“If we have data, let’s look at data.
If all we have are opinions, let’s go with mine.”
– Jim Barksdale, former Netscape CEO
Have you read Tom Davenport’s “Data Scientist: The Sexiest Job of the 21st Century” article in the Harvard Business Review or Jill Dyché’s fun take-off, “Why I Wouldn’t Have Sex with a Data Scientist”? Who knew that a data job/role could have so much, um, appeal?! Could it be that we’re now living in our own Revenge of the Nerds?
All fun aside, it’s interesting to note that the data scientist discussion is saturated with some of the same questions we’re asking about big data:
- What is a data scientist? What is big data?
- Can we get by without a data scientist(s)? Can we get by without big data?
- Why can’t we use the human resources we already have – e.g., business analysts and statisticians – for big data? Why can’t we use the technical resources we already have – e.g., data warehouse and analytical systems – for big data?
And speaking of big data “people,” you’d think it was all about the data scientist. But it’s not.
For years, “Evolve toward a competency center!” has been the battle cry of industry analysts and management consultants. And we’ve listened. We’ve established our BI and analytics competency centers by bringing the right people with the right skills and decision-making power to the table to manage our company’s reporting initiatives. And it’s been working.
But where does the data scientist and big data fit in now? Do we need to set up a new competency center?
A Big Data Best Practice for the People Involved
Back in 2011 when big data started grabbing headlines and keynotes, much of the discussion focused on Gartner’s 3Vs of big data and big data technologies. This went on for about two years – and then the discussion began to shift. The message we now hear is: Big data is not only about the technology; it’s also about the people and the process. Sound familiar? If you’ve been in the data/technology world for any length of time, you know this message is not new. But it’s as relevant as ever.
So let’s go back to the competency center question. The short answer is: No, you don’t need to set up a separate competency center for big data. What you want to do instead is focus on the individual roles and skills to add to your existing competency center(s). This may mean the addition of data scientists, Hadoop experts and/or other big data stakeholders. Or it may mean that existing team members will need to expand their current skill sets and/or responsibilities. Most likely, your organization will need a bit of both to address the big data questions and requests coming in the door.
The bottom line is this: Big data deserves a seat at the table, but it doesn’t need its own table.
Key Takeaways for Marketers
- Find out how many data scientists your organization has.
- Then go hug your favorite data scientist – or nerd – today. We all need love.
- The Organization Dragon on the north side of the island is big and has been there a long time. He may be set in his ways and hard to move.
- Be proactive about understanding how big data could change your current role or set of responsibilities.
- Seek the training you need to stay current with this big data shift.
- Get another view of the people side of big data in marketing by considering culture in this paper, Argyle Conversation - Building a Marketing Analytics Culture.
This is the 8th post in a 10-post series, “A marketer’s journey through the Big Data Archipelago.” This series explores 10 key best practices for big data and why marketers should care. Our next stop is the Investment Isle, where we’ll talk about calculating the intangible ROI of big data.