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Defining the BI Project

Project planning includes creating a project charter, which defines the project in terms of:

  • Goals and objectives
  • Scope (the expected project deliverable)
  • Risks
  • Constraints
  • Assumptions
  • Change-control procedures
  • Issues management procedures

The project charter is the agreement made between the business sponsor and the IT staff for developing the BI application. If any component of the project charter changes, the entire project has to be reevaluated and all project constraints have to be renegotiated.

Project Goals and Objectives

When defining a BI project, first address the goals and objectives. What is the reason for building this BI application? How much business pain (in hard currency) does that business problem, which the BI application is supposed to solve, currently cause? What are the strategic business drivers? Do the BI project objectives fall in line with the strategic business objectives, or is this someone's pet project?

Project objectives should be measurable statements, such as, "In order to increase market share by 10 percent next year, the sales department must have access to month-end sales data as well as pipeline data merged with prospect data within five business days after the close of the weekly accounting cycle." Project objectives must tie in with the expected ROI. The business representative will have to measure the effectiveness of the delivered BI application and report to the business sponsor whether the project was successful or not.

Project Scope

It is impossible to create valid estimates for a project without a solid understanding of the scope. Traditionally, scope has been measured by the number of functions the system will perform (function point analysis). On BI projects that is a sure way to underestimate effort, budget, and resources. BI applications are data-intensive, not function-intensive. Therefore, scope must be measured by the number of data elements that have to be extracted from the source systems, transformed and cleansed, and loaded into the BI target databases.

The main reason for concentrating on data rather than functions is that analyzing and preparing source data takes much longer than providing data access and enabling data analysis through reports and queries. The typical 80/20 rule usually applies: 80 percent effort for data and 20 percent effort for functionality.

Project Risks

Every project is subject to some risks—risks are unavoidable. Such risks could severely affect the project schedule as well as the project deliverables, depending on the likelihood that the risks will materialize and on the impact they would have on the project. Therefore, the risk assessment performed during Step 1, Business Case Assessment, must be reviewed and expanded if necessary. The project manager must identify triggers for each risk and incorporate a mitigation plan as well as a contingency plan into the project plan.

Triggers are situations that signal a potential, perhaps imminent materialization of a risk. For example, if management is reviewing the budget for the project for no apparent reason, this indicates a possible trigger for the risk of losing management support for your BI project.

The mitigation plan specifies what actions the project team can take to prevent the risk from materializing. Continuing with the example above, you could solicit support from your business sponsor and promote the BI initiative to other key executives in your organization to keep management's interest in the BI project. Should the project run into trouble, the risk of having it cancelled is mitigated or prevented.

The contingency plan specifies alternatives in case the risk does materialize. For example, if you lose management support for the BI project due to a long project schedule, plan to shorten the release cycles by delivering a smaller scope sooner. If you lose management support due to the business sponsor's departure from the organization, have an alternate sponsor ready to become the champion for the BI project.

Some common project risks include the following:

  • Lack of management commitment
  • Lost sponsor
  • Lack of business participation
  • Imposed, unrealistic schedule
  • Unrealistic scope for the schedule
  • Unrealistic expectations
  • Unrealistic budget
  • Untrained or unavailable staff
  • Constantly changing business priorities
  • Ineffective project management
  • Limited scalability

Project Constraints

All projects are subject to the same project constraints mentioned earlier: scope, effort (time), budget, and resources (capable and available people). In reality, there is a fifth constraint: quality. Although quality is a measure of how well the deliverables meet the requirements, it can also be considered a constraint that must be balanced with the other four constraints.

While everyone on the business side and in the IT department wants quality, rarely is the extra time given or taken to achieve it because quality and effort are polarized constraints. Higher quality requires more effort and thus more time to deliver. Since time factors drive most organizations, effort is their number one constraint (highest priority), followed by scope, budget, and resources (usually in that order); and quality gets pushed to the bottom of the heap (lowest priority), as illustrated in Table 3.1. BI project constraints should never be in this order.

Fortunately, organizations have full control over changing the priority of project constraints. To insist that time and scope be the top two constraints is acceptable only on projects that have requirements connected to government-imposed regulations. But in most of those cases, the operational systems (and operational reports) are the ones affected by government-imposed deadlines, rarely the downstream strategic decision-support applications. We strongly advise you to get quality out from the bottom of the heap and put scope there because scope can and will continually be expanded through future BI application releases. Table 3.2 shows our recommended order of project constraints.


An assumption is anything taken for granted; it is a supposition or a presumption. It is important to document assumptions because a wrong assumption could very quickly turn into a risk. Here is an example of how two assumptions on a project backfired.

Table 3.1: Typical Order of Project Constraints

Priority (Highest to Lowest)







Effort (time)






























Table 3.2: Recommended Order of Project Constraints

Priority (Highest to Lowest)

























Effort (time)












Assumption 1: "The vendor promises to deliver a new database server in May, and by the end of June the IT staff will install and test a new database management system (DBMS) product on that server. This allows plenty of time before the project deadline, which is September 30, the fiscal year-end."

Assumption 2: "Joe Bamberg will be the database administrator on the project because he is the only person in our organization who has that particular DBMS skill, which is needed for the project. He has already joined the project team."

Problems: On June 20 (one month late) the new server finally arrives, and on July 1 Joe Bamberg quits the organization. The new DBMS product does not get installed and tested on the new server until the end of September.

Impact: The project is delayed by three months at a budget overrun of $60,000 (much of it paid as consulting fees for the high-priced consultant who had to fill in for Joe Bamberg).

Important assumptions should have counterpart risks, in case the assumptions either turn out to be false or do not materialize, as in the example above. For each counterpart risk, identify triggers, a mitigation plan, and a contingency plan.

Change-Control Procedures

Traditional waterfall methodologies became so popular in part because the signed-off, phased development approach attempted to curb scope creep. The mental model was "Change is bad—business people must be held to their decisions." Since BI applications are supposed to be catalysts for improved decision making, the mental model must change to "Change is good—business people should refine and improve their decisions." However, uncontrolled change can still kill a project.

The solution is to manage the changes. Many organizations track their change requests by logging the date of the change request, the name of the requestor, the desired change, to whom it was assigned, and when it was implemented. That is a good practice, but tracking changes is not the same thing as managing them.

To manage a change, you need to start with a baseline—the agreement between the business sponsor and the IT staff, as documented in the project charter. Every change request, once logged, undergoes an impact analysis and a cost-benefit analysis to determine the effects of the change on the project. Changes, unless they are minute, always impact the three constraints of effort (time), scope, and quality. Some changes also impact the other two constraints (budget and resources). When one constraint changes, the remaining constraints will have to be renegotiated. Unfortunately, business managers and IT managers frequently put the project teams under unwarranted pressure to incorporate scope changes without slipping the schedule.


It is not rational to request a significant scope change to a carefully deliberated and agreed-upon project plan without adjusting any of the other constraints.

It is not rational because the business representative, the project manager, and the core team members who developed the plan together believed they could complete the project under the agreed-upon constraints. When the scope constraint changes, the plan is no longer doable without changes to some of the other constraints, namely effort (time), budget, resources, and quality, to absorb the impact of the scope change. Therefore, depending on how critical the change request is, the business representative has to decide whether to:

  • Cut back from the current scope by eliminating some of the originally requested data and functionality

  • Extend the deadline

  • Declare the requested change unfeasible at this time and postpone it

  • Incorporate the requested change in the next release

  • Eliminate complicated transformations, edit checking, and testing, which will impact the quality of the deliverable

Issues Management Procedures

Issues, whether related to business or technical concerns, always come up during projects. Similar to change requests, issues must be not only tracked but also managed. Every issue must be assigned to a person who has the responsibility for its resolution. Any activity regarding the issue must be dated and described on the issues log. At the end of the project, all issues must have a resolution, even if that resolution is a deferral of the issue to a future BI release. Table 3.3 shows an example of an issues log.

Some issues are minor and can be resolved without impact on the project. Other issues can turn into risks or change requests and have to be dealt with accordingly. Therefore, managing issues includes impact analysis and change control.

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