EVIS delivers services to transform your data to information.

Supporting business decisions with information from data

Decision making is a critical part of management. Your success as manager depends on the ability to make wise decisions at the right time: this ensures success for you and your company; poor choices can damage your carrier and your team performance. This course shows how valuable and accurate business modeling – through a Data Mining approach – can be when sound and ethical decision implementation is needed.

The current aggressive and demanding management practice needs to discover which useful information is contained in the enterprises databases in order to be able to take informed and optimal decisions and thus, to achieve competitive advantages. In the discovery process it is essential to integrate qualitative and quantitative analysis (e.g. Data Mining based Modeling) of business concepts.

In this course you will learn - theoretically and practically- to connect Data Mining analysis to Business Modeling in order to accurately evaluate every aspect of your target opportunity and risks. We’ll explicate important issues of the business-oriented data analysis and we’ll give some examples of Business Cases solved by means of Data Mining based modeling. We stress essential Business Modeling techniques and skills that can be supported by Data Mining knowledge: your companies should possess them in order to optimally deal with their business situations, i.e to have the right product in the right place at the right time, in the right quantity and for the right price.

Who should attend it?

The course is intended for Data Mining and Business consultants and managers whose work depends on drawing healthy conclusions from data. For those with a previous knowledge of Data Mining, they will learn about useful application in the world of business. The one familiar with business will get insight into new technologies to improve tactic and strategic decision-making. Whether you are a manager seeking to expand your skills or a seasoned professional looking to broaden your knowledge base, this solution-oriented course put reliable answers at your fingertips.

The course can be immediately applied to your own problems in order to answer questions about your clients like: “What are the characteristics of your most important clients?”, “How can you bind your customers?”, “Which goods should be promoted to this customer?”, “What is the probability that a certain customer will respond to a planned promotion?”, “Why do clients leave you, and how can you prevent it?”, “Which potential customers should you avoid?”,  “Can one predict the most profitable securities to buy/sell during the next trading session?”, “Will this customer be default on a loan or pay back on schedule?”, “How many claims you can expect in the short term?”.

The modeling techniques presented in this course can also be successfully applied to solve problems arising in other business fields like business optimization (“How to reduce your costs?”), or even in other expertise fields like telecom (“How large the peak loads of  a telephone or energy network are going to be?), banking (“how to detect fraud?”, card marketing, predictive life-cycle management), retail industry (“How to  improve the relationships with the clients?”, buyer behavior, sales forecasting, database marketing, etc), and medical care (“Which medical diagnosis should be assigned to this patient?”, “How to minimize the costs without reducing quality?”,  and “how to investigate the quality of care”). For more information about examples of problems in different expertise fields that can be solved with Data Mining Modeling we refer to www.evisolutions.nl

The Structure of the Course

This course offers a clear methodology (only as much as it is necessary to adapt and follow), tools and examples for transforming verbally expressed business situations or problems into qualitative models. Then, by using data mining, into quantitative models (Data Mining supported Models) that yield solutions for your business problem. Also it shows how to interpret the obtained results in the context of the given business problem. The course is divided into three parts: 

Part I: Getting the appropriate Model for your Business situation:

It sharpens and deepens your modeling knowledge’s and skills, and you'll learn how to:

• Formulate business problem such that it can be directly modeled or mined
• Explore interactively the situation that needs to be modeled
• Use exploration tools: mind maps, cognitive maps and cognitive models
• Identify and reveal hidden assumptions, prejudices, biases, options, social and cultural interactions
• Model business situation with physical systems metaphors
• Construct business models as dynamical systems within a certain contextual framework
• Frame Business Models and assess possible strategies, tactics, risks and benchmarks
• Discover mineable problems within the framework of the model
• Recognize business problems for which data mining is fitted at solving
• Align modeler and client/stakeholder expectations

Part II: Getting the Model suitable for Data Mining

It focuses on getting the model suitable for data mining, on finding and using appropriate data for the business situation:

• Identify the key places of the business process map to collect data about the business process: where the process information flow crosses its functional boundaries
• Identify and use data to create the model that accurately represents the business situation
• Select the Data Mining Modeling Technique (Relationship, Context, Forecast and Check) that suit a certain type of process manipulation (it is well known that managing a company/team (performing changes)  requires managers to use different types of process manipulation like flow time, flow capacity, waiting time, process variability and process efficiency)
• Select which Business issues each type of Data Mining model might address 
• Develop and refine the proposed Data Mining approach using the compelling example of Customer Relationship Management (CRM) Model

Part III: Interpretation of the results and Model Deployment

The final part will delve into:

• Many example of problems that can be expected when deploy the Model in the real-world
• Deal with these problems in order to achieve more positive results (changes) than expected
• A common framework for all Model deployment phases
• The impact that different Models can have on your enterprises
• Motivation for success