By Stephen H. Yu, Target Marketing
In my job of being “a guy who finds money-making
opportunities using data,” I get to meet all kinds of businesspeople in various
industries. Thanks to the business trend around analytics (and to that infamous
“Big Data” fad), I don’t have to spend a long time explaining what I do any
more; I just say I am in the field of analytics, or to sound a bit fancier, I
say data science. Then most marketers seem to understand where the conversation
will go from there. Things are never that simple in real life, though, as there
are many types of analytics — business intelligence, descriptive analytics,
predictive analytics, optimization, forecasting, etc., even at a high level —
but figuring what type of solutions should be prescribed is THE job for a
consultant, anyway (refer to “Prescriptive Analytics at All Stages”).
The key is to an effective prescription is to
listen to the client first. Why do they lose sleep at night? What are their key
success metrics? What are the immediate pain points? What are their long-term
goals? And how would we reach there within the limits of provided resources and
put out the fire at the same time? Building a sound data and analytics roadmap
is critical, as no one wants to have an “Oh dang, we should have done that a
year ago!” moment after a complex data project is well on its way.
Reconstruction in any line of business is costly, and unfortunately, it happens
all of the time, as many marketers and decision-makers often jump into the data
pool out of desperation under organizational pressure (or under false promises
by toolset providers, as in “all your dreams will come true with this piece of
technology”). It is a sad sight when users realize that they don’t know how to
swim in it “after” they jumped into it.
the full article here.