Big Ways Data Can Play a Role in Your Relocation Program

DATA CAN PLAY
A ROLE IN YOUR
RELOCATION PROGRAM
POWERED BY
BIG WAYS
slideshare

we’ve all heard this
phrase tossed around.

we’ve all heard this
phrase tossed around.
...a lot.

...it’s hard to
know what it
really even means

WE’RE GOING TO CLEAR THAT UP

and show you how
to use data
properly.

and show you how
to use data
effectively.

and show you how
to use data
strategically.

and show you how
to use data
internally.

and show you how
to use data
externally.

and show you how
to use data
cross-departmentally.

your first experience with
probably looked
something like this...
visual data

Big Ways Data Can Play a Role in Your Relocation Program

this is a fine way to
represent data.

BUT.
what if.
we made something like
this instead...

gets the point across
a little faster,
doesn’t it?

it’s important not to get carried away here

it’s important not to get carried away here
otherwise, you’ll end up with a
chart or graph that looks like this:

this, as we can see, is
not an effective way
to display information

Don’t let this deter you from using visual
representations to show data, though!

Don’t let this deter you from using visual
representations to show data, though!
Just make sure you choose the method
that makes the most sense
and conveys your message the clearest

MAKE IT EASY TO UNDERSTAND
what we mean:
it’s important to pick a chart that gets your point
across in the quickest way possible—take these two
charts for example...

For the sake of understanding the information
quickly, the first chart (while it may look nice) takes
far too long to comprehend.
By using an approach like the second graph
instead, you’re able to quickly grasp on to the
message and spend more time analyzing the
information instead of decoding it.

USE A GOAL LINE
what we mean:
a goal line gives a point of reference for the story you’
re trying to tell—see how much easier it is to
understand the second graph in the following image?

It’s hard to even see what you’re looking at in the
first graph. Is the data indicating something above
average? Below average?
By using a goal line like in the second graph, you
can quickly identify what the goal was and how it
compares to the data. In this case, the data is
climbing at a pace above average.

all organizations
should be using these
types of methods.

117
49.5
“top performing organizations are
to use data to make decisions”
5x MORE LIKELY
17
49.5
- Harvard Business Review
17
49.5

You don’t have to figure it out
all on your own, though.

You don’t have to figure it out
all on your own, though.
In fact, roles that specialize in data analytics
are becoming more and more popular.

1,736 OPENINGS
$116,840 MEDIAN SALARY
DATA SCIENTIST
+
Source: Glassdoor

Historically, HR teams used data in a surface level way.
With the uptick in data scientist and statistician roles,
we are light years
ahead of that now.

HR & Recruiting teams recognized an opportunity to
expand their wheelhouse, growing the distance of how far
their data can reach and the different teams it can affect.
They want to use data to help businesses grow, and in
order to do that, they need a strong comprehension of what
data makes that possible and how to extract and present it.

which brings us
to our next point...

strategies for
using data
contextually

VISUALS
WE PROCESS60,000 TIMES FASTER THAN TEXT

TIME
INFORMATION
PROCESSED
visuals
text

But what good are
visuals if the message
doesn’t make sense?

CONTEXTUAL DATA
what we mean:
we can collect piles upon piles of data, but if we don’t analyze it and
use it in the right context of what we are trying to understand or for
whom we intend the data to impact, the data will just sit there
collecting, ultimately becoming overwhelming instead of useful.

let’s take relocation
for example.

Say you want to use data to help your
transferees figure out where they should
live and how they should get to work.

Say you want to use data to help your
transferees figure out where they should
live and how they should get to work.
You survey your employees, analyze the
data and then compile it into a report.

After surveying your employees, you
learn that 88.2% of employees
live in chicago,
and the rest are spread out
between 4 other suburbs.

After surveying your employees, you
learn that 88.2% of your employees live
in Chicago, then a smaller percent are
spread out between 4 other suburbs.
That’s helpful information, but now let’
s add some context.

who actually
took this survey?

17
49.5
17
49.5
department, age, and salary,
will have an impact on where
you decide to live

Let’s take the other example now—
using data to show how employees
get to work.

17
49.5
17
49.5
it’s pretty clear that most people
walk to work, and right behind that
is public transportation.

Sure, this is great information to know—
most people walk or take some form of
public transportation to work.
But, how useful is it to know that most
people walk to work, if all we know is
that they live somewhere in Chicago?

chicago is a pretty big
place, after all...

Let’s go back and add some context to
this information, and find out exactly
where in Chicago people live

17
49.5
17
49.5
now we know most people live in
lakeview or gold coast, meaning :
If you want to walk or take public transportation,
one of these neighborhoods is the place to live.

Let’s segment this information even further
and find out more about the commute.

Let’s segment this information even further
and find out more about the commute.
for example...

how much time does it
take you to get to work?

how much time does it
take you to get to work?
(because no one wants to spend 2 hours walking to work everyday)

17
49.5
17
49.5
from this data segmentation,
we know the average commute takes
about 16-30 minutes

Now let’s take a step back and make some
assumptions about what we learned.

There’s a pretty good chance that:
If an employee lives in Lakeview or Gold Coast,
they’ll take either public transportation or walk to work,
and that commute will take somewhere 16-30 minutes.

There’s a pretty good chance that:
If an employee lives in Lakeview or Gold Coast,
they’ll take either public transportation or walk to work,
and that commute will take somewhere 16-30 minutes.
By looking at the neighborhoods on a map in
comparison to the office, it’s easy to start
connecting the dots between which method
of commute aligns with which timeframe

see how helpful a few
additional data
points can be?

WE’VE EVOLVED TO CONSUME
bite-sized
PIECES OF DATA

WE’VE EVOLVED TO CONSUME
bite-sized
PIECES OF DATA
because we are constantly switching between tasks

LET THE NUMBERS
SPEAK FOR THEMSELVES:

40% of people abandon a website that takes more than 3 seconds to load
17% of internet page views last less than 4 seconds
Only 4% of page views last longer than 10 minutes
On a page with 111 words or less, less than half of the words get read

Keep it concise
Keep it visually appealing

Keep it concise
Keep it visually appealing
Keep it seg
men
ted

data is one of our
most powerful
tools.

Big Ways Data Can Play a Role in Your Relocation Program

More Related Content

What's hot (20)

Viewers also liked (20)

Similar to Big Ways Data Can Play a Role in Your Relocation Program (20)

More from UrbanBound (12)

Recently uploaded (20)

Big Ways Data Can Play a Role in Your Relocation Program