If 53% of companies can’t utilize data because of a lack of analytical skills, what is the point of collecting gazillions of data? According to the survey that quoted this issue with data consumption, another challenge is that 48% of teams face technical inefficiencies using data.
Data has exploded in every field, and companies are trying to make the best use of it. But these analytical and technical gaps often show up as a road blocker in data literacy.
But what exactly are these issues? And what is data literacy? Let’s see what stops organizations from utilizing data.
Data Literacy and the Hurdles Companies Face
What is Data Literacy?
Data literacy is the capacity to understand and use data for making decisions and taking actions.
It is all about understanding the data you see, making correlation among various aspects of data, and comprehending the presentation in tables, reports, graphs, and charts. It may also mean extracting the meaning from these presentations and changing the displays to suit your needs.
Not only consuming is the capability of a data literate but also figuring where information is misleading or misrepresented. But that is at an advanced level.
Since most employees are not educated in statistics and data analysis, promoting and establishing data literacy could be challenging. But it’s only a myth that data consumption needs you to be educated in the field.
What are other hurdles?
The speed at which technology—specifically related to data and intelligence—is evolving, many employees might not catch up with the revolution. The company’s culture could be a major show-stopper as well.
However, change starts at the top level. If the management is not data-aware and an enthusiast, the trend might not cascade down to the employees consuming data. So, the data-first approach should start from the cabins of the C-League.
People in traditional industries like manufacturing and government offices have been working with papers and legacy systems. They don’t know the scope of business improvement hidden beneath the layers of data at times. And anything unknown is inexistent. Right? Only until it is discovered, though.
Fear of Change
Employees who are technologically challenged are often resistant to using high-end tools. Their skewed idea of ‘I’m not the right person’ or ‘I don’t need this’ is a big barrier, too. Sometimes, people trained in traditional ways fear learning new techniques and lack the spirit to attend training.
Procrastination is another hurdle in the road of data literacy. Assuming that data literacy programs and learning niche BI tools should be the target of data engineers and analysts is a myth, too.
Your employees in every department can use a BI tool that helps them solve many problems. They can at least zero-in to the reason for issues. But the fear of change stops them to adapt and learn.
Technical Challenges with Data
Your company might have data-literate executives, and your enthusiasm for using data in decision making is genuine. But your data collection could still be at the nascent stage, which is only a start.
If you have adopted the data-centered culture only recently, you may not be equipped with the right tools and awareness. Possibly, your collected data is limited and can’t be put to good use yet. Or conversely, the amount is voluminous and varied. Unstructured data from social media, voice calls, emails, and graphical content are difficult to manage if your analytics curve is not matured enough.
If your processes are not spot-on, you wouldn’t be able to publish the data in a simplified manner to your employees for unveiling insights and making decisions. What if your numbers are wrong or incomplete and don’t reveal crucial information?
The answer to major hurdles in the journey to make your organization data literate lies with Augmented Intelligence.
How Does Augmented Intelligence Work in Addressing Data Literacy?
Augmented intelligence supplements human intelligence using AI and its associated branches by taking quick yet fact-based discoveries and decisions.
Establishing a correlation between datasets and understanding sophisticated representations like graphs and charts may sound technical and complex. In reality, the tools that use natural language processing (NLP), machine learning, and AI helps a layperson understand data who is not statistics and analytics experts.
Traditional BI tools with complex UI that demand the presence of data experts even to change or understand a dashboard are obsolete now. Modern tools like Qlik Sense facilitate drag and drop features to create visualizations. This intelligence augmentation software is NLP enabled for voice-based data analysis.
Here is how Qlik, as augmented analytics software, addresses the problems in data literacy.
Your employees, who are not analytics experts, can use search operations. These operations work on text and numbers and change the display in the visualizations immediately. The process is natural language search enabled.
Imagine an HR searching for a particular employee in a report? They might need to pull the data in a sheet and search manually for analysis. Qlik Sense makes such searches easy and offers context search, too. NLP has made it possible.
Once you have completed the search or performed an operation, you need not brainstorm the apt chart or map to present your numbers. Qlik Sense chooses a suitable representation that suits your data. But if you want to change, you get ample of suggestions on the same screen.
As mentioned earlier, your workforce can use natural language. Despite unaware of the data and relations between various datasets, Qlik enables them to type in and modify a dashboard.
You can even speak to pull in desired fields in your reports to reveal the insights hidden so far. All real-time data right at your screen within no time.
What if you can do this in multiple languages? A super feature, right? Qlik Sense is capable of that.
Augmented intelligence in Qlik Sense uses machine learning to automate your tasks. Once you start using Qlik Sense, the tool helps you in cleaning and preparing your mundane tasks and free you from the trivial efforts.
Suggesting the right insights based on your search and intent is another automated task with Qlik.
Before you Leave
Drop your comments below if you have thought about using augmented analytics and the intelligence it generates in organizations. Or are you already using highly intelligent analytics tools that make data literacy easy to embrace even by a layperson?
If your reply is no to the questions above, contact the team at Logesys, which has been an augmented intelligence consultant to clients in various industries. Feel free to initiate a conversation for a consultation call.