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Over the past decade or so, business intelligence (BI) has been adopted by major corporations and government entities around the world, delivering essential business information, advanced tools for analyzing complex business situations, and structured decision support techniques that have allowed enterprises to improve performance of their core business processes and create value for their stakeholders. Recent examples of BI usage to improve business results include:
- A leading energy services and engineering and construction firm invests over $1 million per
year in BI to improve planning, budgeting,
forecasting, and financial reporting.
- A leading financial services firm invests over $2 million per year in BI to build more effective customer
- A leading aerospace product manufacturer invests over $3 million per year in BI to manage
and improve its day-to-day
- A leading pharmaceutical company invests over $5 million per year in BI to ensure regulatory compliance, improve
productivity, and provide timely information to support management needs.
- A leading automotive company invests over $1 million per year in BI to improve its supply chain performance.
- A leading property and casualty insurer invests over $5 million per year in BI to deliver a unified data environment for planning, budgeting, cost allocation, forecasting, variance analysis and regulatory reporting.
As these examples attest, business intelligence is used in a wide range of industries for a variety of key business processes. With this as context, when we work with our clients to develop a BI strategy and business case, we are often asked to weigh in on their business intelligence budget and provide guidance based on what other companies are doing. Some of the factors we consider are detailed below.
As leading companies in a variety of industries have gained experience with business-driven business intelligence, they have come to appreciate the importance of: (a) having a suitable BI and data integration infrastructure that will meet their needs for a five to ten year horizon; and (b) deploying a focused BI team with suitable skills to effectively execute multiple BI projects over a period of years. With respect to BI infrastructure, the required level of investment is a function of factors such as:
- The scope of the BI initiative, where enterprise BI initiatives will require more robust
infrastructures than departmental initiatives;
- The volume of data that must be moved, integrated, managed, and made available for the intended
business uses of BI;
- The frequency with which the data must be updated and the amount of time available for doing
- The degree to which business intelligence is integrated with mission-critical IT applications
and the attendant reliability and availability requirements for the BI environment; and
- The number of business users of the BI environment and the frequency and types of uses, (e.g., complex modeling and optimization applications require more “horsepower” than straight reporting applications).
While having an appropriate infrastructure is critical to leveraging business intelligence to improve business performance, infrastructure alone will do little good if there is no corresponding investment in BI professionals to design and build the BI applications themselves. The typical positions found on enterprise business intelligence programs include:
- A program manager
- One or more project managers, depending on the business intelligence release strategy
- A data architect
- One or more data modelers
- One or more business analysts
- An ETL architect
- One or more ETL developers
- A DBA
- One or more report architects
- A test manager and one or more test analysts
- A user support/help desk specialist
The data regarding actual practice shows that leading companies in a wide range of industries deploy BI teams ranging from four or five people at the low end to teams numbering in the forties and up at the high end. In general, the larger teams are associated with enterprise business intelligence initiatives of large global businesses. Team size is also a function of factors such as:
- The competitive importance of moving quickly to deploy business intelligence;
- The number of BI projects to be undertaken simultaneously;
- The degree to which some of the typical positions can be combined;
- The desire to capture a return on investment more quickly; and
- The rapidity with which a given BI project must be completed.
Based on DecisionPath’s experience analyzing BI opportunities and requirements for large, complex companies, and based on our benchmarking of industry best practices, staffing levels, and budgets, our professional opinion is that many companies would be well-served to budget at least $1 million per year for business intelligence, and that companies often have enough BI opportunities to productively invest $2 million per year or more. When we work with clients to build a budget and business case, some of the key factors we consider include:
- Where a company stands with respect to a BI infrastructure, and thus how much it will need to
invest in IT hardware, software, and technical best practices to create a suitable, scalable BI
infrastructure that includes a development environment, a test and validation environment, and a
- Where a company stands with respect to BI and data integration logical and physical
architectures, and thus how much architecture work and systems engineering will be required;
- How many BI-driven business improvement opportunities (requirements) are in the BI portfolio
and the scope of those opportunities; and
- How much data must be integrated, how many sources must be touched, and the refresh rate and batch processing requirements.
All of these help shape the scope, pace, and composition of the business intelligence program, and thus they drive the budget. For BI budget development, the quality of analysis and the relevance of budget assumptions is enhanced by having BI subject-matter experts involved who can bring experienced judgment into the process. This ensures that practical considerations are adequately addressed and that proper expectations are created for whatever level of BI investment is approved.