Access to data helps many companies respond better to their customers' market needs and optimise their processes. Making data-driven decisions is a necessity to stay competitive. With the modern software tools and measuring methods available today, the amount of data on hand is no longer a limiting factor. Collecting data is one thing, however; the need for structured analysis, documentation and storage is becoming more and more pressing.
The reason? More and more business decisions are based on data, which also means that employees who specialise in data play an important role. Data semantics, or helping to interpret and structure your data, will therefore play a crucial role in many organisations in the coming years.
An example from healthcare: stress measurements and data
Imagine the hospital where you work has developed a new technique for measuring stress through perspiration and blood pressure. Suddenly all kinds of new data appear, which could now be used to make well-founded decisions about health. But how do you do that without mistakes, and without running the risk that the interpretations may not be entirely correct?
This question is still asked a little too rarely. And that while collecting data is only the start. In the healthcare sector, for example, very advanced analysis techniques have already been developed to interpret measurements of people's blood pressure and blood oxygen saturation, and that data can be interpreted correctly. But what if we look back at our example about stress? This variable is currently measured in very different ways, so it can also be interpreted in very different ways, with all the consequences that brings, including potentially wrong advice to patients. What's more, there are currently no validated guidelines for handling physiological stress data. Collecting data is only the start, even though many companies see it as an end goal.
From collection to interpretation and documentation
So how can you tackle this challenge in your company in practice? Put data semantics on the agenda. This term covers everything we mean by structuring, documenting and interpreting data. You can get started right away with the following concrete tips:
Three steps to get started
1. Never interpret your data on its own; also look at the context in which you collected it.
2. Make your employees aware of this issue and involve them in your strategy. When people better understand the possible consequences of wrongly interpreted data, they will be motivated to carry out critical analyses.
3. Work on protocols for data interpretation within your company, and on documentation about them. That way, knowledge can be passed on from employee to employee, and from department to department.
The key to value from data
In an era in which data is the driving force behind progress, data semantics is the key to unlocking the full potential of information. It not only gives meaning to data, but also opens the door to a world of possibilities, ranging from smarter decision-making to advanced artificial intelligence.
Are you facing specific data challenges in your company? Harmony is always ready for a conversation or a brainstorming session. Feel free to contact our Business Consultancy team.
