happy-group_iStock

How to build a data-driven culture with emotion

How to build a data-driven culture with emotion

Many leaders fail in their efforts to build a data-driven culture because they focus too much on logic and not enough on emotion. Logic makes people think, but emotion makes them act.

Data, and the analysis thereof, gives off the false impression of being all about logic. So when leaders approach their organization with the prospect of becoming more data-driven, they approach it in a very logical way. The data scientists in the company are no help because they'll naturally fall in line with whatever seems logical.

Aristotle taught us years ago with his rhetorical triangle that there are three methods of persuasion: ethos (credibility), pathos (emotion), and logos (logic). All three are important, but today we'll focus on pathos.

Most organizations are comfortable with the status quo, and you need enough emotional force to move them in another direction — moving to a data-driven culture is no different. Many leaders overlook this basic aspect of organizational change management, and it drives them crazy when the rest of the organization doesn't see the value of data the way they see it.

Read Also:
How to launch a successful AI startup

I've worked with a number of organizations that were compelled to change their ways after a serious incident. In one case a major gas transmission line exploded under a large city, and in another case a large pipe leak sent smoke billowing into the atmosphere. In both cases, the culprit was bad data practices.

I hope you aren't reliant on a serious event to build your case for a data-driven culture, but it needs to be this serious in the eyes of your workforce. Your organization must connect at a visceral level with the reason for moving to a data-driven culture.

As a leader, you must openly blame bad data practices for the problems your company is facing. Make the status quo uncomfortable for the workforce, and pinpoint your lack of data savvy as the single source of failure.

I'm purposely making this sound extreme to get your attention. Without this level of emphasis on the emotional aspect of your change, it will likely fail. One way to accomplish this is with an audit. Auditors love data, and hate the absence of data.

Read Also:
Risk Avoidance: The Case to Justify Data Governance

I once worked with a very large technology firm whose data was so disorganized that auditors couldn't even perform an audit. These particular auditors held the keys to all their government business, so they issued a mandate to clean up their data or lose the sizable chunk of their revenue that came from government sales.

 



Data Science Congress 2017

5
Jun
2017
Data Science Congress 2017

20% off with code 7wdata_DSC2017

Read Also:
Three Reasons Why Visual Management Boards Fail

AI Paris

6
Jun
2017
AI Paris

20% off with code AIP17-7WDATA-20

Read Also:
Data Warehousing: A Competitive Disadvantage!

Chief Data Officer Summit San Francisco

7
Jun
2017
Chief Data Officer Summit San Francisco

$200 off with code DATA200

Read Also:
5 Common Pitfalls in Current State Analysis

Customer Analytics Innovation Summit Chicago

7
Jun
2017
Customer Analytics Innovation Summit Chicago

$200 off with code DATA200

Read Also:
6 cybersecurity and emergency situations every IT department should train for

HR & Workforce Analytics Innovation Summit 2017 London

12
Jun
2017
HR & Workforce Analytics Innovation Summit 2017 London

$200 off with code DATA200

Read Also:
CIOs are Turning Agile to Meet Demands for Innovation
Read Also:
IoT plus big data analytics translate into better services management at Auckland Transport

Leave a Reply

Your email address will not be published. Required fields are marked *