When I started work on data quality nearly 30 years ago, I had no idea how revolutionary most people would find the concept of preventing data errors at their sources. Nor did I anticipate the outsize resistance that putting this simple idea into practice would engender. Over the years, I’ve learned some hard lessons about what it takes to advance a data agenda, whether that’s advocating for a new data quality program, a different type of data, or a fresh strategy that relies on data. These lessons are particularly timely as more and more people find opportunities to push data into previously uncharted territory.
Those advancing a data agenda — I call them “data revolutionaries” — need to realize just how disruptive they are to most people. Too many data revolutionaries focus only on the potential benefits: the money to be saved, the better decisions that will result, the new markets to conquer. They’re seemingly blind to the changes people and organizations must make to realize those benefits. Everything is disrupted, from the work itself to business relationships to power structures. Many people will feel uncomfortable — even fearful — as they learn new skills, build new relationships, and rate their performance differently. Some others may lose their jobs.
Given the disruption, resistance is both normal and natural. Bear in mind that most new ideas (particularly in the data space) fail. While many ideas are just plain bad and deserve to flop, too many good ones fail because those promoting them are too idealistic and politically naïve. Don’t let resistance surprise you.
In my experience, I’ve encountered four main types of resistors:
- Virulent naysayers: Some resistors are opposed to any change, no matter what the circumstance. Often irrationally so. I’ve found it best to ignore them. You’re unlikely to change their minds and ignoring them frees up your time to work on more productive things.
- Passive resistors: Some opposition is passive, as people wait to see which way the political winds blow. People have seen plenty of ideas come and go (people at one company I worked with refer to this as the “management flavor of the month”), and they see no sense committing. This can be frustrating, especially since many will privately admit that they like your ideas. Communicate constantly with these people — listen to their concerns, explain your vision for the future, and ask for their support.
- Reasonable challengers: Other resistance is truly positive and comes from people with valid objections to your program. Listen to these people and understand their concerns. Addressing them can improve your program. Such individuals can become your biggest, most vocal supporters.
- Organizational resisters: Some opposition is organizational, in the form of committees that vet ideas, approve budgets,
space, set performance standards, and so forth. I often find a not-so-subtle bias in such committees; they favor the status quo, starve new ideas of resources, set barriers, and beat those who think differently into submission. This problem is much more difficult. You must build a base of support to solve it.
Fortunately, many people in your organization also have open minds and can help you advance your data initiative — and overcome some of the resistance you face. You must make supporters out of them. To do so, first demonstrate that your ideas can work. A small pilot study, perhaps with one category of data, in the “data lab,” or in a single department, is the best way to do so.
Next, ask for their help. Too many data revolutionaries don’t do this. They may be too enamored of their ideas, overconfident in their abilities to take on the world, or unwilling to give up control. Their efforts are almost certainly ill-fated unless and until they build a base of support. I almost always find plenty of people willing, even eager, to help. But they don’t often come forward on their own. You have to ask.
You need senior managers among your most active supporters — I’ve yet to see a data agenda advance without senior leaders. They are in a unique position to provide the resources needed to scale up, break the organizational barriers noted above, and convince the passive resistors to sign on.
Once you’ve asked for what you need, actively engage your supporters in the effort. Help them see “what’s in it for me,” and ask them to do specific things. Too many data revolutionaries brief a senior manager, get a nod of support, then walk away. It is okay to admit, “I’m having a little trouble with the Budget Committee. I’m not getting what I need. Can you help me?”
Finally, really listen to those who’ve navigated similar terrain. They can show you ways to speed up, how to get around barriers, and help you make connections. You also need one person who will look you squarely in the eye and tell you when you’re just plain wrong, so you can correct course.
My last piece of advice is certainly the most important: Above all things, persist. While having a great idea is essential, it is not enough. A data agenda prevails because those advancing it work harder than anyone else and persist through thick and thin. They convince some people and outlast others. They figure out ways to make those who join them look good. And they work with senior leaders to show them how they could contribute while at the same time minimizing their exposure should the effort fail.