According to the Project Management Institute, Agile methodologies have become the gold standard for IT projects. 40% of organizations report using it most of the time. When companies just beginning to incorporate Agile are included that number jumps to 71%. These companies are responding to the sizeable increase in performance realized from Agile-guided projects, which are 28% more successful than those developed with more traditional methodologies.
The benefits of Agile aren’t limited to IT. Experts are starting to incorporate Agile ideology into other highly technical domains, most prominently business intelligence.
Agile methodologies have the potential to drive dynamic, responsive business intelligence processes.
What are the Core Values of Agile?
Agile sees a lot of use in software development, but its core principles have wide-ranging applicability. Consider the primary Agile characteristics:
- Early, frequent delivery of usable products
- Openness to change when doing so provides competitive advantage
- Working solutions as a measure of progress
- Sustainable development
- Quality over quantity
- Efficiency in planning and execution
- Communication at all levels
At heart, Agile is about providing outstanding customer service and quality in as efficient and sustainable a manner as possible.
That has a lot of appeal for domains which can otherwise get bogged down in obscure details.
Business intelligence is one such field. It requires both technical skill and business savvy, and sometimes striking a balance between the two threatens to derail a promising project.
Challenges to Business Intelligence Projects
The term “business intelligence” covers a lot of ground.
It’s applied to a wide spectrum of techniques aimed at giving leaders the information they need to make logically sound, data-driven business decisions.
This includes finding inefficiencies and workarounds for them, cutting costs, increasing profit margins, and highlighting opportunities in time to act on them.
As might be expected from such an ambitious goal, business intelligence projects can have erratic success rates.
There are so many moving parts that one misstep potentially jeopardizes the entire project. Some of the most common reasons BI initiatives fail:
- Data sources are insufficient or inaccurate
- The final tool doesn’t meet the needs of users
- Products take so long to create that they’re already outdated on release
- Poor user experience ratings
- Mismatched team schedules and technical philosophies
What's the Best Methodology for Business Intelligence?
Taking Agile methodologies and incorporating them into BI projects makes it possible to mitigate or even avoid these problems altogether.
For instance, following the discovery process is a good way to create a comprehensive requirements list.
Gather all stakeholders together and find out what data they want or need on an ongoing basis. Look for overlapping needs as well as outliers.
Prioritize requirements as a group. Doing so makes the process transparent and reduces the risk of one category of stakeholders feeling minimized (which affects adoption rates).
Short, iterative sprints are excellent for breaking up obscure technical problems. Emphasize creating something that can be used now and build on that.
Provide additional workable tools, processes, or data source at the end of each sprint. Think smaller in size but higher in quality for sprint scope.
Something that may work when stakeholders are skeptical: organize and prioritize projects by place in the business process to allow progress to build momentum.
As people see the value of Agile, they can more confidently embrace its methodologies.
One of Agile’s greatest strengths is regular feedback. Maintain an open channel of communication with those who will be using the project.
Welcome feedback and questions as a way to provide better data, and incorporate changes as they’re needed. Focus on user satisfaction as a measure of success.
Speaking of measuring success, the continual quality assurance process Agile recommends will keep business intelligence resources in top conditions.
Test systems throughout the development cycle to spot problems early, when they’re easiest to fix.
Schedule specific “source updating and validating” sprints at regular periods to eliminate the threat of using outdated data.
Aggressively seek out weaknesses to fix them as soon as possible. Tools that don’t work don’t get used, so proactive testing and repair protects the original investment.
Bending the Rules
A final word of caution: don’t get so dedicated to Agile that the business intelligence project suffers.
For example, many companies spend longer in the “discovery phase” than software developers might because business intelligence requirements tend to be highly complex.
Others have to go back over a testing phase to iron out a tricky component. That’s okay- if a certain part of the project needs more time, give it more time.
At the end of the day Agile is about results, not rules. Adopt the Agile concepts that offer an advantage and don’t stress over those that don’t apply.
There is more powerful business intelligence software on the market than ever, but all those incoming data streams can be overwhelming. Request a free consultation to find out how Concepta can organize all your business intelligence into an intuitive, customizable dashboard.