Editor’s note: Welcome to Throwback Thursdays! Every third Thursday of the month, we feature a classic post from the earlier days of our company, gently updated as appropriate. We still find them helpful, and we think you will, too! The original version of this post can be found here.
The business community and the technical community can sometimes seem like they live on the opposite sides of the planet—or at least opposite ends of the hallway. When it comes to data strategy, many people read the “data” part and automatically dump the topic in the “technical” bucket. It can be a struggle to adjust that thinking, but it’s a critical thing to do.
Ultimately, what is needed is not to reassign the topic, but to merge the buckets.
Data strategy matters to both business and tech. It’s a problem that sits in the center of a Venn diagram, and if we get stuck thinking of those two domains as existing solely in completely separate silos, we’ll lock ourselves out of that key middle ground where the really important problems get solved.
From tech to business and back again
My background means that the circles I run in have largely existed in the technical community. These are wonderfully smart, curious, and capable people. But the tech community often does things simply because they are possible and interesting. For both better and worse, the merit of a given pursuit is not always tied in their minds to the needs of the business.
At SVDS, we spend a lot of our time thinking about data strategy: how to start with a set of business objectives, distill those into a batch of use cases, and translate from there into the technical capabilities necessary to support the overall plan. The tools and techniques that techies love to geek out about only start to matter once you know which technical capabilities you need—an order of operations not always familiar in the land of debates over Python vs. R and Hadoop vs. Cassandra.
The emphasis on data serving the practical needs of a business is one of the reasons why I love working at SVDS. We see a bigger context than many other data science consulting shops, and I love being part of that: if there’s one thing I’ve learned, from data visualization to communications to just about anything else, it’s that context matters.
There are lots of other people who get it, too: in particular, Carl Anderson with his book “Creating a Data Driven Organization.” His central thesis is that a data-driven culture rests on a commitment to every step of the data value chain, from collection through analysis and, crucially, ending in action. I’ve been happy to see more and more data scientists take on the mission to preach the importance of business value to the tech community.
The zen of the Venn
At the CDO Vision summit at Enterprise Data World 2015, a panel discussion on data strategy echoed many of these thoughts. Daniel Paolini, CIO of the Philadelphia Department of Behavioral Health, addressed this by saying, “If you can’t speak the language of your business; if you don’t know what they mean when they say a term; if you don’t understand what their objectives are as a business: you cannot be successful at this.” I was busy nodding my head in agreement when the discussion portion started. But then one of the executives in the room expressed an opinion that caught my attention; he said, “the business has abdicated its role by throwing it over the fence to IT and saying, ‘Talk to my DBA.'”
I had almost forgotten that the onus rests on both sides. A woman sitting at the next table replied, “I’m really glad you pointed that out, because I’ve been critical of IT for having responsibility for something they can’t do well, but it’s not like the business side is stepping up.”
Another attendee added to this: “Increasingly, information strategy and business strategy are the same thing. Especially in customer-facing industries, that is increasingly the norm. We keep talking about data people needing to understand what the business is all about. I’m from the business side and I think businesses do not understand how data is changing their competitive landscapes and opportunities, so I think it’s the other way around: business needs to be more aware of data.”
Part of the ability to inhabit any middle ground is learning to become bilingual. Think of it as a trip to Montreal: some people living there will be native speakers of one language, and some will be native speakers of the other—but everyone is surrounded by the words and sounds of both, to an extent that they can at least understand, if not speak, the language of their neighbors.
And it turns out, we all have a lot to learn. As a woman sitting in front of me at CDO Vision pointed out, “Whether you’re business or technology, I’m not sure people know what it takes to get the data where it needs to go. People are so used to opening their phones and getting access to this instant magical asset, that they don’t appreciate what’s involved in exposing data inside the enterprise.”
Those in both the business circle and the technology circle would do well to listen to each other, to consider each other’s priorities, and to embrace the middle of the Venn diagram. It can be uncomfortable or even jarring to live in a bilingual place; there can be misunderstandings. Ultimately, however, both business and technology bear the responsibility—and the potential rewards—of working together for the greater good.
We’ll be talking about data strategy next month at Strata + Hadoop World Singapore. Check out our talks, and sign up for slides, here.