Navigating the New Data Landscape – Challenges and Solutions

I recently found myself attending the 17th CDOIQ Symposium, an annual gathering of data professionals and thought leaders at the Hyatt Cambridge in Boston. My firm, USEReady, was one of the event sponsors which afforded me the opportunity to listen to and engage with some of the top data minds in the industry. Among these were four speakers: Prof. Tom Davenport, Randy Bean (CEO at Wavestone), Captain Brian Erickson (CDO, US Coast Guard), and Jamie Holcombe (CIO, USPTO) who, during the event, spoke on different aspects of the job that drive Chief Data and Analytics Officers (CDAOs) toward success. Per them, tenure, revenue orientation, product mindset, people empowerment and aligning with Line of Business (LOB) were key.

I have been a practitioner and leader in the data analytics space for 20 years. This experience has given me a front row view of how this industry has evolved. Today, as we stand on the cusp of the next big wave of Artificial Intelligence (AI), I see a few fundamental challenges facing enterprise data programs. In my view, very few organizations have a good handle on these challenges I’m about to highlight.

Challenge 1: Data Technology Rationalization:

The last decade witnessed a tsunami of data value chain tools. The market has flooded with a plethora of tools, with very little differentiation, striving to democratize data for businesses. This, coupled with tools from earlier generations, has created an urgent need to rationalize the Business Intelligence (BI) and Data landscape. The turmoil induced by the aftermath of Covid-19, where we saw huge employee turnover, exacerbated this challenge with many firms bereft of employees proficient in these tools. Naturally, it is a cost that, if rationalized, can help improve the bottom-line for many organizations.

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Navigating the New Data Landscape – Challenges and Solutions

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