Do you need big data? Maybe the question is better

phrased as: Can you afford not to use big data? The age of

big data is here, and to ignore its benefits is to run the risk

of missed opportunities.

Organizations using big data are quickly reaping rewards,

as a survey of 2,022 managers worldwide indicated

recently. In fact, 71 percent of respondents agreed that

organizations using big data will gain a “huge competitive

advantage.” These managers also saw the need for big

data: 58 percent responded that they never, rarely, or only

sometimes have enough data to make key business decisions.

Furthermore, they’ve witnessed the benefits: 67 percent

agreed that big data has helped their organization to

innovate. So why did only 28 percent find that their access

to useful data significantly increased in a year?

According to Amy Braverman, a principal statistician

who analyzes NASA’s spacecraft data, the problem is in

interpreting the new kinds and volumes of data we are

able to collect. “This opportunistic data collection is leading

to entirely new kinds of data that aren’t well suited to

the existing statistical and data-mining methodologies,”

she said. IT and business leaders agree: in a recent survey,

“determining how to get value” was identified as the

number 1 challenge of big data.

With strong need combating the high hurdle for usability,

how should a company get started using big data? The

quick answer seems to be to hire talent. But not just anyone

will do. Here are some points to ponder when hiring

data professionals:

1. Look for candidates with a strong educational background

in analytics/statistics. You want someone who

knows more than you do about handling copious

amounts of data.

2. The ideal candidates will have specific experience in

your industry or a related industry. “When you have all

those Ph.D.s in a room, magic doesn’t necessarily happen

because they may not have the business capability,”

said Andy Rusnak, a senior executive at Ernst & Young.

3. Search for potential candidates from industry leader

organizations that are more advanced in big data.

 4. Communication skills are a must. Look for a candidate

“who can translate Ph.D. to English,” says SAP Chief

Data Scientist David Ginsberg. He adds, “Those are

the hardest people to find.”

5. Find candidates with a proven record of finding useful

information from a mess of data, including data

from questionable sources. You want someone who is

analytical and discerning.

6. Look for people who can think in 8- to 10-week

periods, not just long term. Most data projects have a

short-term focus.

What Is Organizational Behavior? CHAPTER 1 37

 7. Test candidates’ expertise on real problems. Netflix’s

Director of Algorithms asks candidates, “You have

this data that comes from our users. How can you use

it to solve this particular problem?”

Questions

1-18. Let’s say you work in a metropolitan city for a large

department store chain and your manager puts

you in charge of a team to find out whether keeping

the store open an hour longer each day would

increase profits. What data might be available

to your decision-making process? What data

would be important to your decision?

1-19. What kinds of data might we want in OB

applications?

1-20. As Braverman notes, one problem with big data

is making sense of the information. How might

a better understanding of psychology help you

sift through all this data?

can you answer 1-18, 1-19, 1-20

thanks