August 16, 2017
Five Steps to a Data-Driven Culture
We work with a broad spectrum of media companies to help them build a data-driven culture that looks to Business Intelligence (BI) and traffic system data for insights. Many found new profit and success. Others, despite their best intentions, struggle to integrate analytics and performance indicators into their decision-making.
As anyone who has rolled out a company-wide venture will tell you, their success depended on passion, tenacity, and visible commitment from the highest levels of the company. That’s true for BI, too. Successful BI initiatives usually have a single empowered ‘Big Data’ champion who can share a vision of how data will help everyone make better decisions.
To find out how ‘data champions’ managed successful transformations of their media companies into data-driven organizations, we spoke to executives who use WideOrbit’s WO Analytics to guide their decisions. Here are five things their journey to ‘mainstreaming’’ BI at their businesses had in common:
1. Sell the Vision of a Data-Driven Culture
Your senior executives are probably very experienced, have long-standing client relationships, and see no need for change. When introducing new concepts or dashboards to a group with this level of experience, be prepared to pitch it to them just as they would sell you an ad. You’ll need to win them over with a vision of how it will improve their performance and the business. Don’t forget to tell them what they most want to know: “Will it make me more money?”
2. Go Slow to Find Your Best Advocates
Start with a ‘Less-Is-More’ approach. You’ll soon be able to identify which colleagues are most open to shaping decisions with analytics. They will become your best advocates for spreading the wisdom of business intelligence throughout the organization. When others notice the improved performance of your most data-driven business units and salespeople, they’re going to want some of that secret sauce, too.
3. Match Reports with Roles
Different roles attract different kinds of people, and so you should expect they will have differing levels of comfort about working with data. People in highly quantitative roles will find working with analytics to be a natural outgrowth of their work, while others who work in roles where they act on intuition may struggle. It is important for each role to see data that is relevant to them, and not more than can digest without being overwhelmed.
4. Make Everyone Accountable
Set up calls with managers to discuss the data and review progress. If you keep to a regular cadence, they will soon get the message: using data to assess their performance isn’t going away. You will wind up with either of two good outcomes: a success story or a chance to coach and correct. As time progresses, the number of success stories will grow.
5. Be Patient
Quantifying the ‘Return on Analytics’ won’t happen overnight. You’ll need to set up a system for measuring the progress of the measures. To look at how advertisers operate over time, for example, establish a baseline and then commit to regular reviews. You’ll start to see results once the sales team has an opportunity to review and reset client relationships, like after a renewal cycle.