Public sector: Complex data analysis an 'important influence' in decision-making process

Research from Accenture has this week revealed marked differences in how public and private sector management view complex data analysis, with those in the public sector more likely to use analytics in the decision making process.

According to the report, which identified weak analytics capabilities were hindering both private and public sector decision-making abilities, senior public sector respondents scored analytics 3.7 out of 5, where 5 was 'very important' and 1 equalled 'not at all important'.

This compared to the 3.1 scored by respondents from the private sector.

Figures from the survey revealed public sector senior management believe they have the 'cleanest' data in terms of accuracy, completeness and consistency, with these respondents rating each of the three areas of data cleanliness a 3.6 out of 5, on average, where 5 indicates data that is very clean and 1 indicates data that is not at all clean. Respondents at private sector organizations rated their data an average of 3.4 for consistency and 3.2 for accuracy. Accenture hypothesizes this may provide an answer to why the public sector is more likely than the private sector to use complex data analysis to inform its decisions.

Despite a broad acknowledgement of the importance of analytics, Accenture's report revealed gaping holes in its use. Over 600 public and private sector senior managers from the United States and the United Kingdom & Ireland took part in the survey, and over 50% admitting their organisations were 'structured in a way that prevents data and analytical talent from generating enterprise-wide insight.'

Furthermore, over half said they have 'more opportunities to use analytics to improve the business than they have analytical resources to exploit them,' and 13% of UK & Ireland respondents admitted their organisations did not have any analytics-dedicated professionals.

'While there are many tools that enable organizations to examine historical data, what's needed is the ability to properly identify and analyze the data and gain the insight that enables one to make better decisions,' said Dave Rich, managing director of the Accenture Analytics Group. 'Organizations that fail to tackle the issues around data, technology and analytics talent will lose out to the high-performing 10 percent who have leveraged predictive analytics to become more agile and gain competitive advantage.'

'This is a huge opportunity that organizations are failing to harness,' said Rich. 'The need for speed in decision-making is a key competitive differentiator, and lacking the insight into customers' preferences means mounting an expensive come-from-behind response. During previous downturns, companies that thrived used data-derived insights made by informed decision makers to produce lasting competitive advantage. We believe that predictive analytics will be the difference between the winners and losers in the next economic cycle.'