Examples of Application Areas
Nowadays it is straightforward to undertake data analysis and quality control projects by deploying statistics software. It is unimaginable today to undertake such projects without software solutions.

There are three reasons for this:

The huge amount of data available in the modern world has surpassed human cognitive and analytical abilities.

Information Technology has developed fast. As a result, rapid, scalable algorithms, data extraction tools and flexible graph generation procedures are now widely available.

Competition has intensified in industry. Managers, engineers, analysts, scientists and other professionals all require data analysis software, statistical know-how and training to do their jobs properly.
This is exactly the service StatSoft delivers to its clients.

Examples of areas where StatSoft delivers

Analytical CRM

Banking and Financial

Business Intelligence

Credit Scoring

Cross-Selling and Up-Selling

Customer Loyalty and Migration Analysis

Data Access, Analysis and Reporting Systems

Data Mining, Text Mining

Forecasting

Identification of Fraud

ISO 9000, TS 16949 and other Standards

Manufacturing

Medicine and Healthcare

Pharmaceuticals, Biotechnology and Medical Devices

Processes Optimisation, Prediction and Modelling

Research & Development

Sarbanes-Oxley Compliance

Scientific Research

Segmentation

Six Sigma

Statistical Process Control (SPC)

Analytical CRM
For many companies the first step in managing their sales operations is to introduce a Customer Relationship Management application (CRM) to optimise their customer relationships and effectively monitor their sales operations. However, for a CRM strategy to work it is first necessary to thoroughly analyse and understand customer behaviour. This is precisely the kind of task for which STATISTICA analytical CRM solutions are designed. Using data mining techniques, STATISTICA analytical CRM solutions analyse customer relationships and allow marketers to classify groups of customers according to their characteristics and buying behaviour (segmentation). They also help to improve the effectiveness of marketing campaigns and attract new customers, as well as maximising the value of sales to existing customers (cross-selling and up-selling) and minimising customer loss (churn). Data mining techniques are also used to analyse and monitor levels of customer satisfaction and loyalty and diagnose the causes of changes in these levels.

Please see Analytical CRM and Marketing web pages for more details.

Banking and Financial
Financial institutions have always collected detailed customer data - often in many disparate databases and in various formats. To understand customer needs, preferences and behaviour, financial institutions such as banks, mortgage lenders, credit card companies and investment advisors are turning to the powerful data mining techniques in STATISTICA Data Miner. STATISTICA Data Miner enables financial institutions to perform crucial tasks: detect patterns of fraud, identify causes of risk, create sophisticated and automated models of risk, carry out credit scoring, optimise credit portfolios, segment and predict behaviour of customers, uncover hidden correlations, create models to price futures, options and stock, and optimise portfolio performance. To achieve BASEL II compliance financial institutions must build a secure and robust data analysis and reporting system that can be validated and controlled (e.g. version control of reports), provide role-based security (so that only certain individuals can create data queries, report templates and so on) and audit trails for review by regulatory agencies.

Please see Banking and Financial Risk Management web pages for more details.

Business Intelligence
Efficient information delivery and rapid knowledge sharing is like a nervous system for an organization. Knowledge obtained from data should be accessible in the form of appropriate, easy to understand reports available to the personnel that need them and only to them. Easy-to-use business intelligence systems based on STATISTICA Enterprise and WebSTATISTICA Server can be deployed quickly by a company's IT department or with the help of our experts. All aspects of the systems are customizable in the deployment and are very flexible when in use. Now business users can have all the reports they need at their fingertips, with interactive drill-downs and filtering options, without the need to engage IT personnel every time they have a new query. Simple and highly advanced analyses can be run in seconds whether the data are dispersed or stored in a central data warehouse. Power users can run advanced, sophisticated analyses and, with a few clicks, share both results and analysis templates with other users. Millions of dollars worth of knowledge can therefore be discovered and broadcast in the STATISTICA business intelligence system.

Credit Scoring
Companies in the financial services sector are inevitably exposed to an element of risk. In banks, for example, particular importance is attached to the security of credit operations. There are various methods for evaluating credit risk such as descriptive methods or expert assessment. Recently, however, financial companies have been turning to scoring models obtained via statistical data mining techniques to carry out credit risk evaluation. These can produce a substantial reduction in bad credit and faster decision-making in credit-related matters. They also enable less experienced personnel to make decisions, whilst also reducing the quantity of paperwork required to process a credit application. All these elements lead to a substantial reduction in the cost of credit risk assessment, and improve the accuracy of credit evaluation.

Cross-Selling and Up-Selling
Modern marketing involves not only securing new customers but also building lasting relationships with existing customers and maximising the benefits resulting from these relationships, for example by cross-selling and up-selling. A company should understand customers' needs and behaviour patterns. Since information about customers and their actions can often only be found in huge datasets, the best way to achieve this understanding is by employing modern data mining techniques. These allow the extraction of new dependencies and customer behaviour from data, which can then be presented in the form of logical rules for the most frequent buying patterns. Having established correlations for a particular group of customers, managers can then put together a suitable offer for customers with similar features or purchasing preferences, and attract their attention by creating new products or expanding existing product lines. Data mining techniques are also used to create predictive models for identifying target customers for a particular offer.

Customer Loyalty and Migration Analysis
In competitive markets with a low degree of product differentiation, where the cost to customers of switching to another supplier is low, customer loyalty is an issue of central importance. The ability to accurately predict migratory phenomena is vital for companies in this type of market. It allows them to take preventative measures, forecast sales figures, assess the total value of the customer (i.e. expected income generated by a customer over the entire period of his relationship with the company) or modify their offers. Data analysis methods, especially data mining, can be used in a number of ways to prevent customer migration. In particular, statistical techniques are used to analyse customer satisfaction, identify factors determining customer satisfaction and loyalty, monitor changes in the level of customer satisfaction, and identify customer behaviour patterns, thus allowing a company to adapt its offer to suit their needs. One of the most common approaches is the creation of a data-mining model to predict the probability of customer defection (churn).

Data Access, Analysis and Reporting Systems
Given the massive amounts of data that are generated in most business and manufacturing processes and the huge cost of data acquisition, it is surprising that many organisations make so little use of the data they collect. An automated or semi-automated data access, analysis and reporting application offers significant commercial advantages. It can collect on-line production process measurements and combine these with other types of production, testing, R&D and quality data stored in different, non-integrated databases to generate reports. Specific user groups benefit from on-line and off-line analysis results and report templates published more widely via Internet or Intranet servers. Similar examples of automated data access, analysis and reporting systems exist in banking, insurances, healthcare, administration, and virtually all industries.

Data Mining, Text Mining
As a result of the rapid development of technology modern companies and institutions now possess increasingly large datasets. Although these can be a vital source of useful information this potential is not always fully exploited as standard reporting applications are often unable to identify complex relationships hidden within the data. The tools included in STATISTICA Data Miner and STATISTICA Text Miner can be adapted to individual datasets and the information needs of particular managers, allowing faster reaction to changing market conditions on the basis of current information. Reliable data mining is an invaluable asset to any modern organisation. Accurate forecasting and knowledge about clients and their behaviour, supplied at the right time and based on current data, are of key importance in determining the effectiveness of their operations.

Forecasting
One of the most important tasks of a modern manager is to forecast economic parameters affecting financial performance. In commerce and industry it is essential to forecast demand, stock levels and production figures, while in the financial and telecommunications sector the competitiveness of a company depends on its ability to forecast future client decisions and expenditure on a particular group of products or services. Call centre managers, for example, often use predictive models to forecast the number of calls processed by their telephone network. All these tasks involve the use of forecasting models based on time series data to optimise costs. Solutions are selected which guarantee accurate and reliable quantitative or qualitative forecasts appropriate to the subject of analysis and the scope of available data.

Identification of Fraud
Many branches of industry are affected by the problem of fraud: banking, insurance, telecommunications, and also companies that run loyalty schemes. Fraud is a serious threat causing substantial financial losses and undermining the image of the organisation and therefore client confidence. Traditionally, the most popular way of identifying fraud has been to use methods based on expert knowledge. However, because of the growing number of transactions and continually changing fraud methods it is now essential to support this knowledge with information obtained by advanced data mining procedures. These allow the identification of new behaviour patterns (indicating likely occurrences of fraud) and the establishment of connections between individuals taking part in illegal operations.

ISO 9000, TS 16949 and other Standards
One way to meet your customers' demands and concerns is to apply for ISO 9000 series certification. During the implementation of a quality system, 90% of the work consists of establishing and documenting Standard Operating Procedures for SPC. Appropriately integrated analytical and document management software is essential. STATISTICA is unique in combining an analytical platform with the necessary validation, security and document management features in a single off-the-shelf system.

Manufacturing
In order to achieve optimum product and service quality while simultaneously minimizing costs, many organizations have introduced quality management strategies and standards. For these approaches to be effective, a suitable IT infrastructure must be introduced for acquiring data, transforming it into actionable information and then disseminating this knowledge. Effective data acquisition combined with data analysis techniques such as Statistical Process Control, Measurement Systems Analysis (MSA), process prediction, modelling and optimisation, reliability analysis and others, greatly increases productivity, ROI, improves quality and results in more efficient and profitable manufacturing operations. See Manufacturing brochure or Manufacturing page for more details

Please see Manufacturing web page for more details.

Medicine and Healthcare
STATISTICA is widely and successfully used in medicine and healthcare. For example in epidemiological research STATISTICA is used to identify factors increasing the risk of diseases occurring. The software is also used for planning and data analysis for clinical research associated with the development of new treatment methods, analysis of survival rates and factors influencing prognosis etc. Although traditional statistical and data visualisation methods are still extremely useful and widespread in medicine, medical professionals now frequently turn to advanced data mining and text mining techniques to analyse their data. These methods allow them to extract hidden rules from datasets, which can then be used to develop new and more effective methods of treating and preventing diseases. Data analysis tools are also essential for planning and conducting screening programmes and for forecasting the cost of operations and other medical procedures.

Please see Healthcare and Pharmaceuticals web pages for more details.

Pharmaceutical, Biotechnology and Medical Devices
The pharmaceutical industry is set apart from other industries by the strict regulatory framework in which it operates. Maintaining the quality and safety of pharmaceutical products is a critical issue and producers must validate and certify production processes to demonstrate compliance with regulations. STATISTICAl data analysis methods are vital in this process. STATISTICA brings together a wealth of relevant techniques in a single software environment. In addition, STATISTICA integrates directly with process information repositories, LIMS databases and MRP systems and provides tools for access control, configuration management, audit trails and integrated document versioning. The STATISTICA product range is fully compliant with the latest regulatory requirements. What's more, it enables rapid and easy validation of custom-built systems. This creates an important advantage for other FDA controlled industries such as biotechnology, medical devices and cosmetics.

Please see Pharmaceuticals web page for more details.

Processes Optimisation, Prediction and Modelling
Production processes are often extremely complex, involving hundreds of process parameters, environmental factors and quality measures. Design of Experiments (DoE) methods are a proven method for obtaining, at minimal cost, accurate and reliable data about manufacturing processes that can then be analysed in order to find the optimal combination of process settings. By using advanced tools such as multivariate response profiling, several competing quality parameters can be optimised simultaneously. When experimentation is too costly or time-consuming, a multivariate process model based on historical data can be used to detect the causes of defects, identify critical process parameters and even predict events such as machine failures or fault occurrences. It is then possible to correct quality problems before they appear. Multiway PCA, multiway PLS and multivariate SPC or, where a linear approach is inadequate, predictive trees, neural networks and MARSplines algorithms have proved to be extremely effective in addressing difficult manufacturing problems and ensuring critical product quality. This gives manufacturers a vital competitive edge.

Research & Development
Research & Development is a complex, time-consuming and expensive process. While high quality statistical data analysis is crucial to success, it is virtually impossible to define a discrete subset of appropriate statistical methods to meet the needs of diverse research organisations. As a result, Research & Development departments need to provide their staff with a comprehensive easy-to-use and highly customisable statistical toolset that does not impose unnecessary restrictions on them. Deploying a single corporate analysis platform makes best use of IT and training resources and enables researchers to collaborate efficiently on multi-disciplinary projects. Offering a choice of stand-alone, networked, server-based and web-based analytics platforms within a collaborative environment, STATISTICA provides scientists, engineers and statisticians with cutting-edge analytical tools that are easy to use, relevant, and integrated with their data sources, resulting in a rapid return on investment.

Sarbanes-Oxley Compliance
The recent Sarbanes-Oxley legislation imposes new, extensive reporting and record keeping requirements on all publicly traded companies. It requires that executives of these companies take personal responsibility for the procedures involved in collecting data for the company's financial reports and for the integrity of their contents. In order to comply with these requirements, companies need flexible software systems that facilitate record keeping and document management in a secure and efficient manner. The STATISTICA Document Management System (SDMS) provides a costeffective and feature-rich platform for control and management of documents. Integrated with STATISTICA analytical solutions it aids compliance, ensuring a standard and secure approach to managing documents and for the capture of the necessary reviews, edits and approvals through which these documents must proceed.

Please see Sarbanes-Oxley Compliance web page for more details.

Scientific Research
The current progress in many areas of modern science is increasingly dependent on large-scale empirical research. To fully realise its objectives, research work must be properly planned and executed, and supported by appropriate procedures for analysing the data that are generated. Today's interdisciplinary research teams need access to software tools that can provide the breadth and depth of analytical methods required and include the latest data analysis techniques. StatSoft offers the STATISTICA family of software - the most comprehensive, highest performance set of analytic tools available on the market, backed by professional assistance and support in the application of data analysis and data mining in all types of empirical research.

Segmentation
To succeed in a modern economy a company must accurately identify potential customers for particular products and services and formulate their offers to address the individual needs of their target audience. One way of achieving this is by market segmentation. It is impossible for large companies operating in mass markets to establish the preferences of each customer individually. They must therefore rely on data analysis techniques involving market segmentation to divide customers into groups of similar individuals and then select an appropriate marketing approach for each group. Segmentation also allows coherent and precise definition of customer groups and a better understanding of their behaviour and motivation. The information this generates facilitates selection of target markets, adjustment of pricing policy, selection of appropriate distribution channels, and more effective identification of competitors.

Six Sigma
Six Sigma was first introduced by Motorola when the company realised that traditional methods of quality control could not bring sufficient benefit when used in isolation. Applying statistical methods within a well-structured corporate culture of constant quality improvement proved to be a powerful and successful strategy that has developed into a global phenomenon. The driving force behind this movement is its central focus on statistical data analysis, which had often not been allowed to achieve its full potential in earlier quality movements. Six Sigma's emphasis on measurement and analysis requires a full-featured statistical analysis software system. STATISTICA serves as an analytic software platform for Six Sigma programmes and implementations of any size. It provides all the necessary data management, analysis, and graphics capabilities to empower the Six Sigma Green Belts, Black Belts and Master Black Belts with the analytic tools to explore data, determine the most important factors, and perform data-driven decision-making.

Please see Six Sigma web page for more details.

Statistical Process Control (SPC)
In the 1920s Shewhart demonstrated conclusively that the use of appropriate statistical techniques allows effective control of industrial processes. Almost a century later his methods are still relevant and are still being applied to new areas. Quality Control Charts, along with Capability Analysis, are central to SPC and enable manufacturers to monitor and control process variability in order to improve product quality and reduce costs. Again and again, the effective implementation of this technology has proved to be a key characteristic of the world's most successful, customer-focused manufacturing and service organisations. To help companies make this transition, StatSoft offers desktop analytic software and enterprise solutions, as well as training, consultation and assistance in the implementation of integrated quality control systems. Our solutions are used to great effect in various manufacturing industries, banking, healthcare and other public services.