Do you set a minimum estimated time to impact for the data projects that you will consider? For example, would you refuse any data project that is not expected to lead to impact within 3 years?

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Data & AI Practice Lead2 years ago

This question is highly context-dependent, and answers may vary based on specific circumstances. Here are my views on the matter:

My approach to setting a minimum estimated time to impact for data projects is to avoid rigid rules and instead prioritise flexibility. Each project is unique and may require a different timeline to realise its potential impact.

Quick wins can be essential for addressing immediate business needs or seizing opportunities in a dynamic market. These projects can provide results in a relatively short time frame, often within a few months.

However, longer-term strategic initiatives may take years to yield significant results, but they can have a more profound and lasting impact on the organization. The decision should be driven by the alignment of the project's objectives with the broader business strategy.

Several factors, including data availability, the urgency of the business context, resource constraints, and the organization's risk tolerance, should be considered when determining project timelines.

In summary, while it's valuable to have a general framework for evaluating project timelines, it's equally important to treat each project individually and adapt to its unique characteristics and the organization's specific needs and goals.

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