Why the Data Literacy programs are not able to reach Critical Mass?

30 Jun 2020   /   Joseph Sursock and Sushant Ajmani   /  Digital

 


 

In this podcast, both Sushant Ajmani (VP, Product Management) and Joseph Sursock (SVP, EU Partner Sales) discussed on why the Data Literacy programs are not able to reach their critical mass and what are some of the novel ideas organizations can experiment with to create a data-driven culture with-in their organization. Below mentioned are the 2 broad topics of the conversation:

Why are the data literacy initiatives not working out despite making millions of dollars of investments in Training and Evangelization sessions?

If we focus on the last decade, we will find that a significant % of digital investment in the corporates went into five significant areas i.e.

  • Setting up Data Infrastructure on the Cloud (AWS, Azure, and GCP) along with the vendors and consulting firms who collaborated with the internal team.
  • Deployment of the Self-Service BI Platforms (Tableau, Qlik, and PowerBI) to bring data and insights closer to the consumers.
  • Enabling Data Layers, Tag Management Solutions, and 100s of MARTECH pixels on the Mobile Apps and Desktop Websites, along with multiple external vendors who made it possible in collaboration with the corporate IT and BI teams.
  • Subscription of the enterprise cloud-based analytics platforms such as Adobe, IBM, and Google along with the external solution partners who made it possible.
  • Series of technical training hosted by the corporates to empower their internal workforce, which was majorly driven by the Product & Technology vendors.

If we combine the investment done in the above areas, it would be in multi-million dollars for any large enterprise. Some of the large corporates I have engaged in the last decade across 17+ countries; this investment is over $20-25mn over a span of 3-4 fiscal years. But unfortunately, this massive investment is not able to create a scalable data-driven organization and deliver on the promise of Data Literacy for a larger workforce.

Today, if we approach any large digital enterprise and ask them their three fundamental challenges with respect to the investment that has been made in the last decade, we would find the following concerns standard across the board:

  • How can we boost the adoption of the technologies that we have subscribed to across multiple business functions globally?
  • How can we demonstrate the incremental ROI from this investment?
  • How can we create an Insights-First culture that rewards data-driven decision making?

Now, if we try to find out why the organizations are failed to create a data-driven culture and deliver on their Data Literacy programs, we would find multiple reasons ranging from Data Quality, Lack of Relevancy and Context, to Inept Storytelling, not enough data for the smarter decision making, Lack of Trust in the Technology and Processes, No Standardization with respect to the Metrics and their Definitions, Complex Tools and Technologies, Limited Analytical Professionals, Data Leakages in the Value Chain, Lack of Collaboration among different business functions, Limited access to the data from the suppliers and partners and so on.

What kind of radical thinking is required to create an insight-first culture that rewards data-driven decision making?

For any enterprise, it's a Hercules task to solve the above problems and reach an idealistic state of Data Literate organization. Today, we have plenty of frameworks and methodologies available in the industry to alleviate and circumvent some of these problems and create a data-driven culture. Some of the large enterprises in our network have been managed to create this culture with a lot of grit and accountability, and if we look at their journey, we will find some novel approaches they took to spread Data Literacy across the board. Before we discuss those novel approaches, let's define the term Data Literacy. According to Gartner, Data Literacy is the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied — and the ability to describe the use case, application, and resulting value.

The above definition from Gartner is pretty comprehensive and has various important elements that often get overlooked while running the Data Literacy programs. So; let's talk about some of the novel and effective approaches the organizations can take to make their Data Literacy programs a big success:

  • CREATE A GROUP OF INFINITE AND EXPLICIT LEARNERS
  • CREATE A CULTURE OF EXPERIMENTATION
  • DECENTRALIZE YOUR ANALYTICS FUNCTION
  • SETUP A CLOSED-FEEDBACK LOOP AND PRODUCTIZE YOUR PROCESS AND OPERATIONS KNOWLEDGE
  • AUGMENT YOUR DATA STORIES FOR BETTER ADOPTION
  • DEVELOP PRODUCT MINDSET WHEN IT COMES TO DATA AND ITS CONSUMPTION

The above are some of the critical initiatives organizations can take to deliver a scalable digital literacy program and create an insights-first culture that rewards data-driven decision making. To deep-dive in to the above approaches, please visit "Novel Approaches for a Scalable and Effective Data Literacy Program" blog post on our website.

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