By Greg Laugero, Vice President Product Strategy
I recently asked two of Numeric’s most seasoned business intelligence consultants – Rob Saunders and Angela Tang — to tell me the most important challenges they’re seeing in the lives of the data analysts they work with. Here’s what they said:
Rob: I think the biggest challenge for analysts and analytical teams is understanding the big picture. What is the purpose of the website and how do I connect everything we measure to key objectives of the site? Good analysis includes the ability to tell a compelling story with data and should not just be a spreadsheet of numbers.
Angela: I agree with Rob. I see companies are still very oriented toward populating dashboards for management; some companies still worship dashboards. Rather than dumping a complex dashboard for management to review and interpret, it is more effective to simply provide the insights and three main bullets on recommended actions. Senior management normally doesn’t have time to look at the dashboard until a fire drill has started and escalated to their attention.
As a data analyst, a key question to ask yourself is, “How much time do I spend creating reports versus interpreting results?” We like to see this balance right around 50/50. Think about it like this: the creation of a report is not valuable to anyone. It only has potential value that lays dormant until someone interprets the numbers and takes some action. If you’re spending most of your time creating reports, you’re mostly on the cost side of the equation. Like the reports you create, you only have potential value. It’s what you do with the data you collect that determines value.
Of course this is the hard part. Getting it right means moving yourself from a cost to a benefit. But here’s the trick: a single report in isolation may do more harm than good. You’re tempted to focus only on what’s visible, and it’s easy to miss the bigger picture. You end up trying to fix things that ultimately don’t matter because you’re reacting to the data you have, not the Key Performance Indicators (KPI’s) you should be measuring.
As a modern data analyst in a big-data era, delivering value means working as much on understanding and insights as it does exercising your technical know-how in getting data from system to page. Yes, knowing how to combine and transform data sources is an essential skill, but its value is only realized when it leads to beneficial action.
