Dot Collectors and Dot Connectors

The attention blindness inherent in the digital age often leads to a debate about multitasking, which many claim impairs our ability to solve complex problems.  Therefore, we often hear that we need to adopt monotasking, i.e., we need to eliminate all possible distractions and focus our attention on only one task at a time.

However, during the recent Harvard Business Review podcast The Myth of Monotasking, Cathy Davidson, author of the new book Now You See It: How the Brain Science of Attention Will Transform the Way We Live, Work, and Learn, explained how “the moment that you start not paying attention fully to the task at hand, you actually start seeing other things that your attention would have missed.”  Although Davidson acknowledges that attention blindness is a serious problem, she explained that there really is no such thing as monotasking.  Modern neuroscience research has revealed that the human brain is, in fact, always multitasking.  Furthermore, she explained how multitasking can be extremely useful for a new and expansive form of attention.

“We all see selectively, but we don’t select the same things to see,” Davidson explained.  “So if we can learn to work together, we can actually account for, and productively work around, our own individual attention blindness by seeing collaboratively in a way that compensates for that blindness.”

During the podcast, an analogy was made that focusing attention on specific tasks can result in a lot of time spent collecting dots without spending enough time connecting those dots.  This point caused me to ponder the division of organizational labor that has historically existed between the dot collection of data management, which focuses on aspects such as data integrity and data quality, and the dot connection of business intelligence, which focuses on aspects such as data analysis and data visualization.

I think most data management professionals are dot collectors since it often seems like they spend a lot of their time, money, and attention on collecting (and profiling, modeling, cleansing, transforming, matching, and otherwise managing) data dots.

But since data’s value comes from data’s usefulness, merely collecting data dots doesn’t mean anything if you cannot connect those dots into meaningful patterns that enable your organization to take action or otherwise support your business activities.

So I think most business intelligence professionals are dot connectors since it often seems like they spend a lot of their time, money, and attention on connecting (and querying, aggregating, reporting, visualizing, and otherwise analyzing) data dots.

However, the attention blindness of data management and business intelligence professionals means that they see selectively, often intentionally selecting to not see the same things.  But as more of our personal and professional lives become digitized and pixelated, the big picture of the business world is inundated with the multifaceted challenges of big data, where the fast-moving large volumes of varying data are transforming the way we have to view traditional data management and business intelligence.

We need to replace our perspective of data management and business intelligence as separate monotasking activities with an expansive form of organizational multitasking where the dot collectors and dot connectors work together more collaboratively.

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Comments

[Jim Harris]

From the LinkedIn Group for Information Management, Jim Ericson commented:

“I hear informally that these are often different people to start with and likely insensitive to each other.”

And I responded:

Yes, the historical view of data management and business intelligence views these people as residing on opposite ends of data’s journey throughout the organization, starting with the dot collection of data management at data’s binary birth out of a primordial sea of 1s and 0s, and ending with the dot connection of business intelligence when data’s bits and bytes come of age by the paradise of the dashboard lights.

However, the reality is that data’s journey never really ends. As it continues to be used and reused, the lines separating who is doing data management and who is doing business intelligence begin to blur.

And sometimes the re-pixelated data dots distort their new images so much that we cannot track the trail of those data dots back to where they came from — and especially if the trail has crossed the organization’s dotted lines that only appear to separate data management from business intelligence.

[Mark Troester]

Hello Jim,

Couldn't agree more with the direction that you are promoting here. We are encouraging organizations to adopt a strategic and comprehensive information management approach that combines traditional the data management discipline (data integration, data quality, MDM, etc.) with analytics and decision management. Ultimately it is all about driving decisions and using information fortified by analytics to improve those decisions.

We will be talking about this approach much more as we move forward but for some initial thoughts on this topic, you can check out my blog post: Data Integration is old news!!

Thanks,

Mark Troester
SAS
Twitter: @mtroester

[Adrian Putley]

Interesting article. I do a lot of data quality work and this certainly involves both dot collection and dot connection. I do find when doing cerebrally intense tasks I want to shut off all distractions as much as I can, so I can really get into 'flow' with the particular task I'm doing. But I would also agree that those 'aaah' moments when you suddenly realise something about the data - i.e., when your mind makes a new connection about it - often occur a short time after I have finished an immediate task, and have gone off to take a comfort break or do something else.

[Jim Harris]

Thanks for your excellent comments, Mark and Adrian.

@Mark — Thanks for sharing the link to your blog post, where I definitely agree with your perspective that “it’s about pulling together fragmented data both inside and outside the enterprise, managing it properly and turning that data into valuable information that drives insightful decision making.”

@Adrian — I am also an advocate of the flow described by Mihály Csíkszentmihályi, but I have found my flow works best when combined with a little creative distraction.