the same top-tier care as if they traveled directly to the center’s offices in Manhattan. IBM’s Watson provides the framework to learn, connect, and store the data, while MSK is imparting its knowledge to train the computer.”

Financial Services – cognitive computing is assisting financial advisors so  they can better serve their  clients.  By ingesting financial information and client data, Watson can answer the everyday client questions while also using its processing power to help identify potential options for the advisor to evaluate.  Many believe that by integrating with Watson financial advisors will be able to expand their practices and serve more clients. William Sprouse of Financial Planning further explains, “In practice, such cognitive computing power would work with an adviser just like a helpful Star Wars droid: virtually present during a meeting with a client, gathering data, and ready to instantly assist with queries and projections, along with its own suggestions based on client data.”

These two examples both demonstrate not only the processing power of augmented intelligence systems like Watson but also the ability to “learn”.  This ability to learn can provide access to critical expertise to more people than ever before in healthcare and financial services.