If you’re not on the data science wagon yet, you should probably consider jumping on in the near future. With 2020 right around the corner, data will continue to remain at the forefront of decision-making – and we’re bound to witness ever more ways it can evolve the marketplace.
Still convincing yourself that data can help a business thrive? Here are three benefits that might make you think it can.
It can improve efficiency.
In an episode of the Go beyond disruption podcast, Elaine McVey explained how data can help companies optimize how they’re carrying out their business. For example, it can provide a deep understanding of a customer’s journey through the sales pipeline. Once you measure what clients want in their purchasing quest, a clearer picture of what’s working – and what’s not – will come into view.
You’ll communicate with customers or investors more effectively.
Once you learn what your customers want, you can give it to them. Data can also help quantify and predict the impact of the work your company is doing so you can communicate it to customers or investors. Probably one of the most well-known examples is how Netflix uses data to drive success. Users’ data profiles enable the company to understand what plots work with different audiences – which creates new business models and opportunities.
Silos will start to break down.
Finance and business leaders will have to work cohesively with people on the data side. During her interview, McVey said that people on the data side shouldn’t be intimidated by their lack of understanding of finance, and people on the finance side shouldn’t worry about not understanding all the technical parts of what a data science team does. It will be important to learn how to ask the right questions, discuss pain points, and come up with solutions together.
Ready to take a deeper dive into data analytics? The AICPA offers a Data Analysis Fundamentals Certificate which provides you with knowledge on the different job roles involved in analytics practice and the most commonly encountered technologies in today’s data ecosystem.