“The pace of change will never be as slow as it is today.” So said The Economist’s Matthew Bishop back in 2015. It’s a daunting thought, considering the phenomenal rate at which technology is advancing right now and how far it has come.
But it should also be heard as a call to action for large organisations looking to mature their data analytics capabilities to help them solve their most pressing business problems.
Innovations including artificial intelligence, robotic process automation and the Internet of Things are advancing at an exponential rate. And for companies set on executing three-year digital transformation plans, that can prove a tricky business.
But it’s important to note that while analytics tools and techniques are rapidly improving and keeping pace with technological advances, what doesn’t change approach to solving these problems. That means that businesses can establish a standard analytics process that underpins the tools used, and can continue to be relied upon, whatever the future brings.
As PwC Australia’s chief data scientist Matt Kuperholz explains as part of PwC’s Board of the Future initiative, the standard analytics process is the foundation for increasing value from data, and for businesses to become an analytically enabled organisation:
- BUSINESS UNDERSTANDING Start with a business problem, not an analytics problem. Have in mind what you’re going to do with the solution.
- DATA UNDERSTANDING Understand the assets you have within the organisation and externally (eg social) and how you’re going to use them.
- DATA PREPARATION This is where the art and the science of data mining really adds value. Fantastically prepared data using a less powerful technique delivers more value than poorly prepared data with a leading edge technique.
- MODELLING Choose and apply various analytics modelling techniques. The techniques depend on the problem you’re trying to solve.
- EVALUATION evaluate your models against the business need before you roll them out in your business.
- DEPLOYMENT now you’ve got to do something with it. Too much analytics turns into shelfware to collect dust.
Remembering that the process (and there is more than one) is more important than the tools used is the key to scaling data analytics and ultimately using that data to deliver insights that can help a business meet its goals.
In this video, Matt gives some practical, process based approaches that can make a substantial and long lasting difference.
For further insights, visit PwC’s Board of the Future initiative.