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CPG manufacturers can gain a lot from an improved approach to forecasting.

Consumer packaged goods represent an established market sector, one that captures the attention of a sizeable majority of the general public and will continue to for some time to come. With a strong foundation and brands that have a high level of recognition among shoppers, the CPG market is an indelible part of the shopping experience. However, with this segment of the economy full of large and established companies, competition is growing fiercer. How can product-makers stand out and generate more sales? Predictive analytics is a major part of the puzzle.

Predictive analytics provides stronger, more unifying insight

"The CPG market is an indelible part of the shopping experience."

The most powerful and effective predictive analytics tools, like the IBM Cognos suite of solutions, help CPG businesses drill down and learn more about customers and how new and existing products appeal to them. The IBM Big Data & Analytics Hub said a trend among CPG manufacturers and other companies is an advance in forecasting, called what-if scenario analysis. This approach moves beyond creating a single picture of potential future opportunities and concerns to create a series of forecasts based on differences in customer interest, regional markets, product variations and much more. The end result is more useful visualizations of the future than can be leveraged in a variety of specific contexts.

Using the same relevant data for each scenario analysis – and across all areas of operation – is another consideration CPG businesses have to make. The effectiveness of forecasting is significantly hampered when different data sets are used at various points in the process. This process is common across a number of businesses, but does little except make results less stable and accurate. Ensuring that this thorn in the side of effective analysis is removed and the resulting forecasting is all based off the same data is critical to success, especially when using a what-if forecasting model.

Aviana offers our partners plenty of experience and aptitude in terms of predictive analytics, big data and similar advanced techniques that help businesses make operations more effective and efficient. Our past work with businesses in the CPG market means we don't only understand the ins and outs of predictive analytics, but we also have a strong grasp on how they specifically fit into the operations of CPG manufacturers. To learn more, visit our dedicated industry page.

Posted in Business Intelligence
Michele Harnish

About Michele Harnish

Michele Harnish has extensive experience in marketing and consulting to various industries. Her professional resume includes both corporate and field marketing executive roles. Her former role as Senior Director of Field Marketing at Cognos Corporation allowed her to leverage her strong corporate marketing background as she managed a large team of field marketing managers and business development managers and was solely responsible for lead generation across North America. In 2009, Michele joined Aviana Global and continues to leverage her unique approach to marketing which incorporates the branding and strategy of corporate marketing with the results driven lead generation power in field marketing. Michele enjoys spending time with her husband and four boys in Orange County, California.
The hospitality industry can gain a lot from predictive analytics.

Addressing the needs of each and every customer is a top priority for high-performing businesses in the hospitality industry. While the basic desire of most hotel guests is the same – to have a place to sleep and store their belongings – there are uncountable variations that exist beyond this foundational desire.

Some guests will want to make use of many different hotel facilities and offerings, be it lounging by the pool, taking a trip to the spa or using a well-supplied gym room. Others will want to do little beyond use the bed at night and keep their clothes and other items safe.

How can hospitality businesses better define and understand the differences between each customer and effectively appeal to all of them? A big part of the answer lies in predictive analytics.

Effective differentiation and personalized appeals

"Understanding customer desires is critical for success."

Understanding customer desires, both in the present and future, is critical for success. Knowing when, how, why and where to appeal to them, be it through personalized marketing or a larger, mass-market approach, can mean the difference between occupied rooms and empty ones.

As eHotelier pointed out, a major gain for hotels in terms of appealing to customers more effectively can come through big data. The sheer amount of information regarding customer preferences, decision-making, past experiences and other relevant metrics is larger now than it has ever been in the past.

Using the right dimensions of information captured during previous visits means better marketing with more positive results. Business intelligence software, like the IBM Cognos suite of products, gives hospitality organizations the tools they need to conduct effective analysis and reach out to customers in ways that increase engagement and fill rooms.

Additionally, eHotelier said guests are growing accustomed to personalized experiences, to one degree or another, because they're becoming more common in everyday life. Businesses that can offer these relevant and enticing experiences have a distinct edge over those that don't.

Aviana has the hospitality industry experience to provide effective solutions for hotels and similar businesses in the market, with a focus on creating more effective customer outreach. Our past efforts, working with major hotel and casino groups like MGM Resorts International, mean we have a deep understanding of the unique aspects of hospitality and the ability to use big data and predictive analytics to improve performance. To learn more, check out our video on the topic.

Posted in Business Intelligence
Francois Ross

About Francois Ross

François has been managing software sales and delivery of Business Analytics and Information Management solutions for more than 25 years. Prior to joining Aviana, his name has been predominant within the IBM Cognos analytics space. Leveraging a strong technical background, elite demonstration capabilities, and understanding of Big Data Analytics proven practices, he has brought thought leadership in the most active clients and organizations. His passion and mission statement: delivering the most impactful data to the best user experience through the art of possible.
Setting the attractive price for a specific customer is possible through predictive analytics.

As retail businesses grow and diversify, pricing becomes an especially important consideration. Whether a company wants to dynamically price merchandise based on the sales channel, maintain the same pricing across all avenues or use both strategies simultaneously, they need data to accurately set price points.

Without the reliable intelligence and forecasting provided by predictive analytics, determining competitive prices and making sure merchandise is sold in the most effective way possible is a difficult and time-consuming endeavor. When retailers have business intelligence software like the IBM Cognos suite of products in place, however, they can make sure pricing is accurately determined and reflected across all sales channels.

"Predictive analytics gives retailers powerful insight into their pricing strategies."

Optimization and differentiation both benefit retailers
The market for nearly any product or good is significantly more diverse now than any at time in the past. The rise of e-commerce and the ability to quickly analyze and communicate information across an entire business mean different prices can be used in a variety of contexts. Whether dealing with the differences between online customers and those who visit a brick and mortar store, or shoppers from different regions of the country, dynamic pricing can lead to more sales and more satisfied buyers.

The Harvard Business Review highlighted improved pricing as one of the areas where predictive analytics is making the most positive change for businesses. The article discussed how rapid changes in pricing in e-commerce have benefited retailers. By drawing on the large amounts of customer information that are stored and utilized, retailers can determine the best possible cost to display.

By using predictive analytics, businesses can gain this advantage in both digital and physical sales channels. Having that kind of flexibility – derived in physical stores from developing effective customer segments through tracking mobile device use and related behaviors – means significantly better outcomes in terms of encouraging the next purchase

Aviana has plenty of history developing successful projects in the retail world, partnering with retailers like Patagonia and Columbia Sportswear to take full advantage of big data and predictive analytics. Our experience in the industry means we understand the unique challenges faced by merchants and how to best apply predictive analytics to a variety of concerns and opportunities. Want to learn more about how Aviana can help your retail brand grow? Visit our dedicated industry page.

Posted in Predictive Analytics
John Martin

About John Martin

After several years of continued excellence in performance as a top producer at Aviana, John Martin is now the Vice President of Sales. As the founder of three prior startups, Mr. Martin has applied his entrepreneurial experience and background in marketing and technology to help organizations evaluate and implement enterprise software solutions for the last 20 years. Mr. Martin’s success can be credited in part to his dedication to putting the customer first and relentlessly striving to deliver excellence in all areas. Mr. Martin earned his bachelor’s degree in speech communications with a minor in computer programming from Point Loma Nazarene University. John lives in Carlsbad, California with his wife and two children.
Watson's processing power is impressive to say the least.

IBM's Watson supercomputer system has attracted plenty of attention since it made its first public appearances. Watson, famed for its ability to understand questions posed to it in natural, conversational language – as opposed to computer code or other highly regimented forms of communication – gained perhaps its biggest jump in popularity when it appeared on game show "Jeopardy!" in early 2011. That public exhibition served as a debut of sorts for the highly advanced system, with Watson winning both games against former champions on the show.

There's more to Watson than just answering questions on game shows, though – much more. Let's take a look at what makes Watson such a powerful business intelligence software solution in a variety of industries.

The driving forces behind Watson

"Watson draws on a combined 200 million pages of information through 90 servers."

IBM has a well-deserved reputation for developing technology on the cutting edge and deploying it in areas where it's highly visible. With past successes like Deep Blue's chess games against grandmaster Garry Kasparov in mind, the company developed Watson starting in the mid-2000s. After years of growth, the "Jeopardy!" appearances introduced Watson to much of the world. With that impressive debut in mind, work continued and Watson's ability to understand and respond to human language was developed in a variety of contexts.

Watson's central role as a question-answering machine was highlighted by TechTarget, which noted the many technological specifications of the system. Watson's 80-teraflop processing power means it can handle a trillion operations per second, which gives it the necessary speed to function quickly and accurately. It draws on a combined 200 million pages of information through 90 servers and uses about six million logic rules to provide accurate and contextual answers. This vast library of information allows Watson to mimic and even exceed the human capability for contextualized and correct recall in a variety of situations.

Now, Watson is used in applications ranging from assisting doctors in diagnosing patients to helping people and businesses prepare more effective tax returns. As IBM's own website pointed out, the ability of Watson to understand, reason, learn and interact means it has a variety of current and potential applications across the entire business world.

Want to learn more about Watson? If you're close to Chicago, you can attend a Watson overview led by Aviana's Watson expert, Lillian Taylor. Check out these Eventbrite and Meetup links for more information on the event, to be held in downtown Chicago on April 7, starting at 5:30 p.m.

Posted in Business Intelligence
Lillian Taylor

About Lillian Taylor

Helping clients leverage Big Data, Cognitive, and Advanced Predictive Analytics to reach their maximum potential in the most cost effective way possible. Passionate about leveraging technology for the greater good! "Without data, you're just another person with an opinion" - W. Edwards Deming - Data Scientist.
Predictive analytics provides a more complete picture for the financial services industry.

The financial services industry as a whole has to put a lot of effort into identifying trends, risks and opportunities, as well as acting on them. Without the ability to accurately engage in this future-facing behavior, it's far more difficult to offer relevant products to consumers and maintain business operations. Through powerful predictive analytics solutions, like the IBM Cognos suite of tools, businesses in this industry can develop a stronger forecasting process. In turn, that means presenting a knowledgeable and active vision of your company to clients, encouraging them to work with you.

"Reactive analytics only do so much to create a viable picture of the future."

Nonprofit banking and financial services organization Mobey Forum pointed to a common issue across the industry: Much of the analysis used by organizations tends to look at the past instead of the future. Reactive analysis certainly has a place in operations and can be a critical element for some important decisions, it only does so much to create a viable picture of the future.

Without the vital pieces of insight provided by predictive analytics, businesses miss out on the accurate descriptions of future scenarios that guide decision-making and help them present the best array of choices possible to clients. A truly complete analytics strategy involves reviewing past facts and figures as well as developing reasonable predictions of the future. Drawing on both elements means the most complete picture possible of risks, opportunities and trends.

Aviana offers businesses across the financial services industry the opportunity to improve their forecasting and intelligence-gathering efforts. Our deep familiarity with predictive analytics and the IBM solutions used to realize them means we bring expertise and a problem-solving attitude to each and every project. Our work in the financial services market specifically helps us start each project with a strong knowledge base and a deep understanding of the specifics of the industry. To learn more, visit our dedicated industry page.

Posted in Predictive Analytics
Mark Ishikawa

About Mark Ishikawa

Mark Ishikawa is a managing partner with Aviana managing all sales and marketing activities. Mark is a successful and seasoned sales and marketing executive with over 16 years of strategic solution selling, team building and executive positioning in the enterprise solution and consulting industry. Mark’s most recent position since joining Aviana was a Partner with Ineum Consulting where he was responsible for growing the business with aggressive revenue targets as well as customer acquisition of new business. He also worked to improve the firm’s people development and retention while being responsible for recruiting and development of all staff. Mark enjoys coaching youth sports, playing golf & traveling. Mark and his wife live in Orange County, California with their three boys.
retailers can improve customer engagement and operations through predictive analytics.

Predictive analytics isn't a concept limited to any one industry or market. However, the benefits it provides to the retail world are especially notable. Customer engagement and efficient, effective analysis of shopper data are both cornerstones of successful operations, and predictive analytics can offer benefits in both areas, along with many others. With business intelligence software a priority – along with the selection of an effective platform, like the IBM Cognos suite of products – retailers can improve everything from inventory management to the development and execution of sales and similar offers.

Data and analysis provide more context and value for retailers

"With predictive analytics in place, businesses can better understand customers."

Efforts to analyze information related to customer behavior and preference, along with operational data, are tried-and-true methods in the retail world. Predictive analytics takes these processes an important step further by using the power of automated analytics to draw conclusions that are difficult or extremely time-consuming for employees to discover without assistance.

The growing volume of data businesses have about their customers is valuable, but only when effectively harnessed. Without the proper tools, this data only has a limited ability to bring about positive change. With a reliable solution in place, businesses can better understand customer data. Companies can also engage in more accurate and useful forecasting, allowing parts of the organization to prepare for likely scenarios before they happen – one of the biggest advantages of predictive analytics.

Finding the right partner

Aviana has helped a variety of retailers implement predictive analytics across many different operational and marketing contexts, ensuring each of our clients has a system that provides the best possible results for their specific needs. To learn more about our work in the retail industry, visit our dedicated industry page and take a look at case studies of our work with major retailers like Patagonia.

Posted in Business Intelligence
Michele Harnish

About Michele Harnish

Michele Harnish has extensive experience in marketing and consulting to various industries. Her professional resume includes both corporate and field marketing executive roles. Her former role as Senior Director of Field Marketing at Cognos Corporation allowed her to leverage her strong corporate marketing background as she managed a large team of field marketing managers and business development managers and was solely responsible for lead generation across North America. In 2009, Michele joined Aviana Global and continues to leverage her unique approach to marketing which incorporates the branding and strategy of corporate marketing with the results driven lead generation power in field marketing. Michele enjoys spending time with her husband and four boys in Orange County, California.
Using predictive analytics and big data to improve patient outcomes is already a reality.

Medicine is both a universal concern and a big business across the world. The unique, ubiquitous nature of medical care – something everyone needs at points in their lives – means it can derive some major benefits from effective and novel applications of big data and predictive analytics. With business intelligence software like the IBM Cognos suite of products in play, healthcare providers can make a number of advances, from more effective risk factor profiling to collecting and utilizing individualized patient data. That second possibility is currently a hot topic in some areas of the medical world.

The concept of advanced personalized care

Widely sourced patient data could eventually provide the kind of preventative care that is only a theory in the present day. In an interview with The Huffington Post, Dr. Eric Schadt said he's working on a variety of approaches that would capture individualized information from patients through a number of mobile devices. That includes general purpose technology intended to measure various biometrics as well as more specialized tools focused on a specific bodily process or function. Schadt is the director for the Icahn Institute for Genomics and Multiscale Biology, part of New York City's Mount Sinai Hospital.

That data would then be used to better understand broad-based health trends as well as provide important information about potential conditions for individual patients. Personalized risk identification is just the first step, with individualized treatment an exciting possibility as well. With a wealth of broad and specific information at hand, healthcare providers could engage in more proactive care while also better tailoring treatment options to the unique needs of each patient.

"The biggest medical systems are going to own no hospitals," Schadt said to The Huffington Post. "It's going to be devices that are monitoring the lives of millions of patients simultaneously, that are looking to see if you have the beginning signs of cancer emerging – not to treat the cancer, but to prevent the cancer from ever emerging."

Healthcare outcomes could improve significantly with the effective application of predictive analytics and big data.
Healthcare outcomes could improve significantly with the effective application of predictive analytics and big data.

Health systems already using predictive analytics successfully

This wide-scale application of predictive analytics and big data is impressive in its scope and reach. However, it is in many ways building on ideas that have already been successfully implemented in the healthcare world.

The IBM Big Data & Analytics Hub reported on a variety of initiatives undertaken by health systems that rely on elements of these advanced computing functions to increase the health of their patient populations. HealthInfoNet, A Maine nonprofit that helps providers in the state coordinate their efforts uses the combined data of more than 1 million patient records to identify risk factors for emergency room visits. By sharing this data with healthcare facilities, doctors and other healthcare professionals are now able to notify patients who demonstrate risk factors before they arrive in the emergency room, instead of after.

Similar efforts by healthcare systems in the Carolinas and Iowa, focused on lifestyle risk factors and post-operation infection risk, respectively, demonstrate the power of big data and predictive analytics in the healthcare world. The growing number of potential applications, and their increase in scope, should be exciting for healthcare providers of all types.

Using new technology to its fullest in healthcare

Aviana's work in the healthcare field means we're not only knowledgeable about using big data and predictive analytics to their fullest extent, we also understand the unique nature of the industry. With this mix of technological and industry-specific experience, we offer a unique value proposition to all of our healthcare clients. To learn more, visit our dedicated industry page.

Posted in Business Intelligence
Francois Ross

About Francois Ross

François has been managing software sales and delivery of Business Analytics and Information Management solutions for more than 25 years. Prior to joining Aviana, his name has been predominant within the IBM Cognos analytics space. Leveraging a strong technical background, elite demonstration capabilities, and understanding of Big Data Analytics proven practices, he has brought thought leadership in the most active clients and organizations. His passion and mission statement: delivering the most impactful data to the best user experience through the art of possible.
Increasing efficiency is a major consideration when it comes to predictive analytics.

While all businesses have to contend with risk management to some degree, it's especially vital in the world of financial services. Anticipating and understanding potential hazards and setbacks, and then acting accordingly, are essential elements for building positive relationships with clients and furthering the mission of a financial services organization. Predictive analytics can offer businesses in this industry substantial enhancements to their current ability to assess and manage risk. Business intelligence software offers actionable analysis that allows staff to build strategies for internal processes and client-facing concerns, ultimately leading to more successful operations.

Gaining an edge through effective analysis
One interesting aspect of the power of predictive analytics, the ability to reduce unnecessary costs, was highlighted by the IBM Big Data & Analytics Hub. While many discussions about predictive analytics tend to center around making improvements that lead to increased returns, the process also offers plenty of avenues to make businesses more efficient.

"Predictive analytics offers plenty of avenues to make businesses more efficient."

On a basic level, predictive analytics makes the process of deriving meaning from information – perhaps more central to success in the financial services industry than any other element – a more focused, concentrated and fruitful effort. Instead of trusting this important process to basic, limited software and manual analysis by individual staff members, business intelligence software removes many of the potential issues with human error and missing relevance in the connections between different pieces of information.

In turn, the analytical process becomes more accurate and is less of a drain on resources. That improvement also pays off by reducing the costs associated with the many analytical processes required in the industry. Employees are then free to focus on areas where high-level considerations or a human touch are needed. Just as importantly, they can provide better service to clients, whether directly in roles that have customer contact or through the work they do to identify and act on opportunities and risks.

Aviana understands the many ways in which predictive analytics helps businesses in the financial services sector assess risk, make accurate predictions and provide customers with the best results possible. Improvements in everything from assessing the credit-worthiness of potential new customers to fraud detection and analysis are possible with predictive analytics and the right strategy. To learn more about our work with companies in the financial services industry, visit our dedicated industry page.

Posted in Predictive Analytics
Mark Ishikawa

About Mark Ishikawa

Mark Ishikawa is a managing partner with Aviana managing all sales and marketing activities. Mark is a successful and seasoned sales and marketing executive with over 16 years of strategic solution selling, team building and executive positioning in the enterprise solution and consulting industry. Mark’s most recent position since joining Aviana was a Partner with Ineum Consulting where he was responsible for growing the business with aggressive revenue targets as well as customer acquisition of new business. He also worked to improve the firm’s people development and retention while being responsible for recruiting and development of all staff. Mark enjoys coaching youth sports, playing golf & traveling. Mark and his wife live in Orange County, California with their three boys.
Improving risk awareness and assessment is a major consideration for the financial services industry.

Risks and opportunities are integral elements of operation for financial services companies. The ability to accurately predict, understand and analyze risk factors and potential opportunities gives companies in this industry an advantage over the competition and the base on which long-lasting client relationships can be built. Predictive analytics improves the overall ability of an organization to comb through many sources of data, identifying positive and negative trends and developing a plan of action to avoid or take advantage of them. Through business intelligence software, companies increase their insight into the market and a variety of other factors, from risk exposure to hedging strategy.

"Developing the best possible strategy and ensuring a high level of execution is critical for success."

The power and speed of automation
One of the central principles of predictive analytics is using advanced algorithms to seek out and present trends apparent in the many mounds of data that financial services companies regularly gather. Instead of relying on the work of individuals or entire departments to make these same determinations – and potentially introduce human errors to the process or miss connections – companies can rely on proven software like the IBM Cognos suite of products. With a software solution handling this intensive, time-consuming process, financial services companies can more efficiently allocate other resources and develop strategies that focus on further mitigation of risk.

An article in the Credit Union Times discussed the power of predictive analytics as an early warning system. CUT used the example of identifying risks related to employees misrepresenting investment opportunities to clients. With the right predictive analytics solution in place, businesses can develop more comprehensive insight into internal risks and take action to stop them before they turn into bigger problems. Predictive analytics can also help the financial services industry find concerns across markets and in other industries, revealing opportunities to avoid certain decisions and encourage clients to make others.

Developing the best possible strategy and ensuring a high level of execution in terms of predictive analytics is critical for success. Aviana understands how the industry can utilize predictive analytics in the most effective and efficient way through our experience helping a variety of financial services companies establish successful approaches and follow through on them. To learn more about our work in the realm of financial services, including past examples of our successful partnerships, check out our dedicated industry page.

Posted in Predictive Analytics
Miten Bhatt

About Miten Bhatt

Miten Bhatt is Client Director, Healthcare & Financial Systems at Aviana Global Technologies. Prior to coming to Aviana, he was a Sr. Project Manager at Niteo Partners (An NEC Company) where he was responsible for deploying financial consolidation applications and managing project deployments. He currently manages a delivery team delivering analytics projects for one of Aviana’s Fortune 500 healthcare industry clients. He has experience deploying financial applications and other enterprise systems across healthcare, financial services, manufacturing, distribution , retail and transportation industries across 3 continents. He is an avid badminton player and enjoys travel.
Predictive analytics create a variety of benefits for the hospitality industry.

Predictive analytics has quickly moved from being a new and exciting concept to something that's utilized in a variety of contexts across a large number of markets. The hospitality business is no exception, with hotels, casinos and many other facets of the industry using the solutions provided by business intelligence software to streamline workflows, develop actionable insights and generally improve operations. Let's consider one of the major advantages provided by predictive analytics, the ability to more accurately forecast demand for rooms and, in a related fashion, set room prices and reach out to potential guests.

Targeting and relevance in operations are boosted by predictive analytics
Forbes contributor Bernard Marr pointed to some notable actions taken by national hotel chain Red Roof Inn, moves that were empowered by predictive analytics. The company looked to improve its yield management efforts – optimizing room prices to ensure high levels of occupancy – through the insights delivered by analytics. In the winter season of 2013-2014, the U.S. experienced a winter more severe than usual, with associated issues in terms of travel delays and passengers stranded at and near airports. Red Roof Inn realized it could capitalize on its existing resources, namely a large number of locations near airports, by using predictive analytics along with real-time, publicly accessible data about weather and flight cancelations.

With that combination, the chain hit on a new and effective method for reaching out to travelers stranded at nearby airports, an especially interested group of potential guests. Red Roof Inn used a targeted digital marketing campaign to reach out to these customers, based on the idea that smartphones and web searches would be the most common tool for and method of finding accommodations. The hotel chain saw a 10-percent increase in room rentals in the areas where the strategy was used, Marr said.

Using predictive analytics to determine the best times and places to deploy effective marketing campaigns is an excellent application of the concept, but far from the only one. Aviana understands the many potential applications of analytics as well as the unique demands of the hospitality industry. Our work with a variety of leading companies in the field means we have practical experience and insight to apply to new projects, too. To learn more about our work with hotels, casinos and similar companies, visit our dedicated industry page.

Posted in Business Intelligence
John Martin

About John Martin

After several years of continued excellence in performance as a top producer at Aviana, John Martin is now the Vice President of Sales. As the founder of three prior startups, Mr. Martin has applied his entrepreneurial experience and background in marketing and technology to help organizations evaluate and implement enterprise software solutions for the last 20 years. Mr. Martin’s success can be credited in part to his dedication to putting the customer first and relentlessly striving to deliver excellence in all areas. Mr. Martin earned his bachelor’s degree in speech communications with a minor in computer programming from Point Loma Nazarene University. John lives in Carlsbad, California with his wife and two children.