Approaching Business Intelligence (BI) not only in the sense of infrastructure, but also in view of competence, processes and organizational aspects remains a hot topic in 2010. Therefore, we review the top five misconceptions around Business Intelligence (BI).
- BI is just reporting
- BI is a software product
- BI is an IT issue
- A BI software is my BI strategy
- Implementing BI is a one-time activity
1) BI is just reporting
Many times BI is confused with providing some reports. And while the definition of BI from Gartner tries to correct this misconception, the term is unfamiliar to most business users and is not really tangible enough to give a real feeling for what is meant by BI.
Business Intelligence is “…an umbrella term that describes a broad range of applications, technologies and methodologies that support a user’s access to and analysis of information for making decisions and managing performance.” (Gartner, 2008)
Here are some examples of what BI is really all about:
Automobile parts retailer:
- the types of automobiles that are located in a specific geographical region to determine where new stores should be located for the best revenue potential.
- based on the types of parts most bought in the past determine what parts should be stocked in the store to provide the highest store sales, but also respond “yes, we have that part” when customers come to the store.
Combining demographic, policy, and sales commission to determine:
- the profile of customers that buy and renew certain types of policies year-on-year.
- the best commission scheme to ensure brokers sell policies that the customer will not cancel.
- how to maximize the casinos’ per person revenue through combining gambling and hotel room prices.
- what incentives to give different levels of gamblers so that they come more often to the casino.
- how to design the best possible casino layout to increase the time customers spend at each slot machine and increase the per slot machine revenue.
BI is more than just reporting. It is collecting data, transforming it from raw, unstructured data to business-use-ready data, deploying it, and then using it in the business for decision-making and management.
BI relies heavily on the use of data: historical data, predictive data, forecasted data, and descriptive data in structured and unstructured formats. The data is collected from a variety of input sources, analyzed to address specific business topics using many different analytical and reporting techniques: spreadsheets, ad hoc reports, performance management, dashboard, forecasting. Finally, the information is fed into the business process through various types of media – reports, systems, automation, web pages – to support decision making and management.
2) BI is a software product
The second misconception regarding BI is that it is a single BI tool. For example, SAP Netweaver Business Warehouse (SAP BW) is the name of the Business Intelligence, analytical, reporting and Data Warehousing solution produced by SAP AG. Therefore, many SAP customers consider that SAP BW represents their complete BI strategy. In fact, there is no one standard software solution for providing intelligence across an entire organization.
In 2008 Queisser, Miller, and Göttsche conducted a global study on the use of software in the decision-making process. There were 529 respondents from 50 countries and 30 industries. In the study, 90% of the respondents indicated that their organization used business intelligence software from five different software vendors. Furthermore, they used a wide selection of software tools, including spreadsheets, reports, analytics, performance management, and ad hoc queries.
The strategic use of BI is about using data and information in decision-making and management to have positive financial benefits for an organization. When BI is deployed throughout an organization, it can compel an organization to the top of the market space, increase revenues, help to save or eliminate costs, meet regulatory requirements or improve corporate governance. Finance, Production Processing, Sales & Marketing, Human Resource, Call Centers, and Suppliers are some of the functional areas where BI can be used to support business improvements.
To support the selection of needs that could be fulfilled by the promise of BI requires a selection of BI tools, technologies and solutions from a wide selection of vendors. (Figure 1)
Figure 1 BI Misconceptions and Promise
3) BI is an IT issue
Data used in the decision-making process comes from many different business functions and operational systems. Typically source data comes from core business systems, systems that track data about customer interactions, and sales, financial, supplier, or staff transactions. In addition, external demographic, statistical, financial, and competitive data may also be required. While an ERP may be the primary data source, not all data will come from a single source.
Bringing together data from different sources that were never meant to be used for any purpose other than what they originally stored, can present big issues with transforming the data. In addition, as the data is studied quality issues with the content of the data will be uncovered, even within one system. The business functions have to drive activities for ensuring the use of quality, consistent, and reliable data. Implementing remedies to data quality issues often requires a change in business operations, processes, and systems usage patterns or standards.
Furthermore, the knowledge and experience required in constructing reports and analysis requires not only an understanding of the data, but also thorough understanding of the business operations and business processes.
While IT can deploy the platforms, technologies, solutions, and tools and establish the key infrastructure used in BI, delivering intelligence to the business requires business ownership, sponsorship and execution.
4) A BI software is my BI strategy
There are a number of challenges in using BI tools and technologies in the decision-making process and in realizing business benefit.
- Collecting data. Data is not always available. The data is not consistent across departmental boundaries. There are quality issues with data.
- Analyzing data. Which techniques and methods are used to perform the analysis? Do people within the organization have the right skills and competencies for the analysis?
- Competency. The people that know about the data, understand it, and use it on a routine basis have to be identified and made available for the initiative. They have to participate in analyzing the business processes and must define the standards for the data.
- Politics. Often there are political challenges around establishing BI strategies. Initiatives compete with other programs and the operational business for access to people and other resources. Decisions have to be made about what comes first and what takes priority. There are issues around ownership; who owns what data, and can it be used in new and different ways.
- Credibility. The right people must know what exists (data, tools, etc), have access to the data, have the skills to apply it to the business process, and be able to trust the data enough to use it.
(Successfully) using BI –especially enterprise-wide — will take a willful act of management.
5) Implementing BI is a one-time activity
The effective use of BI in the decision making and management process can bring clear, measurable business value to organizations in every industry. It requires:
- the establishment of a technology platform and an information process for decision making and management
- continuous changes the way different organizational units share information,
- enforcement that ensures consistent terminology and definitions are used across different organizational units,
- and drive and foresight that ensures that the new information process is really used as part of the business process.
This is not a one-time activity. It is a continuous improvement process.
This article was first published on www.maxmetrics.com on 28-Sept-2010.
Queisser, T. D., Miller, G. J., Goettsche, T. (2008), Performance and organizational change through a business intelligence entity in public sector organizations: A global internet survey and case study, Heidelberg, Germany
Richardson, James (2008). The Basics of Business Intelligence (p. ) The Hague, The Netherlands, Gartner