This is a multi-post thread. Big Data/AI/Data Science (BAD) projects have been and will continue to have management attention. That's great because they are typically complex, expensive, require multiple skill sets, and involve multiple parts of the organization.
As we move through the third quarter of 2022 though, all projects are being scrutinized and re-evaluated. That great idea that provided a 6% return won't look so good if the cost of money is 10%.
If you're a Director or head up a BAD team it may be time to consider how or if you're going to defend your projects. Why was the project approved? Did it promise unique results that no other method offered? Did it reduce organization risk, or was it to find out a causal relationship?
Our next post will discuss how the executive team may be reassessing BAD projects.
If you'd like to read more BAD Project Blog posts you can find them at www.ekalore.com/bad-project-blog If you'd like to compare notes with an industry veteran (Free and Confidential!) www.ekalore.com/contact
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