The prevalence of big data has fuelled a seemingly unquenchable desire of the business to derive more intelligent insights. As such, the research, published in an IDC InfoBrief entitled, The State of Self-Service Data Preparation and Analysis Using Spreadsheets in Europe, showed a growing demand for self-service data analytics by tech-savvy business users that want access to their data on their own terms. It is now being used by approximately 12 per cent of employees in Europe.
Research findings: Excel and other spreadsheet tools were never designed to handle the workload being asked of them
· There are 30 million advanced spreadsheet users worldwide, with 5.5 million of them in Europe
· On average, advanced spreadsheet users in Europe spend 28 hours per week working in spreadsheets
· In Europe this represents approximately 8 billion hours every year
· Advanced spreadsheet users represent about 12 percent of all enterprise employees in Europe
· Each advanced spreadsheet user can spend up to nine hours per week repeating effort as data sources are updated, wasting on average ˆ10,000 per year
· In Europe, this represents, on average, 2 billion hours of duplicate work, or ˆ55bn per year
IT has been looking for technology that can put data analytics (be it descriptive, spatial, predictive, prescriptive or cognitive) capabilities into the hands of business users, where the requirements and desires of analytic outcomes are best understood. Stand-alone spreadsheet tools such as Excel are not designed to prepare enterprise level data for analytics. This includes: Cleansing, standardisation, merging, joining, and augmentation capabilities in an intuitive business-user-friendly interface.
Stuart Wilson, SVP and GM of Europe, Alteryx, explained: “Organisations can improve self-service data preparation and analysis for fast and actionable results. Primarily, any organisation still mired in a sprawling spreadsheet situation should consider self-service data preparation software as an alternative to spreadsheets. Secondly, build a business case for self-service data preparation software based on productivity cost savings alone – ˆ10K/person/year in the EU. Then, expand the business case by highlighting additional benefits including better controls that provide higher levels of data and analysis integrity (trust, availability, security and compliance), and promote collaboration.”
The top three uses for spreadsheets include operations/forecast modelling (49%), data visualisation (44%) and ad-hoc data analysis (38%). But 95 percent of people preparing data for visualisation will fail to get the information desired from their business intelligence visualisation tools, forcing them back into spreadsheets for further analysis.
This is untenable – data is core to the ongoing digital transformation powering the economy. Yet data without integrity will not best support digital initiatives, allow consumer trust to grow, or enable high performing data-powered businesses.
As a result, a new breed of self-service data preparation and analytics software has emerged that puts the power of data discover, sharing, analytics and integrity testing into the hands of the business rather than technical experts, also enabling automation and operationalisation.
Mired in the past: Why aren’t more organisations switching away from stand-alone spreadsheets?
The top three concerns from the survey respondents relating to spreadsheet alternatives were:
- Lengthy implementation times
- Compatibility with other applications
- Potential costs of alternative solutions
“Organisations have been reluctant to move away from spreadsheets for data preparation and analytics, citing cost, implementation time, and compatibility with other applications as concerns when considering alternatives,” says Stewart Bond, director of Data Integration and Integrity Software Research at IDC. “Yet purpose built data preparation and analytic applications are more open now than ever before, easier to install and more intuitive – reducing both learning curves and implementation times. In addition, the automation and traceability value of purpose built software may outweigh the costs, and it may be more costly not to use an alternative when dealing with high impact data.”
