Business Analysis Information determination Information specification Alternative generation and...

Business Analysis

• Information determination

• Information specification

• Alternative generation and selection

Information determination

• The Art of Listening to stakeholders

• The Art of Sending Appropriate Stimuli to Stakeholders so that the response is worth Listening to

• The Art of Establishing an environment in which Stakeholders are willing and able to describe their problems

... Information determination

•Defining the users in more details

•Building a logical model of the current system

•Refining the estimates

•Presenting the facts to mgt. - oral or written.

Stakeholders

• Users

• Customers

• Marketing

• Designers

• Development Managers

• Testers

• Trainers and Other Support Persons

What are the Basic Requirements

• Understand the business process

• Understand the data used or produced during that process.

• Understand the limits of volume and time.

• Understand the performance controls

• Understand the transaction / decision reqts.

• Understand the organizational requirements.

Understand the business process

• What is the Purpose?

• What steps -where and by whom?

• Duration or life cycle?

• What frequency?

• Who benefits / interacts?

Data used / Produced

• What data

• What format of data

• What stored data items within the process

• Who is the user

• What is missing / redundant

• What is temporary /permanent data

Time and Volume of Data

• What is the volume

• What is the frequency

• Random or predefined cycle of occurance

Performance Controls

• What areas need controls

• What methods of diagnosis

• What measures of performance

• Which yardsticks / benchmarks

• What prevention

Environment

• Key persons - who and why

• Political influences

• Organization culture

• Organizational Strengths / Weaknesses

• History of the system

Fact Finding Techniques

• Interviews– Structured / Unstructured

• Questionnaires– Open / Closed

• Brainstorming

• Prototyping / Story Boarding

• Use Cases

...Fact Finding Techniques

• Record Reviews – Internal / External

• Observations

System Modelling

Process Modeling

Process Modeling

• Graphically represent the processes that capture, manipulate, store and distribute data between a system and its environment and among system components

• Data flow diagrams (DFD)– Graphically illustrate movement of data

between external entities and the processes and data stores within a system

8.148.14

Process Modeling

• Modeling a system’s process– Utilize information gathered during

requirements determination– Structure of the data is also modeled in

addition to the processes

• Deliverables and Outcomes– Set of coherent, interrelated data flow

diagrams

8.158.15

Process Modeling

• Deliverables and outcomes (continued)– Context data flow diagram (DFD)

• Scope of system

– DFDs of current system• Enables analysts to understand current system

– DFDs of new logical system• Technology independent• Show data flows, structure and functional

requirements of new system

8.168.16

Process Modeling

• Deliverables and outcomes (continued)– Project dictionary and CASE repository

8.178.17

Data Flow Diagramming Mechanics

• Four symbols are used

– Two different standard sets can be used• DeMarco and Yourdan• Gane and Sarson

8.188.18

Data Flow Diagrams - Symbols

Process

Data Store

Source/Sink

Data Flow

DeMarco &Yourdon Gane and Sarson

Comparison of DeMarco & Yourdan and Gane & Sarson DFD symbol sets

8.208.20


• Data Flow– Depicts data that are in motion and moving as

a unit from one place to another in the system.

– Drawn as an arrow– Select a meaningful name to represent the

data

8.218.21


• Data Store– Depicts data at rest– May represent data in

• File folder• Computer-based file• Notebook

– The name of the store as well as the number are recorded in between lines

8.228.22


• Process– Depicts work or action performed on data so

that they are transformed, stored or distributed

– Number of process as well as name are recorded

8.238.23


• Source/Sink– Depicts the origin and/or destination of the

data– Sometimes referred to as an external entity– Drawn as a square symbol– Name states what the external agent is– Because they are external, many

characteristics are not of interest to us

8.248.24

Data Flow Diagramming Definitions

• Context Diagram– A data flow diagram (DFD) of the scope of an

organizational system that shows the system boundaries, external entities that interact with the system and the major information flows between the entities and the system

• Level-O Diagram– A data flow diagram (DFD) that represents a system’s

major processes, data flows and data stores at a high level of detail

8.258.25

Developing DFDs: An Example

Hoosier Burger’s automated food ordering system

• Context Diagram contains no data stores

• Next step is to expand the context diagram to show the breakdown of processes

8.268.26

Context diagram of Hoosier Burger’s food ordering system

8.278.27

Level-0 DFD of Hoosier Burger’s food ordering system

8.288.28

Data Flow Diagramming Rules

• Basic rules that apply to all DFDs– Inputs to a process are always different than

outputs– Objects always have a unique name

• In order to keep the diagram uncluttered, you can repeat data stores and sources/sinks on a diagram

8.298.29


• Process– No process can have

only outputs (a miracle)

– No process can have only inputs (black hole)

– A process has a verb phrase label

• Data Store– Data cannot be moved

directly from one store to another

– Data cannot move directly from an outside source to a data store

– Data cannot move directly from a data store to a data sink

– Data store has a noun phrase label

8.308.30


• Source/Sink– Data cannot move

directly from a source to a sink

– A source/sink has a noun phrase label

• Data Flow– A data flow has only one

direction of flow between symbols

– A fork means that exactly the same data goes from a common location to two or more processes, data stores or sources/sinks

8.318.31


• Data Flow (Continued) A join means that exactly the same data comes

from any two or more different processes, data stores or sources/sinks to a common location

A data flow cannot go directly back to the same process it leaves

A data flow to a data store means update A data flow from a data store means retrieve or use A data flow has a noun phrase label

8.328.32

Decomposition of DFDs

• Functional decomposition– Act of going from one single system to many

component processes– Repetitive procedure– Lowest level is called a primitive DFD

• Level-N Diagrams– A DFD that is the result of n nested decompositions of

a series of subprocesses from a process on a level-0 diagram

8.338.33

Balancing DFDs

• When decomposing a DFD, you must conserve inputs to and outputs from a process at the next level of decomposition

• This is called balancing• Example: Hoosier Burgers

– there is one input to the system, the customer order– Three outputs:

• Customer receipt• Food order• Management reports

8.348.34

Balancing DFDs

• Example (Continued)– We have the same inputs and outputs– No new inputs or outputs have been

introduced– We can say that the context diagram and

level-0 DFD are balanced

8.358.35

Balancing DFDs

• An unbalanced example– In context diagram, we have one input to the

system, A and one output, B– Level-0 diagram has one additional data flow,

C– These DFDs are not balanced

8.368.36

An unbalanced set of data flow diagrams(a) Context diagram(b) Level-0 diagram

8.378.37

Balancing DFDs

• We can split a data flow into separate data flows on a lower level diagram

• Balancing leads to four additional advanced rules

8.388.38

Four Different Types of DFDS

• Current Physical– Process label includes an identification of the

technology (people or systems) used to process the data

– Data flows and data stores are labeled with the actual name of the physical media on which data flow or in which data are stored

8.398.39


• Current Logical– Physical aspects of system are removed as much as

possible– Current system is reduced to data and processes that

transform them

• New Logical– Includes additional functions– Obsolete functions are removed– Inefficient data flows are reorganized

8.408.40


• New Physical– Represents the physical implementation of the

new system

8.418.41

Guidelines for Drawing DFDs

• Completeness– DFD must include all components necessary

for system– Each component must be fully described in

the project dictionary or CASE repository

• Consistency– The extent to which information contained on

one level of a set of nested DFDs is also included on other levels

8.428.42


• Timing– Time is not represented well on DFDs– Best to draw DFDs as if the system has never

started and will never stop.

• Iterative Development– Analyst should expect to redraw diagram

several times before reaching the closest approximation to the system being modeled

8.438.43


• Primitive DFDs– Lowest logical level of decomposition– Decision has to be made when to stop

decomposition

8.448.44


• Rules for stopping decomposition– When each process has been reduced to a

single decision, calculation or database operation

– When each data store represents data about a single entity

– When the system user does not care to see any more detail

8.458.45


• Rules for stopping decomposition (continued)– When every data flow does not need to be split further

to show that data are handled in various ways– When you believe that you have shown each

business form or transaction, on-line display and report as a single data flow

– When you believe that there is a separate process for each choice on all lowest-level menu options

8.468.46

Using DFDs as Analysis Tools

• Gap Analysis– The process of discovering discrepancies

between two or more sets of data flow diagrams or discrepancies within a single DFD

• Inefficiencies in a system can often be identified through DFDs

8.478.47

Using DFDs in Business Process Reengineering

• Example: IBM Credit– Credit approval process required six days

before BPR– DFD after reengineering– IBM was able to process 100 times the

number of transactions in the same amount of time

8.488.48

Summary

• Data flow diagrams (DFD)– Symbols– Rules for creating– Decomposition– Balancing

• Four different kinds of DFDs– Current Physical– Current Logical– New Logical– New Physical

8.498.49

Summary

• DFDs for Analysis

• DFDs for Business Process Reengineering (BPR)

• Oracle’s Process Modeler

• Functional Hierarchy Diagrams

8.508.50

Using DFDs as Analysis Tool

• Identify redundant flows – data captured, not read.– Identical updations

• Identifying overlapping responsibilities and hence inefficiencies

• Identifying system requirements

• Identifying Alternate design strategies

Logic Modeling

Logic Modeling

• Data flow diagrams do not show the logic inside the processes

• Logic modeling involves representing internal structure and functionality of processes depicted on a DFD

• Logic modeling can also be used to show when processes on a DFD occur

9.539.53

Logic Modeling

• Deliverables and Outcomes– Structured English– Decision Trees– Decision Table

9.549.54

Modeling Logic with Structured English

• Modified form of English used to specify the logic of information processes

• Uses a subset of English– Action verbs– Noun phrases– No adjectives or adverbs

• No specific standards

9.559.55

Modeling Logic with Structured English

• Similar to programming language– If conditions– Case statements

9.569.56

Modeling Logic with Decision Trees

• A graphical representation of a decision situation

• Decision situation points are connected together by arcs and terminate in ovals

• Two main components– Decision points represented by nodes– Actions represented by ovals

9.579.57

Modeling Logic with Decision Trees

• Read from left to right

• Each node corresponds to a numbered choice on a legend

• All possible actions are listed on the far right

9.589.58

Decision tree representation of the decision logic in the decision tables with only two choices per decision point

9.599.59

Modeling Logic with Decision Tables

• A matrix representation of the logic of a decision

• Specifies the possible conditions and the resulting actions

• Best used for complicated decision logic

9.609.60

Modeling Logic withDecision Tables

• Consists of three parts– Condition stubs

• Lists condition relevant to decision

– Action stubs• Actions that result from a given set of conditions

– Rules• Specify which actions are to be followed for a

given set of conditions

9.619.61

Modeling Logic with Decision Tables

• Indifferent Condition– Condition whose value does not affect which action is

taken for two or more rules

• Standard procedure for creating decision tables– Name the condition and values each condition can

assume– Name all possible actions that can occur– List all rules– Define the actions for each rule– Simplify the table

9.629.62

Complete decision table for payroll system example

9.639.63

Deciding Among Structured English, Decision Tables and Decision Trees

Criteria Structured English

Decision Tables

Decision Trees

Determining Conditions and Actions

Second Best Third Best Best

Transforming Conditions and Actions into Sequence

Best Third Best Best

Checking Consistency and Completeness

Third Best Best Best

9.649.64

Summary

• Several methods of logic modeling– Structured English

• Primarily communication technique for analysts and users

– Decision Tables• Conditions are listed in condition stubs• Possible actions are listed in action stubs• Rules link conditions with actions

9.659.65

Summary

• Decision Tables– Lists all possible rules

• Decision Trees– Conditions are portrayed by decision points– Values are represented by paths between

decision points and ovals that contain actions

9.669.66

Summary

• Comparison of Structured English, Decision Tables and Decision Trees– Most studies show that decision trees are

best for many criteria– There is no best technique– Analyst must be proficient in all three

9.679.67

SRS-Template

Requirement Specification Template

• Product Constraints– Purpose of the Product– Client, Customer and Other Stakeholders– Users of the Product– Requirements Constraints– Naming Conventions and Definitions– Relevant Facts– Assumptions

...Requirement Specification Template

• Functional Requirements– Scope of the Product– Functional and Data Requirements


• Non Functional Requirements– Look and Feel– Usability– Performance– Operational– Maintainability and Portability– Security– Cultural and Political– Legal


Open Issues Off the shelf solutions New Problems Tasks Cutover

Risks Costs User Documentation Waiting Room

Project Issues

Requirement Shell

Requirement #: Requirement Type: Event/Use Case:

Description:

Rationale:

Source:Fit Criterion:

Customer Satisfaction: Customer dissatisfaction:

Dependencies: Conflicts:Supporting Material:History:

Business Analysis Information determination Information specification Alternative generation and...

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