How to go from no data analytics to a data-driven organization?
Updated: Nov 24
A data-driven organization is an organization that can collect and refine data and finds ways to use the minded information to drive growth and profitability. Companies like Netflix, Google, Coca-Cola, and Uber are using business intelligence to assist in making logical decisions with a high probability of success. If you are not one of the CEOs of these giants with a stockpile of cash and resources, how do you build these capabilities? Good news, you can with the right approach. Following are the key steps to start a successful data analytics program in an organization irrelevant of the maturity level of the organization.
Prioritize the critical business areas to analyze and improve
Determine the initial business questions to investigate
Educate stakeholders about the benefits of business analytics
Plan the effort: define success and create timelines and outcomes.
Build internal rapport and congruence
Inventory data sources and decide how much to include.
Establish a Master Data Management policy
Create a dictionary that defines your standard business terms
Combine and integrate key data sources in the central data mart
Define acceptable standards for data cleanliness
Correct duplicate, missing, and inconsistent data.
Standardize procedures to reduce future data discrepancies
Teach “The Analytical Mindset” to shift the culture
Visualize your data with interactive dashboards
Forecast outcomes with Predictive analytics
Discover patterns and correlations through data mining
Ask new questions with data discovery.
Iterate through the process to refine
Demonstrate results to communicate value
Ensure the level of detail is appropriate for the audience
Describe the visualizations with stories
Encourage questions and new hypotheses.
Tech “A Conversation with Data” to speed adoption
Understand the difference between AI and ML
Prioritize the main driver(s) of value
Select the areas to build cognitive capabilities
Evaluate your internal capabilities
Consider consulting a domain specialist to build models for your business.
Iterate to improve the models and ways to measure improvements
No matter where the organization is on its data analytics journey. The above approach will add value at any stage of this journey. We have seen improvements in all business areas by taking a systematic approach to decision-making using clean data with the right tools. Some of the most valued areas of improvement include employee productivity, marketing activities, product innovations, and personalized customer experiences.
The ideas mentioned above are meant as information to ease your organizational processes. However, if you would like a more detailed overview, do not hesitate to reach out to me at firstname.lastname@example.org.
I have years of experience building Technology and providing Technology Due Diligence as a CTO, and I am available for fruitful discussions.