Data & Analytics Strategy
New Year’s Resolution: Move Beyond the Data Help Desk
It’s the first week back to work after the holidays. People are announcing personal goals for the year and New Year’s resolutions. It’s also a good time to apply that same reflective approach towards the health of your company or organization.
Most large companies have a few good data people. They’re usually the ones that get called into meetings at the last minute or get pulled into conference rooms to look at an executive’s or manager’s spreadsheet. “Can you make this look good?”
This behavior is common and typically means these valuable resources are spending time on one-off tactical requests and pet projects. Companies need to move beyond this data analyst help desk model and start investing in strategic data help. The opportunity to use data more efficiently is too big to act like each data project is a fire drill.
TCB Analytics has a few recommendations on how you can get started:
- Recognize your good data people. Give that poor group of data scientists and analysts some love. They’ve been doing your bidding for a while now and they’re in high demand. Retain them. It’s usually not money that provides this kind of recognition, it is respect and appreciation. Enable them to work on interesting side projects. Include the team in the planning process or provide advanced notice of requests, so the analysts can effectively manage workload and offer the greatest value.
- Provide direction for your data teams. It’s one thing to let your good data people know they’re important and valuable to the organization. It’s another thing to provide them with direction. First evaluate their skill set and understand their strengths. Then set longer term goals with metrics, including reach goals so they can advance their training.
- Create opportunities for education. In the world of data science, there are lots of ways analysts can continue to grow. They can advance their data visualization skills with Tableau or d3. They can improve their data manipulation skills with tools like R and Python. Since most companies don’t have a deep data bench, it’s likely a good idea to bring in outside speakers and thought leaders. Different types of data require different techniques so cross-industry experience may help broaden your team’s perspective.
- Enable collaboration. Like most of us, data scientists and analysts want to show off their work. If you’ve been to a stats or data conference, there’s a very academic air to the events – and to the field in general. Papers are submitted. Posters are set up. Data scientists stand next to their work and explain their approach. This kind of showcase is familiar and we’ve seen a number of companies implement similar internal events that provide a great deal of value in disseminating important information and fostering collaboration between departments.
It’s 2016. Most people say data science is the sexiest career, but it’s not fully rewarding unless the rest of us start to appreciate its value and move beyond abusing our data scientists and analysts as if they are “data help desks”. Here’s a New Year’s resolution for innovative firms: move beyond the data help desk model and empower your best data people to work on strategic projects, learn from outside talent, and share their work with others. It will lead to good things.•