Business intelligence (BI) and analytic technologies continues to see rapid
growth in today's tight economy, driven by fierce competitive pressures. Also
fueling growth is the technologies' ability to improve decision-making,
identify new business opportunities, maximize cost savings, and detect
inefficient business processes.
BI is much more than a set of software tools. It describes a set of processes
and technologies for simplifying and enhancing the use of information within
an organization. In particular, BI provides a data foundation together with an
associated analytic environment that can support, underpin, and improve
decision-making capabilities in organizations.
Technology efforts must be underpinned by a BI strategy. A BI initiative
provides little strategic use unless it is driven by the objectives of the
organization. Before embarking on any type of BI initiative, organizations
must invest in defining a BI strategy that outlines how BI will help the
organization meet its strategic and operational business goals.
A multitude of factors influence the BI suite selection process. As part of
the selection process, organizations need to acknowledge that tools and
organizational needs are typically diverse.
Features and Benefits
- Understand Ovum's definition of BI and analytics and how it can play a
pivotal role in helping your organization to achieve better results.
- Understand what to look for and what questions to ask when implementing
and deploying a BI solution.
Key Questions Answered
- What are the functional layers of a BI suite?
- Who are the common BI users in an organization?
- What trends are affecting the BI market today?
Table of Contents
- Ovum view
- Key messages
- BUSINESS IMPACT
- Rationalizing and reducing operational costs
- Improving the customer management process
- Maximizing operational agility
- Enhancing business performance alignment across the enterprise
- Avoiding unnecessary risk exposure and ensuring adherence to regulatory
- SELECTION CRITERIA
- BI strategy comes before technology selection
- A range of factors affect the BI suite selection decision
- What type of analysis is needed?
- What number and type of users need supporting?
- How should BI be deployed?
- What data storage, integration, and latency requirements are needed?
- What level of integration with existing IT infrastructure is needed?
- Components of a BI suite
- Data management and data integration service
- Analysis service
- Application service
- Information access and interaction layer
- SOLUTION MATURITY
- A consolidating market landscape
- The cloud BI market is small but growing
- BI in a Big Data world
- The emergence of mobile BI
- Consultants and systems integrators have an important role to play
- DEPLOYMENT AND MANAGEMENT CONSIDERATIONS
- BI projects can be high risk, but also high reward
- Common barriers and pitfalls
- Running a BI initiative - best practice
- Building a business case
- Securing executive sponsorship
- Ensuring closer alignment of IT and business
- Deliver quickly, but keep the big picture in mind
- New mobile technology requires delivery rethink
- Train users effectively
- Recommendations for enterprises
- Look towards EPM for greater organizational alignment
- Analytics brings a higher yield of analysis
- Consider the implications of moving to operational BI
- Get the data foundation right
- A business intelligence competency center can lower TCO
- Consider alternative deployment models
- Recommendations for vendors
- Increase user interface usability efforts
- Continue on the path of integration and interoperability
- Verticalize BI product offerings
- Consider alternative pricing and licensing models
- Further reading
- Ovum Consulting
- Figure 1: Questions to ask when establishing BI suite requirements
- Figure 2: The functional layers of a BI suite