Tips for Building a Data Science Capability
WH4vS
WH4vS
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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.