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.
Placing the blame
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.
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.
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. At that moment, the CEO of the company became very emotional about their data, and we launched a major initiative to build a data warehouse (very quickly).
Hope comes in small victories
The fear of today must be complemented with the promise of a better tomorrow. Fear is the emotion that will push them away from the current state, but hope is the emotion that will pull them into the future state.
The challenge is that it's often difficult to sell the workforce on a nirvana that sits somewhere out on the strategic horizon. That's why it's important to shoot for quick wins. The quicker you can produce some evidence that your analytic prowess is working, the quicker hope is reinforced with strong belief.
Look for an opportunity to run a pilot, and deploy your best tiger team to get through it as quickly as possible. And don't make your life more difficult than it needs to be: segment your opportunities by impact and ease of implementation; hopefully, you'll have at least one opportunity that has a high impact and an easy implementation. Take that opportunity and move through your pilot as quickly as possible so you can demonstrate — with evidence — how much better life will be when your company is more data-driven.
Don't just stop at one small win; in fact, use the momentum from your small win to tackle another small win, and then another and another. Stay in the high-impact / easy-implementation quadrant to ensure quick success that can be celebrated. Once you've cleared through all of the high impact / easy implementation opportunities, take down a few low impact / easy implementation opportunities.
You want to create a snowball effect on wins, gradually building hope and confidence that data-driven is the way to go. Then when the timing is right, cross your fingers and tackle one of those high-impact / hard-to-implement opportunities. This is where the stakes are high, but so are the rewards. Once you take this one down, your emotional capital will be very high, and you'll be well on your way to a data-driven culture.
SEE: Big Data Primer for IT Pros (Tech Pro Research)
To move your organization to a data-driven culture, there must be a strong emotional component. Don't be fooled by the illusion that data-driven is all about logic — if there's no emotional connection to the change, it won't happen. Use negative emotions to drive people away from the way things are now and positive emotions to propel them into the future, and use small victories to quickly build momentum.
I'm sure you have your reasons for building your company's analytic capabilities, but until your workforce has strong emotional reasons to move them off the status quo, that's likely where they'll stay.
- Scary and fascinating: The future of big data (ZDNet)
- Microsoft's cloud video analytics can tell if you are happy, sad or angry (ZDNet)
- Why big data analytics strikes out sometimes (TechRepublic)
- Why you keep failing at big data (hint... it's your vendors' fault) (TechRepublic)
- Can IT keep up with big data? (TechRepublic)
John Weathington is President and CEO of Excellent Management Systems, Inc., a management consultancy that helps executives turn chaotic information into profitable wisdom.