How organizations leverage analytics to build a data-savvy workforce


Can data create a competitive advantage in business today? During the Jigsaw Academy virtual roundtable on “Analysis as a driver of talent transformation” Ashish Gupta, the program manager at Manipal Jigsaw, explained how to create a workforce in data analytics or knowing the data and various strategies / methods to improve employee skills.

The session began with an opening speech by Sarita Digumarti, co-founder and CEO of Jigsaw Academy where she highlighted the importance of honing data skills within teams, and its impact on organizational performance and the future of work.

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The virtual roundtable panel consisted of thought leaders from industry, Learning and Development (L&D) leaders and HR directors, including from UnitedHealth Group Aalok Ajay Purohit, CGI Anil santhapuri, Accenture Ray Aniruddha, Birlasoft Deepak Kumar Arora, Mindtree Manoj Karanth, GlobalLogic Neeru Mehta and Telstra Rohin Radhakrishnan.

You can watch the entire recorded session here.

Data as a competitive divide

Ashish highlighted the need for teams to better control data through training and development programs. “Do you see data science and analytics training as a functional component? He asked to start the discussion.

While Anil emphasized the importance of conducting internal surveys to understand employee learning requirements before evaluating learning partners, Birlasoft’s Deepak emphasized the need to contextualize learning about professional roles. .

“Not everyone can be a data scientist or an analyst. So we have to look at the right fit and where it starts. We cannot start from the moment the candidates join the organization. It should start on campus or colleges, ”Deepak said.

Manoj from Mindtree takes a different approach. “There is nothing called a data problem. There is a business problem, and the best way to make a decision from it becomes crucial, ”he said.

He said it was about learning about data-driven decision making and suggested three key points:

  1. Excel remains a powerful tool
  2. Arm yourself with at least one way to find data where you can solve the given problem.
  3. To ask questions.

Explaining further, he said, “Today we ask questions and get an answer, and that brings us to more questions. This is how the differential capacity of an organization grows.

Meanwhile, Telstra’s Rohin is all for a top-down approach, where companies need to make sense of data at every level of the organization. “This is where the problem lies. So how you create an ecosystem that consumes data and uses it to deliver relevant skills becomes important, ”Rohin said.

Neeru of GlobalLogic said they are moving towards a data-driven ecosystem by building data science and data engineering academies within the organization.

“The data-savvy and analytics-savvy workforce will create a competitive edge in the market for most businesses, whether they are fortune 1000 companies or startups,” said Aniruddha of ‘Accenture, stating that a majority of successful companies in recent years have analytics as a differentiator.

“We really can’t afford to do anything without data,” said Aalok of UnitedHealth Group. He said it wasn’t about using R or Python or any other powerful BI tool, but about having a data-friendly mindset and knowing how to interpret and analyze data.

You can watch the entire recorded session here.

How to Build an Efficient, Data-savvy Workforce

In the second half of the session, Ashish spoke about the nuts and bolts of building an efficient and data-savvy workforce. “In a world full of distractions, how do you make learning effective and what are the different approaches needed to build an effective organization?” Ashish asked the question to the panel.

In response, Anil said his company had formed a DNI strategy to develop a clear roadmap, alongside building a career framework to adopt new technologies and advanced tools. “However, when it comes to developing a suitable culture, there is a confirmation bias. I think culture plays a big role where you have to be specific, and should also see one or two areas where you can make inroads, ”he added.

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Explaining the three pillars of building an efficient and data-savvy workforce, Deepak said the HR fraternity or the training and development team should lead data analytics operations within the organization. Second, employees of different experience levels need to hone their data skills. Finally, the third pillar is to use these skills to solve real life problems. “I think the central ecosystem where all these components are aligned is very important,” added Deepak.

Manoj said Mindtree has implemented various e-learning courses, both one-on-one (personalized) and workshops, to develop their employees at different levels of experience (entry-level, intermediate to senior levels).

“When people step into data science roles, they think the application of an algorithm is its ultimate nature. However, learning to appreciate data by doing the hard work of defining and slicing the data is crucial, ”said Manoj. Mindtree addresses this problem effectively by hosting coaching and case study sessions to help employees understand the nuances of solving data science problems.

Rohin said companies should tap into existing talent to create a culture of fun and learning across the organization. He said Telstra strives to help people improve their skills through a collaborative approach. “Most organizations follow multimodal approaches, blended learning programs, etc. But what I haven’t seen in my limited experience are organizations, which tap into resources and ensure fungibility of skills within the workforce.

Making an interesting analogy between learning and insurance, Neeru said that learning is a lifelong process. “The biggest trend I see is how to get people to learn by learning together. All of the individual learning from the e-learning model is not working. So that’s what we’re focusing on right now, making sure there’s a lot of learning and community collaboration, ”she added.

Aniruddha Ray, on the other hand, said that Accenture provides individual learning platforms for employees – small learning experiences based on their interests and build a community of champions and evolve accordingly.

Aalok said that the success of any model specifically in these times has several parameters. For example, he said UnitedHealth Group uses a template to make sure its workforce is ready for the future. “By the time we decided that these two approaches were different, the whole model changed. It is now working very well for us, ”said Aalok.

You can watch the entire recorded session here.

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