According to NCC’s survey, which interviewed 68 key IT decision makers in the UK, only 13% of respondents felt they had achieved their BI objectives, while 22% thought their BI performance was lower than expected.
The survey, done on behalf of Californian applications infrastructure firm Sybase, also revealed some interesting drivers for BI adoption with 85% of respondents looking to BI to improve the quality of their decision making, while 66% cited improvements in business performance measures. 56% indicated data accuracy and integrity.
The survey also found that the lead time for companies adopting BI technology and going live with a production system is less than one year. Almost three quarters of companies surveyed said they had implemented BI in the last five years.
Once companies got their BI systems operational they cited lack of data availability (21%) and slow system performance (21%) as hindrances. Companies were also strapped for time and adequate IT resources, agreeing generally that the process of querying and analyzing data was slow and painful.
NCC’s survey also shows that BI systems are having to work with increasing data volumes. The average data warehouse among the respondents surveyed was 3.7 terabytes of raw data – with a respondent range of 0.1 to 30 terabytes. But half of respondents expected their current data capacity to double in the near future.
Looking ahead, 54% of respondents are thinking of aiming BI at more functional areas. Meanwhile 31% of firms surveyed, particularly small and medium sized businesses, were keeping an especially close eye on keeping costs down to a manageable level.
The research reveals that the deployment of BI might be a panacea of management decision-making, but like most process changes, cultural issues around deployment can be a significant barrier, said Stefan Foster, managing director of Manchester-based NCC.
Foster also warned companies not to overly focus on technical issues at the expense of getting the cultural issues right first.
Deployment problems occur when the wrong data is collected, when the wrong questions are asked, and when staff are unsure of what they want from the system, or are wary of using it.
