Stakeholders across many types of organizations are clamoring for data democracy. Leaders in human resources, marketing, sales, customer service, supply chain and nearly every other department are painfully aware that information is key to their success, and they’re pushing IT to tear down the siloes that make data difficult to access and analyze.
IT teams can’t ignore the cry for data democratization, which is the broad availability of all the metrics needed to make decisions and measure performance. But the response will not be easy.
There are technological challenges involved, of course, but the political hurdles are just as difficult to surmount. On both fronts, IT has to lead the way.
Before tackling the thornier political questions that can impede data democracy, IT leaders need to evaluate the technological impediments. The following questions are a useful place to start:
- How mature is our organization in its approach to data storage and normalization?
- Do we have a centralized data officer?
- How have we organized information in our data warehouse?
- Is the structure normalized and conducive to broad access?
- What data types do we have?
- When our users ask for access, is it CRM data, sales data, loyalty data, customer call data, social media data or other information streams they want?
- Do we have a standardized set of business intelligence and analytics tools used across the enterprise?
All of these technology challenges need to be addressed to make data democracy a reality inside the enterprise, but solving them is not enough to destroy the siloes. Many of the walls that separate information were put there by people, and people will need to agree, enthusiastically, to bring them down.
Everyone wants to protect “their” assets. They want to own “their” data. And they often fail to see how that mentality hampers overall organizational success. Why is that IT’s problem? Because no matter how elegant the technological solutions you put in place might be, if data “owners” revolt, those tools become irrelevant. So how do you get people onboard?
As individuals, we’re willing to give up some personal data if it benefits us in a tangible way. The same is true inside organizations: If you explain the benefits that teams will get when they share access to the data they control, then they’ll be more likely to evangelize it to colleagues, paving the way for data democracy.
Consider these examples:
Ambitious customer care representatives and managers need to know who’s complaining the most. Questions to consider: Are the customers who are reaching out to the call center also voicing their complaints on social media? If the customer service department shares its data with other teams via centralized databases or dashboards, will they be more successful?
Similar scenarios apply in HR, where recruiters might be more successful targeting people already engaged with the company on social media, if only they had access to that data that may be “owned” by the marketing team.
In product development, the ability to cross-reference historical survey data with real-time social media focus groups could be critical to creating innovative products that do well in the market.
And in retail, data created and owned by individual brick-and-mortar stores could be used companywide to understand sales performance and inform marketing, merchandising and dozens of other functions.
Here’s one example for how true data democratization worked out in real life, with JetBlue providing a clear example of how technology and people contribute to data democracy.
JetBlue developed a social analytics strategy aimed at turning customer feedback and insights into a hiring guide. The company switched the focus of customer-facing hires from people who seemed pleasant to people with a singular focus on solving customer problems. This switch was directly a result of data democracy.
By analyzing customer service complaints and other feedback, JetBlue had identified the characteristics of the ideal customer service employee. Then, it developed a personality test that identified those traits in their applicants. This initiative created a team that was 15 to 25 percent more likely to elicit positive feedback on social networks.
But for this to work, JetBlue first needed to elicit these insights with a social analytics platform, and then make sure those insights were distributed beyond the customer service team to HR. The concept of data has shifted past the simple analysis of one type of data within one department to the broad use of information of all kinds to drive better business decisions.
Data democratization helps organizations use data more effectively, but it’s only achievable when IT leaders push for the right technology—and the right attitudes—to pull down data silos. Identifying the challenges present in an enterprise and overcoming them are critical steps in the long-term success of data and analytics in the enterprise.
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