Excerpt from the Designed Analytics Report: “Innovating With the Cloud: The Starting Point”.

Just like we did with every other technology that we have ever leveraged, we are looking at cloud technologies from the same siloed lens. IT professionals claim to have generated innovation by migrating to the cloud, data science teams claim that they have generated innovation by building data science solutions in the cloud. The fact is, while these teams may have found a more efficient way, in the cloud, they may not have innovated. We touched upon this when we discussed the three levels of efficiency, transformation and innovation in Chapter 2. Let us review another example to understand this better.

A data science team was developing a real-time sentiment analysis model for a social media website leveraging on-premises resources. Now the team is leveraging cloud infrastructure for the same. The cloud infrastructure definitely provides significant improvements over the constrained, on-premises infrastructure. But if you revisit the three levels in the previous chapter, this transition is not yet innovative.

Let us revisit our data science team example that we highlighted in the beginning of this chapter. As stated, while transitioning to the cloud-based development provides significant improvements over the constrained, on-premises infrastructure, this transition is not yet innovation. However, it is not difficult to extrapolate the solution by leveraging cloud technology to generate innovation. And for that, we will need to break the siloed view.

If we pick up our sentiment analysis example again, we can leverage it to understand the “extrapolation” approach better. The same analytics methodology, leveraging the three layers of cloud-based impact that we discussed in the previous chapter, can be extrapolated into an innovative solution.

Efficiency:

Move the data science and data pipeline workload for sentiment analysis to the cloud. Powerful VMs, on-demand. Run time reduces significantly.

Transformation:

Leverage data based service offerings and analytics and AI services offered by the service provider. Changes the way sentiment analysis is done. But the capability does not change at its core.

Innovation

Streaming data is now being captured leveraging cloud services, allowing the team to develop an algorithm that can send near-real time personalization SMSs to those visiting the stores, leveraging their store activity and sentiment analysis.

With this understanding of how cloud and innovation intertwine, we are now ready to understand how all of these concepts we have discussed come together to create innovation across all levels of the enterprise and help build a truly innovation-driven organization.