Evolution of Business Intelligence in the Digital Era - Part Two

March 25, 2024

In 2001 a maturity model of ERP usage was developed and then considered how; cost, entropy (level of disorder), complexity, flexibility and competitiveness would be impacted at each stage. Three stages have been identified in this model 

  • In stage one, companies are commencing their ERP implementation while at the same time managing their existing legacy systems. 
  • In stage two, the implementation is complete across the organisation and the functionality is being adopted. 
  • In the third stage and final stage, the ERP system has been accepted and companies are investigating avenues for achieving strategic value from the additional functionality available in the ERP system. 

There was another model where maximum shareholder value could be gained when an organisation efficiently and effectively adapts to its environment. This could be in relation to mergers, acquisitions, spin offs, new markets and improved collaboration with customers and suppliers. It was believed that ERP systems can assist in the gaol of an adaptive enterprise through what was termed, ‘Adaptive ERP Value Trajectory’. Such a model focusses on companies moving form core ERP transactions to Enterprise Application Integration (EAI) to integrate and collaborate with business partners. This implies a reliance on BI solutions. There are three value drivers that helped in the evolution of ERP systems towards BI - 

  • Integrate - where a company is able to integrate their data and processes internally and externally with customers and suppliers, 
  • Optimise - where a company standardises processes based on best business practices as offered by the ERP system, and 
  • Informate - where a company has the ability to provide context rich information to support effective decision making.  

There are a list of benefits companies were expecting from their systems. The top benefits identified are related to effective decision-making and business intelligence. All the ERP usage models identify the evolutionary nature of how companies use these types of systems to gain greater business value. Accordingly, to satisfy customer demands, ERP systems have evolved from a transactional focus to a more analytical strategic focus incorporating BI functionality.  

ERP and Business Intelligence 

Although an ERP system’s strength is in the integration of data across various functional areas to support particular business processes, the reporting capability has been limited. This was the case for SAP’s ERP system (R/3) which primarily focused on transaction processing and the associated reports. In an attempt to solve this problem sap developed its Logistic Information System (LIS), which was incorporated into its ERP system (R/3., Version 2). This was SAP’s first foray into a data warehouse solution however there were a number of shortcomings. One of the major issues was that Transaction Processing Systems (OLTP) are finely tuned for performance with much of the processing required for Analytical Processing (OLAP) impacting on the performance of the OLTP system. 

Therefore, it is often recommended that these two systems are separated in order to optimise performance. In addition the LIS interacted with only certain modules of SA{, and this necessitated a separate system being used for human resource reporting. Another significant disadvantage of the LIS was that it assumed that all the data required for effective decision-making was contained in the ERP system. Rarely is an ERP system responsible for all of a company’s transaction processing needs; often there are still numerous legacy systems operating. This is either due to budgetary constraints or because the ERP system did not have the necessary functionality. The result of these performance issues encouraged SAP to develop a separate data warehouse to facilitate business intelligence. This is known as Business Information Warehouse (BW). An analysis of SAP’s customers was performed and it was identified that BW was the most common ‘second wave’ solution implemented post core ERP. 

Another research also found that 56% of SAP customers who had implemented three or more modules, planned to implement BW within the next two or three years. This percentage increased to 63% when customers had five or more modules implemented. The evolution of ERP systems has resulted in a broad range of ‘bolt on’ solutions being developed. These solutions built upon the underlying data contained within the ERP system and provided extended functionality to assist with more strategic decision making. In addition to the Business Information Warehouse (BW) the other solutions included - 

  • Customer Relationship Management (CRM),
  • Strategic Enterprise Management (SEM), 
  • Advanced Planner Optimiser (APO), and 
  • Workplace (later to become Enterprise Portal) 

SAP originally, collectively referred to these solutions as ‘new dimension’ solutions and later re-branded these as part of marketing and licensing exercise to be included with the ERP system as part of mySAP.com. As mentioned previously companies ERP system are considered a necessary infrastructure, maturing companies are placing similar importance on their data warehouse solution. One of the characteristics that was identified as an important of any decision support system including a data warehouse was - 

‘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’ 

In accordance with this characteristic, SAP introduced ‘Business Content’ to enable companies to fully utilise the power of their BW solution. This was comprised of pre-defined reports including the underlying infrastructure to support specific business situations. The more strategic solutions of mySAP.com relied heavily on the data contained in BW and provide domain specific information to assist in decision making. For example, Advanced Planner Optimiser (APO) is responsible for facilitating planning, pricing, scheduling and product shipping across the supply chain using real time information from retailers and suppliers. This solution uses various models to assist decision makers in satisfying customer demands and requires data from internal systems, suppliers and retailers to be transformed and analysed and presented in a format which allows easy interpretation. Obviously BW plays an important role in this solution as it acts as the extractor, integrator and repository for this data. 

In the next blog, part three of this series, we will look at the CRM and its ‘bolt on’ solutions.

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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