How ‘Missing’ Data and Other Inefficiencies Cost Companies Millions

Intro: While it may sound ironic, data professionals apparently spend relatively little time actually analyzing data, according to a recent survey from Alteryx. The accompanying report, titled “The State of Data Discovery and Cataloging,” reveals that process-driven duties such as data governance and description take up a major portion of the day for these employees. They also spend a great deal of time unsuccessfully searching for and preparing data. What’s worse, they often end up building data sets that already exist, i.e., “reinventing the wheel.” More than 400 North American and European professionals who work with data took part in the research, which was conducted by IDC. This slide show presents highlights of the survey, with charts and graphics provided courtesy of Alteryx and IDC.

When asked to rank the top data discovery business drivers, 82 percent of survey respondents cited operations/efficiency benefits. This was followed by policy compliance (as cited by 81 percent of respondents), risk reduction (80 percent), regulatory compliance (78 percent) and increased revenues (77 percent).

Data professionals account for just over one-third of every organization’s workforce. One-fifth of enterprise employees today say they are data analysts, and 14 percent said they are data managers.

Alteryx reports that 78 percent of data professionals work more than 40 hours a week. In fact, 51 percent work at least 50 hours per week.

Data professionals spend only 60 percent of their day “getting to insight” about data. They spend the rest of their time governing, collaborating upon and describing data.

Only 27 percent of the “getting to insight” time is spent actually analyzing data. The rest of this time is devoted to searching for data (37 percent) and preparing it (36 percent).

Data professionals “waste” 14 hours of their week due to an inability to find, protect or prepare data. Alteryx predicts that this will only increase in the future, as data volume and variety grow and “data and information assets will be harder to find.”

In addition to data search/protection/preparation problems, data professionals waste hours of their week building information assets that already exist. To avoid this, organizations must store knowledge of how and where data is used—and by whom, i.e., data cataloging.

U.S. organizations lose on average $103 million a year due to the described data-related work inefficiencies. Breaking this down, the losses amount to $1.7 million per year for every 100 employees.