Each day during FICO World 2013, we’re surveying attendees. The theme of yesterday’s survey was “Implementing Analytics”—quite fitting on the day that Kenneth Cukier of The Economist gave a keynote address on the “datafying” of society and the rapid growth of analytics. (View responses from the previous day’s Big Data survey.)
We began the FICO World survey by asking: “How quickly can you change your decision-making strategies and systems to incorporate a new analytic model or a new insight about your customers?”
The most common answers by respondents, who primarily work in banking, were “a month or less” and “up to three months,” both receiving 26% of responses. This was followed by “up to six months” (20%), “up to a year” (13%), “a week or less” (8%) and “more than a year” (6%).
Clearly, those who want to incorporate new analytic insights into decision strategies felt they could do so rather quickly. Some 60% said they could do so in 90 days or less.
Our second survey question was very simple: “Do you plan to use any cloud-based analytic software within the next 12-24 months?” Nearly 1/3 said yes (32.5%), while the rest (67.5%) said no.
We expect the pendulum will shift toward greater adoption of cloud-based analytics—and soon. Indeed among recent analyst projections, industry statistics, expert commentary and media coverage, the general consensus is that cloud computing will grow significantly in the near future. Perhaps we should ask the same question of FICO World 2014 attendees to see if responses change.
For our third and final survey question, we asked: “What is typically the biggest challenge to implementing analytic projects at your company?"
The top answer was “limited bandwidth of our IT team” (48%), followed by “limited bandwidth of our analytic experts” (21%), “cost” (18%), and “concerns about data security and privacy” (13%).
These responses are somewhat surprising. Despite noise in the media and elsewhere about an emerging analytic talent shortage, only about 1 in 5 respondents said the bandwidth of their analytic teams is the main limitation to implementing analytic projects. Limited IT resources appear to be the real culprit.
