This white paper discusses the findings of a study conducted by SAS and Health Data Management in an effort to shed light on the attitudes of senior actuarial executives toward the use of analytics. According to study findings, SAEs are not fully aware of tools that offer advanced functionality, such as forecasting, predictive modeling and optimization capacity. The study, which was conducted via in-depth interviews with health plan actuarial executives from across the country, uncovers opinions on the use of analytics in managing and leveraging data, forecasting, trend analysis, reserve management and related matters.

This white paper provides five steps to resource optimization, with a visual model and a variety of real-world examples to help business leaders understand how to allocate resources in alignment with enterprise-level objectives. You'll also learn about the technology required to support resource optimization.

In the insurance industry, the companies that focus on product lines typically under the diversified insurance umbrella (such as group and individual life, annuities, retirement plans, financial services and supplemental health products) have been slow to adopt predictive analytics within their organizations. Other industries, including property and casualty insurers, continually demonstrate success in using analytics to grow their businesses more profitably and increase revenue while managing risk. Life insurance executives are beginning to recognize the need to evaluate analytics as a way to innovate, differentiate and improve their organizations. This paper discusses business strategies enabled by analytics and provides examples of analytic innovation that insurers can introduce into their business processes.

More than ever, insurance companies need to optimize their business processes. But what does this mean in practice? At SAS, we believe that the "optimized insurer" or "analytical insurer" is one that can integrate analytics into its daily business processes to gain competitive advantage by reducing operational expenses, increasing premium revenue and ensuring regulatory compliance. This white paper will discuss how Property & Casualty (P&C) insurers are embracing analytics throughout their organizations to increase their operational efficiency, while minimizing losses and maximizing profits.

Natural resources agencies in the Americas must understand how to enhance the effectiveness of programs and policies while maintaining an adequate level of funding. This white paper describes how analytics can provide optimized solutions to these challenges. The paper first describes the use of analytics in resource management, education and CRM, operations and performance management. Ultimately, you will learn about SAS' analytic capabilities for natural resource agencies.

This research brief from IIA (International Institute for Analytics) discusses how to bring value to your organization. Written from the viewpoint of a CIO, learn how and why business intelligence and analytical tools are a CIOs best friend, how implementing a decision-support approach can truly transform your business, and one of the most important questions you can ask executive team members and their staff when implementing new IT systems. 

Analytic expertise is in short supply in most organizations. Quantitative specialists carry a heavy workload and need to focus on the most critical business issues. As a result, other decisions that may be important or influential to the organization—but not deemed critical—are made based on suboptimal information. But what if the power and sophistication of analytics could be made simpler, faster, and more intuitive and repeatable than ever? What would that do for the quality and timeliness of your organization's decision making? That was the topic of a SAS webinar in the Applying Business Analytics series. This paper provides a summary of that webinar and describes new capabilities for visual data exploration, visual programming of structured and unstructured data, and wizard-driven shortcuts for rapid model development.

This white paper describes ways the healthcare industry can use the data at its disposal to evolve toward more personalized medicine. In particular, you will learn about the promising possibilities of electronic medical records and powerful analytic solutions for healthcare providers from SAS. The paper also includes some real-life situations in which SAS analytics are being used to improve patient care and research.

Pharmaceutical sales and marketing professionals face a unique set of challenges in their efforts to boost sales enough to recoup staggering development costs. This white paper explores the possibilities of data integration and advanced analytics in marketing and selling pharmaceuticals. The paper also includes a list of key analytical techniques and several industry case studies.

This paper describes five business analytics styles used today and the building blocks required in implementing these styles. Building a business analytics architecture to create a competitive advantage requires multiple styles as the needs of the organization change. Organizations are seeing new opportunities to incorporate business analytics into operational systems and processes.

Most pharmaceutical companies focus their sales and marketing activities on the top-decile prescribing physicians for a given therapeutic area, based on purchased data. But such practices are no longer yielding desired results. This white paper discusses why now is the right time to make sales and marketing decisions based on deeper analytic insights - using predictive modeling - and how organizations that take control over their own physician targeting will get more timely insights, targeting decisions aligned with business issues and real competitive advantage.

The use of predictive analytics has enabled organizations to more accurately predict outcomes and increase profitability. As the number of models grows, it is imperative that organizations implement sound model management practices. This white paper provides an overview of the model management lifecycle process and gives an introduction to SAS Model Manager. Ultimately, the paper recommends best practices for the management of predictive models in a production environment.

While many areas of government have successfully employed aspects of fact-based decision making, current initiatives to reduce waste and expenses correspond with what business analytics offers organizations. This white paper produced by BusinessWeek looks at how government agencies are struggling to embrace the spirit of initiatives like the President's Management Agenda and how business analytics can give them an anchor on which to operate as they search for operational agility based on deeper insights, better answers and faster reaction times geared toward the future. 

This report examines the rise of big data and the use of analytics to mine that data, especially focusing on the application of analytical platforms in organizations from both a business and technical perspective. Learn how advances in analytical technology and new architecture are changing the way that organizations stage, store and process large volumes of structured and unstructured data.

This white paper discusses some of the key infrastructure challenges that IT faces in meeting the ever-increasing demands for intelligence across their organizations. It provides an overview of how the platform for SAS Business Analytics can help overcome those challenges. It also describes SAS strengths within each of the platform components -- data integration, analytics, and reporting. Most importantly, it outlines how SAS is here to help organizations achieve success through analytic solutions built upon an integrated framework. 

This paper, based on research by nGenera Corporation, provides answers to six key questions that executives should be asking about how to use business analytics to improve performance and compete successfully -- from "Where should we leverage business analytics?" and "What's the payoff?" to "What kinds of people do we need?" and more.

More sophisticated state government revenue departments are accurately identifying and prioritizing tax returns that have a high likelihood of under-reporting and a high magnitude of potential collection by augmenting their rules-based tax auditing systems with scores generated by analytical modeling – improving audit success by as much as 20 to 50 percent. This paper describes the benefits of advanced, non-linear modeling over traditional rules-based approaches, for more precision and better rank ordering, fewer false positives, higher revenues and faster ROI.

Ce libre blanc explore comment SAS® Analytics aide les assureurs à exploiter leurs données de manière proactive, en renforçant leur comprenhension des mécanismes du fonctionnement de leur entité, au niveau  des sinistres, de la valeur client, de l’adéquation de l’offre produit au canal de distribution, ainsi qu’au niveau des risques et de la mise en conformité réglementaire.

One of the most powerful ways to use data mining and predictive analytics is to apply analytic models and results on a production scale. These models can be applied to help make critical business decisions, or improve decisions. This research brief from IIA (International Institute for Analytics) discusses the technology and organizational challenges businesses must address in order to succeed in using analytics this way, specifically, organizational and attitudinal differences, compliance, time to deploy and data consistency differences. 

To improve student achievement, educators and administrators are effectively using valuable data -- through data warehousing and business analytics -- to integrate and analyze data sources in a flexible, easy-to-manage reporting environment. This white paper describes the benefits of using data-driven decision making, as well as information and case studies on SAS onsite and hosted solutions for education.

Data mining is past the hype stage and has proven that it can produce significant bottom-line results. This paper discusses the many measurable benefits that data mining delivers, including solving complex needle in the haystack problems, eliminating the bad (such as fraud), pinpointing the good (opportunities), streamlining decision processes, and used on qualitative data. Learn how organizations are using data mining to solve their problems, including a $1 billion decision that produced positive results. 

Globally manufacturers spend more than $70 billion to cover warranty expenses each year, but that is only the beginning of the true costs associated with poor product quality and suspect warranty claims. Increased government scrutiny, tarnished brand image, reduced stock prices, dissatisfied customers and lost sales can quickly dwarf the direct monetary losses. To reduce claim costs and increase customer satisfaction, forward-thinking manufacturers are applying automated analytics across the warranty chain. Detecting and preventing fraud, finding emerging quality problems sooner and accelerating the problem-solving process can reduce warranty costs by more than 20 percent while keeping customers happy. This paper shows how some companies are applying analytics at multiple points across the warranty timeline and the results they have achieved in both issue and fraud detection.

This white paper reviews a portion of a research program conducted by BusinessWeek Research Services designed to understand how companies can optimize business analytics to improve fact-based decision making and to determine the attitudes and opinions of C-level executives with regard to the use and value of business analytics. It is part of a series of white papers for C-level executives intended to facilitate sharing the most important insights from the research. 

Many forward-looking executives are turning to predictive maintenance (PM) solutions to help prevent equipment failures and avoid the costs of unplanned downtime. This paper explores the business case for investing in predictive maintenance solutions, examines how they work to lower maintenance costs and minimize disruptions across the enterprise, and describes what is required to get started with PM today.

Amid the current climate of greater demand for both environmental awareness and corporate accountability, organizations are finding that success is increasingly being measured not only by financial performance, but also by ecological and social accomplishments as well. In addition, the current economic climate has reinforced the need to plan for long-term success. This white paper, based on a launched research program conducted by BusinessWeek Research Services, looks at how the most forward-thinking enterprises are using analytics to their advantage by applying it to sustainability.

The new compositions of source power, meter infrastructure and grid design, and regulatory requirements place increased pressure on utilities' planning and execution capabilities. With the proper application of business analytics, a set of technology solutions that optimizes the energy portfolio, utilities can convert their challenges into opportunities. For best results, utilities should consider four key areas of business analytics: • Advanced forecasting. • Data management. • Optimization. • Energy commodity risk aggregation and analysis.

Etude mondiale sur le déploiement et la perception de la Business Analytics dans les entreprises. Selon un récent sondage réalisé par Bloomberg Businessweek, 97% des entreprises avec des revenus de plus de 100 millions de dollars utilisent une ou plusieurs solutions de Business Analytics, ce chiffre était de 90% il y a deux ans. Téléchargez l'étude complète : « The Current State of Business Analytics : Where do we Go from here »

To truly exploit analytics enterprisewide for a competitive edge, an organization must have a centralized group that provides core expertise, supports users, enforces standards and drives performance. The author dubs this group an "analytical center of excellence" (ACE). After laying out his recommended ACE infrastructure, the author prepares you to engage your organization in establishing an ACE. He describes three primary phases of infrastructure, the different levels of enterprise analytical maturity that determine ACE requirements, and the analytical maturity assessment that must occur in order to develop an implementation plan.

Current trends justify utilities gaining every cash flow improvement option available, including setting a framework for the use of smart meter data to improve collections. By identifying and predicting the conditions when a customer may have trouble paying their bills and then developing plans for helping those customers using the tremendous data already present, utilities can create advanced, customized bill payment plans. This white paper describes how utilities can use predictive analytics to optimize their bad debt collections, with inherent business value that is quantifiable and often significant.

This paper reviews a portion of the research done by BusinessWeek Research Services to determine the attitudes and opinions of C-level executives with regard to the use and value of business analytics and provides analysis and insights on the topic of business analytics.

This white paper discusses the drivers and the challenges in implementing a longitudinal data system. It then explores how, with SAS' Business Analytics Framework, information gaps among key educational agencies need no longer exist, and decision makers can be armed with the accurate data they need to make proactive decisions and effective education policies.

For organizations to make the most of their data assets and create value, they need to consider how analytic talent is deployed and equipped to drive continuous improvements. As a result, many organizations have begun enterprise initiatives that focus on applying analytics to set future directions, survive in troubled economic times and identify opportunities that set them apart from competitors. But these initiatives need more than just technology. An enterprise strategy is required to coordinate and align key players. Analytic centers of excellence (CoEs) can do just that. This paper provides a comprehensive overview of the need, structure and benefits of establishing and analytic center of excellence. It discusses best practices and explores the various organizational aspects that should be considered to help effectively deploy analytics across your organization.

Online retailer Gilt Groupe understands its customers and what they want, which in turn enables them to better segment customers and drive them to the sales most relevant to them. This paper provides a summary of a webcast in the SAS "Applying Business Analytics Webcast Series" that explored how Gilt Groupe uses analytics to create a signature shopping experience with distinctive appeal for each of its millions of members, even though members have different tastes, needs and values.

This white paper by Stephen E. Arnold explores the value of text mining as a way to process unstructured information and identify themes without reading an entire collection of text. In particular, Arnold focuses on the value of SAS Text Miner for integrating text-based information with structured data and enhancing organizations' predictive modeling capabilities.

In our fast-paced world, consumer opinion can make or break your company's products or services virtually overnight. To understand consumer sentiment and respond quickly to opinions, you must continually monitor and evaluate relevant Web content. Most companies rely on automated techniques to help them quickly characterize the sentiment of documents in a variety of domains. This white paper compares two different approaches to sentiment analysis and illustrates why combining domain-specific linguistic rules with data mining methods improves both the effectiveness of models and the efficiency of model builders.

Even for a brand that is marginally recognized, the volume of comments coming from social media and other online sources can reach up to a terabyte a day. Add to that tens of thousands of call center records, guest surveys, emails and other internal data, and you have a rich view into customer opinion. How can hotels and casinos manage, analyze and use this fast-moving flood of unstructured text to make better business decisions?

That was the subject of a webcast co-sponsored by SAS and Casino Journal. This paper summarizes the discussion about how natural language processing and text analytics work to help you classify and understand what is in those text records and what is being said about you and your competitors on the Internet.

Recent developments in semantic technologies add a new level of intelligence and meaning to enterprise content management and promise to improve information access across any organization. This paper describes how a semantic infrastructure is a platform for building a broad variety of applications and enabling them to communicate with each other – at a higher level than simply exchanging data. To get the full value from semantic technologies, organizations cannot take the typical "project" mindset toward development and implementation. Instead, they must devise a strategic vision of how automating and associating text data fits within – and ultimately transforms – their organization.

Radio frequency identification (RFID) is spreading quickly through the global network of supply chains. The technology promises improved efficiency and more accurate tracking--along with untold amounts of data. Read this white paper to get a brief introduction to RFID and learn about a variety of SAS technologies that can help you harness the value of your RFID-related data. Such technologies include data quality, business intelligence, predictive analytics and even retail-specific applications.

This paper illlustrates how Credit Scoring for SAS Enterprise Miner software is used to build credit scoring models for the retail credit industry. It discusses the benefits of performing credit scoring and the advantages of building credit scoring models in-house using SAS Enterprise Miner. It goes on to discuss the advantages and disadvantages of three important model types: the scorecard, the decision tree and the neural network. Finally, it presents a case study where an application scoring model is built with SAS Enterprise Miner, beginning with reading the development sample, through classing and selecting characteristics, fitting a regression model, calculating score points, assessing scorecard quality (in comparison to a decision tree model built on the same sample) and going through a reject inference process to arrive at a model for scoring the new customer applicant population.

Read this white paper to learn how SAS helps governments reduce the taxpayer burden for fraud, error and abuse, ultimately allowing governments to better fund efforts for improving the lives of citizens. This paper focuses on three key areas: improper payments, purchase card fraud and Medicare/Medicaid fraud. The paper discusses how governments can develop anti-fraud strategies to improve collection rates and reduce improper payments, fraud, waste and abuse.

The ability to make effective, fact-based decisions is not based on data quantity. In fact, most organizations are awash in data. Rather, success is based on an organization's ability to discover more meaningful and predictive insights from the data it already has. This paper provides a summary of a SAS webinar in the Applying Business Analytics series that showed how predictive analytics and data mining can reveal new insights out of existing data to improve business performance.

As in other sectors of the economy, the insurance industry has experienced many changes in information technology. Advances in hardware, software, and networks have offered benefits, such as reduced costs and time of data processing as well as increased potential for profit. Competition has also increased, making effective IT solutions even more necessary.

This paper discusses how insurance companies can benefit from modern data mining methodologies, which help companies reduce costs, increase profits, retain current customers, acquire new customers, and develop new products. You will learn about how to implement data mining projects and about changes in U.S. legislation that affect insurance firms. A list of recommended reading is also included.

Data mining is past the hype stage and has proven that it can produce significant bottom-line results. This paper discusses the many measurable benefits that data mining delivers, including solving complex needle in the haystack problems, eliminating the bad (such as fraud), pinpointing the good (opportunities), streamlining decision processes, and used on qualitative data. Learn how organizations are using data mining to solve their problems, including a $1 billion decision that produced positive results. 

Even for a brand that is marginally recognized, the volume of comments coming from social media and other online sources can reach up to a terabyte a day. Add to that tens of thousands of call center records, guest surveys, emails and other internal data, and you have a rich view into customer opinion. How can hotels and casinos manage, analyze and use this fast-moving flood of unstructured text to make better business decisions?

That was the subject of a webcast co-sponsored by SAS and Casino Journal. This paper summarizes the discussion about how natural language processing and text analytics work to help you classify and understand what is in those text records and what is being said about you and your competitors on the Internet.

This white paper illustrates a new patent-pending approach that may be helpful in certain new product forecasting situations.  It combines human judgment with time series mining and statistical modeling.  This "structured analogy" approach helps automate the selection of analogous products ("like items"), facilitates review and clustering of past new product introductions, and generate statistical forecasts.  Users can make manual overrides to the statistical forecasts, and get a better sense of the risks and uncertainties in new product forecasts through visualization of past new product introductions.

What-if scenarios that predict what might happen given different business conditions and decisions are most enlightening when we understand the relationships between the variables that influence potential results. Data visualization expert Stephen Few describes the characteristics of good visual analytics and describes how to use the JMP Prediction Profiler to build predictive business models and interact with data and graphs to observe how changes in one variable influence changes in the others.

This Industry Week report explains how an enterprise analytical quality platform (EAQP) works and how using an EAQP can accelerate time-to-market for new products; reduce the negative effects of existing problems by resolving them faster; and enable long-term sustainment of quality improvements. This report also ties these benefits to the results of the IW/SAS Enterprise Quality Survey, which reveal a need for such a platform in all sectors and sizes of manufacturing enterprises.

Manufacturing and supply chain organizations must not only optimize resources and minimize waste, but also predict future growth and demand. Event-handling and transactional systems cannot merge data into an integrated source of business intelligence; organizations need adequate data management, forecasting, optimization and modeling techniques to bring disparate data together and gather useful intelligence from it. With key performance indicators and process metrics that span functional areas, managers and other stakeholders can see changes and trends as they occur and make business decisions based on those indicators.

This paper presents a methodology for conducting a forecasting strategic value assessment for your organization.

In today's unstable economy, many organizations are finding out that they have inadequate processes to handle demand planning, and traditional methods of predicting demand aren't efficient in a fluctuating market. The paper makes specific recommendations for organizations striving to move up the demand forecasting maturity curve by providing them an assessment framework to evaluate their current stage, and highlighting the characteristics common to best-class companies.

The new compositions of source power, meter infrastructure and grid design, and regulatory requirements place increased pressure on utilities' planning and execution capabilities. With the proper application of business analytics, a set of technology solutions that optimizes the energy portfolio, utilities can convert their challenges into opportunities. For best results, utilities should consider four key areas of business analytics: • Advanced forecasting. • Data management. • Optimization. • Energy commodity risk aggregation and analysis.

How effectively an organization manages its supply chain depends on many factors. An organization can have excellent business processes, yet lack the ability to successfully align supply with demand. Read this white paper to learn how advanced forecasting technology and business intelligence can enhance Sales and Operations Planning while supporting better communications and collaboration throughout an enterprise.

Organizations spend much time and money searching for a magic formula for the perfect forecast, yet still get bad forecasts. But it doesn't have to be this way. This paper provides a summary of a webinar in the SAS “Applying Business Analytics” series originally broadcast in July 2010 that discussed how businesses can achieve better accuracy and forecasting process efficiency by understanding the nature of demand patterns and where forecasting process is adding value — or not.

Retailers are commonly faced with the challenge of forecasting demand for items that are sold only at certain times of the year, but in high volumes. This paper suggests a compression approach for dealing with these kinds of highly seasonal forecasts using SAS software, which could produce more accurate results than forecasts based on standard time series modeling. It provides an illustrative example based on real-life data. 

This case study describes how SAS helped the Ontario Ministry of Health and Long-Term Care achieve a solution to predict hip and knee replacement demand – enabling the Ministry to solve what had become a crisis in long wait-times for the surgery. Based on powerful SAS® Forecast Server, this solution now provides the forecasts that guide Ontario’s ongoing investment in orthopedic staff, facilities and services.

Ensure that your organization is getting the best possible forecasts, as efficiently as possible. Through this paper you will discover how the forecast value added (FVA) metric can be used to identify waste in forecasting processes and expose factors that diminish accuracy. The author provides detailed instruction on using FVA: from gathering data, to conducting analysis, to effectively reporting the results to management. He also discusses the real-world results of FVA analysis at companies from a variety of industries. 

In an October 2010 webcast, Cornell and SAS experts presented their latest findings on four critical issues that could spell the difference between an organization thriving or simply surviving. The topics include pragmatic advice for optimizing customer reward programs; survey findings about engaging with customers online; some common myths about forecasting, and creative new approaches in the hospitality field.

This white paper discusses fundamental issues that impact an organization's ability to forecast accurately. These issues include the operational definition of "demand," what to forecast, how to measure performance, organizational practices and demand volatility. Without addressing these issues, the investment may yield no return.

This white paper examines new challenges affecting utilities forecasters, as well as the opportunities for harnessing Smart Grid data to maximize the value of forecasting and is based on insights shared in a SAS On-Demand Webcast: Smart Solutions for the Smart Grid: Enhancing Your Forecasting Methodology for the 21st Century. 

This white paper discusses multi-causal analysis as a way of integrating consumer demand information with shipment forecasts to capture the impact of marketing activities on shipments. With improvements in technology, data collection, data storage and analytical knowledge, CPG companies are now looking to integrate consumer demand with their shipment forecasts to capture the impact of marketing activities on shipments. As a result, multi-tiered causal analysis (MTCA) is receiving renewed interest. This paper explains the MTCA process, including an anonymous beverage industry case study that describes the process used to develop and link the Consumer Demand and Factory Shipment models. The by-product of this process was a more accurate forecast that reflected the company's marketing investment strategy.

Web sites and transactional databases collect large quantities of time-stamped data. Businesses often want to make future predictions based on numerous sets of time-stamped data (sets of transactions). The number of time series to forecast, however, may be enormous or the forecasts may need to be updated frequently, making human interaction impractical. This detailed white paper proposes a technique for automating large-scale forecasting using SAS Forecast Server. You will learn about time series data, forecast modeling and statistics of fit. The paper also provides a step-by-step explanation of the automated forecasting technique and a brief discussion of implementation.

This paper details challenges that affect how communications are planned and deployed, including limiting factors such as budget caps, campaign volumes and channel capacities. Communications often can't be anticipated until a trigger-based or real-time interaction uncovers a need and the opportunity for an additional communication. Successful processes utilize the latest analytical techniques and consider a company's corporate objectives and business rules. This paper discusses a process called adaptive contact planning as a way to create more effective, and thus more profitable, marketing campaigns.

This white paper provides five steps to resource optimization, with a visual model and a variety of real-world examples to help business leaders understand how to allocate resources in alignment with enterprise-level objectives. You'll also learn about the technology required to support resource optimization.

This extensive white paper describes the nature and purpose of optimization today, and considers the various types of optimization problems that can be solved with SAS/OR software. It also touches briefly on SAS optimization solutions, including the SAS Revenue Optimization Suite and SAS Service Parts Optimization. The paper includes introductory sections on how optimization models are built and solved, and the role of data and analytics in solving optimization problems. It then delves into the details of using SAS/OR software, including sections on the OPTMODEL language and procedures and sections on genetic algorithms and constraint programming. This paper was written specifically for operations research professionals who are interested in finding out how SAS can solve their challenges and what advantages SAS/OR software offers.

Based on feedback from SMB organizations from around the globe, this report from Aberdeen Group examines the processes, methodologies and technologies that enable companies to leverage Business Intelligence for fact-based insight into decision making. Learn what criteria distinguished certain companies as top performers within the SMB sector, the factors to consider when assessing your organization's BI competency and the required actions to achieve best-in-class performance.

Business intelligence and data analytics are pushing into health care. But how can you make the most of these technologies? This e-book explores how clinical data analytics can unlock the potential for quality improvement. It also explores the increased use of business intelligence by health care providers and explains why standards are needed to go to the next level.

In spite of the promise of business analytics – and new technologies that make analytic power more accessible than ever – few organizations have taken full advantage. They have questions about where to focus their efforts, how to address data management issues, and what types of analytic techniques to use where. That was the topic of a SAS-sponsored webinar in the "Applying Business Analytics" series, in which participants offered practical advice about how to make analytics pervasive in the organization, predictive for maximum value, and proactive to drive meaningful action. This paper provides a summary of that webinar.

This white paper discusses some of the key infrastructure challenges that IT faces in meeting the ever-increasing demands for intelligence across their organizations. It provides an overview of how the platform for SAS Business Analytics can help overcome those challenges. It also describes SAS strengths within each of the platform components -- data integration, analytics, and reporting. Most importantly, it outlines how SAS is here to help organizations achieve success through analytic solutions built upon an integrated framework. 

In an effort to provide better, cost-effective care, health care providers are increasingly turning to IT-enabled business strategies. This white paper by Health Industry Insights, an IDC company, and sponsored by SAS presents the findings and analysis of in-depth interviews conducted with nine senior executives and system architects at three prestigious teaching hospitals acknowledged to be industry leaders in their use of health information technology, in general, and BI applications, in particular.

In March 2007, SAS conducted a survey of 175 business intelligence professionals from around the globe to assess current trends in the use of business information -- specifically business intelligence and competency centers -- and their effect on organizational performance. This report outlines the results of that survey and its implications for information management in your organization.

The implementation of a business intelligence (BI) environment is not simple, but it does yield tremendous benefits for companies that want to receive the most value from their data resources. Read this paper by BI visionary Dr. Claudia Imhoff to understand the fundamental questions anyone must ask to ensure a successful BI implementation.

You will learn to identify what you have, build a business case for the BI environment, establish the technical infrastructure to support it, maintain data quality and, ultimately, to expand the capabilities of BI through predictive and embedded analytics.

Healthcare leaders are challenged to improve care delivery, reduce costs and enhance physician and employee engagement. Doing so requires the ability to access data from a variety of siloed and disparate systems, and then to get that data into the hands of those closest to the issues. Applying business intelligence in a healthcare setting is a powerful way to break down political barriers, overcome resistance to change, align strategic priorities and improve communication. This white paper explores the ways that business intelligence and performance management software systems can facilitate evidence-based healthcare delivery in hospitals. The paper provides background on implementing business intelligence and then offers case studies demonstrating successful BI at several prominent hospitals.

To improve student achievement, educators and administrators are effectively using valuable data -- through data warehousing and business analytics -- to integrate and analyze data sources in a flexible, easy-to-manage reporting environment. This white paper describes the benefits of using data-driven decision making, as well as information and case studies on SAS onsite and hosted solutions for education.

This white paper reviews a portion of a research program conducted by BusinessWeek Research Services designed to understand how companies can optimize business analytics to improve fact-based decision making and to determine the attitudes and opinions of C-level executives with regard to the use and value of business analytics. It is part of a series of white papers for C-level executives intended to facilitate sharing the most important insights from the research. 

How effectively an organization manages its supply chain depends on many factors. An organization can have excellent business processes, yet lack the ability to successfully align supply with demand. Read this white paper to learn how advanced forecasting technology and business intelligence can enhance Sales and Operations Planning while supporting better communications and collaboration throughout an enterprise.

Smart corporations today are creating one source of consistent, reliable and high-quality data for strategic analyses and tactical decision making. This paper, written by BI expert Claudia Imhoff, outlines some of the key considerations for companies working toward enterprise business intelligence, including data quality, maintaining a program approach to BI and establishing centers of competency for managing a BI program. The paper also provides some advice for getting started with an enterprise BI program.

Etude mondiale sur le déploiement et la perception de la Business Analytics dans les entreprises. Selon un récent sondage réalisé par Bloomberg Businessweek, 97% des entreprises avec des revenus de plus de 100 millions de dollars utilisent une ou plusieurs solutions de Business Analytics, ce chiffre était de 90% il y a deux ans. Téléchargez l'étude complète : « The Current State of Business Analytics : Where do we Go from here »

To truly exploit analytics enterprisewide for a competitive edge, an organization must have a centralized group that provides core expertise, supports users, enforces standards and drives performance. The author dubs this group an "analytical center of excellence" (ACE). After laying out his recommended ACE infrastructure, the author prepares you to engage your organization in establishing an ACE. He describes three primary phases of infrastructure, the different levels of enterprise analytical maturity that determine ACE requirements, and the analytical maturity assessment that must occur in order to develop an implementation plan.

OLAP has become a standard requirement for almost any BI-related project because it enables users to navigate quickly through complex business data. This white paper provides an overview of several integrated SAS products that can be used for OLAP. You will learn how these products, all part of SAS Enterprise BI Server, allow different types of users to perform analysis of varying sophistication, from simple reporting and exploration to advanced visualization and publishing of results.

Enterprises are experiencing information overload. Dozens of systems generate reports, slice and dice data and collect it from every possible data point within the enterprise. With all this data, enterprises are beginning to see how effective delivery and sharing of information improves the process of making informed business decisions.

This white paper provides a detailed overview of the SAS Information Delivery Portal, a powerful vehicle for delivering enterprise information to the right people at the right time. The paper describes the state of enterprise information and provides a roadmap and business scenario for implementing the SAS Information Delivery Portal. You will learn about the flexibility of the portal and about its architecture, functionality and administration.

For many business users, the search for useful, valuable information is time-consuming and inefficient. Business visualization can transform how you see, discover and share insights hidden in your data. This paper offers highlights from a September 2010 webinar that showed new ways business users can bring movement, graphics and data together to explore data and share insights, right from the desktop.

For many years, the first instinct of most clinical programmers has always been to write SAS® code by hand, because that was the best approach available. The next innovations from SAS were tools like SAS Enterprise Guide and SAS Clinical Data Integration, with their graphical user interfaces that made programming a great deal easier, faster and more efficient. This white paper discusses how experienced programmers can learn novel tricks and techniques with new tools, solutions and technology.

Data integration involves combining data residing in different sources to provide a unified view or to make it analysis-ready. It improves the flow of accurate, enterprisewide information, enhances data quality and enables collaboration across the organization. This paper looks at the best practices involved in a maturing data management practice, as outlined in a SAS-sponsored webinar in the Applying Business Analytics series.

Data management and data quality are no longer optional components of an insurance company's analytical environment – they are essential. And an insurance data model is fundamental to these initiatives. This white paper discusses the benefits of building an analytical data warehouse based on an insurance-specific data model that will enable insurance companies to get the most out of their investment in business analytics.

The women's specialty retailer, Chico's FAS Inc., needed to gain a more holistic view of its middle- to high-income clientele, but the company was operating with a fixed data model that didn't adapt well to a changing environment. Data was sent out for modeling, so the results were often stale by the time campaigns were developed. This paper summarizes an event in the "Applying Business Analytics Webinar Series," in which the company's director of CRM and enterprise information management describes how Chico's has benefited from a software-as-a-service (SaaS) solution for customer and campaign management. With its SaaS solution, Chico's can create timely, personalized offers, and has dramatically reduced the time needed to produce campaigns.

Opinion des décideurs informatiques et opérationnels sur la gestion du risque (Solvabilité II) et les contraintes en matière d'alignement de l'informatique. Enjeu clé des sociétés d'assurances dans les mois à venir, la mise en conformité avec la directive Solvabilité II concerne en premier lieu les directions financières mais aussi les responsables informatiques. Alors qu'il ne reste que quelques mois aux entreprises, 45 % des responsables interrogés dans cette étude déclarent être encore en cours de décision sur le sujet.

This report examines the rise of big data and the use of analytics to mine that data, especially focusing on the application of analytical platforms in organizations from both a business and technical perspective. Learn how advances in analytical technology and new architecture are changing the way that organizations stage, store and process large volumes of structured and unstructured data.

New business intelligence (BI) innovations in front-end and back-end technologies are raising the question - What are the capabilities of next-generation BI tools? This BeyeNetwork report profiles the capabilities of next-generation BI tools with emphasis on new visual analysis tools and in-memory processing. It examines the types of BI users and capabilities they need, including casual users, power users and IT administrators. It also examines BI architectures — how front-end tools interact with back-end servers and databases — to deliver those capabilities.

SAS, Teradata and Platform Computing collaborated with ComputerWorld to produce this tech dossier/white paper on using high-performance computing and business analytics to transform data assets into meaningful insights, gain faster time to results and maximize the productivity of resources to drive sustainable growth. The Tech Dossier will help prospects and customers learn how grid computing and in-database technology can be combined with SAS Business Analytics to drive proactive, evidence-based business decisions.

SAS, Teradata and Platform Computing collaborated with ComputerWorld to produce this tech dossier/white paper on using high-performance computing and business analytics to transform data assets into meaningful insights, gain faster time to results and maximize the productivity of resources to drive sustainable growth. The Tech Dossier will help prospects and customers learn how grid computing and in-database technology can be combined with SAS Business Analytics to drive proactive, evidence-based business decisions.

New business intelligence (BI) innovations in front-end and back-end technologies are raising the question - What are the capabilities of next-generation BI tools? This BeyeNetwork report profiles the capabilities of next-generation BI tools with emphasis on new visual analysis tools and in-memory processing. It examines the types of BI users and capabilities they need, including casual users, power users and IT administrators. It also examines BI architectures — how front-end tools interact with back-end servers and databases — to deliver those capabilities.

Health and human service agencies can comprise up to 40 percent of state budgets. Yet, in spite of this large investment and the best intentions of these agencies, individuals and families regularly fall through the cracks. This white paper explores ways to use data integration to fill the gaps in service delivery.

This white paper discusses some of the key infrastructure challenges that IT faces in meeting the ever-increasing demands for intelligence across their organizations. It provides an overview of how the platform for SAS Business Analytics can help overcome those challenges. It also describes SAS strengths within each of the platform components -- data integration, analytics, and reporting. Most importantly, it outlines how SAS is here to help organizations achieve success through analytic solutions built upon an integrated framework. 

Recounting the CTO Telecom Summit's peer-to-peer roundtable facilitated by SAS CIO Suzanne Gordon, this paper shares the challenges and best practices in effective customer data management from the CIOs and CTOs of leading service providers. Participants addressed cultural issues, including building collaboration and information sharing, obtaining clear business objectives and bridging the business-IT divide. They also discussed technology issues, such as ensuring data quality and integration to provide a holistic customer view to business leaders.

Collaborative data integration supports governance and stewardship, and it fosters reuse and remote management for distributed development teams. Read this white paper by TDWI's Philip Russom to learn about organizational issues, best practices and software tools for collaborative data integration.

This paper summarizes a webcast that describes how Courtyard by Marriott redesigned the lobbies of their properties to be more stylish and functional. Analytics played a role during all phases of design by providing insight from focus groups, surveys and concept testing.

To improve student achievement, educators and administrators are effectively using valuable data -- through data warehousing and business analytics -- to integrate and analyze data sources in a flexible, easy-to-manage reporting environment. This white paper describes the benefits of using data-driven decision making, as well as information and case studies on SAS onsite and hosted solutions for education.

Most organizations have spent the last decade acquiring data integration tools from different sources to manage, govern and utilize data. This generally means they now possess a nonintegrated toolbox of technologies. Organizations need a solution that enables employees to focus on better managing data instead of integrating disparate technologies. A comprehensive data management platform would address all aspects of data integration, data quality and master data management, be underpinned by adapters and a federation capability, and share technical and business metadata. Ultimately, a single user interface should surface all of the data management capabilities. This white paper describes the evolution of data integration tools and the benefits that can be achieved with a comprehensive data management platform.

The challenge of integrating enterprise data is not getting any easier, according to this research report published by TDWI. This paper analyzes the results of a survey designed to provide insight into the development of data integration technologies and techniques. The paper also explores requirements for developing an enterprise data integration strategy.

Data integration involves combining data residing in different sources to provide a unified view or to make it analysis-ready. It improves the flow of accurate, enterprisewide information, enhances data quality and enables collaboration across the organization. This paper looks at the best practices involved in a maturing data management practice, as outlined in a SAS-sponsored webinar in the Applying Business Analytics series.

To survive and emerge stronger from the current financial crisis, it is essential that insurance companies implement an enterprise risk management strategy. And for any ERM project to be successful, it must be fundamentally linked to a holistic, unified approach to data management - one that ensures a smooth flow of information throughout the organization. This white paper discusses how using SAS for data management enables decision makers at all levels to see a complete picture of enterprise risk.

This white paper reviews a portion of a research program conducted by BusinessWeek Research Services designed to understand how companies can optimize business analytics to improve fact-based decision making and to determine the attitudes and opinions of C-level executives with regard to the use and value of business analytics. It is part of a series of white papers for C-level executives intended to facilitate sharing the most important insights from the research. 

Data migration projects often fail because of an underestimation of the effort required or a lack of planning. This paper focuses on the main areas associated with data migration: source system exploration, data assessment, migration design, migration build, execution, transition and production, and provides recommendations to enhance your chances for successful data migration projects. SAS Enterprise Data Integration Server provides a complete suite of functionality to complete all types of data migrations, as well as a platform that is reliable and scalable. It helps accelerate the delivery of data migration projects and also facilitates component reuse between projects.

Opinion des décideurs informatiques et opérationnels sur la gestion du risque (Solvabilité II) et les contraintes en matière d'alignement de l'informatique. Enjeu clé des sociétés d'assurances dans les mois à venir, la mise en conformité avec la directive Solvabilité II concerne en premier lieu les directions financières mais aussi les responsables informatiques. Alors qu'il ne reste que quelques mois aux entreprises, 45 % des responsables interrogés dans cette étude déclarent être encore en cours de décision sur le sujet.

Data is only as valuable as its actual or perceived quality. The traditional approach to data quality management is to correct quality problems as they are encountered. There is an emerging approach to data quality that takes a more proactive approach by putting data quality standards and processes in place that govern data throughout its lifecycle. This white paper, based on two research projects, describes a three-tiered approach the research uncovered for managing data quality in the insurance market.

Oil and gas companies invested heavily in ERP and DCS systems, which brought about increased efficiency. But when global business dynamics – driven by increased data volumes and changes in transaction infrastructures, decision patterns and performance criteria – began to shift from the status quo attitude of  "let things run by themselves," proactive planning and decision making took on greater importance as a way to adapt to change and gain competitive advantage. This white paper focuses on a four-layer model for regaining the benefits of ERP and DCS systems by enabling organizations to make full use of their corporate information and knowledge.

Healthcare Informatics Research surveyed 418 health care providers to find out whether and how they're integrating payer and provider data now, and how they might proceed in the near future. This special report, based on the results of that survey, takes a look at how looming health reform law is lending urgency to the need for health organizations to streamline their processes to lower costs and optimize quality, and how access to essential data remains a hurdle for many providers.

From the patrol officer to the chief executive, law enforcement faces myriad challenges that push them into necessity-driven, reactive approaches. With the lack of resources, changes of scope and nonintegrated information, new opportunities to innovate and advance policing will have to emanate from the maximized utilization of the resources that remain: existing staff and accessible information. By pulling together operationally relevant intelligence from vast sources of internal and external data, law enforcement agencies can see the big picture and the critical information necessary to do their jobs effectively.

Data migration projects often fail because of an underestimation of the effort required or a lack of planning. This paper focuses on the main areas associated with data migration: source system exploration, data assessment, migration design, migration build, execution, transition and production, and provides recommendations to enhance your chances for successful data migration projects. SAS Enterprise Data Integration Server provides a complete suite of functionality to complete all types of data migrations, as well as a platform that is reliable and scalable. It helps accelerate the delivery of data migration projects and also facilitates component reuse between projects.

This report from Bloor Research evaluates SAS ETL^Q, outlining a number of key findings about the SAS offering. In particular, this report highlights that, while SAS has not traditionally been well known in the ETL marketplace, SAS ETL products are mature and worth consideration. In addition to outlining key findings, this report provides some background on SAS, its available products, and its capabilities in data access and data quality. The paper also includes a discussion of SAS ETL Studio, the primary development environment for ETL processes in SAS ETL^Q.

This white paper discusses the drivers and the challenges in implementing a longitudinal data system. It then explores how, with SAS' Business Analytics Framework, information gaps among key educational agencies need no longer exist, and decision makers can be armed with the accurate data they need to make proactive decisions and effective education policies.

Opinion des décideurs informatiques et opérationnels sur la gestion du risque (Solvabilité II) et les contraintes en matière d'alignement de l'informatique. Enjeu clé des sociétés d'assurances dans les mois à venir, la mise en conformité avec la directive Solvabilité II concerne en premier lieu les directions financières mais aussi les responsables informatiques. Alors qu'il ne reste que quelques mois aux entreprises, 45 % des responsables interrogés dans cette étude déclarent être encore en cours de décision sur le sujet.

This paper summarizes a webcast that describes how Courtyard by Marriott redesigned the lobbies of their properties to be more stylish and functional. Analytics played a role during all phases of design by providing insight from focus groups, surveys and concept testing.

This white paper discusses some of the key infrastructure challenges that IT faces in meeting the ever-increasing demands for intelligence across their organizations. It provides an overview of how the platform for SAS Business Analytics can help overcome those challenges. It also describes SAS strengths within each of the platform components -- data integration, analytics, and reporting. Most importantly, it outlines how SAS is here to help organizations achieve success through analytic solutions built upon an integrated framework. 

This technical white paper discusses the test results of SAS Scalable Performance Data Server (one component of SAS Intelligence Storage) on a Sun Solaris 10 x64 Sun Fire X4600 server with two attached Sun StorageTek 6540 arrays. The findings of the test can be applied easily to any engine or server being used as a component of SAS Intelligence Storage.

According to analysts, business intelligence applications are a top priority for CIOs. To help cut through the clutter of conflicting and overstated vendor claims, SAS has developed a comprehensive framework that can be used to evaluate any and all BI vendors. This white paper outlines the criteria included in this framework, which include measures of technology, alignment with customer needs corporate vision and geographic scope.

This paper explores the concepts of Information Management, including the challenges and importance of effectively managing ALL data whether it is structured, unstructured or semi-structured. It discusses the evolution of information management and outlines the SAS approach for a coherent IM strategy, which includes implementing a business intelligence competency center and the use of a comprehensive, integrated software platform.

This IDC paper, sponsored by Platform Computing and SAS, focuses on the value of deploying business analytics solutions on grid computing platforms. It discusses high-performance computing environments (evolution is moving from clusters to grids to cloud computing), the reasons for choosing business analytics software on grid computing platforms and the benefits achieved by three organizations. These case studies illustrate how SAS Business Analytics and grid computing technologies can enable competitive differentiation, even with increasing data volumes, challenging and ever-changing decision-support requirements, and pressure on IT departments to do more with less.

This paper provides information on key highlights of SAS 9.2 that have been released thus far, and is intended to help existing SAS customers understand SAS 9.2 software enhancements. It includes a short section on why customers should upgrade and provides a general overview of what is included with the release. It discusses new software modules and provides enhancement information for many other SAS products. It also includes a section on system management and security features, and a section on installing, configuring and migrating to SAS 9.2.