To what extent can an organization's level of reliance on spreadsheets act as an indicator of their readiness to use AI?
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Senior Systems Analyst / Team Leader in Government3 months ago
An organization's reliance on spreadsheets CAN be a key indicator of its readiness for AI. However, relying heavily on spreadsheets may reveal a lack of integrated data systems and a culture still tied to manual processes. While spreadsheets have their uses, they can also highlight a gap in advanced analytics and real-time data processing capabilities essential for AI readiness. To transition successfully to AI, organizations need to cultivate a data-driven culture that values automation, strong data governance, and innovative thinking, moving away from spreadsheets towards the transformative power of AI insights. This journey involves not only technological upgrades but also a shift in mindset towards valuing data as a strategic asset, promoting collaboration, and continuously upskilling the workforce for AI challenges.Senior Data and Analytics Leader in Government3 months ago
In most organizations reliance on spreadsheets is a starting point, however they must build on this foundation, investing in data infrastructure and AI skills, for advanced analytics and automation capabilities. A company like Netflix, which moved from manual data tracking to sophisticated AI algorithms for recommendations, showcases this evolution. Initially, Netflix relied on user ratings in spreadsheets but soon realized the need for scalable AI to handle massive datasets and real-time analysis.
1. Data collection practices are in place and there is a historical, structured dataset available. As rudimentary as these practices and data might be, it is evidence that there is a need already well established within the organization, and it is being solved in a way that is more painful that it needs to be. Moreover, looking at the bright side, data structured in spreadsheets is not the hardest format to ingest into a data pipeline feeding a new AI solution.
2. The need to collect such data suggests there could be further analytical and reporting activities / requirements. Again, it points to a validated need, which is probably underserved by the current spreadsheet solution. However, I would also note that spreadsheet use also often means employees have become used to a great degree of freedom in how the record, analyze and present information, may have high expectations of customization, flexibility and ease of use out-of-the-box for an AI solution replacing it.
3. Suggests data collection, analysis and reporting practices are siloed and decentralized, or manually aggregated in multiple painful steps across BUs and functions; this may be positive or negative depending on the problem the AI solutions to be implemented aim to solve.
4. It also likely means there is very little legacy tech infrastructure to be replaced or integrated with, which could make the change management and new deployments of AI solutions a lesser burden.
I acknowledge that these signals are more validating a need than assessing tech readiness to adopt AI solutions, but awareness of the need, the pain points and limitations the current ‘system’ presents can create a strong to willingness to change / transform within the organization that should not be underestimated as a readiness factor when adopting new tech.
From a tech readiness perspective there’s is no denying that such an organization would not rank high from a tech readiness standpoint, and major business, process and people transformations will likely be required.
I’m highlighting these more optimistic signals because - in my experience - aligning stakeholders and working around legacy tech infrastructure are often and by far the biggest blockers to adopting new technologies and executing on the transformation required to leverage their value.