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Data Science: Lifecycle approach to data-driven value creation

Data science had broad applications across many different industries. 

If we focus on industries that are in the business of buying (some or all) of a company, then trying to improve the operations before selling then we can identify at least three critical stages for data science to play a significant role.

  1. Early Exploration: Mining databases for trend and customer insights
  2. Enhanced Pre-acquisition Analysis: Linking early exploration insights with company data. Testing growth, customer value and other key assumptions.
  3. Post-acquisition Value Creation: Leveraging internal and external data to improve operations, identify growth opportunities and enhance profitability.

Much of the current data science activity is in Stage 3, post-acquisition though there will be increasing activity in Stages 1 and 2 as companies see more of the value of investing in data science capabilities.

Note: The industries that are involved in these types of activities include: holding companies, private equity firms, family funds, VCs, investment banking, etc.2808356750

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