The recently released report by TDWI’s Wayne Eckerson is all about how the need among business intelligence (BI) teams to do "more with less" has significantly increased following the recession. We summarize the underlying points in the report.
One of the ways that BI teams have coped with shrinking budgets is via tactics. In the short-term, they have managed to cut costs without sacrificing quality or output by actions such as cutting low-priority projects, dismissing consultants working on them, and avoiding buying new products and expensive software upgrades. Successful negotiation of software maintenance contracts while relying on vendors for assistance has also lowered capital outlay.
In the longer term, Eckerson notes that BI has been focusing on efficiency and effectiveness to deliver a better ROI, for example by implementing self-service BI tools, consolidating spreadmarts and datamarts, and getting rid of redundant data, infrastructure, and staff.
Of course, tight or nonexistent budgets are the norm in many SMBs, which is why the recession hasn’t changed much in the dynamics of how they deliver BI solutions. They continue to choose low-cost offerings, such as open source tools, cloud solutions, and in-memory visualization products, which with SMBs representing a large growth in the BI market, is good news for BI vendors offering these types of products.
Finally, new technology is the next move taken by organizations finding themselves constrained by their budgets - companies are aggressively searching out new technologies to improve the efficiency and effectiveness of their BI operations. SMBs are jumping on new offerings to get a foot in the door, while established BI teams are replacing existing technology with next-gen capabilities.
Eckerson makes a few recommendations for doing more with less:
1. Empower users. Users want tools that empower them to create their own reports and rescue the BI team from report writing so that they can deliver added value within budget constraints.
2. Align with the business. With limited resources, it’s essential that BI teams are focused on projects of significant value. To do that, they need to work closely with the rest of the organization.
3. Work smart. When resources are tight, BI teams need to work more efficiently and effectively. They can do this by embracing existing tools instead of purchasing new ones, postponing expensive upgrades and making do with existing versions, and more.
4. Consolidate and negotiate. One method to cut costs is to negotiate new maintenance licenses with vendors and ask them to donate software to build prototypes and conduct proofs of concept for free. Another strategy is to consolidate data marts and BI tools to reduce overheads.
5. Explore new technology. Open source, cloud BI, visual, and discovery tools, plus data warehousing appliances all offer better functionality and performance for less money. These technologies are increasingly being adopted by small and midsize BI programs and on-the-ball, larger BI teams.
6. Tactics vs. strategy. BI teams should look for instant tactics to reduce costs without sacrificing output, such as those tactics with more or less immediate returns, as discussed earlier. Strategic initiatives could compromise any number of things, but in particular deployment of self-service BI tools, consolidation, implementation of new technologies and better management of scope and risk.
The bright side of the downturn is that BI teams are now ready to go with new processes, organizations, and technology which can deliver significant value to their organization and clients. With budgets being cut, most BI teams have been forced to focus on their efficiency drive by innovating and coming up with new ways to deliver projects. The recession has really tested the resilience of BI teams, as well as the ability of solution providers to adapt to their changing needs. This is partly why we've built Bime to be like it is - requiring no upfront cost, no maintenance and no technical expertise, this makes it lightweight and scalable, which in turn, makes data analysis faster, easier and cheaper - a perfect combination for those on a tight budget.