Analytics & Insights
Leverage data science and augmented intelligence for optimal profitabilityRead More
Author: Meghan Villard
If your organization hasn’t yet invested in data science, they will soon. From manufacturing, to healthcare, and even to the non-profit world, mining data for new and actionable insights has become one of the most effective ways to grow a business or solve a problem.
Data science differs from more traditional analysis by applying the rigor of other scientific disciplines to process and review large amounts of data, often making connections that would otherwise go unrecognized. However, just like any other business function, data science needs support to strike insight gold.
How can an organization set themselves up for success? RevGen recommends using this strategic framework to make the most of your data science projects.
Much like any other initiative, a data science project must be aligned to the organization’s broader goals. Whether it’s a project to uncover why employee turnover is so high, identify where time can be saved on an assembly line, or better understand how customers are responding to your marketing, there must be a strategic impact in mind.
Some of the pre-work involved includes:
Let’s say your organization wants to understand the customer base and why churn has increased month-over-month. If you are the Chief Marketing Officer tasked with understanding and preventing churn, the pre-project checklist might look like this:
In many cases, this step requires the most attention, as there is usually a plethora of problems, opinions, stakeholders, and KPIs to consider. It’s especially daunting when considering how to measure success, as there’s often not a single “silver bullet” metric. Working through these initial questions will help your organization strike the right balance and start your project off on the right foot.
Most people assume this step is the entirety of a data science project. It’s true that the data discovery, cleansing, exploration, feature engineering, and building a model takes significant brain power and coding – but there are many pre-built packages and frameworks to streamline this process.
Typically, RevGen’s Data Science team follows this pattern when approaching a new project:
There are many different methodologies with which to approach your organization’s data. For instance, machine learning is a very popular approach but isn’t necessarily right for every project. This is another reason that understanding the goal is key – it’s far too easy to realize in hindsight that your team might have been better off taking a different analytical path.
Of course, insights are only as good as what you do with them. As we mention in our Business Strategy to Execution framework, understanding your business enablers will help your project take that final step from learning to action. This means looking into the people, processes, and technologies that can turn an idea into a reality.
Let’s use our marketing example:
The power of data science is truly awesome – in the oldest sense of the word. It can be a massive boon to every organization, but without strategy and action behind it, projects quickly become overwhelming and difficult to capitalize upon.
No matter what your current data science capabilities are, RevGen can help guide you through the process of optimizing your business with the power of data. Contact us today to schedule a chat with one of our in-house data scientists.
Meghan Villard is a Manager of Data Science at RevGen Partners. She is passionate about empowering clients to make data-driven decisions that deliver value to their business.
Susan O’Connell is a Director of Client Services who understands the ins and outs of data management, business intelligence, and the importance of bringing people together to create the best possible solution.