Thomas C. Redman
March 30, 2015
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 na ve. 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, allocate 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.
Thomas C. Redman, Ph.D., the Data Doc and President of Navesink Consulting
Group, advises organizations on their data and data quality programs. He is the
author of Data Driven: Profiting from Your Most Important Business Asset,
published by Harvard Business Press in 2008 and one of Library Journal s best
business books that year.