Tips for Building a Data Science Capability

THE DATA SCIENCE CHALLENGE
How Design Thinking Can Help
You Realize Organizational Value
Organizations are operating in an increasingly complex environment. They
extend across traditional boundaries in both market reach and operational
footprint. Operations often involve messy and complicated human interactions
either through customers, partners, and/or employees. To further
complicate matters, organizations are tapping into increasingly sophisticated
technology capable of capturing oceans of data with varying degrees
of structure and quality. Many organizations have turned to data science
and advanced analytics to tackle today’s complex organizational challenges.
They still struggle, however, to capitalize on the power of analytics
to address their most important business challenges. Therein lies the data
science challenge. How does an organization focus the strength of its data
and analytics to create impactful organizational value?
Two key dimensions make it hard for organizations to
appropriately focus their data and analytics. First,
they need to have a deep and innate understanding
of their business. While this may seem obvious, the
reality is that this type of understanding is often
dispersed among organizational leaders, business
units, data scientists, individual employees, and
customers. It requires an insatiable curiosity and
institutional collaboration to discover. Without this
level of understanding, the organization will not be
able to identify and articulate the most pressing
business issues, and there is no way to ensure that
the organization’s analytical horsepower is cohesively
focused on rich and relevant business questions.
Second, the organizational value desired from data
science is often found at the intersection of analytics
and context. While data science can provide predictive
and perspective analytics, insightful context can
explain the answer of “why,” including “why does this
matter.” Without the proper context, analytics will
only go so far.