Big data may be the buzzword du jour, but that doesn’t mean that everyone is on board. So, how do you build an analytics-friendly culture within your organization?

That’s the question that Rick Davis, vice president of business intelligence for the Kellogg Company, sought to answer at the 2016 SAS Global Forum in Las Vegas. Davis sat down with Jill Dyche, the vice president of best practices for SAS, to explain his company’s journey to creating a strategic analytics culture.

SEE: Quick glossary: Business intelligence and analytics (Tech Pro Research)

Many organizations, like Kellogg, are reaching a pivot point with data where something has to be done to keep moving forward.

“It’s a little bit like getting lost in the woods,” Davis said. You are hiking along and suddenly realize you are running out of water and need to find your way back to the trail. Your spreadsheets are no longer cutting it, and the answers you are currently getting aren’t palatable to the organization.

Once you reach that point, Davis said the best starting point is “looking outside.” Begin your journey of building a data analytics culture by talking to other companies that have gone through the same things and see what insights they can give you.

As you begin to understand that data is needed, you may notice that there are little pockets of analytics going on in different silos within the organization, as was the case with Kellogg for Davis. So, finance or marketing may be doing their own thing, but you have to find a way to connect them, to get people to play “in each others’ sandbox.” Cross-functionality is key.

You can have assumptions for potential correlations among the data, but the foundation question is: Have you proven it? That’s where data comes in.

For example, when the temperature drops, more soup is sold. Kellogg sells crackers, which go well with soup, so the hypothesis is that more crackers will be sold when it gets colder outside. But, if you don’t have the data to prove that, you cannot make business decisions based on that hypothesis.

As you seek out that cross-functionality, you have to be ready for pushback. As you connect the silos and increase transparency by connecting data, it will be disruptive to your organization, Davis said. This can frustrate certain users, as you may be uncovering that the performance of certain employees wasn’t good for the company, even if they were hitting their targets.

“Maybe that wasn’t the right target to start with,” Davis said.

One of the real values of utilizing data is that it can uncover questions or ideas that aren’t currently being considered in your organization. A data science team will need specific tasks to accomplish, but they also need a certain degree of autonomy to explore the data and experiment with it.

“If you want to build a culture, set them free,” Davis said.

Change is hard, especially in a large organization with many moving parts. As someone arguing for an analytics culture, you are a change agent, and you have to determine how resistant to, or accepting of, change your organization is. Try asking yourself the following questions:

  1. Can you operate within the existing culture, or do you need to break down some of the tenets that it is built on?
  2. Do you know and understand potential barriers or in-roads for analytics in your organization?

At a certain point, you’ll no longer be able to carry the torch alone. Davis argues that you should look for “kindred spirits.” Try to figure out who in the organization understands your plight and see if they are willing to work with you. That includes leadership.

Executives within functions that are struggling might be the first ones to jump on board if analytics offers a potential uplift. However, they may be struggling for different reasons. So, you may get moral support from them early on, but they might not be there to see the transition through.

Davis said that SAS helped them share a vision for analytics with leadership at Kellogg. Try reaching out to potential vendors or partners to see if they can help you share a cogent argument on why your company needs strategic analytics. In building this argument, make sure you have a clear roadmap and timeline for when you can deliver value and what that value will look like.

“The organization’s patience will run thin if value doesn’t come with it, Davis said.

SEE: Big data’s biggest problem: It’s too hard to get the data in (ZDNet)

In addition to finding kindred spirits, you will also need to identify potential saboteurs and be able to speak to their concerns. Dyche said she has encountered two types of saboteurs relative to creating an analytics culture:

  1. People who shoot down your ideas or talk behind your back.
  2. People who say “We’re already doing that.”

Ask these people to show you the potential problems they see with analytics, or how they believe it is already being implemented, and politely explain how your plan is different.

Finally, invest in the future to keep analytics supported. Kellogg offers education partnerships and internships to local high school students and works with them to understand what kind of careers there are in data science. This is in the hope that they might return to their hometown to pursue a career with Kellogg.

The 3 big takeaways for TechRepublic readers

  1. Many organizations are coming to a pivot point where they need to invest in analytics to keep moving forward. Start by reaching out to other companies or partners to see how they handled the transition.
  2. The key to creating a culture of strategic analytics is cross-functionality among departments in your organization. However, that will be painful and you will need to be able to fight against the inevitable pushback.
  3. Have a plan for addressing executives and explaining how and when analytics will bring value to the organization. Conversely, be able to speak to potential naysayers and saboteurs about how your plan is different from existing solutions.