Revving Up a Data-Driven Team

Part 2: Shifting Your Organizational Structure

In Part 1 of our series, we discussed why business teams need to become data driven and focused on team culture. It’s not an easy transition to navigate, so we’re breaking this into several installments.

Part 2 covers how employees should work together in a data-driven environment. Much like a pit crew, you need your key players working together seamlessly while performing their specific roles.

Specific ways to improve your team operations:

1. Data is a shared responsibility. In the current way of working, there are data requestors and data creators. Those in the first bucket are business owners: marketing, sales, customer service, and so on. Any of those resources identify an analytics gap and make a request of the data creators. The data creators are technical analysts, sitting in a centralized group like IT. The data requestors have to wait days or even weeks for their analytics request to be completed.
   
   With a data-driven approach, everybody is a data creator. Line-of-business teams pull their own analytics with easy-to-use BI tools. With many of these tools, business owners can collaborate and share their findings with others. You’ve now expanded your analyst team beyond that select group of technical specialists. And more importantly, you’ve sped up the pace of drawing insights from your data.
2. Collaborate across functional areas. Get sales and marketing talking. Customer service and operations. Share your findings. If you see insights or have a brainstorm that’s not in your area, share it. You’ll all ultimately responsible for the same customers and overall company targets.
   
   You may also want to hold a recurring meeting to cover key learnings and brainstorm new ideas. Want to make those meetings really productive? Bring your self-service analytics tool into the meeting and answer questions as they get asked. Leave meetings with fewer action items, more action.
3. Establish a common ground for your data. “Customer name” or just “name”? Sales from invoices or sales from orders? You and colleagues need to be consistent with your data field titles and values. Consistency is all the more critical when you connect several datasets together. Make sure you don’t have a mismatch of “NY” in one database and “New York” in another.
4. Tap your technical gurus for tougher analysis. Frankly, the analysts at your company are bored by your routine requests. In a data-driven model, your team is now empowered to quickly handle those requests on their own. But don’t cut ties with those analysts. Ask them to tackle more complex analysis your team doesn’t have the technical skills for.
   
   Also, remember point #2 about collaboration? You definitely want to share what you’re learning with your technical analysts. Your findings will help them better understand your needs. They may be able to proactively help you find additional insights.
5. Rethink what you need. A lot of reporting just carries over. Maybe a new category required a lot of focus when it first launched, but it’s now a mature part of your business. If you don’t need that level of detail or frequency anymore, scrap it. You’ll gain both time and focus for the areas that are a priority.
6. Present a unified front to your leadership. Make sure your executives benefit from this newfound efficiency as well. Give your VP of sales and VP of marketing the same analysis. Consolidate your reporting, so leaders don’t have to make connections between multiple files.

Your team has now turned the corner toward becoming data driven. In our next installment, we’ll discuss how to steer your talent.

Nic Redhead CC BY