The European Business Review - July-August 2019

20 The European Business Review July - August 2019

the data? How do I motivate the neces-

sary investments? The answers will

provide a guide for companies to use

existing information resources to enter

the IoT era now.

1

What data are being generated?

Although Big Data and the

Internet of Things have become

hot topics of discussion, those who

want to analyse IoT data must first

identify what data are being generated

within their processes. In many cases,

managers are only aware of a small

fraction of the total data generated by

operational technology and other equip-

ment. The CTO of an Industrial IoT

application provider explains: “most of

the dark data we’re probably not aware

of [is dark] simply because historically

we have not been looking for it. But

the fact that it is dark data, it’s data we

weren’t thinking as having value, we

weren’t cataloging it or indexing it.”

Different functional units within an

organisation may be unaware of the

data generated by their sister units.

The managing director of an analytics

service firm paints an all too common

scenario: “I remember a customer

being with a client and their IT depart-

ment, and the client said, ‘Well, if I

had X & Y, I could do that.’ He then

explains the IT department’s answer:

‘Yes, we know we have this. We have

the data. Why don’t you ask us?’ Well,

the line of business is not going to ask

what they don’t know.”

Sometimes, it is a classic situation

of “not seeing the forest because of all

the trees.” Employees know about the

data and use it every day. But because

they view it as common, they don’t

recognise that it is a form of IoT data.

The managing director of a consor-

tium of IoT companies shares how

common this is in the oil refining busi-

ness: “There is a significant amount of

intelligence, information, or data from

a petrochemical refinery that would

be considered instrumentation of the

physical world. Being in the middle of it

could be blinding me to the possibilities

of how it’s different.”

Our research finds that data audits are

effective solutions for breaking down

information silos and for bringing over-

looked data to light. A related strategy is

to start charging for data storage, which

can motivate business units to take a

close look and reflect upon what kinds

of data they are creating.

Companies need to educate

employees that much of the IoT is

old technology that they already use,

not some mysterious innovation, and

that the information it produces is

IoT data. Sometimes, people may need

an extra incentive to identify the data

they generate in their operations and

other processes. For example, a deputy

CIO who we interviewed suggests

that companies create games in which

people identify data, contemplate its

value, and are rewarded for finding new

uses for existing data.

2

What problems can I solve

with the data?

Even when organisations know

that they are generating IoT data, they

may not understand which challenges

the existing IoT data are well suited to

solve. The CEO of a Healthcare IoT

firm explains: “People don’t under-

stand what to do with the data – they’re

not educated enough.” He explains

that many companies do not know

how to leverage simple website data

and information from basic forms, let

alone IoT data.

Sometimes, it is a classic situation of “not seeing the forest because of all the

trees.” Employees know about the data and use it every day. But because they

view it as common, they don’t recognise that it is a form of IoT data.

Industry 4.0