Data Discussions with Tom Redman

October 31, 2016 Joe Barbato

Welcome, data provocateurs! This recording is the first segment of a discussion with Tom Redman about his new book, Getting in Front on Data. Over the course of this week we’ll attach another segment, 10-15 minutes, where Tom discusses different themes about becoming a data-driven business.

Tom Redman - getting in front of data

Tom Redman, the “Data Doc,” helps companies, including many of the Fortune 100, improve data quality. Those that follow his innovative approaches enjoy the many benefits of far-better data including far lower cost. He is the author of Getting in Front on Data: Who Does What (Technics Publications, 2016) and Data Driven (Harvard Business Review, 2008). His articles have appeared in many publications, including Harvard Business Review, The Wall Street Journal and MIT Sloan Management Review. Tom started his career at Bell Labs, where he led the Data Quality Lab. He has a Ph.D. in Statistics and two patents.

For more information on Getting in Front on Data, visit Tom’s website or follow him on Twitter @thedatadoc1. Enjoy! To take the first steps towards a comprehensive data quality management plan, request a free data assessment today! Know the health of your database. 

Data Driven:

Joe: So, just jumping right into it. You published “Data Driven” back in September 2008, is that correct? If you could just briefly talk about what is covered in “Data Driven” for those who aren’t familiar with the book.

TR: I’ll be happy to do that. At the time, in the run up to that book, this notion that you ought to manage data as assets was running around the industry, and people kind of talked at that at a high level as though it was obvious what one should do. And I got to worrying about that question of, “Manage data assets, manage data assets,” what does that really mean? And so tearing apart what that phrase meant was the motivation for “Data Driven”.

TR: I kind of stepped back and looked at it and had this observation that anything that either a person or an organization considers an asset, they do three things:

1) The first thing they do is they take care of it

2) The second thing they do is they put it to work, largely to make money if you’re a corporation.

3) And then you recognize that the asset needs to be managed. This particular asset is different than other assets and so it requires a different management mindset.

TR: And for data, taking care of it’s mostly about privacy and security. Just a simple example is, you can’t share a dollar. I mean you can share the dollar in the sense you can each have 50 cents, but if we work in the same company and we’re looking at budget, and I get the dollar and you don’t, that’s the end of it.

But not so with data, we can be using the same data at exact same moment for remarkably different purposes. And so what Data Driven really aimed to do is explode those concepts out, and really take the point of view that if you say you’re managing data as an asset, then you must be doing tolerably well at all of those three things.

Data as an Asset:

Joe: Can you speak to a little bit about why there’s such a disconnect around the importance of data quality, and how it actually affects your business?

TR: There’s many facets of this. Frankly, I think that people go to extraordinary lengths, day in and day out, to get good quality data, and the problem is they go about it all wrong.

I find that, at all levels in all organizations, people know they need good data, and so what do they do? They take what they have, they recognize it’s not very good, and they go to extraordinary lengths to fix it. And up and down, we have whole departments that this is all they do. The problem of course is that most aren’t very good at it, right?

It’s far easier to get the data right the first time than it is to correct it. It’s far easier to get to the root cause of a problem and address thousands of future data quality issues than it is to play catch up all the time. So, I think people always understood the fundamental importance of data quality. What they didn’t understand is the importance of addressing it proactively, getting in front really, and not being tolerant of so much bad data day in and day out.

Data: Who’s Problem Is It?

TR: I think this is the number one thing organizations can do to make immediate improvement. Either explicitly or implicitly there is some reasoning going on that if it’s in the computer, it must be IT’s responsibility. And so they assign responsibility to IT, and IT is not a creator of data, nor is it a customer of data. So, it’s really not in a very good spot to get to the root causes of issues, to focus on the most important things.

And sometimes IT puts in place programs to clean up the data, but fundamentally they’re addressing the problem wrong and it’s the only way IT can address the problem. And individuals make this mistake, and corporations make this mistake. And the first step, is find a better spot for leadership of the data quality program than IT. Your chances of success go way up simply with that change.

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