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Impact of business intelligence on enterprise productivity
- 1. IMPACT OF BUSINESS INTELLIGENCE ON ENTERPRISE PRODUCTIVITY Submitted By Nirali Shah PGDM-IT Roll no. 215
- 2. CONTENTS • Objective • Introduction • Methodology • Findings • Learnings • Limitations • Recommendations • Conclusion • References
- 3. OBJECTIVE • To examine the use and awareness of Business Intelligence. • Its impact on the Enterprise Productivity. • Satisfaction of Enterprise after using BI.
- 4. INTRODUCTION • Business Intelligence => Set of techniques and tools. Transformation of raw data into meaningful and useful information for business analysis purposes. To create new strategic business opportunities. • Enterprise Productivity => the effectiveness of productive effort, especially in industry, as measured in terms of the rate of output per unit of input. Measure of efficiency.
- 5. • Descriptive Study is used in this project. • Literature review. • Questionnaire. • The respondents for the sample were selected on random basis. • The sample size for the project is 61. • These respondents were part of some enterprise and were selected on random basis without any categorization. • Analysis through MS Excel 2010. METHODOLOGY
- 6. FINDINGS Awareness of the term Business Intelligence Respondent’s Organization Size 24 15 22
- 7. Usage of BI in Various Organizations 6 55
- 8. Usage of BI for analytics and decision making Improved performance and profits 7 54 20 25 10
- 9. Satisfaction level of Use of BI for enterprise productivity Different size of organization and their satisfaction of use of BI to improve productivity. 17 28 10
- 10. LEARNINGS • Various BI tools can be deployed across various business functions. • BI can be deployed across various type of Enterprise. • BI solution is positively related to the quality of managerial decision making.
- 11. LIMITATIONS • The resources that drive more benefits of BI solution => operations, customer service, performance, etc. • The tool which is more beneficial BI solution. • There was no personal interview or group discussion done with the respondent which could have been a detailed study of the impact of BI on Enterprise Productivity.
- 12. RECOMMENDATIONS • Small organization should search out for the right tool and techniques for better performance management.
- 13. CONCLUSION • Business intelligence can be applied to the following business purposes, in order to drive business value and increase productivity: Analytics Measurement-comparing past results Reporting Data sharing • BI has a positive impact on the Enterprise Development Process/Enterprise Productivity.
- 14. REFERENCE • http://search.ebscohost.com/login.aspx?direct=true&db=lxh&AN=92717627&site= ehost-live • http://www.toddwestmedia.com/594/the-importance-of-business-intelligence-in- your- organization.html • https://en.wikipedia.org/wiki/Business_intelligence
- 15. THANK YOU
Editor's Notes
- Business intelligence (BI) is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes. BI technologies are capable of handling large amounts of unstructured data to help identify, develop and otherwise create new strategic business opportunities. The goal of BI is to allow for the easy interpretation of these large volumes of data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability. BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. BI can be used to support a wide range of business decisions ranging from operational to strategic. Basic operating decisions include product positioning or pricing. Strategic business decisions include priorities, goals and directions at the broadest level. In all cases, BI is most effective when it combines data derived from the market in which a company operates (external data) with data from company sources internal to the business such as financial and operations data (internal data). When combined external and internal data can provide a more complete picture which, in effect, creates an "intelligence" that cannot be derived by any singular set of data. Advantages of investing in business intelligence software and skilled personnel are it will boost the ability to analyze the current consumer buying trends. Once you understand what your consumers are buying, you can use this information to develop products that match the current consumption trends and consequently improve your profitability since you will be able to attract valuable customers. Organizations can even improve their control over various important processes. Business intelligence software will improve the visibility of these processes and make it possible to identify any areas that need improvement. Instead of skimming through hundreds of pages in your detailed periodic reports to assess the performance of your organization’s processes, one can save time and improve productivity by having skilled intelligence analysts using the software. Another important reason why an organization needs to invest in an effective business intelligence system is because such a system can improve efficiency within the organization and, as a result, increase productivity. Business intelligence can be used to share information across different departments in the organization. This will save time on reporting processes and analytics. This ease in information sharing is likely to reduce duplication of roles/duties within the organization and improve the accuracy and usefulness of the data generated by different departments. Measurement – program that creates a hierarchy of performance metrics and benchmarking that informs business leaders about progress towards business goals (business process management). Analytics – program that builds quantitative processes for a business to arrive at optimal decisions and to perform business knowledge discovery. Frequently involves: data mining, process mining, statistical analysis, predictive analytics, predictive modelling, business process modeling, data lineage, complex event processing and prescriptive analytics. Reporting/enterprise reporting – program that builds infrastructure for strategic reporting to serve the strategic management of a business, not operational reporting. Frequently involves data visualization, executive information system and OLAP. Collaboration/collaboration platform – program that gets different areas (both inside and outside the business) to work together through data sharing and electronic data interchange. Knowledge management – program to make the company data-driven through strategies and practices to identify, create, represent, distribute, and enable adoption of insights and experiences that are true business knowledge. Knowledge management leads to learning management and regulatory compliance. Business intelligence can also provide a pro-active approach, such as alert functionality that immediately notifies the end-user if certain conditions are met. If some business metric exceeds a pre-defined threshold, the metric will be highlighted in standard reports, and the business analyst may be alerted via e-mail or another monitoring service. This end-to-end process requires data governance, which should be handled by the expert. Thus we can say that BI has a greater impact on the Enterprise Development Process. Detailed analysis is done using quantitative approach and collecting primary data. Thus relation between BI technology and Enterprise Productivity is quantified.
- This paper focuses on examining the impact of Business Intelligence on the Enterprise Productivity. This project begins with the review of existing literature available, which provides an insight into the research topic and clarifies many important aspects related to the subject. A quantitative method is used for this research project to investigate the technology and its subsequent impact on productivity of an Enterprise. The data was collected through a questionnaire and later analyzed using the data analysis through MS Excel 2010. And thus the result quantify the impact of BI on Enterprise Productivity.
- 22 large 24 small 15 medium
- 55 use BI 6 dont
- 3not 3less 10moderate 20 sat 25 high 7 no 54 yes
- 28 highly satisfied 10 satisfied 17 moderate 3 less satisfied 3 not satisfied
- All examples of BI software can be deployed across various business functions. Enterprise data warehouses, for example, and predictive analytic tools can potentially support any business function of an organisation. Other software may have a stronger subject-oriented focus in terms of being purpose-built for particular business functions (e.g. market analysis and sales forecasting, budgeting, corporate performance management, or HR analytics). Accordingly, we also expect large variations in terms of scope of BI business functionality supported with BI tools. BI solution scope is positively related to the quality of managerial decision making. Better management of BI is expected to have two effects on BI solutions scope. Firstly, a direct effect insofar as it will result in higher project success rates and a more holistic approach towards generic BI functionality; secondly, successful BI management will increase the trust in BI resulting in higher diffusion of BI applications across various business functions. We therefore conclude: BI management quality is positively related to BI scope. Thus the effect of BI on the quality of managerial decision making is mediated by the scope of the BI solution.
- While we did not investigate the resources that drive BI management quality directly, we were able to conclude that organisations which have resources to enable superior BI management will also realize more benefits of BI solutions. Important implications for practice include that proper management of BI is important for data quality and/or information quality, for the diffusion of BI and eventually the benefits of BI. Furthermore, managing data to ensure correctness, consistency, completeness, transparency and therefore trust in data is an important pre-requisite to achieve high levels of information quality, but to excel on the latter, proper tools are required to easily access only relevant and current information. Rolling out large scale BI solutions may result in benefits; but it is not primarily quantity that matters, it is (data and esp. information) quality.
- Business intelligence can be applied to the following business purposes, in order to drive business value and increase productivity: Measurement – program that creates a hierarchy of performance metrics and benchmarking that informs business leaders about progress towards business goals (business process management). Analytics – program that builds quantitative processes for a business to arrive at optimal decisions and to perform business knowledge discovery. Frequently involves: data mining, process mining, statistical analysis, predictive analytics, predictive modelling, business process modeling, data lineage, complex event processing and prescriptive analytics. Reporting/enterprise reporting – program that builds infrastructure for strategic reporting to serve the strategic management of a business, not operational reporting. Frequently involves data visualization, executive information system and OLAP. Collaboration/collaboration platform – program that gets different areas (both inside and outside the business) to work together through data sharing and electronic data interchange. Knowledge management – program to make the company data-driven through strategies and practices to identify, create, represent, distribute, and enable adoption of insights and experiences that are true business knowledge. Knowledge management leads to learning management and regulatory compliance. Business intelligence can also provide a pro-active approach, such as alert functionality that immediately notifies the end-user if certain conditions are met. If some business metric exceeds a pre-defined threshold, the metric will be highlighted in standard reports, and the business analyst may be alerted via e-mail or another monitoring service. This end-to-end process requires data governance, which should be handled by the expert. Thus we can say that BI has a greater impact on the Enterprise Development Process. Detailed analysis is done using quantitative approach and collecting primary data. Thus relation between BI technology and Enterprise Productivity is quantified.