Advancements in data science are making it easier than ever to predict your business performance.
Winning in business is a complex game. In any business, each of the areas you invest in affects the other, in a completely non-linear way. Your marketing spend affects your supply chain. Your supply chain affects your IT infrastructure. Your IT infrastructure affects your advertising spend… And they all affect, and are affected by, your customer experience. In today’s data-rich world, it should be possible to invest precisely in the initiatives you know are going to deliver a brilliant customer experience and optimal financial return. But making it happen can be a challenge.
The world of data science is advancing fast. Some of the most exciting advancements include machine learning predictive models and simulators, such as Bayesian Networks, that determine how all the elements in a complex system work together: which variables affect each other, and to what extent, so you can predict what will happen if you change one thing or multiple things in your system, before you spend the time and money on making a change. These simulators often come with simple visualizations so you can see quickly and easily which variables are having the most impact.
This kind of predictive modeling is starting to revolutionize the world of business. As business data systems become more and more connected, models become more automated and self-learning, and UIs become simpler and more powerful, accurately predicting financial outcomes will become more and more possible.
How to win in this new world:
- Be clear on goals and metrics: Machine learning helps you optimize key metrics – so make sure you are focusing on the right ones. Know what success in your business truly looks like and start from there.
- Perform a data audit: Understand all of the data available to you. You probably already have most of what you need. Identify gaps and build plans to acquire where necessary.
- Start with a simple model: Don’t rush to the most complex, trendy model. Often a simple initial model will identify the largest areas for improvement.