ACTIVITY WAREHOUSE: DATA MANAGEMENT FOR

BUSINESS ACTIVITY MONITORING

Oscar Mangisengi, Mario Pichler, Dagmar Auer, Dirk Draheim

Software Competence Center Hagenberg(SCCH) GmbH, Softwarepark 21, A-4232 Hagenberg, Austria

Hildegard Rumetshofer

FAW Software Engineering gGmbH, Hauptstrasse 119, A-4232 Hagenberg, Austria

Keywords: Activity Warehouse, Business Process Management, Business Activity Monitoring, Workflow Management

Systems.

Abstract: Nowadays collecting checkpoint data of business process activities of transactions becomes important data

resource for business analyst and decision-makers to support tactical decisions in general and strategic

decisions in particular. In the context of business process-oriented applications, business activity monitoring

(BAM) systems, which are predicted to play a major role in the future business-intelligence area is the most

visible use of the current business needs. In this paper we address an approach to derive an activity

warehouse model based on the BAM requirements. The implementation shows that data stored in activity

warehouse is able to efficiently monitor the business process in real-time and provide a better real-time

visibility of the business process.

1 INTRODUCTION

Providing high quality services to gain market

presence and competitive edge are essential for

organizations in the continuously changing business

environment. An effective and efficient way for

addressing challenges of the current business needs

is to optimize business process of the organization,

such as monitoring activities of the business process

in detail, earlier detecting the unexpected problem of

business process activities within a unit transaction

to deliver information as fast as possible to make a

decision.

Data warehouse (DW) and On-Line Analytical

Processing (OLAP) (Codd, E.F., Codd, S.B., Salley,

C.T., 1993) tool nowadays are almost identical to

Business Intelligence (BI) tools for supporting a

high-level business management to take decisions.

DWs store historical data that is integrated and

collected from different data sources and are

organized as multidimensional data (Kimball, R.,

Ross, M., Merz, R., 2002; Inmon, W., 2002). OLAP

tools allow decision-making users to dynamically

manipulate the data contained in the DW. Although

they have been developed over a decade, however,

they are inadequate to meet the current business

needs. DWs store end counts, rather than process

checkpoints (Creese, G., 2005). For example, total

unit shipped in a month, rather than a unit tracked

through milestones of assembly, quality assurance,

packaging and distribution. In addition, storing

internal checkpoint numbers into the data warehouse

was usually difficult.

In the context of business process-oriented

applications, in fact a unit transaction of business

process of the organization is represented as a long

running process and may work at intervals. Within

the interval, applications apply business process

activities, so that process checkpoints occur in the

business process.

Workflow management (WfM) systems

developed in the last decade is an essential

framework for managing and controlling the

complex administrative business processes of either

an organization or inter-organizational. It allows for

the explicit representation and support of business

processes and in addition to avoid the need to re-

code applications every time a business process

137

Mangisengi O., Pichler M., Auer D., Draheim D. and Rumetshofer H. (2007).

ACTIVITY WAREHOUSE: DATA MANAGEMENT FOR BUSINESS ACTIVITY MONITORING.

In Proceedings of the Ninth International Conference on Enterprise Information Systems - DISI, pages 137-144

DOI: 10.5220/0002377801370144

 SciTePress

change (Lawrence, P., 1997; Sheth, A.P., van der

Aalst, W.M.P., Arpinar, I.B., 1999).

In the past two years, business process

management (BPM) has generated considerable

interest in the information technology area to have

control and visibility over any type of business

process (i.e., short or long-running transaction,

system-centric or people-centric) (Chang, J., 2004).

In addition, Business Activity Monitoring (BAM)

(Dresner, H., 2002), which is predicted to play a

major role in the near future for the business-

intelligence application, is the most visible use of

addressing the current business needs. The notions

of BAM systems are to provide real-time event

management and visibility of business performance

data to enhance operational effectiveness and

decision making. The BAM system is a broad

concept and a business process-oriented solution,

encompassing more than information from BPM

systems.

This paper addresses data management for

business process monitoring, optimization, and

performance. The activity warehouse model is

derived based on business activity monitoring

requirements.

This work is organized as follows. Section 2

outlines the related works and contributions. In

Section 3 we present our research motivation, our

solution approach, and a short description of the

system architecture overview. Section 4 describes a

conceptual structure of the business process,

requirements for modelling an activity warehouse,

and the model of activity warehouse. Finally,

conclusion and further work based on our

implementation are presented in Section 5.

2 RELATED WORK &

CONTRIBUTION

In the context of the BAM architecture, research

works have been initialized and introduced by some

research institutes and organizations (Dresner, H.,

2002; Nesamoney, D., 2004; Hellinger, M,

Fingerhut, S., 2002; White, C., 2003; McCoy, D.,

2001). In relation to the workflow technology,

(Nishiyama, T., 1999) introduces the concept of

process warehouse that contains an assortment of

various aspects of a target technology compiled into

an easy to understand matrix of information. It

focuses on a general information source for software

process improvement. Moreover, (Pankratius, V.,

Stucky, W., 2005) introduce a formal notation for

such compositions in form of a workflow algebra

based on Petri Nets, which allow expressing the

creation of a workflow model from other models

using an algebraic notation with operators similar to

those known from relational algebra in databases.

They also propose a repository called as the

workflow warehouse. In addition, concerning the

data warehouse technology, (Schiefer, J., List, B.,

Bruckner, R.M., 2003) proposes architecture allows

transforming and integrating workflow events with

minimal latency providing the data context against

which the event data is used or analyzed. They use

the Extraction, Transformation, and Loading (ETL)

process to store workflow events stream in Process

Data Store (PDS).

The existing approaches of process warehouses

have not pay attention to separate tactical data from

strategic data yet. However, the separation of tactical

and strategic data is essential for monitoring

business process to improve business performance

and efficiency, since both data semantically differ.

Our approach decomposes a system into three

functions, such as delivery, regulator, and control

functions. Thus, operational, tactical, and strategic

data respectively can be separately provided.

3 MOTIVATION

This section presents our motivation to derive an

activity warehouse model. First, we discuss the

challenges of research issues in related to BPM and

BAM, an approach for the solution, and finally an

overview of the system architecture.

3.1 Motivational Issues

Our research partner aims at automating the business

process using workflow technology to monitor and

optimize business process of the organization and to

provide tactical and strategic decision. The business

process and workflow manage unit transactions at

intervals. The organization and its branches are

distributed at different locations as well as provinces

shown in Figure 1, such as the locations A, B, C, and

D. The organization and its branches apply the

corporate workflow. A unit transaction is identified

as a long-running transaction, can be submitted by a

customer at the particular location and then can be

forwarded to the other location and it can be

processed by other user in a particular role. The

institution is organized into a hierarchical structure.

That means that the decision of a particular business

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process activity is dependent on the business

hierarchy and the roles of the organization.

Business process

Location

Figure 1: The motivational issues.

3.2 Business Activity Monitoring as the

Solution Approach

Monitoring, controlling, and optimizing business

process are focused on these challenges. Thus, a

solution should be able to as follows:

• Monitor business processes, such as what, how,

who, and when an activity has been executed.

• Provide the current state of a business process

activity of a unit transaction.

• Track the business process activities of

transactions in detail.

Data warehouses (DWs) store end counts data of a

transaction and are intended for supporting strategic

decision. On the contrary, business activity

monitoring applications as well as business process

efficiency and performance applications, require

tactical data, e.g. the checkpoints of business process

activities of transactions, for supporting tactical

decisions. DWs cannot be used for monitoring

business process and for storing checkpoints of

business process activities. To overcome the current

challenges, we require an activity repository, called

Activity Warehouse. Furthermore, our approach

deals with three data decompositions, such as

operational, tactical, and strategic data.

3.3 An Overview of System

Architecture

Figure 2 shows the overall system architecture. An

overview of the system architecture is given as

follow:

On -Line

Transaction

Processing (OLTP)

Strategic

Decision

Controller

BI Tools

OLAP

BPM

Process

Monitoring

Business

Performance

Activity

Warehouse

Data

Warehouse

Workflow

Business Activity Monitoring

Event-based data capture

SOA

Figure 2: The overall system architecture.

Each module is discussed as follows:

1. On-Line Transaction Processing (OLTP) system

manages and stores the transactions of customers

and provides the operational data.

2. DW stores end counts data extracted from the

OLTP system used for supporting strategic

decision-making. However, this paper does not

focus on data warehousing as well as the

extraction, transformation, and loading (ETL)

process.

3. Controller and BI tool, such as BPM software,

provide services for to the business intelligence

applications.

4. Service Oriented Architecture (SOA) addresses

issues, such as the distributed accesses, the

diversity of location and provinces, since

transactions can be submitted at different

locations and provinces. In addition, the aim of

the SOA is to wrap the whole architecture.

5. The BAM layer consists of modules as follows:

• Workflow management (WfM) system.

Workflow system manages and controls the

business process activities of transactions

and automates the business process. It is

coupled directly to the OLTP system to

avoid the time delay between the OLTP and

BAM systems.

• Activity-based data capture. The activity-

based data capture is coupled directly to the

workflow system to track events of

business process activities of the

organization. Thus, WfM System generates

the audit trail in the correct format.

ACTIVITY WAREHOUSE: DATA MANAGEMENT FOR BUSINESS ACTIVITY MONITORING

139

• Activity warehouse. The activity warehouse

stores the data checkpoints of business

process activities of transactions in real

time.

4 ACTIVITY WAREHOUSE

This section presents our approach to manage data

for monitoring business activities. Data management

for optimizing and monitoring business process is

strongly dependent on business process requirements

of the organization. We use a top-down approach to

classify requirements for deriving the model.

4.1 A Conceptual Structure of the

Business Process

In order to manage completely the checkpoints of

business process activities of transactions, the

conceptual structure of a business process is

required. Assumed that an activity is the lowest level

of business process and the business process of a

transaction may be decomposed into activities. Thus,

a conceptual hierarchical structure of a business

process can be given as follows:

• A process model is a complete representation of

a set of business processes and its associated

resources for managing process execution.

• A unit transaction is identified as a long-running

transaction and is valid at intervals.

• A business process can be organized into a

hierarchical structure that represents different

level of importance from the highest level

process to the lowest level process, or vice-

versa.

• The business process may be decomposed into a

set of processes. A process may consist of a set

of sub-processes, and a sub-process includes of

a set of activities.

• An activity represents a particular activity of the

business process of a unit transaction.

A conceptual hierarchical structure of business

process of the organization is shown in Figure 3.

Fig. 3a shows that a unit transaction contains a

business process; Fig. 3b presents a hierarchical

structure of the business process of the Fig. 3a, and

Fig. 3c shows that an activity is represented as three-

dimensional workflow.

A unit transaction

A business process

Process 1 Process 3 Process nProcess 2

Sub process 1 Sub process 2

Sub process n

Sub process 3

Activity 1 Activity 2

...

Activity n

...

(a)

(b)

Attribute 2 Attribute 3Attribute 1

...

Attribute n

Actor

Process

Action

Status

Role

(c)

Figure 3: The unit transaction and its business process and

the conceptual of a business process.

4.2 Business Activity Monitoring and

Business Process Management

Business activity monitoring (BAM) systems consist

of components, such as Business Process

Optimization (BPO) and Key Performance

Indicators (KPI) for supporting the business process

optimization and the business metric information.

Furthermore, the BAM system architecture must be

able to support such as event-driven decision

making, rules-based monitoring and reporting, real-

time integration of event and context, and no

latency; comprehensive exception-alert capabilities

(Nesamoney, D., 2004). Meanwhile, the BPM

technology enhances the business efficiency and

responsiveness and optimizes the business process in

order to improve services of an organization (Chang,

J., 2004; McDaniel, T., 2001). Specifically, BPM

has closed relationship to the BAM system in

general and the business strategy of an organization

in particular. Thus, the BAM and BPM systems

support data as follows:

• Strategic data. The strategic data provides the

result of an organization that can be achieved

and its hypotheses. Also, it can be supported by

the scorecards.

• Tactical data. The tactical data controls and

monitors the business process activities and its

progress in detail and supports a contextual

data. The queries are given as follows:

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o Give transactions has been completely

processed today?

o Give transactions has been accepted and

can be processed in advanced today?

• Business metrics data. The business metrics

data supports the strategic improvements for the

higher level goals. It supports departments and

teams to define what activities must be

performed. The example of query is as follows:

o Give transactions have been processed for

a particular department for a particular

time today?

4.3 Workflow Management

Workflow aims at supporting the BAM and BPM

requirements presented in Section 4.2. A workflow

process definition specifies which tasks need to be

executed and in what order (i.e., the routing or

control flow). There are some workflow perspectives

(i.e. control flow or process, resources or

organization, data or information, task or function,

operation or application). In our approach, the

process and state workflow management is used for

the activity warehouse. Depending on the business

requirements, which workflow will be used for

managing a business process, however, in general

there exist two characteristics of workflow that are

be included in the activity warehouse to store data in

the particular context of business process activities.

4.3.1 Common Workflow

The common characteristics of all workflow

applications are that they are concerned with the

registration of information and with tracking that

information in a simulated environment; it is

possible to determine the status of information while

it is in the environment and which stakeholders are

responsible for performing activities pertaining to

that information. For the common workflow

requirement, the following data in the activity

warehouse are as follows:

• Tracking Activity. The tracking activity deals

with the checkpoints of business process

activities of a unit transaction. It provides the

history of activities of a unit transaction. The

queries are typically provided as follows:

o Give the progress of a particular unit

transaction?

o Give the progress of transactions on

October 24, 2006.

• Status Activity. The status activity provides the

status of a unit transaction after the execution of

a business process activity. The current status

also is be used by an actor to decide for

executing the next activity of the business

process and in addition to arrange the

executions of workflow in order. Typically the

queries is given as follows:

o Give the current status of a particular unit

transaction?

o Get transactions with the current status

“submitted” in October 2006.

4.3.2 Three Dimensional Workflow

An activity that is the lowest level process of

business process shown in Fig. 3c can be represented

as the three dimensional workflow. The three

dimension workflow at least is as follows:

• Action. An action is represented by the method

of a particular activity and is corresponded with

an actor. Activities may be assigned to actors,

applications, or system queues based on rules.

• Process. A process is a network of activities,

with rules for the start and exit conditions for

each activity and for the control and data flow

between the activities. It defines the business

process activities and the sequence in which

they are to be performed.

• Actor. An actor is defined as the person who

will execute a particular action.

In the activity warehouse, the three dimensional

workflow is provided by a set of dimension tables,

such as the dimension process, the dimension actor.

Additional dimensions for supporting three

dimensional workflow requirements are as follow:

• Role. An actor must have a particular role. A

role has close relation to the specific department

of an organization or intra-organization.

• Organization. Organization supports the

organization of an actor as well as the actor role.

An organization is usually structured into a

hierarchy model.

Moreover, to support the three dimensional

workflow of activity warehouse, the dimension role

ACTIVITY WAREHOUSE: DATA MANAGEMENT FOR BUSINESS ACTIVITY MONITORING

141

and the dimension organization are essential for the

activity warehouse.

4.3.3 Additional Requirement

This specific requirement of workflow is dependent

on the business process requirements. The activity

warehouse requires the following additional

attribute:

• Next Actor. A next actor with the particular role

is required to be recorded. For example,

forwarding an activity that is processed by the

other actor in advance. Who is responsible for

the next activity in the business process? Thus,

the activity warehouse provides the attribute

NextActor.

4.4 Time Dimension

Time aims at recording when activities are executed.

The activity warehouse has to deal with the entry

date of an activity, and furthermore it uses the

dimension time like in the multidimensional model.

In our approach for the activity warehouse, we

separate between the execution time and the

measurement times for an activity. The dimension

time manages when an activity is executed. Thus,

the dimension time is limited up to the day basis.

Also, the dimension time can be used for

aggregating the business process, such as rolling-up,

drilling-down. Examples of queries are as follows:

• Get activities have been accepted by the

particular actor, role, and department on the

October 24, 2006.

• Get activities have been finished by the

particular actor, role, and department on the

October 24, 2006.

• Get all activities that have been accepted by the

particular actor, role, and department by

rolling-up from date to month of the time

dimension, i.e., October 24, 2006 to October

2006.

In order to optimize the business process

performance and its efficiency, the activity

warehouse must be able to capture the execution

time of an activity up to second, millisecond, or

microsecond. Therefore, the activity warehouse uses

additional attributes for the time efficiency for the

purpose given in Section 4.5.2.

4.5 Measurement Data

To reach the business performance optimization, the

activity warehouse supports a set of attributes for

measurement data (e.g., the efficiency of cost) and a

set of attributes for time efficiencies. The

measurement data and the time efficiencies must be

to be tracked in detail for the checkpoints of

business process activities of transactions.

Furthermore, like OLAP tools, measurement data

can be aggregated against the dimension tables. In

the context of BAM, data stored in the activity

warehouse must be able to provide an event-driven

decision-making that means the lowest data level or

an activity can be used to make decision for the

business process efficiency. For example, the lowest

business process data can be used for finding

unexpected problem in the business process. To

support the measurement data for the activity

warehouse, we classify measurement data into as

follows:

4.5.1 Macro Level Data

The macro level data represents end count of a unit

transaction that is stored in the operational data

management and it will be stored in data warehouse

in advance.

4.5.2 Micro Level Data

The micro level data provides activities of the

business process data and represents the lowest level

data. Therefore, the micro level data is defined as a

checkpoint data of a business process activity of a

unit transaction. The micro level data is

distinguished into time efficiency data and

measurement data. Micro level data includes data as

follow:

• Time efficiency. The existence of the time

requirement is very important in the activity

warehouse. The time efficiency is intended to

answer how long an activity has been done. The

activity warehouse provides the time efficiency

attributes to measure the performance and

efficiency of business process. Attributes for the

time efficiency are dependent on the business

optimization performance requirements. A set

of time efficiency attributes could be as follows:

o Cycle time. The cycle time is the total

elapsed time, measured from the moment

when a request enters the systems to when

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it leaves it. This is the time measure that is

most obvious to the customer.

o Work time. The worked time that the

activities that execute the request are

worked on. Practically, activities are

sometimes idle or waiting for other

activities to finish and for this reason cycle

time and work time are not the same.

o Time worked. It concerned with the actual

hour of work expanded on the request.

Sometimes more than one person is

working on a request at one time. Thus,

time worked is not the same as work time.

o Idle time. The idle time refers to when an

activity or process is not doing anything.

o Transit time. The time spent in transit

between activities or steps.

o Queue time. The time that a request is

waiting on a critical resource; the request is

ready for processing, however it waiting for

resources from another activity to reach it.

o Setup time. The time required for a resource

to switch from one type of task to another.

• Cost efficiency. The cost efficiency attributes

are dependent on the value of the attributes time

efficiencies. The cost measurement data is

essential to optimize the business process and to

calculate the cost of business process.

The macro and micro data levels enable the

business process management tools to monitor and

drill down data from the macro data level to the

micro data level as well as horizontal and vertical

rolling-down to each individual transaction or

business process. Using these functionalities, an

organization can improve the visibility of the overall

performance of the organization at both the macro

and micro data levels. The macro and micro data

level are shown in Figure 4.

A2 A3

A4 A5

SP1

SP2

Macro level

Micro level

Rolling down

Rolling up

Sub-process

Process

Activity

Figure 4: The macro and micro level data.

4.6 An Activity Warehouse Model

An activity warehouse model can be shown in

Figure 5. Fig 5.a shows the relationship between the

OLTP system and the activity warehouse (AW),

whereas Fig 5.b shows the activity warehouse in

detail.

Status

Activity

ActorID

Name

Role

Actor

StatusID

Description