by  Serge Haziyev

To Advance or Defend, That Is the Question 

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A data value strategy designed to keep pace with a rapidly changing marketplace must be agile to succeed in quality data advancement, whereas a more defensive strategy is required to protect data in a way that individuals and regulators demand.

Companies should not be too quick to assume that having an equally offensive and defensive strategy is optimal.

Offense (O) 

Industries such as retail and media are prime examples in need of an offense-driven data value strategy. Technological advancements such as AI, ML, and AR/VR require agility, and perpetual quality data is needed for genuine personalization in a rapidly changing, consumer-controlled marketplace.

data-value-strategy-software-accelerate

Defense (X) 

More heavily regulated industries like healthcare and financial services require a more defense-oriented approach to data value strategy. When personal information has been entrusted, the highest priority must be to protect and serve. Security, privacy, and compliance can be the difference between enduring trust or a financial and public relations nightmare.

Both (XO) 

It could be rightly argued that all industries need new business and to ensure security. But some industries have strict regulations while competing in heavily-contested marketplaces, like education, insurance, and banking. In such cases, a data value strategy should be created giving more equality to offense and defense. For all others, it is more effective to place the emphasis on the side most pertinent to industry expectations and consumer/regulatory demands. 

Regardless of whether you play X’s or O’s—without a properly-aligned data value strategy, it’s game over.

Read more in SoftServe’s latest whitepaper, “Why You Need a Data Value Strategy.” 

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