As we continue to move into a more digitally orientated business environment, organisations have an astronomical amount of data at their disposal. Over the next few years businesses will deal with more data than ever before, with IDC predicting that the digital universe is expected to reach 40,000 exabytes by 2020.
With access to such vast swathes of data, many companies will naturally consider how they can derive business value from the information they have access to and consequently look to add data scientists to their payroll to drive this. However, before they do so, business leaders would do well to take a step back to check that they will be spending wisely.
Effective data analytics requires expertise
The data that companies today hold is not only vast but is so incredibly complex. Simply sending existing staff on a short course or hiring an enthusiastic graduate is not going to help businesses gain the benefits from their data that they are looking for – the people they bring in need to truly understand the industry they are working in and what the data is telling them.
While the quality of staff is crucial to understanding data, the business must also have a clear strategy in place for extracting value from data, and agreement on what that the project should achieve. An organisation could have huge pools of data and the best staff in the world, but if they don’t know what they are looking to achieve with this information, the project is likely to fail.
The importance of a clear strategy
Organisations that have a clear strategy with an end goal in mind benefit from data projects most. For example, AkzoNobel Marine Coatings worked with Tessella to develop an award-winning predictive coating efficiency application using 3.5 billion data points. From the beginning of the process the business had a very clear vision of what they wanted to do with their business and how data would support it.
This was important in an industry where coating selection can make a significant difference to a vessel’s operational costs and environmental performance, it was important to ensure that the team involved in the project approached it from a point of experience.
However, our teams would not have been able to work to implement this detailed and successful project without AkzoNobel providing us with a full brief on their plan for the data and what was to be achieved. This allowed our staff to go in and get straight to work to find the most valuable parts of AkzoNobel’s data and harness this to quickly and efficiently develop the product.
The key to successful data analytics projects
Businesses that are looking to use their data to innovate will need to analyse what experience and information they have at their disposal, and what will be the best course of action to gain the biggest benefit from it.
From there, organisations can look at who and what they need to bring in to make the most of their data - because the most powerful tool that successful businesses will have when it comes to data analysis is expertise and planning. If you'd like to learn more, we read our executive guide to data analytics.