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This article was written by Starmind's founder and CEO, Marc Vontobel.
People working in large organizations spend a lot of time looking for answers. In the last 2 years, 90% of the world's data has been created. 2.5 quintillionbyte of data is created every day, with the number growing. Our understanding of how to manage data has not grown with the amount of data we produce.
Workers and businesses are starting to see the extent of the damage. Employees can't find the knowledge they need because they are overwhelmed by data. Business productivity, employee collaboration, project completion efficiency, and innovation all suffer. Before the gap between data production and management becomes too wide, businesses need to tackle data overload. We need to increase access to knowledge and improve problem-solving speed to drive engagement and productivity at work. Here is how we start.
Identifying redundant or outdated data.
It is hard to find what we need as data pools grow. The useful and the trivial all coexist. Manually sifting through all this information takes valuable employee time and leads to low productivity.
Consider how businesses treat their data. You finish a piece of work, whether it's a spreadsheet of sales targets or a project status update, and you save it to various databases. What will happen next? Usually, nothing. Over time it becomes redundant because it is simply stored. It is difficult to understand whether the information is useful or not when a colleague stumbles across it.
We are talking about more than a couple of documents. More data is produced each year than there are stars in the visible universe. It is no wonder that when we fail to manage our data, the space between us and the information that we seek feels useless. A survey from the International Data Corporation showed that enterprises are struggling to deal with their own data.
outdated data harms the productivity of entire businesses despite its potential, despite being damaging to individual workers. The impact of how businesses use data and enable access to valuable knowledge will have a make or break impact on the organization. How do we get better at this?
Artificial intelligence to enhance, not replace human knowledge.
The data overload challenge is a collaboration challenge. People become overwhelmed when they can't find what they need. Improving access to knowledge by better connecting experts helps to tackle this.
The benefits of contextualizing data and using artificial intelligence are shown here. The key to unlocking knowledge is all that information which is overwhelming.
To enable true knowledge collaboration and connect employees with the information they need, we must start using the data we have in organizations to draw conclusions. We can connect people with questions to the right person.
Artificial intelligence has two important qualities that help businesses achieve this and overcome the issues with legacy knowledge management to date.
First, it is possible to teach the artificial intelligence to forget. This means that it can identify who knows what about a topic, but it can also recognize when information is redundant and not useful, meaning it can forget. Second, using non-sensitive information drawn from existing tools, is able to see through silos. It can use all kinds of information to draw conclusions at scale, creating a live map or a knowledge network of who knows what within an organization.
Data can be used to build a network of knowledge and expertise. Everyone can access the most up-to-date and accurate information when searching for answers, so that they can help instantly.
It is time to embrace the role of artificial intelligence in tackling data overload. We can leverage data in a way that businesses and employees want: to connect, solve problems, and find answers.
Starmind is a company founded by Marc Vontobel.
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