When it comes to the cost of a BI deployment, it’s not the software that will get you; it’s the miscellany--the miscellaneous integration work, in particular.
Forrester analyst Boris Evelson, who focuses on application development and delivery, recently explored how to estimate the cost of a BI deployment. His piece made me curious, so I did a bit more reading on the topic.
Software licenses are often a big chunk of any IT initiative, but when it comes to BI, the license fees are often “a red herring,” according to Elad Israeli, co-founder of SiSense, a Big Data analytics platform company that recently made CIO.com’s “10 Hot Big Data Startups to Watch” list.
“This may be a little hard to believe, but the proof is found in open source,” Israeli wrote. “Open source BI is free, and there’s no shortage of choices if you’re dead set on getting open source software. But none of these free options are as popular as established non-open (paid) BI tools from for-profit vendors, even though they’ve been around for as long or longer than the paid options. If the software licensing were the most costly element of BI implementation, it would follow that open source vendors would be far more prominent.”
As additional proof, he points out that major BI vendors will “easily negotiate” volume discounts for licenses.
“Pay attention to software costs, but there are hidden costs associated with most BI solutions,” he warned. "If you must compare the cost per license, factor in additional systemic costs as well.”
These systemic costs are what Evelson addressed in his post, and not surprisingly, many relate to integration, including:
That doesn’t mean you shouldn’t worry too much about the software package you choose: One variation in the integration costs will be the BI software vendor you choose.
A 2012 BI implementation report issued by IT research firm Gartner ranks vendors based on average integration scores, product ease of development and product quality. The color of the dot on the chart represents whether the product’s integration cost is below average (blue) or above average (orange). IBM Cognos 8, Microsoft and Quiterian ranked well below average, while Tibco Spotfire, Prognoz and Alteryx hold the biggest dots for above-average integration costs.
Evelson applied the 80-20 rule in a previous post about BI costs, writing that you should anticipate the initial design and build of the data integration to be about 80 percent of your start-up costs, compared with the reporting and analytics, which should be about 20 percent.
It makes sense that integration would be a significant cost for any BI project. After all, you’re trying to bring in the relevant data from systems designed for other purposes.
When you look at ongoing costs, though, the roles reverse, making data integration 20 percent of the costs versus reporting and analytics.
Israeli suggests a few options for lowering your costs, including, if possible, using a single commodity box and building an architecture that will easily scale. According to the post, too often, companies fall prey to the Goldilocks Syndrome, and build either too small or too large.
“Buying more software or hardware on an as-needed basis is cheap compared to the cost of rebuilding the entire system from scratch periodically,” he writes.
That may explain why companies continue to report a low adoption rate for BI. The last BI adoption survey by BI Scorecard.com found that 2012 adoption was about 24 percent of all employees, even though respondents on average said 54 percent of employees within their organizations could potentially use or consume BI.