ClusterSeven: AI isn’t magic, it too needs accurate data
Posted: 28 February 2019 | Author: Henry Umney | Source: ClusterSeven
Every so often we hear people sounding the death knell for spreadsheets. Most recently artificial intelligence (AI) and machine learning are being posed as the panacea for spreadsheet user-related woes in terms of facilitating data accuracy by protecting against human error. No one can refute the potential that AI offers for reducing the friction within business processes and stripping out costs, to deliver greater business efficiency and enhanced employee productivity.
However, for the foreseeable future, the spreadsheet is here to stay. For all the challenges that it presents to businesses, it is a readily available, ‘zero cost’, ‘go to’ tool for project management, complex business calculations, financial analysis, data manipulation and indeed for overall business management and strategic decision making. This is because spreadsheets offer institutions the flexibility and agility to continually adapt, change and enhance business processes – without the constraints presented by corporate IT systems.
This, of course, is not to underestimate the significant risk spreadsheets pose to the business, which largely emanates from the uncontrolled use of these applications. Often, the change controls applied to other IT applications are exempt in spreadsheet-based processes. This then compromises the accuracy and integrity of the data that resides in them and therefore the spreadsheet applications themselves.
With or without AI, the answer lies in recognizing the strategic benefit spreadsheets provide to the business and adopting best practices in their use. An enterprise-level model for end to end spreadsheet risk management, underpinned by technology, ensures visibility of the inventory spreadsheet applications being used, tiered for risk and protected for security, providing management with visibility of this activity. This approach is already proven.
AI isn’t a panacea, it’s success depends on good quality, well controlled and structured data at source.