Guest blog: www.biblogg.no
Jill Dyche, Vice President of SAS Best Practices, was keynote speaker at SAS Forum Norway in September, and was interviewed by Lars Rinnan
Jill, you delivered a strong keynote, and the audience was really attentive.
You talked about big data and how to get the c-suite to listen. It sounds almost impossible. How do you get them to listen?
You need to meet executives where they are. In other words: figure out what’s important to them now, and then map big data as the answer.
Here’s an example: A large cable company sees an uptick in customer complaints in its call center. They have to add expensive headcount to the support staff. But they decide to incent customers to use social media interactions to ask for support or lodge complaints. By adding social media transactions to customer profiles, the cable company can not only monitor valuable customers who may be at-risk, it can also “score” its brand reputation based on text analytics of social media interactions. They understand that over half of customer feedback comments are actually installation questions and not complaints. They develop customer support videos and post them on YouTube. Both questions and complaints are reduced, and support staff can be redeployed to cross-selling functions.
Data governance is essential, but how do you get the CXO interested?
Find the problem the CXO needs to solve, and explain how data enables the solution. Many senior executives don’t make the link between a business need and data. If you “deconstruct” the business problem into the data necessary to solve it, you can see the lights go on with executives.
How would you start a data governance process at a large company who has no clue of data governance?
We recommend starting with what I call a “small, controlled project.” Take a business problem, scope it down to a level where data can enable it quickly, and then implement a well-bounded process around data rules and policies necessary to address it.
How is data governance related to big data?
Big data is like any other data: It requires policy making and oversight. In that respect big data should be beholden to larger rules. For instance, data from sensors or devices that may be streaming into your company should be handled in a different way. Is it sensitive? Is it defined? Is it targeted to be consumed by a department? An individual? A machine? All of these factors, and others, should inform the policies around that data. And that’s data governance.
In your experience, are businesses giving data governance enough attention in terms of resources, technology and funding?
Only after they feel enough pain. Very few companies new to data governance actually say, “Hey! Let’s make sure we factor data governance into this new initiative.” Most have to experience the pain of not having the right data for the right business purpose. Go back to the days of Customer Relationship Management and remember how everyone thought they could just plug in a new tool? The validity of the data is directly proportional to the value of the resulting application. Data can no longer be considered an afterthought.
Thanks you for sharing these valuable insights with the readers of biblogg, Jill!