Weak Analytics Capabilities Hindering Decision-Making

February 8, 2010

Weak analytics capabilities – ranging from siloed data, outdated technology and a lack of analytical talent – are preventing organizations from gaining valuable insight that could lead to better business results.

The survey of 600 senior managers at more than 500 blue-chip organizations in the United States and the United Kingdom & Ireland (UK&I) found that more than half the respondents said their organizations are structured in a way that prevents data and analytical talent from generating enterprise-wide insight.

For instance, almost half of the respondents (45 percent) said data are housed in isolated parts of their organization, and more than half the respondents (52 percent) said that analytical talent is housed separately from the relevant data at their organization. In addition, nearly one-third (30 percent) of US respondents, and 13 percent of their UK&I counterparts, said that their organizations do not have any professionals dedicated to analytics.

Overall, four out of 10 respondents said that their current technological resources and systems greatly hinder the effective use of enterprise-wide analytics in their organizations. Additionally, half (51 percent) said they have more opportunities to use analytics to improve the business than they have analytical resources to exploit them. Respondents from companies in nearly every industry represented in the survey also acknowledged that they must improve the consistency, accuracy and completeness of their data before they can become more ambitious in terms of their analytics capabilities.

“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 adaptive ? and gain competitive advantage.”

Despite the apparent current lack of analytics capabilities, the companies surveyed are committed to developing these capabilities. For instance, over two-thirds of respondents (71 percent) said that their organization’s senior management is “totally” or “highly” committed to analytics and fact-based decision-making.

In addition, nearly half (46 percent) of respondents said that among the long-term goals of their senior management teams are applying analytics in useful areas of the business and becoming more analytical in decision-making styles and methods across their businesses. The most widespread long-term analytical priority among organizations surveyed is developing the capability to model and predict behavior, actions and decisions, cited by between two-thirds and three-quarters of respondents in each industry sector.

Nonetheless, the research revealed that senior managers currently fail to see fact- and data-driven analysis as critical when making key business decisions and instead rely heavily on ‘gut feel’ and ‘soft’ factors such as consultation with others, intuition and experience.

Further, some organizations are making analytics-based decisions using flawed data, as the survey identified issues related to the consistency, accuracy, completeness and format of company data applied to analytical decision-making. When rating each of these fundamental aspects of data quality on a scale of 1 to 5 (where 1 equals not at all clean and 5 equals extremely clean), the rating for each hardly rose above 3. For each of these aspects of data quality, US respondents rated the quality of their data lower than their UK&I counterparts rated the quality of their data.

The findings indicate that little has changed since 2008, when a previous Accenture survey found that 40 percent of business decisions were based on judgment rather than business analytics, often due to a lack of good data.

“Accenture’s findings reinforce a key challenge – and opportunity – that we face today: that businesses and government organizations are dealing with a flood of information that overwhelms the human ability to process. Decision-makers then revert to best guesses rather than making empirical decisions,” said Russ Cobb, VP of Alliances and Marketing at SAS. “But with predictive analytics, we can derive the critical insights from the data that will lead to optimal business outcomes.”

Along with the quality of corporate data, security issues are significantly limiting the more widespread and sophisticated use of business analytics. For instance, two-thirds (67 percent) of respondents overall said that data-security concerns are having at least a moderate impact in preventing their organizations from extending the use of data analysis and business intelligence, with respondents in the public sector more likely than their private-sector counterparts to cite this factor (80 percent vs. 65 percent).

Organizations are also failing to tap into one of the most innovative capabilities of analytics: the ability to predict future business events in order to act before the events occur. For example, the survey found that when it comes to examining market growth, only about one-third (36 percent) of respondents said their organizations use the predictive analytics function to a “great extent,” and more than one-fifth (22 percent) said they do not even use it to a moderate extent. Further, while some organizations do analyze data to predict what might happen in the future in terms of competitor activities, market trends, product/service development, risk management, financial/economic trends and skill requirements, many organizations are still using predictive analytics only to a minor extent, if at all.

“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.”