It's crucial to have various standard Service Level Indicators in place to ensure clarity, reliability, and performance. These include Data Availability, which determines when data is accessible to users, Data Freshness for ...read more

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What is the best measures or set of measures that you have defined to assess whether as an organization you are data driven?

Dr Joe PerezSenior Systems Analyst at NC DHHS, Chief Technology Officer at CogniMind in Government3 months ago

If I’m understanding your question correctly, you may be able to gauge how much an organization values being data driven if they have metrics around the following:
1. Data literacy or mindset training metrics with the ...read more

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To what extent can an organization's level of reliance on spreadsheets act as an indicator of their readiness to use AI?

Data & Analytics People & Leadership Strategy & Architecture

Dr Joe PerezSenior Systems Analyst at NC DHHS, Chief Technology Officer at CogniMind in Government3 months ago

It depends on many additional contextual factors for course, but a few quick thoughts - I think an org heavily using spreadsheets as a system of record sends some interesting signals:

1. Data collection practices are ...read more

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I see a shift in the talent landscape where the value of data, analytics, and tech expertise is increasingly measured/compensated by capability rather than tenure. What is considered as equitable is a struggle between business leadership and human resources. Is there an opportunity to lead the market by adapting our approach and become a destination for top talent, drive innovation and secure a competitive edge? How do we respond?

Dr Joe PerezSenior Systems Analyst at NC DHHS, Chief Technology Officer at CogniMind in Government4 months ago

Responding to the Talent Landscape Shift

Market Research:

Conduct thorough market research to understand the evolving expectations of top talent in the data, analytics, and tech fields.
Benchmark against ...read more

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What are the most significant limitations of GenAI today? How do you maintain awareness of these limitations when considering applications and possible use cases?

Data & Analytics Disruptive & Emerging Technologies Strategy & Architecture

Dr Joe PerezSenior Systems Analyst at NC DHHS, Chief Technology Officer at CogniMind in Government4 months ago

tribal knowledge (both genAI, humans got limitations here) and niche functional expertise.

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One of the proposed principles of our organisations data strategy is to move to "fully online" data consumption with no extraction or manual manipulation. I am questioning if this is the right aspiration... for context we are a global, matrix organisation with multiple business lines and centralised functions. Could we ever reach a point where we have an online window that serves the needs of every business line, region, country, function etc. in one place? At every level of the hierarchy? Are we not better to serve up the essential information and allow users to slide and dice the data to their particular need? Interested in the views of the Data & Analytics community on whether "fully online" data consumption for your users is a target... or not...

Data & Analytics

Dr Joe PerezSenior Systems Analyst at NC DHHS, Chief Technology Officer at CogniMind in Government3 months ago

Striving for complete online data consumption is a pretty commendable goal, especially for a large, diverse organization. However, due to the complexity of such a structure, a one-size-fits-all approach may not be practical. ...read more

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Faced with volatility, uncertainty, complexity and ambiguity (VUCA), what do you do to cultivate trust in your data and analytics function? How do you ensure that your end users will support the new technology you implement or changes made to the data and analytics ecosystem?

People & Leadership Strategy & Architecture Data & Analytics

Dr Joe PerezSenior Systems Analyst at NC DHHS, Chief Technology Officer at CogniMind in Government6 months ago

Trust is earned. The best way to earn it, is through the delivery of tangible business value, coupled with a operating model within the data team that focuses on listening, transparency, humility, and a customer centric ...read more

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