Data quality issues for accounting information systems’ implementation

MANAGEMENT INFORMATION CONTROL SYSTEM

Data quality issues for accounting information systems’ implementation:Systems, stakeholders, and organizational factors

Presented byAditya Ahuja (09609054)

Anshul Pachoria (6503861)Pooja Bagga (09609085)

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INTRODUCTION

Quality information is one of the competitive advantages for an organization. In an accounting information system, the quality of the information provided is imperative to the success of the systems. This paper uses a case study to address the important systems, stakeholders, and organizational factors that influence the data quality in accounting information systems’ implementation.8-6-2010 DQ issues for AI information systems' implementation 2

INTRODUCTION…(CONT,)

The management of organizations has much more focus on systematical issues than was previously required.

Accounting Information System (AIS) is one of the most critical systems in the organization and has changed its way of capturing, processing, storing and distributing information.


•More and more digital and on-line information is utilized in the accounting information systems.•They must focus on critical factors if they are to attain high-quality accounting information. Failure to do so has negative impacts on the organizations’ financial process.•Poor information quality may have adverse effects on decision making (Huang, Lee and Wang 1999, Clikeman 1999).8-6-2010 DQ issues for AI information systems implementation

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Stakeholders Involved In data Quality Issues

In data quality studies, four types of stakeholders have been identified; they are data producers, data custodians, data consumers, and data managers (Strong et al. 1997, Wang 1998). In AIS, these stakeholders were identified as follows:

(1) Data producers are those who create or collect data for the AIS;(2) Data custodians are those who design, develop and operate the AIS;(3) Data consumers are those who use the accounting information in their work activities;(4) Data managers are those responsible for managing the entire data quality in AIS.


METHODOLOGYCase-study research method is used

by collecting data from multiple sources.

In-Depth interviews of AIS stake-holders were taken to develop the case.

Sources also includes position descriptions, organizational charts, policy manuals.

Published sources were financial data and annual reports.

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ANALYSIS TECHNIQUES

All Interviews and documents were imported in a software package for qualitative analysis.

Content analysis was done with the use of coding in transcripts too.

Index tree was also generated to categorize and grouping of the qualitative material.

Quotes were used to showcase the important information.


CASE STUDYOrganization E is education and

training infrastructure organization. It partners with universities to

market and offer online courses to students and organizations.

It’s a mid-sized organization with strength of 100.

They use shelf commercial software as AIS and report against budget.

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CASE STUDY

Each of the business unit serves as the different entity.

They use their local budget and do separate analysis in software for each unit.


DATA ANALYSIS


CONTENT ANALYSISAccording to CFO, “We have to monitor

our cash balances fairly closely and it [data quality] is definitely one of the highest priorities”.

According to IT Manager, “You have to trust

your information at the end of the day and if you

don’t you are going to spend a lot of time worrying

about it”. 8-6-2010 DQ issues for AI information systems' implementation 11

CONTENT ANALYSISAccording to General User, “It is

management commitment to it and management review of how things are going. At the end of the day they should be the ones who have to ensure it works properly”.

According to IT Manager, “I think each person has to actually be their own data quality manager for that part of their job that requires high quality data”. 8-6-2010 DQ issues for AI information systems' implementation 12

CONTENT ANALYSISAccording to CFO, “The people at the

front end who are responsible whether they are answering to someone called data quality manager or someone doing the data quality manager function, I don’t think it makes any difference”.

According to IT Manager, “Now it of course has all the edit checks and balances for the data that they actually enter (Next Slide)


FINDINGSData Quality is served as the most

important factor in accounting information system followed by the stakeholders and organizational factors.

Data Quality policies and characteristics are rated the highest important.

Information supplier quality is rated highest among stakeholders factors.

Manage Change is most important among organizational factors.


FINDINGSThe commitment of management is

found out to be an important issue.Proper incentives and rewards

needs to be defined for Data Quality.Delivery of Documents on tight

timelines affects data quality adversely.

They don’t believe that any data quality manager can make some difference.


FINDINGS

To tackle, the problem account relationship manger is held responsible for data quality.

Input controls are divided into two main parts namely systems control and human controls.

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CONCLUSION Competent personnel is as important

as the suitable system;In online transaction environment,

input control should be incorporated with data suppliers’ quality management;

Data quality manager functions should be incorporated into those stakeholders’ job functions that should be responsible for DQ in AIS.


Thank you

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Date post:	24-Jun-2015
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