One of the great things about being a consultant is that you are able to work with a lot of different people in a lot of different industries. Whether it was the short, team-based client projects that I started with or the longer, more independent projects I am doing now, I have learned that every opportunity to take a client's data and turn it into something usable and insightful provides a unique and valuable learning experience. With that said, let's look at some of the central themes that I think define all data analysis projects, no matter the industry. These are the ideas I always keep in the back of my head when working on a project and I believe they are all important for driving successful outcomes in this amazing industry space we find ourselves in.

Remember Your Audience, From Initial Exploration to Final Product

When I was just starting to make data products for clients my inclination was usually to share my entire thought process. This meant detailing what I planned on doing every step of the way, the struggles I was inevitably going to have with their data, the colors their dashboard was going to have, and so on. There were two problems with this approach. One was that usually, my audience didn't have the expertise to weigh in on these concerns. At times I was opening the door to audience input that wasn't going to serve me, or my final product. There is value in remembering that when it comes to data analytics, you are usually the expert in the room! You don't need to show them how the cake was baked, just let them taste the final product and be wowed. The second problem with oversharing is that usually the audience is on the business side, and they either don't know or don't care about what is happening on the backend. It is important to remember your audience and that usually means focusing on outcomes, as opposed to the steps needed to arrive to those outcomes. Now, there are times when I am presenting to a business intelligence team and can get into the nerdy details that make us love what we do, but I have found those situations are very rare. Remember your audience.

Define The Final Outcomes Early On and Follow Through

I've found with clients that when they realize how their boring tabular data can be turned into some powerful, insightful visuals it is comparable to an addict having their first hit: They will just want more and more! In the context of a business that has well-defined budgets and fiscal plans, it can be difficult when the client suddenly wants to add a mountain of enhancements, some possible and some not, to what was basically a final product ready for release. Take the extra time and effort early on to establish clear expectations for the final product with your client. Usually, this involves having a clear list of questions that need to be answered and key features that will need to be available, such as filter options. With a well-established plan, it will not only be easier for you to make the product, but when you are presenting the final product to the stakeholders you can remind them of those initial goals. If they want enhancements that fall outside of the initial scope that isn't a problem, but it's important they know it may require more time and resources to make it happen.

There Will Always Be Barriers to A Succesful Product

One of the biggest and most consistent mistakes I make when defining the scope and timeline of a project is not considering all of the external barriers I will run into to. When I get a new project my first thought usually tends to be: "Wow there is only one data source and two questions to answer!? I should be able to knock this out in one afternoon!" As a result of this dangerous thought process, I end up selling the project as limited in scope which makes the client believe they'll be getting their product in no time. Then I start the project and realize I'll need access to be granted by the remote worker on the other side of the world. Uh oh! Turns out the remote worker just went on vacation and I need to find an alternative person. A week later I've finally been granted access but now that I see the table I realize there is column-level security and I have to put in an IT ticket to get access to the fields I need. Even if you think you can make a data product in little to no time, it is important to recognize you are going to run into problems outside of your control and preemptively expand the scope! Although you may feel like you won't need the extra time, being accurate with your deadlines will better serve you and the client long term.

When it comes to data analysis projects, what are the key ideas you always keep in the back of your head and how do they help you create successful outcomes? Reach out on LinkedIn or Twitter and share your thoughts with me!