Great Data Teams Play Both Offense and Defense

by   |   August 17, 2016 5:30 am   |   0 Comments

Tom Davenport, left, and Tom Redman

Tom Davenport, left, and Tom Redman

Most of the information-oriented executives we have encountered in our work have been focused primarily on either information opportunities or information problems. That also goes for those of us who write books and blog posts on information-oriented topics. For example, one of us (Redman) recently asked the other (Davenport) how interested he was in information quality. Davenport replied, “That’s a good question. Probably not as interested as I should be.” He went on to explain that he “liked to play offense” and he always viewed “data quality as defense.” While Redman didn’t initially like the analogy, he had to admit that it resonated.

Offense, of course, attempts to put points on the scoreboard. With regard to information, it includes analytics (at least when they are used for marketing or better decision making), customer relationship and sales data, e-commerce, and digital transformation, and aims to grow revenue. Defense – solving problems or neutralizing threats related to information – includes data quality, security, privacy, governance, and regulatory compliance, and aims to reduce cost and risk.

Related Stories

How to Blend Data, Experience and Intuition for Better Decision Making.
Read the story »

Boost Security Compliance with Big Data in the IoT Era.
Read the story »

Report: Companies Continue to Struggle with Data Quality.
Read the story »

Make Customers Happy with Immediate, Actionable Data Insights.
Read the story »

Of course, these two areas are related. While we don’t want to push the sports analogies too far, they are instructive. Some examples: Just as good defense can make it easier to score, high-quality data makes analytics easier. In American football, it is much easier to score a touchdown when the defense intercepts a pass near the opponent’s end zone than when the offense starts from their own 10-yard line. If the data are clearly defined and trustworthy, it’s much like starting on your opponent’s 20. But when the data is an unsightly mess, it’s much like starting in the shadow of your own goal posts.

In the same vein, good defense can keep a baseball game close until the late innings. Then a couple of runs in the bottom of the eighth inning can win it all. High-quality data can keep costs low and a business competitive while an analytics team gets up and running. And then that big insight is the equivalent of a three-run homer.

Find the Balance

Unfortunately, few in business (or in sports, for that matter) are blessed with equal orientations and skills for both offense and defense. You have to make choices with your time and emphasis. Most Chief Analytics Officers (and related titles) emphasize offense. Most Chief Data Officers and Chief Information Security Officers focus on defense. There are some exceptions, of course. Charles Thomas, the Chief Data Officer at Wells Fargo, strives to devote equal attention to both – which is not easy in the heavily regulated world of banking.

Like Thomas and Wells Fargo, we would argue that companies should find some degree of balance between offense and defense. For CAOs, some pretty basic analytics can help you root out the sources of data errors and prevent future errors. Analytics also can be used to identify patterns of security threats.

On the CDO side, try looking for something that benefits customers in every initiative to improve regulatory compliance. And partner with CAOs and business leaders to find ways that beneficial insights can be achieved with better data quality and integrity.

Wherever CDOs and CAOs decide to focus their energies, at some level within the enterprise general managers need to focus on both offense and defense. CIOs need to ensure that their organizations add value to information as well as not getting into trouble. CEOs need to ensure that their organizations have a balance of offensive and defensive information capabilities. And all general managers should seek offenses and defenses that complement each other. Some may emphasize offense and a “good-enough” defense; others just the opposite. However constructed, your offense and defense must be part of the same team.

Over time, companies that bring everyone into the effort have the best prospects for success. Everyone who touches data can contribute to the data-quality effort, just as everyone can bring more analytics into his or her work. We are big believers in our respective foci. Redman usually emphasizes quality, citing “defense wins championships,” while Davenport emphasizes analytics, citing “the best defense is a strong offense.” The main point or course, is that both must be part of your long-term information strategy and that you must do both at least tolerably well.

Tom Davenport, the author of several best-selling management books on analytics and big data, is the President’s Distinguished Professor of Information Technology and Management at Babson College, a Fellow of the MIT Initiative on the Digital Economy, co-founder of the International Institute for Analytics, and an independent senior adviser to Deloitte Analytics. He also is a member of the Data Informed Board of Advisers.

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. Tom’s book, Data Driven, is the guiding light for companies seeking to build their future in data. He has a Ph.D. in Statistics and holds two patents.

Subscribe to Data Informed for the latest information and news on big data and analytics for the enterprise, plus get instant access to more than 20 eBooks.








Tags: , , , , , ,

Post a Comment

Your email is never published nor shared. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>