Around 62 billion data and analytic work hours are lost annually worldwide – the equivalent to almost 100,000 human lifetimes, according to an Alteryx-commissioned IDC report.
The Data and Analytics in a Digital-First World study also revealed that 95 per cent of organisations are still being challenged by creating analytic outcomes from the terabytes of complex raw data piling up across the business.
As businesses strive to move from being data-hoarders to driving real insights by democratising analytics, the report reveals how complexities, constraints, skill gaps, and a lack of analytics automation are hurting productivity.
With that, businesses are now striving to move from being data-hoarders to driving real insights by democratising analytics.
Despite 70 per cent of organisations citing that they want to be more data-driven now, 95 per cent still struggle with operational challenges around data and analytics and 88 per cent continue to be hindered by legacy technologies.
Of the 78 million advanced spreadsheet users worldwide, data-native workers report they are losing 800 hours annually due to due to 61 percent of data activities still being completed in inefficient legacy spreadsheets
“While data and analytics power the future, data literacy continues to be a challenge for organisations globally,” said Stewart Bond, research director, data integration and data intelligence software, at IDC.
Data and analytics experience needs to be improved with 91 per cent of organisations reporting some area of skills gaps in advanced analytic skills and 44 per cent reporting that predictive, prescriptive and machine learning skills gaps exist in their business.
Among other key findings from the global study of data workers’ activities:
- A lack of analytics automation is harming data native productivity. Of the 61 per cent of data workers who perform activities in only spreadsheets, 27 per cent of their time is spent repeating the same or similar activity steps every time a data source has been updated or refreshed. The equivalent to on average seven hours per week.
- Data and analytics complexity illustrate the need for skills and technology improvements. For example, data natives process highly distributed, diverse, and dynamic data at scale from an average of four unique sources per analytic input and 6.6 million rows of data to deliver an average of four unique analytic assets for consumption.
- The data and analytics experience needs to be improved as 91 per cent of organisations report some area of skills gaps in data and analytics. Advanced analytic skills are at the top of the list with 44 per cent reporting predictive, prescriptive and machine learning skills gaps exist in their business
“Data workers now expect more of their time to be spent on complex data science and application development instead of more basic prep and analytics tasks, but skills constraints and insufficient tools hinder progress. To succeed, organisations need to prioritise the democratisation of data and analytics – putting the right tools in the right hands – with solutions that offer unified and automated data prep and analytic experiences,” Bond added.
Businesses are striving to work smarter by delivering value from data at the scale and speed of today’s digital-first world demands, increasingly seeking to remove complexities associated with creating analytic outcomes.
