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  • Rizwan Khan

Tips on how to succeed in making data the king of your organization

Updated: Jan 15

Innovative organizations are using data as an asset to drive market differentiation and growth. Business success nowadays depends on Data and Analytics (D&A) capabilities that can scale with business ambitions.



According to Gartner, organizations need to improve the flow of value to customers and establish a clear connection between D&A and business value creation. To be successful in these initiatives, organizations need to develop business decision-making processes and the underlying D&A ecosystem enabling decisions.


Many organizations need help to build or improve D&A capabilities that add greater business value. According to a Global Survey done last year by McKinsey. Most executives expect their analytics activities to positively impact on company revenues, margins, and organizational efficiency in the coming years. To date, respondents report mixed success in meeting their analytics objectives. A lack of strategy or tools is not necessarily to blame for those lagging. Instead, the results suggest that the biggest hurdles to an effective analytics program are a lack of leadership support and communication, ill-fitting organizational structures, and trouble finding (and retaining) the right people for the job.


Companies need to evolve with their data to implement a D&A program that can eventually help them succeed in providing on-time business insights and AI enablement.


Following is a quick startup guide for driving the D&A program with impactful business outcomes.

  1. Step 1: Strategy & Planning

  2. Prioritize – Key business areas to analyze and improve

  3. Determine – The initial business questions to investigate

  4. Educate – Stakeholders about the benefits of business analysis

  5. Plan – Define success, create timelines and outcomes

  6. Build – Internal Support

  7. Step 2: Establish and Collect

  8. Inventory – Data sources and decide how much to include

  9. Establish – A Master Data Management Policy

  10. Create – A dictionary that defines standard business terms

  11. Combine - & integrate critical data sources in a central data mart

  12. Step 3: Clean & Standardize

  13. Define – Acceptable standards for data cleanliness

  14. Correct – Duplicate, missing, and inconsistent data

  15. Standardize – Procedures to reduce future data discrepancies

  16. Step 4: Build and Analyze

  17. Tech – “Data-Driven Decision-Making Mindset” to shift the culture

  18. Visualize – Data with interactive dashboards

  19. Forecast – Outcomes with predictive analytics

  20. Discover – Patterns and correlations through data mining

  21. Ask – New questions with data discovery

  22. Iterate – Through the process to refine

  23. Step 5: Communicate and Educate

  24. Demonstrate – Results to communicate value

  25. Ensure – The level of detail is appropriate for the audience

  26. Describe – The visualizations with stories

  27. Encourage – Questions and new hypotheses

  28. Tech – Right tools to speed adaption

  29. Share – Success and show value


An approach can be devised to address the organization's immediate and long-term D&A needs for building or improving these capabilities. A D&A assessment can show where the most focus is needed in the above steps to accelerate the D&A program for immediate results.


As a seasoned CTO, I have assisted dozens of organizations in their D&A optimization and alignment journey, including prominent organizations in healthcare, associations, nonprofits, education, manufacturing, logistics, and supply chains. For more information and guidance, you can find me at rizwan.khan@mac.com.



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