5 Tips for Making Your Next Big Data Project A Success
Over the last several years companies have invested a significant number of dollars in big data projects. Depending on the organization the projects are started in a variety of ways. Some companies want to become more innovative and provide a wide-reaching goal, some want to adopt artificial intelligence and see big data as a foundational element, and some just want to better understand their business and customers. Although there has been a lot of investment in data, executives are becoming disappointed in the outcomes of their investments.
The team at Stonehill has significant experience driving big data projects and ensuring that they have a positive ROI. We work across departments, spend time understanding how individuals execute their jobs, and discuss what information would allow leaders to make better decisions. In order to remain effective, the team follows several principles to ensure that outcomes remain focused and results are accomplished in a limited amount of time. Here are some of the guiding principles; I hope they help make your next big data project a success.
1. Define What You Want to Accomplish – The first thing you need to do is to define what you are trying to accomplish. This seems logical, but as previously discussed, many projects are started with a goal of using big data. Good goal statements traditionally have an identified person/department, an action verb, and an outcome. Some common examples of this include “Identify households that will purchase our services within the next 12 months” or “Increase cross selling of banking services to new business loan customers.”
2. Establish a Cross Functional Team – Although data scientists are important to the completing the project, they are only effective when paired with other individuals from the organization. Consider creating a team that consists of individuals from sales, marketing, operations, and finance. Everyone will see the project through their own lens and will prioritize items that positively impact their department.
3. Map the Journey, Identify Available Data, and Define a Scorecard – Before you jump into analyzing mounds of data, spend some time to document the variables that you are trying to influence. Identify key inflection points in the process or the “moments that matter.” Work to understand what data you need, what data is available, and what initiatives need to be put in place to capture missing information. Create a scorecard that shows leading and trailing indicators – helping you to understand if your project provided impact.
4. Create a Simple MVP (Minimum Viable Product) and Expand Later – Once you finished the above, it’s time to start building. Don’t try to boil the ocean in one sitting. Create a small model that will allow you to understand the flow of data and potential interconnections. Use technologies and tools that are available – you don’t need to be an expert in R and Power BI to be a data scientist. Excel is a great tool and provides a lot of functionality that most people can use.
5. Communicate, Get Feedback, and Create Ideas – This is one of the most important steps, but it is also commonly overlooked. In order to have a great big data project you must build something that provides value, is simple to use, and that people will actually use. The easiest way to accomplish all three of these goals is to include the user in the development process and integrate their ideas. Keep them informed on the progress, communicate when you make updates, and celebrate when they use the outcomes.
As you begin to plan your big data projects, remember that Stonehill can help. Our integrated services include analytics, marketing, service design, and organizational design. Our team can be reached at 813-444-1984 or info@stonehillinnovation.com