Documents » cima data flow diagram scenario hospital.
Abstract: Hospital de la Santa Creu i Sant Pau I is the oldest
hospital in Spain, with over 34,000 admissions each year and 150,000 emergencies. In 1999, the
hospital began to implement an intranet to provide information to employees, with an update in 2003 to provide visibility of corporate information. Learn how the company is integrating a content management system with portal tools to integrate processes and improve efficiency.
PubDate: 7/7/2008 10:16:00 AM
Abstract: You have convinced upper management that flow manufacturing will enable your company to leapfrog the competition. You have appointed a flow process leader, and selected a line for your flow pilot. Now it’s time to physically perform your first line implementation. The big question is, what exactly do you need to do to make the transition from discrete to flow?
Abstract: El Hospital Sant Joan de Déu, uno de los hospitales más importantes de España, recurrió a Polymita para crear su web corporativa, una intranet personalizada para cada uno de sus trabajadores y automatizar sus procesos internos. Las soluciones BPM y ECM de Polymita llevaron al hospital a ganar el Premio al Mejor Portal del Empleado, y a lograr una gestión unificada de personas, procesos y contenidos.
Abstract: A non-profit hospital needed to protect its critical clinical systems without either interrupting system availability or overloading the small IT security team. The hospital had to overcome several vulnerabilities, such as the fact that some clinical systems could not be patched due to Food and Drug Administration (FDA) regulations. Find out how a server security solution helped the hospital address these challenges.
Abstract: Data leakage and data breach are two disparate problems requiring different solutions. Data leakage prevention (DLP) monitors and prevents content from leaving a company via e-mail or Web applications. Database activity monitoring (DAM) is a data center technology that monitors how stored data is accessed. Learn why DAM complements DPL, and how you can benefit by making it part of your overall data security strategy.
Abstract: Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.
Abstract: Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.
Abstract: You can blame your sales people all you want, but if the lead data is bad, they’re not going to bring in business. You can blame your product managers for ineffective promotions, but if the target lists are redundant, the pitches fall on deaf ears. You can blame your customer service representatives for low satisfaction scores, but if customer data is missing, then no wonder the complaint resolution pipeline is backed up. Think it’s your customer resource management (CRM) system? Think again. It’s bad data, and it’s costing you millions. Request your copy of The Bottom Line on Bad Customer Data that delivers detailed advice from Jill Dyche, partner and co-founder of Baseline Consulting, about what you can do to address the impact of bad data on your company. The report gives you insight into how bad data is impacting your company and what you can do about it. How to identify where the bad data is and quantify its impact, and different approaches to determine the sources and causes of bad data are all offered in this paper.
Abstract: While lean/flow leverages practices to stay ahead of actual demand, traditional approaches better coordinate secondary, back-office systems like accounting and HR. Moreover, flow should be a company-wide strategy that impacts more than manufacturing.
Abstract: University of Wisconsin Hospital and Clinics (UWHC) had never suffered from a shortage of data sources. But the executives felt it wasn’t effectively using this data to make decisions—leading the university to seek a solution that would help it rise above the data confusion. With an automated dashboard system from ActiveStrategy, the UWHC has aggregated its data and can now focus on issues that will help move its strategy forward.
Abstract: Sant Joan de Déu Hospital is one of the most important hospitals in Spain, and specializes in pediatrics and women’s medicine. Because of its status, it needed to find a way to automate its internal processes and develop a corporate portal for patients and health professionals. Since deploying a business process management (BPM) solution, Sant Joan has increased accessibility and created autonomy within its departments.
Abstract: Lean execution strategies within enterprises and across supply chains can dramatically reduce cycle times, improve quality, reduce waste, and improve bottom lines. In other words, lean is more than an advantage: it is a competitive necessity. Oracle’s Flow Manufacturing module capabilities in lean execution can enable the transition from a discrete, push-based manufacturing environment to a flow, pull-based one.
Abstract: Today’s critical cash-flow and liquidity concerns are demanding executive-level attention. Turmoil in the financial markets is leaving many companies struggling to ensure the cash flow and liquidity needed for normal operations. Learn about software solutions that can help your company protect its commercial cash flows, improve visibility into sources and uses of cash, and increase control over global cash balances.
Abstract: Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you.
Abstract: There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.
Abstract: Data auditing is a form of data protection involving detailed monitoring of how stored enterprise data is accessed, and by whom. Data auditing can help companies capture activities that impact critical data assets, build a non-repudiable audit trail, and establish data forensics over time. Learn what you should look for in a data auditing solution—and use our checklist of product requirements to make the right decision.
Abstract: Rising data volume is not the only reason companies are concerned with issues of data integration and data quality. The growing numbers of disparate systems that produce and distribute data add to the complexity. But in many companies, data quality management has not kept pace with the growth of data integration projects, and its use is immature. Find out how moving toward a single data services architecture can help.
Abstract: Companies are fighting a constant battle to integrate business data and content while managing data quality. Data quality serves as the foundation for business intelligence (BI), enterprise resource planning (ERP), and customer relationship management (CRM) projects. Learn more about software that unifies leading data quality and integration solutions—helping your organization to move, transform, and improve its data.
Abstract: Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.