MGMT 382 Ch. 2

Swim Lane

Layout arranges the steps of a business process into a set of rows depicting the various elements .

Operationalized Analytics

Make analytics a part of a business process. Improving business processes is critical to staying competitive in today's electronic marketplace.

Online Analytical Processing (OLAP)

Manipulation of information to create business intelligence in support of strategic decision making

Algorithm

Mathematical formulas placed in software that performs an analysis on a dataset.

Variance Bias

Mathematical property of an algorithm. - Only bias not associated with the input or training data.

Workflow Control Systems

Monitor processes to ensure tasks, activities, and responsibilities are executed as specified.

Business Process Patent

Patent that protects a specific set of procedures for conducting a particular business activity.

As-Is process models

Represent the current state of the operation that has been mapped, without any specific improvements or changes to existing processes.

Estimation Analysis

determines values for an unknown continuous variable behavior or estimated future value

Pie chart

graph in which a circle is divided into seectors that each represent a proportion of the whole

Customer Satisfaction

measured by satisfaction surveys, percentage of existing customers retained, and increases in revenue dollars per customer

Visualization

produces graphical displays of patterns and complex relationships in large amounts of data - EIS use to deliver specific key info to top managers at a glance, with little or no interaction with the system.

Affinity Grouping Analysis

reveals the relationship between variables along with the nature and frequency of the relationships

Pivot (also known as rotation)

rotates data to display alternative presentations of the data. - Can swap the rows and columns of a report to show the data in a different format.

Step One

- Create campaign - Check inventory

When is the time right to initiate a business process change?

1) There has been a pronounced shift in the market the process was designed to serve. 2) The company is markedly below industry benchmarks on its core processes. 3) To regain competitive advantage, the company must leapfrog competition on key dimensions.

Steps in Business Process Improvement

1. Document as-is process 2. Establish measures 3. Follow process 4. Measure performance 5. Identify and implement improvements

Data Mining Process Model Activities

1. business understanding 2. data understanding 3. data preparation 4. data modeling 5. evaluation 6. deployment

How many steps are there in the Order-to-Delivery Business Process?

5

Common Business Processes

Accounting & Finance Marketing & Sales Operations Management Human Resources

Business Process Modeling (mapping)

Activity of creating a detailed flowchart or process map of a work process that shows its inputs, tasks, and activities in a structured sequence.

Data Understanding

Analysis of all current data along with identifying any data quality issues

Evaluation

Analyze the trends and patterns to asset the potential for solving the business problem.

Data Modeling

Apply mathematical techniques to identify trends and patterns in the data

Digitization

Automation of existing manual and paper-based processes and workflows to digital format.

Benchmarks

Baseline values the system seeks to attain.

Recommendation Engine

Data mining algorithm that analyzes a customer's purchases and actions on a website and then uses the data to recommend complementary products.

Deployment

Deploy the discoveries to the organization for work in everyday business

Market Basket Analysis

Evaluates such items as websites and checkout scanner information to detect customers' buying behavior and predict future behavior by identifying affinities among customers' choices.

Business Understanding

Gain a clear understanding of the business problem that must be solved and how it impacts the company

Data Preparation

Gather and organize the data in the correct formats and structures for analysis

Streamlining

Improves business process efficiencies by simplifying or eliminating unnecessary steps

Workflow

Includes the task, activities, and responsibilities required to execute each step in a business process.

Sample Bias

Problem with using incorrect training data to train the machine.

Data Mining

Process of analyzing data to extract information not offered by raw data alone.

Data Profiling

Process of collecting statistics and information about data in an existing source.

Automation

Process of computerizing manual tasks, making them more efficient and effective, and dramatically lowering operational costs.

Data Replication

Process of sharing information to ensure consistency between multiple data sources.

Deep Learning

Process that employs specialized algorithms to model and study complex datasets; the method is also used to establish relationships among data and data sets.

Digital Dashboard Analytical Capabilities

- Consolidation - Drill-down - Slice-and-dice - Pivot

Accounting & Finance

- Creating financial statements - Paying accounts payables - Collecting accounts receivables

Step Four

- Deliver goods - Bill customer

Data Mining Techniques

- Estimation Analysis - Cluster Analysis - Affinity Grouping Analysis - Classification Analysis

Purpose of Business Process Models

- Expose process detail gradually and in a controlled manner - Encourage conciseness and accuracy in describing the process model - Focus attention on the process model interfaces - Provide a powerful process analysis and consistent design vocabulary.

Human Resources

- Hiring employees - Enrolling employees in health care - Tracking vacation and sick time

Criteria to Identify Reengineering Opportunities

- Is the process broken? - Is it feasible that reengineering this process will succeed? - Does it have a high impact on the agency's strategic direction? - Is it antiquated? - Does it fall far below best-in-class? - Is it crucial for productivity improvement? - Will savings from automation be clearly visible? - Is the ROI from implementation high and preferably immediate?

Types of Robotic Vision

- Machine Vision - Machine Vision Sensitivity - Machine Vision Resolution -

Step Three

- Manufacture goods

Step Two

- Place order - Notify production - Check credit

Step Five

- Support sale

Three Benefits an organization can identify by investigating business processes

1) Find bottlenecks 2) Remove redundant tasks 3) Recognize smooth-running processes

Managerial Duties

1) Make decisions quickly 2) Apply sophisticated analysis techniques, such as Porter's Strategies or forecasting, to make strategic decisions 3) Managers need to analyze large amounts of information

AI Primary Overview Includes 4 Areas:

1) Natural Language Processing 2) Natural Language Understanding 3) Knowledge Representation 4) Knowledge Planning

Machine Vision

Ability of a computer to "see" by digitizing an image, processing the data it contains, and taking some kind of action. A machine vision system uses a video camera to capture data and send it to the robot controller.

Machine Vision Sensitivity

Ability of a machine to see in a dim light or detect weak impulses at invisible wavelengths.

Business Process Improvement

Attempts to understand and measure the current process and make performance improvements accordingly.

Core Processes

Business processes, such as manufacturing goods, selling products, and providing service, that make up the primary activities in a value chain.

Dynamic Process

Continuously changing and provides business solutions to ever-changing business operations. - Managing layoffs - Changing order levels based on currency rates - Canceling business travel due to extreme weather.

Natural Language Understanding

Determines a user's intentions based on what the user typed or said.

To-Be process models

Display how the process problem will be solved or implemented. - Show the results of applying change improvement opportunities to the current (as-is) process model.

BPMN Flows

Display the path in which the process flows. Flows are represented by arrows in a business process model. - Shows the path the customer takes through the taxi cab booking process.

Strategic Business Processes

Dynamic, non routine, long-term business processes such as financial planning, expansion strategies, and stakeholder interactions.

Machine Vision Resolution

Extent to which a machine can differentiate between objects. - In general, the better the resolution, the more confided the field of vision.

Business Process Model

Graphical description of a process, showing the sequence of process tasks, which is developed for a specific purpose and from a selected viewpoint.

Business Process Model & Notation (BPMN)

Graphical notation that depicts the steps in a business process. - Provides businesses with a graphical view of the end-to-end flow of their business processes.

Business-facing processes (back office processes)

Invisible to the external customer but essential to the effective management of the business; they include goal setting, day-to-day planning, giving performance feedback and rewards, and allocating resources.

Bottlenecks

Occur when resources reach full capacity and cannot handle any additional demands; they limit throughput and impede operations

Redundancy

Occurs when a task or activity is unnecessarily repeated; for example, if both the sales department and the account department check customer credit.

Customer-facing processes (front office processes)

Result in a product or service received by an organization's external customer. - Fulfilling orders - Communicating with customers - Sending out bills and marketing information

Autonomous Robotics

Robot capable of making its own decisions and perform an action accordingly.

Decisions

Routine choices, unexpected choices

Managerial Business Processes

Semidynamic, semiroutine, monthly business processes such as resource allocation, sales strategy, or manufacturing process improvements

Prediction

Statement about what will happen or might happen in the future; for example, predicting future sales or employee turnover.

Operational Business Processes

Static, routine daily business processes such as inventory stocking, customer checkout, or daily opening and closing processes.

Knowledge Representation

Stores large amounts of data with fast access.

Business Process Reengineering (BPR)

The analysis and redesign of workflow within and between enterprises.

Cycle Time

The time required to process an order, common KPI for operations management.

Data Mining Tools

Use a variety of techniques to find patterns and relationships in large volumes of information that predict future behavior and guide decision making.

Robotic Process Automation (RPA)

Use of software with artificial intelligence (AI) and machine learning capabilities to handle high-volume, repeatable tasks that previously required a human to perform.

BPMN Gateway

Used to control the flow of a process. Handles the forking, merging and joining of paths within a process. Represented by a diamond shape in a business process model. - Determining availability status - Accepting/declining request

Static Process

Uses a systematic approach in an attempt to improve business effectiveness and efficiency continuously. - Managers constantly attempt to optimize static process. - Running payroll - Calculating taxes - Creating financial statements

Natural Language Processing

Uses language as input that a computer system can decipher and act upon its meaning

Knowledge Planning

Uses stored data to make predictions and decisions in real time such as goal-seeking analysis.

Haptic Interface

Uses technology allowing humans to interact with a computer through bodily sensations and movements - for example, a cell phone vibrating in our pocket.

Process (DSS)

What-if Sensitivity Goal-seeking Optimization

BPMN Activity

a task in a business process. - Any work that is being performed in a process. - Represented by a rounded-corner rectangle in a business process model. - Checking availability - Picking up the customers - Confirming the booking

Cluster Analysis

a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible

BPMN Event

anything that happens during the course of a business process - Represented by a circle in a model. - Customer requests, time requests, or the end of the process

Time-series chart

graphical representation showing change of a variable over time. - Stock prices

Classification Analysis

the process of organizing data into categories or groups for its most effective and efficient use

Genetic algorithm

an artificial intelligence system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem - Essentially an optimizing system: It finds the combination of inputs that gives the best outputs.

Optimization Analysis

an extension of goal-seeking analysis, finds the optimum value for a target variable by repeatedly changing other variables, subject to specified constraints

Bar chart

chart or graph that represents grouped data with rectangular bars with lengths proportional to the values they represent

What-if analysis

checks the impact of a change in a variable or assumption on the model

Critical Success Factors (CSFs)

crucial steps companies perform to achieve their goals and objectives and implement their strategies - Crucial for a business strategy's success Ex: Create high quality products, retain competitive advantages, & reduce product costs.

Transactional Information

encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks Created when: - Customers are purchasing stocks - Making an airline reservation - Withdrawing cash from an ATM.

Goal-Seeking Analysis

finds the inputs necessary to achieve a goal such as a desired level of output - sets a target value for a variable and then repeatedly changes other variables until the target value is achieved.

Source Documents

inputs for a TPS; original transaction record.

Slice and dice

the ability to look at information from different perspectives. - Once slice of information could display all product sales during a given promotion.

Usability

the ease with which people perform transactions and/or find information

Best Practices

the most successful solutions or problem-solving methods that have been developed by a specific organization or industry

Conversion Rate

the number of customers an organization "touches" for the first time and persuades to purchase its products or services

Efficiency Metrics

throughput, transaction speed, system availability, information accuracy, response time

Effectiveness Metrics

usability, customer satisfaction, conversion rates, financial

Artificial Intelligence

Simulates human thinking and behavior, such as the ability to reason and learn. - Ultimate goal is to build a system that can mimic human intelligence.

Sparkline

Small embedded line graph that illustrates a single trend. - Often used in reports, presentations, dashboards, and scoreboards

Input

Source Documents (Time sheets, wage rates, employee benefits)

Sensitivity Analysis

Special case of what-if analysis, is the study of the impact on other variables when one variable is changed repeatedly.

Operational Level (Base Level)

Structured decisions, where employees develop, control, and maintain core business activities required to run day-to-day operations.

Financial

Such as return on investment (the earning power of an organization's assets), cost-benefit analysis (the comparison of projected revenues and costs including development, maintenance, fixed, and variable), and break-even analysis (the point at which constant revenues equal ongoing costs).

Throughput

The amount of information that can travel through a system at any point in time.

Transaction Speed

The amount of time a system takes to perform a transaction.

Input (DSS)

Transaction processing system

Transfer Machine Learning

Transferring Information from one machine learning task to another. For example, in multi-task learning, a single model solves multiple tasks, such as a deep model that has different output nodes for different tasks.

Augmented Reality

Viewing of the physical world with computer-generated layers of information added to it. - Google Glass

Strong AI

Words toward providing brainlike powers to AI machines; in effect, it works to make machines as intelligent as humans.

Virtual Workspace

Work environment that is not located in any one physical space. It is usually a network of several places, connected through the Internet, without regard to geographic borders.

Histogram

a graphical display of data using bars of different heights. Similar to bar, but groups numbers into ranges.

Model

a simplified representation or abstraction of reality - Help managers calculate risks, understand uncertainty, change variables, and manipulate time to make decision

Neural Network Features:

- Learning and adjusting to new circumstances on their own. - Lending themselves to massive parallel processing - Functioning without complete or well-structured information. - Coping with huge volumes of information with many dependent variables. - Analyzing non-linear relationships in information. (Fancy regression analysis systems)

Operations Management

- Ordering inventory - Creating production schedules - Manufacturing goods

Marketing & Sales

- Promoting discounts - Communicating Marketing Campaigns - Attracting customers - Processing sales

4 Types of Bias in Machine Learning

- Sample Bias - Prejudice Bias - Measurement Bias - Variance Bias

Types of Machine Learning

- Supervised Machine Learning - Unsupervised Machine Learning - Transfer Machine Learning

Common DSS Analysis Techniques

- What-if analysis - Sensitivity analysis - Goal-seeking analysis - Optimization analysis

Benchmarking

A process of continuously measuring system results, comparing those results to optimal system performance (benchmark values), and identifying steps and procedures to improve system performance

Executive information system (EIS)

A specialized DSS that supports senior level executives and unstructured, long0term non-routine decisions requiring judgement, evaluation, and insight. - No right or wrong, only effective or efficient.

Project

A temporary activity a company undertakes to create a unique product, service, or result

Consolidation

Aggregation of data from simple roll-ups to complex groupings of interrelated information. - Data from different sales representatives can then be rolled up to an office level, then a state level, then a regional sales level.

Structured Decisions

Arise when established processes offer potential solutions. - Made frequently, most repetitive in nature; they affect short-term business strategies.

Transaction Processing Systems (TPS)

Basic business system that serves the operational level (analysts) and assists in making structured decisions - Operation accounting system such as payroll system or an order-entry system (cash register)

Process

CRUD (create, read, update, delete) Calculate Summarize (Update employee records, calculate payroll, summarize benefits)

Weak AI:

Can still make own decisions based on reasoning and past sets of data.

Online Transaction Processing (OLTP)

Capturing of transaction and event information using technology to 1) process the information according to defined business rules 2) store the information, 3) update existing information to reflect the new information

Neural Network (Artificial neural network)

Category of AI that attempts to emulate the way the human brain works.

Virtual Reality

Computer-simulated environment that can be a simulation of the real world or an imaginary world. - Fast growing area of AI that had its origins in efforts to build more natural, realistic, multi-sensory human-computer interfaces.

Expert Systems

Computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems.

Managerial Level (second level)

Employees are continuously evaluating company operations to hone the firm's abilities to identify, adapt to, and leverage change. - Cover short and medium-range plans, schedules, and budgets along with policies, procedures, and business objectives for the firm. - Concern how the organization should achieve the goals and objectives set by its strategy, and they are usually the responsibility of mid-level management. - Semistructured decisions

Drill-Down

Enables users to get details, and details of details, of information - Reverse of consolidation; a user can view regional sales data and then drill down all the way to each sales representative's data at each office.

Analytical Information

Encompasses all organizational information, and its primary purpose is to support the performing of managerial analysis tasks' - Includes transactional information along with other information such as market and industry information - Trends, sales, product statistics, and future growth projections

Output (DSS)

Forecasts, simulations, ad hoc reports

Systems View of a DSS

Input Process Output

Systems Thinking of a TPS

Input Process Output Feedback

Strategic Level (Third Level)

Managers develop overall business strategies, goals, and objectives as part of the company's strategic plan. - Monitor strategic performance of the organization and its overall direction in the political, economic, and competitive business environment. - Involve higher level issues concerned with overall direction of the organization; these decisions define the organization's overall goals and aspirations for the future. - Unstructured decisions

Fuzzy Logic

Mathematical method of handling imprecise or subjective information. - Basic approach is to assign values between 0 and 1 to vague or ambiguous information. - 0 represents information not included, whereas 1 represents inclusion or membership.

Efficiency MIS metrics

Measure the performance of MIS itself, such as throughput, transaction speed, and system availability - Measure the impact MIS has on business processes and activities, including customer satisfaction and customer conversion rates. - Focuses on the extent to which a firm is using its resources in an optimal way.

Metrics

Measurements that evaluate results to determine whether a project is meeting its goals - Two core metrics are critical success factors and key performance indicators.

Effectiveness MIS metrics

Measures the impact MIS has on business processes and activities, including customer satisfaction and customer conversation rates - Focuses on how well a firm is achieving its goals and objectives.

Case-based reasoning

Method whereby new problems are solved based on the solutions from similar cases solved in the past.

Decision Support System (DSS)

Models information using OLAP, which provides assistance in evaluating and choosing among different courses of action. - Enable high level managers to examine and manipulate large amounts of detailed data from different internal and external sources. - Doctors enter symptoms into a decision support system so it can help diagnose and treat patients. - Insurance companies also use DSS to gauge the risk of providing insurance to drivers who have Imperfect driving receords.

Semi-structured decisions

Occur in situations in which a few established processes help to evaluate potential solutions, but not enough to lead to a definite recommended decision

Unstructured decisions

Occurs in situations in which no procedures or rules exist to guide decision makers toward the correct choice

Underfitting

Occurs when a machine learning model has poor predictive abilities because it did not learn the complexity in the training data. - Solution is to try different machine learning algorithms.

Overfitting

Occurs when a machine learning model matches the training data so closely that the model fails to make correct predictions on new data.

Data Augmentation

Occurs when adding additional training examples by transforming existing examples. - Can rotate, stretch, and reflect each image to produce many variants of the original images providing enough examples of training. - Two additional learning problems: Overfitting and underfitting

Measurement Bias

Occurs when there is a problem with the data collected the skews the data in one direction.

Mutation

Process within a genetic algorithm of randomly trying combinations and evaluating the success (or failure) of the outcome.

Key Performance Indicators (KPIs)

Quantifiable metrics a company uses to evaluate progress toward critical success factors. - More specific. - Measure the progress of CSFs with quantifiable measurements, and one CSF can have several KPIs. - Can focus on external and internal measurements - Common external --> Market Share - Common Internal --> Return on Investment (ROI) Ex: avg. customer spending, # new customers, turnover rates of employees

Granularity

Refers to the level of detail in the model or decision-making process.

Output

Reports (Generating payroll reports, creating paychecks)

Infographic

Representation of information in a graphical format designed to make the data easily understandable at a glance.

Prejudice Bias

Result of training data that is influenced by cultural or other stereotypes.

Information Accuracy

The extent to which a system generates the correct results when executing the same transaction numerous times.

System availability

The number of hours a system is availabble for users.

Decision Making Essentials

The structure of a typical organization is similar to a pyramid, and the different levels require different types of information to assist in decision making, problem solving, and opportunity capturing. St

Response Time

The time it takes to respond to user interactions such as a mouse click.

Machine Learning

The type of artificial intelligence that enables computers to both understand concepts in the environment and also to learn. - Are able to act without human programs detailing how to perform tasks.

Digital Dashboards

Track KPIs, CSFs by compiling information from multiple sources and tailoring it to meet user needs.

Supervised Machine Learning

Training a model from input data and its corresponding labels. Supervised machine learning is analogous to a student learning a subject by studying a set of questions and their corresponding answers. After mastering the mapping between questions and answers, the student can then provide answers to new (never-before-seen) questions on the same topic. Compare with unsupervised machine learning.

Unsupervised Machine Learning

Training a model to find patterns in a data set, typically an unlabeled data set. The most common use of unsupervised machine learning is to cluster data into groups of similar examples. For example, an unsupervised machine learning algorithm can cluster songs together based on various properties of the music. The resulting clusters can become an input to other machine learning algorithms (for example, to a music recommendation service). Clustering can be helpful in domains where true labels are hard to obtain. For example, in domains such as anti-abuse and fraud, clusters can help humans better understand the data. Another example of unsupervised machine learning is principal component analysis (PCA). For example, applying PCA on a data set containing the contents of millions of shopping carts might reveal that shopping carts containing lemons frequently also contain antacids. Compare with supervised machine learning.

Reinforcement Learning

Training of machine learning models to make a sequence of decisions.