Big Data has gotten a lot of hype from the tech industry lately. But for businesses that have started implementing Big Data, are those investments paying off? Not yet, according to some recent research.
Big Data projects can be difficult and costly — and not just in terms of the technology involved, but also in the skilled staff needed to pull everything off. IT pros with Big Data expertise are tough to find, according to a recent survey from TEKsystems. The majority (81%) of IT managers agree there’s a shortage of workers with those skills and experience now.
Even companies that have those people on staff may not for long, as 56% of IT managers said it’s difficult to retain analytics pros because of the high demand for their skills.
All in all, the costs of Big Data implementations can add up — and only a small number organizations say they’re getting value in return, according to a survey from Bain & Co.
In a survey of 400 large organizations, just 4% said their business has achieved better decision making and stronger financial performance due to Big Data.
Those findings echo similar results in a survey conducted earlier this year by IDG Research Services and Kapow Software which found that only 23% of companies that had implemented Big Data said the project was a success.
Not time to abandon Big Data
But does that mean the Big Trend is over before it really began? Not so, according to those survey respondents.
Despite the lack of enthusiasm for the results so far, many companies plan to expand their Big Data efforts. The organizations surveyed by Bain & Co. plan to increase their Big Data spending by an average of 30% each year through the end of the decade.
And nearly all (85%) of the respondents in the IDG survey agreed that being able to analyze that mass of information would help the company make better business decisions.
The experts at Bain say there simply needs to be more time for companies to figure out how to get the most from Big Data. The companies that have been seeing good results all had three things in common:
- They have a clear analytics strategy and leadership,
- The company employs a dedicated data team, and
- High-quality data is being analyzed.
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