A common problem that good Data Teams face is that they are significantly backlogged. They are pulled in many different directions by different leaders with different priorities. It’s a good sign that they are a valued asset to your organization, but it can be frustrating waiting for them to get to your urgent requests. Sometimes it’s like they are clogged up like bad plumbing …

So, what can an organization do to unclog their Data Team? Here are four tips:

Tip 1: Get crystal-clear on the outcomes of the Data Team
Data Teams often spend a lot of time talking about their efforts and the resources they feel they need. But instead it’s better to focus on the outcomes of the team … how will your organization know that the Data Team is doing a good job? Until everyone in the organization (including the Data Team) is clear on the outcomes that they need to achieve, the demands on the Data Team will continue to grow unchecked. Some example Data Team outcomes could be:

• To ensure top-level management has the reports they need to maintain profitability
• To provide management insights on market competitiveness
• To trigger management alerts on operational areas that require attention
• To detect patterns related to decreasing customer satisfaction
• To support improvement projects in the organization

… and so on (Hint: It would be unrealistic for most Data Teams to attempt to meet all of these outcomes.)

Once the outcomes of the Data Team are clear, the next step is …

Tip 2: Calculate the ROI for different Data Team efforts
Most Data Teams hold responsibilities for maintaining reports and analyses … some of which are easy and some of which are very hard. Rarely do the users of these deliverables appreciate the effort that goes into them, particularly when there is a lot of interpretation required, or a lot of extra data cleaning that can’t be automated.

In these situations it may make sense to assess if the value of the information is commensurate with the effort involved in generating it. This is especially true if there is a suspicion that the information isn’t really being used for decision-making. More tips are on this topic are described in the blog post Turning Analysis Into Action, but generally speaking the Data Team efforts should be fully aligned with the outcomes of the Data Team.

If the ROI on a difficult analysis isn’t there then …

Tip 3: Give your Data Team permission to purge
Data Teams typically find themselves in situations where they don’t have enough capacity to meet all of the demands imposed on them. And every week requests for new analyses and reports come up.

So, if they are working on difficult things that are clogging them up, empower the team with a business process to periodically review the ROI of the analysis and how popular it is. Set a bar for minimum expectations, and discontinue anything that doesn’t meet it. For example, if a report is only being used by one or two people, that’s a pretty good sign that it could be discontinued. The whole power of reporting is creating common measurement of performance that everyone can get behind. So, if a complex analysis is only interesting to one or two people, then chances are they aren’t aligned with the rest of the organization.

A sure-fire way to test the popularity of a periodic report is to just let the report take a vacation. If you don’t provide the report, does anybody come asking for it? If not, then you’ve just liberated some bandwidth for your Data Team.

But you don’t have to stop there … you can unclog your Data Team even further with the next tip …

Tip 4: Hold some reserve capacity for emergent work
Important and urgent things come up, and when they do, Data Teams often drop everything to respond. So why not maintain some reserve capacity for this? You can even review your past urgent and important requests to get a sense of the timing of these requests … year end, month end, just before planning sessions, etc.

As a Data Team when you plan out your week, and assign responsibilities, try as best as you can to not schedule every last hour. Build a couple hours of flex into every day, or plan for “catch up” days. Worst case scenario, your team members can get ahead on some neglected projects with this flex time. Best case scenario, when your CEO calls needing something urgent, you’ll be able to impress them with your ability to respond quickly.

If you have stories about how you’ve unclogged your Data Team, please share them. And as always, please feel free to connect

Via our website: http://www.analysisworks.com

Via LinkedIn: http://www.linkedin.com/pub/jason-goto/2a/bb/a5a

Via Twitter: #analysisworks

Note: What is a Data Team?
When we refer to “Data Teams” it’s a catch-all for groups of technical, statistical, and subject-matter domain experts that are involved in providing information to support their organization. These teams are sometimes called “Business Intelligence”, “Decision Support”, or “Information Management”, but they can also be internal consultants such as “Operations Analysts”, “Strategic Information” or “Research”. Many of these concepts equally apply to teams of Data Scientists.