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Recent data from industry analyst firm IDC reveals what may seem, on the surface, to be a relatively minor issue – the use of spreadsheets in organizations as a mechanism for data preparation. But what IDC discovered is that advanced spreadsheet users waste eight hours a week doing repetitive data preparation tasks. This productivity loss costs U.S. companies a staggering $60 billion annually.
This is just one of the insights we gained from this research, which you can find in The State of Self-Service Data Preparation and Analysis Using Spreadsheets. The report, based on a comprehensive survey of 500-plus individuals performing business and data functions across a variety of sectors, revealed to us the dramatic cost of repeating work performed in spreadsheets as organizations seek to harness vast and disparate data sources for business insights. These results also point directly to not only the productivity gains possible with new types of automated, self-service data solutions, but the level of analytic sophistication that is achievable with better tools, and more time available for analysis instead of mundane data preparation.
According to IDC, there are 21 million advanced spreadsheet users worldwide, 5 million of whom are in the U.S. Survey results showed us that:
On average, users spend 26 hours per week working in spreadsheets – 6 billion hours each year in the U.S. alone
Up to 8 hours of this work per week in spreadsheets is used to repeat efforts due to refreshed data, representing 1.3 billion hours of duplicate work in the U.S.
With each user wasting $12,000 per year duplicating effort, productivity loss costs $60B annually just in the U.S.
More than 80% of respondents report using the copy/paste function as the primary way to get data into spreadsheets, significantly increasing chances of human error
Nearly 50% disagree that analytics performed in spreadsheets are controlled or governed
Spreadsheets are ideal for financial analysis and containing lists of data, and even for one-off and minor data preparation and analysis tasks. But using a spreadsheet tool like Excel to cleanse, standardize, blend and ultimately analyze multiple data sources is equivalent to trying to put a square peg in a round hole. Businesses today are increasingly looking to data to drive decision-making in every facet of the organization. As data becomes more democratized across enterprises, business users need to conduct advanced analysis without the assistance of IT. They naturally turn to spreadsheets because it’s what they are familiar with, but leaning on spreadsheets for complex analytics is compromising the integrity of the process and the output.
Cleansing and combining data is the foundation of an effective analytics process – the necessary first step to getting to higher value analytics like descriptive, spatial, predictive, and prescriptive. Spending less time on manual processes means more time for gaining business critical insights. At Alteryx, we’re working to get our customers off on the right foot on the analytics continuum – and, free them up for the type of work that transforms their organizations!