Evolution of Business Intelligence in the Digital Era - Part One

March 18, 2024

Much attention has been given to optimising businesses transactions and the associated processing of data however there is disappointment by top level management as to the role that information technology plays in supporting decision making in organisations. The concept of using information systems to support decision making has been a goal since their introduction of computer technology to business. One type of information system with this specific goal was termed a ‘Decision Support System’ (DSS). 

In this blog series will look at how DSS promises to provide managers with timely and relevant information in addition to analytical capabilities to assist effective decision-making. There are three major characteristics of DSS - 

  • Designed specifically to facilitate decision processes, 
  • Support rather than automate decision making, and, 
  • Ability to respond quickly to the changing needs of decision makers.

Also, there are other five characteristics that should be common across DSS. These are - 

  • The inclusion of a body of knowledge that encompasses a component of the decision-makers’ domain. This includes how to achieve various tasks and the possible valid conclusions for various situations,  
  • The ability to acquire and maintain descriptive knowledge, 
  • The flexibility to present knowledge on an ad hoc basis in a variety of customisable formats, 
  • The ability to derive subsets of stored knowledge to facilitate decision making, and, 
  • The flexibility to provide the user with choice in the sequence of knowledge management activities.  

As the demand for information systems ot support effective decision making have increased, so have the terms used to describe them - data warehousing, knowledge management, data mining, collaborative systems, online analytical processing, with business intelligence tending to encompass all. The market for business intelligence solutions has been one of the fastest growing with revenues reaching $12.8 billion in 2002 - 2003. The lowest level of the hierarchy is the business intelligence infrastructure. This represents the data warehouse which extracts dara from operational systems and then transforms, consolidates and aggregates this data in readiness for reporting to assist in decision making. The next level, business performance management refers to the use of the data from the data warehouse to provide feedback for management on Key Performance Indicators (KPI). Decision enablement refers to the automation of decisions including KPI’s based on historical decisions stored in a knowledge repository. The highest level of the hierarchy refers to the Business Activity Monitoring (BAM). This terms, first coined by Gartner, refers to a process whereby key business managers to take corrective action. These BI systems are event driven, real time and rule based. This also gives rise to the concept of analytics and dashboards. A dashboard in the corporate world provides a visual summary to the performance of the company as measured by the key performance indicators in a similar fashion to an automobile dashboard which provides a visual summary to the car’s performance. 

In recent times there has been a consolidation of vendor BI solutions through takeovers and mergers. The effectiveness of a business intelligence solution is largely reliant on the underlying data infrastructure. Accordingly, the major Enterprise Resource Planning (ERP) systems vendors with their data warehouse solutions have become major players in the business intelligence market. Although ERP systems have traditionally been concerned with managing the processing of business transactions rather than business intelligence, ERP systems vendors are transforming their solution into the BI arena. 

ERP Systems 

ERP systems are information systems that are; integrated, modular, have broad business functional scope and are responsible for transaction processing in a real time environment. The purported benefits of ERP systems make them essential information systems infrastructure to be competitive in today’s business world and provide a foundation for future growth. A recent survey of 800 top US companies showed that ERP systems accounted for 43% of these companies’ application budgets. The market penetration of ERP systems accounted varies considerably from industry to industry. A report by Computer Economics inc., stated that 76% of manufacturers, 35% of insurance and health care companies, and 24% of federal government agencies already have an ERP system or are in the process of installing one. The global market ERP software, which was $16.6 billion in 1998, had a compound annual growth of 32%, which reached more than $66 billion in sales by 2003 and is estimated to have $300 billion spent over the last decade alone. 

The major vendor of the ERP systems, SAP has approximately of the ERP worldwide market. A recent report identified the top 100 companies by IT usage. This was then compared with SAP’s customer list to determine the market penetration of this vendor’s ERP system. It was determined that 9 out of the top 12 IT users were SAP customers and 45% of the total list were also SAP users. Researchers believe the growth in the uptake of ERP systems is due to several factors; the need to streamline and improve business processes, better manage information systems expenditure, competitive pressures to become a low cost producer, increased responsiveness to customers and their needs, integrate business processes, provide a common platform and better data visibility, and, as a strategic tool for the move towards electronic business. 

The benefits expected from the implementation of ERP systems varies from company to company and is dependent upon the level of ERP maturity of a company. Early research indicated the main benefits companies were expecting were related to technical issues. A landmark study by Deloitte identified the main benefits of implementing an ERP system was associated with addressing the Y2K problem and overcoming issues associated with poor and disparate systems. This research also identified an evolutionary nature to ERP usage post implementation. They identified three different phases: stabilise, synthesise and synergise. 

  • In the stabilise phase companies familiarise themselves with their implementation and master the changes which have impacted on their organisation. 
  • At the synthesise phase companies seek improvements by implementing improved business processes, adding complimentary solutions, and motivating people to support and adopt the changes. 
  • In the final phase, synergise process optimisation is achieved, resulting in business transformation.  

In the next blog, part two of this series, we will look at the evolution of the ERP systems. 

Further Reading :

Alter, S. L. (1980). Decision Support Systems: Current Practice and Continuing Challenge. Reading, MA: Addison-Wesley, 1980. 

Benbasat, I., Goldstein, D., & Mead, M. (1987). The Case Research Strategy in Studies of Information Systems. MIS Quarterly, 11(3), 215-218 

Carlino, J. (1999). AMR Research Unveils Report on Enterprise Application Spending and Penetration, Located at www.amrresearch.com/press/files/99823.asp Accessed July 2004. 

Chan, R. & Roseman, M. (2001) Integrating Knowledge into Process Models – A Case Study. Proceedings of the Twelfth Australasian Conference on Information Systems, Southern Cross University, Australia 

Comley, P. (1996). The Use of the Internet as a Data Collection Method, Media Futures Report. London: Henley Centre. 

Davenport, T., Harris, J., & Cantrell, S. (2003). Enterprise Systems Revisited: The Director’s Cut. Accenture. Davenport, T., Harris, J., & Cantrell, S. (2004). Enterprise Systems and Ongoing Change. Business Process Management Journal, Vol. 10, No.1. 

Deloitte, (1998), ERP’s Second Wave, Deloitte Consulting. Drucker, P. (1998). The Next Information Revolution. Forbes, located at www.Forbes.com 

Gartner (2003), Predicts 2004: Data Warehousing and Business Intelligence, Located at www4.gartner.com Accessed July 2004. 

Hammer, M. (1999). How Process Enterprises Really Work, Harvard Business Review, Nov./Dec. 1999

Holland, C., & Light, B. (2001). A Stage Maturity Model for Enterprise resource Planning Systems Use. The Database for Advances in Information Systems, Spring, Vol. 32, No.2

Holsapple, C. W., & Whinston, A. B. (1996). Decision Support Systems: A Knowledge Based Approach, Minneapolis, MN: West Publishing. 

Iggulden, T. (Editor) (1999). Looking for Payback. MIS, June 1999 

Keen, P. G., & Scott Morton, M. (1978). Decision Support Systems: An Organizational Perspective. MA, Addison Wesley. 

Knights, M. (2004). BI Spending Outpaces Rest of IT Market, located at www.computing.co.uk/news/1155945 Accessed December 2004 

Markus, L., Petrie, D., & Axline, S. (2001). Bucking The Trends, What the Future May Hold For ERP Packages, in Shanks, Seddon and Willcocks (Eds.) Enterprise Systems: ERP, Implementation and Effectiveness. London: Cambridge University Press. 

Mehta, R. & E. Sivadas. (1995). Comparing response rates and response content in mail versus electronic mail surveys. Journal of the Market Research Society, 37, 429-439. 

META Group, (2004), Business Intelligence Tools and Platforms, Retrieved December 2004 located at http://ftp.metagroup.com/mspectrum/BusinessIntelligenceT oolsMarket.Summary.pdf 

McDonald, K., Wilmsmeier, A., Dixon, D. C., & Inmon W. H. (2002). Mastering SAP Business Information Warehouse. Canada: Wiley Publishing 

McDonald, K. (2004). “Is SAP the Right Infrastructure for your Enterprise Analytics” a presentation at the 2004 American SAP User Group Conference, Atlanta, Georgia 

Nesamoney, D. (2004). “BAM: Event-Driven Business Intelligence for the Real-Time Enterprise”, DM Review, March. 

Nolan & Norton Institute, (2000). SAP Benchmarking Report 2000. KPMG: Melbourne. 

Rose, C. M., & Hashmi, N. (2002). SAP BW Certification: A Business Information Warehouse Study Guide, Wiley Publishing. 

Schlegel, K. (2004). SAP BW: Staying One Step Ahead of a Juggernaut, META Group, July 2004. 

Somer, T. & Nelson, K. (2001). The impact of Critical Success Factors across the Stages of Enterprise Resource Planning Systems Implementations, proceedings of the 34th Hawaii International Conference on System Sciences, 2001, HICSS 

Stanton, J. & Rogelberg, S. (2000). Using Internet/Intranet Web Pages to Collect Organizational Research Data. Organisational Research Methods, Vol. 4, No. 3, 199-216 

Stedman, C. (1999). What’s next for ERP? Computerworld, Vol. 33, August 16

Stein, A., & Hawking P. (2002). The ERP Marketplace: An Australian Update, Enterprise Resource Planning Solutions and Management. Hershey: IDEA Group Publishing.

Walsham, G. (2000) Globalisation and IT: Agenda for Research. in Organisational and Social Perspectives on Information Technology, Boston: Kluwer Academic Publishers, 195-210.

Yin, R. (1994). Case Study Research, Design and Methods (2nd Edn). Newbury Park: Sage Publications. 

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