The curse of scope creep when working with data and how to avoid it

I love data, and I’m curious. In many ways working as a research analyst was the perfect fit for someone like me. Data analysts, in essence, exists to unearth insights that will result in a market advantage for their clients. That’s it. But to reach that point many peripheral actions needs to take place. I'm referring data extraction, cleaning of the data, preparation – and that is even before you start getting into the good stuff. Afternoons could lead into never-ending quests of analysis looking for that Golden Insight that will give my clients brand an unfair competitive advantage and me a promotion. Unfortunately, this effectively took many nights away from my family, time that I would never get back. Sounds familiar?
Welcome to a phenomenon called scope creep. Scope creep frequently happens to data analysts, but it can happen to anyone with a penchant for perfection. I call it scope creep when after finding a set of insights that completes my deliverables and goals of a project, an additional set of ideas is sought to expand the understanding of a particular event all within the same framework of time expectations for completion of a project. A team member can propose this or even (long sigh) yourself. It 's okay to find insights that will change your understanding of a problem and for you to want to explore more! I propose that when this happens, we need to let our team know that this is normal and that if its desirable to pursue, then you will need additional resources to continue down that rabbit hole.

So here I want to leave you with some steps to prevent you from ending up like me in the office past 10 pm at least due to scope creep.

1)    Identify the business problem that you will take on board based on the total value contribution that solving that issue has for your organization. Like I said before, not only data analysisrequires lots of work, but its very time consuming. I want you to make sure to choose the work you will take on considering how impactful it is. Even if this means saying “no” to a friend. In the end, your boss and your team will appreciate your work more when they notice the importance of the projects in which you take part.

2)    Set up the expectations by making sure that you explain the time commitment and requirements. To do this as accurately as possible, you will need to receive as much information as possible regarding the project. Familiarize your client with the time required to prepare and analyze data once you can collect the information necessary to start the job. Give yourself ample time to under promise and over deliver.  Also is important to communicate that in data analysis is not a project where everything is defined. It will be a good idea to ask them if they have a plan if what you find is not what the are expecting. Finally, keep your client abreast of the progress and updated along if facing challenges with the data.

3)    Complete the promised deliverable. If additional requests emerge, you can always set up a follow-up project with a new timeline.

There's no better feeling like one of incredibly productive in the most important situations at work. The trick is to keep having a life while at it. By having a direct and clear communication with your peers regarding work expectations, you are doing them and yourself a big favor and avoiding scope creep from taking away precious time from the people you love the most.