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Tips for Building a Data Science Capability

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ANALYTICS CULTURE<br />

Why Hasn’t Your <strong>Data</strong> <strong>Science</strong><br />

Investment Delivered on its<br />

Promise?<br />

The promise of game-changing results from data science has been touted<br />

<strong>for</strong> years, and the allure of that promise has driven organizations across all<br />

commercial markets and the public sectors to invest huge sums of money,<br />

time, and resources to make it happen. Encouraged by the outcomes of<br />

analytical pilots, organizations are now looking to scale data science<br />

across their enterprise. As they continue their pursuit, they have found the<br />

benefits are elusive and they are often humbled by organizational inertia.<br />

The hard truth is that a key enabler to delivering on the biggest promise of<br />

data science is trans<strong>for</strong>ming organizational culture. And, contrary to popular<br />

belief, it’s not about trans<strong>for</strong>ming to just any culture. Organizations must<br />

start to pursue an analytics-driven culture.<br />

An analytics-driven culture uses analytics to generate<br />

insights that can be used by organizations to in<strong>for</strong>m<br />

strategic decisions and propel the organization to the<br />

next level of per<strong>for</strong>mance. One of the key benefits of<br />

an analytics-driven culture is the difference in<br />

timescales in findings solutions. With an<br />

analytics-driven culture, the organization becomes<br />

particularly adept at asking the right questions and<br />

rapidly (within minutes sometimes) getting answers.<br />

That shifts the time available to thoughtful discussion<br />

on what analytical outputs mean and how they<br />

in<strong>for</strong>m decisions to derive desired outcomes.

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