Data and analytics have been a top investment priority for CIOs in recent years – and for good reason.i Data streaming from new digital channels, platforms and connected devices has the potential to reshape virtually any business. But to successfully transform, you need to know which data to use, how to blend it, and which analytics tools are best to visualize and interpret the results.

Did You Know? 

Organizations that make data-driven decisions have 4% higher productivity and 6% higher profitability.ii

Four Data Analytics Capabilities Required for Innovation

When you get the right data in the right format to the right decision-makers,

your organization can act on the insights and put transformation into motion. 

1

DESCRIPTIVE DATA

PAST

Data about what happened.

2

DIAGNOSTIC DATA

PRESENT

Data that quantifies drivers of performance.

3

  PREDICTIVE DATA  

FUTURE

Data that forecasts likely outcomes.

4

PRESCRIPTIVE DATA

OUTCOME

Data about what happened.

DATA  TYPES

DESCRIPTIVE DATA

2

3

4

1

DIAGNOSTIC DATA

PREDICTIVE DATA

PRESCRIPTIVE DATA

DESCRIPTIVE DATA


DIAGNOSTIC DATA

PREDICTIVE DATA

PRESCRIPTIVE DATA

DESCRIPTIVE

DATA

DIAGNOSTIC

DATA

PREDICTIVE

DATA

PRESCRIPTIVE

DATA

DESCRIPTIVE DATA

Use it to:

See where you’re hitting targets and where you need to improve.

Case Studies

Diagnostic Data

Use it to:

Summarize high volumes of real-time data to make rapid and better-informed decisions. 

Case Studies

Predictive Data

 

Use it to:

Plan ahead to prevent unexpected downtime and bottlenecks in your business operations. 

Case Studies

PRESCRIPTIVE DATA

Use it to:

Recommend actions for future decisions.

Case Studies

Which of the Four Data Capabilities Are in Your Data Analytics Roadmap?

IT leaders were asked: What capabilities do you seek to achieve with real-time data analytics?

Descriptive Data    
Diagnostic Data    
Predictive Data    
Prescriptive Data    
Descriptive Data
Diagnostic Data
Predictive Data
Prescriptive Data

0%

10%

20%

30%

40%

50%

60%

Most organizations see the value in descriptive and predictive data, but there is still a lag in making the leap to prescriptive data – or the perception that there is a need for it. 

 

IoT data will help create a better opportunity to use prescriptive analytics by giving real-time insight into the environmental conditions surrounding an event.

Get Inspired: How major industries are using analytics to uncover insights across key touchpoints.iii

  • Transportation
  • Manufacturing
  • Mining
  • Construction

Transportation

For fleet maintenance data analytics
For fleet operations data analytics
To manage maintenance scheduling
To manage field service
For manufacturing maintenance optimization
To manage maintenance parts inventory
To extend asset life
For manufacturing machinery optimization
To manage integrated scheduling for factories
Not using analyics in any meaningful way
Other
For fleet maintenance data analytics
For fleet operation data analytics
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling

0%

10%

20%

30%

40%

50%

N=350

60%

Manufacturing

For manufacturing maintenance optimization
For manufacturing machinery optimization
To manage maintenance scheduling
To manage integrated scheduling for factories
To manage maintenance parts inventory
For fleet operations data analytics
To extend asset life
To manage field service
For fleet maintenance data analytics
Not using analyics in any meaningful way
Other
For fleet maintenance data analytics
For fleet operation data analytics
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling

0%

10%

20%

30%

40%

50%

N=351

60%

Mining

To manage maintenance scheduling
For manufacturing maintenance optimization
For fleet maintenance data analytics
To manage maintenance parts inventory
To manage field service
To manage integrated scheduling for factories
For fleet operations data analytics
For manufacturing machinery optimization
To extend asset life
Not using analyics in any meaningful way
Other
For fleet maintenance data analytics
For fleet operation data analytics
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling

0%

10%

20%

30%

40%

50%

N=151

60%

Construction

For fleet maintenance data analytics
For manage maintenance parts inventory
For fleet operations data analytics
To manage field service
To manage maintenance scheduling
To extend asset life
For manufacturing maintenance optimization
For manufacturing machinery optimization
To manage integrated scheduling for factories
Not using analyics in any meaningful way
Other
For fleet maintenance data analytics
For fleet operation data analytics
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
To manage maintenance scheduling
Other

0%

10%

20%

30%

40%

50%

N=150

60%

Get Ready To Be a Data-Driven Organization

Remember to plan ahead: ​

As the amount of data continues to grow, so will your need for more advanced analytics to improve the accuracy and speed of decision making.

94%

of industrial companies plan to increase their use of analytics. 

Invest in data-driven technology: ​

According to a recent survey, most enterprises are investing in data processing and analytics technologies, with a goal of becoming more data-driven.

SEE SURVEY RESULTS

84%

say that at least some of the decisions at their organization are data-driven.

75%

say data will become more important to their organization in the next 12 months.

20%

say data will retain the same level of importance.

Let’s Get Data-Driven Decision-Making Done Together



i 2018 Gartner CIO Agenda Survey
ii “Data Driven Decision Management”, www.whatis.techtarget.com, http://whatis.techtarget.com/definition/data-driven-decision-management-DDDM (from the Applying Economic Concepts…. PDF)
iii Source: Hitachi Primary Research Survey, IDC, October, 2017