A company´s data and data-driven learning processes can help companies generate competitive advantages. But what conditions must be in place for this competitive advantage to be effective and sustainable?
To determine the extent to which a competitive advantage provided by data-driven learning is sustainable companies must answer 7 questions:
Is the data proprietary or can it be purchased from other sources or replicated by reverse engineering? The more proprietary and difficult to replicate the better for the company.
How difficult is it to mimic product improvements that are based on customer data? Can competitors easily copy the results?
How quickly does the relevance of user data fall out of favor? If data quickly becomes obsolete, the value of learning from user data is important.
How fast does the marginal value of data-driven learning fall? That is, how long does it take for the company before the data no longer enhance the offering.
How much value does the terminal data add relative to the standalone value of the offering? The greater the value-added the greater the likelihood that it will generate enduring competitiveness.
Does one user’s data help improve the product for one user or another?
How quickly can insights from user data be incorporated into products?
Improving customer service with the use of datawill be a fundamental requirement to stay in the game in the coming years. It will not create a winner-take-all dynamic but the most valuable companies will be those that have a good data strategy and can generate network effects.
In conclusion, data-driven learning processes are helping companies generate competitive advantages against their competitors.
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