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Companies are seeing the promise of what cloud, data, analytics, and AI can do to transform their business, but many are struggling to realize the impact. Amongst the key challenges holding leaders back is the ability to access talent to fulfill their strategies. D&A talent – from solution architects to data engineers to business consultants – is hard to find and harder to retain. Meanwhile your executives are expecting results promised by your business case.

According to Forrester’s Business Technographics Data and Analytics Survey 2020,

“Nearly half (49%) of organizations are still at the beginner stage of their insights-driven business journey and only 60% of them have dedicated data, technical and insights staff available to teams across the organization to help them transform outcomes with data and insights”

Getting business results under these circumstances requires leaders to embrace new models and thinking for building D&A teams. In this webinar video, Our CEO, Shashank Garg and guest speaker, Forrester Research VP and Principal Analyst, Boris Evelson discuss tried and tested talent strategies to achieve success with D&A initiatives. Watch the video to understand:

  • Top challenges customers face when forming D&A teams
  • Strategies to deal with talent acquisition, development, and retention
  • Recommendations for strengthening your D&A talent strategy

Interesting Quotes from the Webinar

On Data Driven Businesses

“It was a few years ago when analysts such as myself and other economists predicted that insights driven businesses were going to grow 8 to 10 times, that’s not 8 or 10 percent faster, 8 to 10 times faster than the global economy, than industry averages, than competition. And today at Forrester, we absolutely are seeing this coming to fruition.”

On Central IT Teams

“If you fast-forward a few years, we know that central teams will struggle on the user engagement side and they will never be able to react to fast changes that are required to run modern businesses. You often see a huge sort of shadow IT coming up in the business unit. So you got central IT, you got shadow IT and then you know, they are doing anything and everything right from data wrangling to data ingestion to analytics. Not ideal!”

On AI and the Enterprise

“Artificial intelligence obviously is all over the place, we do not talk about any enterprise technology where AI is not taking a foothold. And while AI is helping us and helping enterprises get richer insights, deeper insights and further helping us democratize insights. AI requires some additional TLC, tender loving care in terms of building models, training the models and doing all of the model operations. So, yes, AI brings additional benefits but also requires additional care.”

On Competency Based Hiring

“We are saying that we don’t need a Snowflake or a Tableau developer, we need to hire for higher level competencies. So we need a data engineer, a cloud engineer, an analytics and data management professional who can go through these platforms and if I decide to switch, I don’t have to switch people, switching people is expensive. It should be easy to switch technology and cross-skill these people because they are embedded in that business, they understand my processes and they can make those shifts very very quickly.”