How to make dollars (and sense) of all that data.
the power of analytics to work and create positive business outcomes.
you’re like countless small businesses, your most pressing question about data
is, “what do we do with it?” For many companies, that means job one is
developing a viable data storage plan.
taming the data monster is one thing. The real trick is figuring out how to
turn that mountain of data into mountains of cash. Recently, TechRepublic
writer Alison DeNisco Rayome, drawing from a new book about monetizing your
data, shared five ways to do just that.
What’s your problem?
Ironically, the best way
to set the stage for leveraging your data is to set it aside. Instead, think
about any challenges facing your organization. If you could solve these
problems, what kinds of opportunities might open up? This early strategic phase
sets the stage for everything that follows — and will give you a sense of
direction on the best ways to marshal data resources.
Create a roadmap. Put some meat on the bones of the problem you plan to
tackle. This will help your staff bring a systematic approach to the process,
testing assumptions and identifying action steps as they go. (Helpful hint:
Don’t forget to flush out any biases that may pre-determine an outcome! This
happens when a team decides what the solution is before completing research —
and goes looking for data that will “prove” their concept!)
on the money?
Now that you understand the problem and have explored
potential solutions, the next step is to determine if the
really enhance your business. Put the proposed action steps under a microscope
and see if they will help the bottom line. In other words, use analytics to
Seek value. The goal is to help
managers tap data at a micro level — not just the usual generalized reports
that don’t help much. Data modeling enables drilling down in a way that can
produce measurable results for your marketing, IT and business initiatives.
In data we trust.
results in data that’s capable of supporting a monetization strategy. Simply
put, the goal is for data to be both useful — and trusted. Why? Two reasons:
First, the data is deemed to be accurate. And second, your team is genuinely
involved in the process.
further explore the endless
possibilities of intelligent data management, look here.