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Kumar Singh

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Talent Strategy For Analytics Capabilities

This article is an excerpt from the Designed Analytics Report, ” Top Five Focus Areas : Data and Analytics” . You can download the report here.

Highlights from the report:

https://videopress.com/v/Kvl3s3Jf?resizeToParent=true&cover=true&preloadContent=metadata&useAverageColor=true

Excerpt

You have seen in other focus areas that talent strategy is a critical element in helping realize your corporate strategy. Your people will eventually leverage every technology that you invest in. Hence, the success or failure of your every data and analytics initiative depends on your talent strategy. There are two broad strategies that you will need to formulate. One leverages the lens of initiatives focusing on building capabilities, whereas the other concentrates on sustaining those capabilities.

Though not starkly different, talent requirements and management will have certain unique nuances for each of the two lenses mentioned above.

The primary reason I say both requirements and management, is because we tend to focus too much on the type of talent needed and forget that we are required to retain that talent for a specific minimum duration as well.

Figure 7 below illustrates one possible way to start strategizing about talent requirement planning for new initiatives, across these three phases:

  • Identification
  • Pilot
  • Development and Go-live

The key is understanding the roles you will need for each phase. Then, obviously, for each role, you will be required to define the responsibilities. These will be based on the capabilities you need to develop so a comprehensive review of capabilities is necessary since you obviously don’t want to hire for each project.

The next set of talent that you want to build is the most critical in my opinion- analytically savvy people working within the processes.

Figure 8 below illustrates one possible way to start strategizing about talent requirement planning for sustained capability. A fundamental input for this strategy is the “analytics on the edge” focus discussed before. This also assumes that the solutions that have been built have been designed to be aligned with the “analytics on the edge” strategy.

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Kumar Singh

Kumar Singh is the founder of Designed Analytics LLC, which is focused on helping organizations explore how to leverage data and analytics to effectively compete, thrive and innovate. Kumar has over a decade of hands-on experience in supply chain and operations analytics. With over a decade of industry experience, he has worked across multiple industries, helping companies set up analytics centers of excellence. Post his industry experience, Kumar also did a stint in external consulting as a data science consultant with Boston Consulting Group (BCG). Kumar holds an MSc. in AI from Liverpool John Moores University, a Masters in Supply Chain from The Ross School of Business at The University of Michigan, Ann Arbor, an MBA in Operations Management from IIT Roorkee, India, and an undergraduate degree in Electrical engineering. Kumar is ASCM CPIM, CSCP, and CLTD certified and holds the PMP certification from PMI. He is also an AWS-certified Machine Learning Specialist and Microsoft certified in the Azure IoT developer specialty.

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