Disruption threat
Data-driven transformation of the economy will lead to significant changes in the business environment of X. Therefore, it is critical to anticipate from where disruptions will challenge X, to allow X to prepare for it. The following provides visibility about the unlikeliness of being disrupted amongst 4 areas. A high unlikeliness of disruption score is positive, while low levels urge for a deeper exploration of the disruption field.
:: Anticipating a shortening of the value chain where companies leveraging data bypass you as intermediate.
With an average unlikeliness score of 18%, the threat for X to be disintermediated is quite high representing the highest disruption threat for X and requires further exploration.
Unlikeliness to be disintermediated (100% = Very unlikely)
:: Anticipating an increase of bargain power of partners before or after you in the value chain due to ownership of data.
With an average unlikeliness score of 25%, the threat for X to lose bargain power towards partners that own data that is or will be relevant to X is quite high and requires further exploration.
Unlikeliness to lose bargain power (100% = Very unlikely)
:: Anticipating a reduction of market entry barriers through data leading to entrants from adjacent markets
With an average unlikeliness score of 28%, the threat of entrants from adjacent markets is slightly lower than the other disruption threats, but should not be neglected.
Unlikeliness of new data-driven entrants from adjacent markets (100% = Very unlikely)
:: Anticipating data-driven expansions of international competitors to own markets.
With an average unlikeliness score of 23%, the threat of geographic expansions to X’s markets from international competitors is quite high.
Unlikeliness of geographic data-driven expansion of international competitors (100% = Very unlikely)
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