The world we live in is witnessing an information transformation. Though technological advancements have made it easy to consume information, they have also led to the proliferation of data in large volumes and diverse formats, from multiple sources, at varying paces, and with different significance. As a result, knowledge workers have now moved from a world of data scarcity to one where terms like big data and information overload are not unheard of. Moreover, this transformation has resulted in abundant data and demands considerable efforts to collect, store, organize, retrieve, and analyze it. Thus, it also proves to be one of the most critical factors impacting productivity loss regularly.
There’s no denying that information is the most valuable asset in the knowledge economy, which is valid for the current hyper-competitive business world. However, the abundance of information that knowledge workers consume today has swamped them, significantly affecting productivity and efficiency. The tidal wave of information impacts how companies function and perform. When consuming information, knowledge workers, researchers or analysts, say in an asset management company, traditional bank, fintech startup, or investment management firm, consume raw data from news articles,journals, research reports, or images posted on social media. Such data overload leads to high information noise. The more data they consume, the less they perceive because the ratio of useless information increases.
As the world moves towards digital transformation,data generation expands at a breakneck pace. On the one hand, emerging technologies like machine learning and artificial intelligence are helping knowledge workers mine enormous banks of information. However, on the other hand, they fail to convert the incoming data into usable and relevant information. This is due to the 5 Vs of data, which are explained in the following section.
The 5 Vs of data give rise to what is called the Information Noise! No matter the industry, everyone is generating and consuming volumes of secure and unsecured data, making a home for information noise.
In essence, noise is an unfiltered stream of information in which valuable data is reduced directly proportional to the amount received. Thus, information noise is random information that is useless and needs to be cleaned up to make sense of what we are perceiving. What makes data overload a significant concern for today’s knowledge workers is their:
Why information noise has become a buzzword in 2021 is because when businesses acquire vast information, the chances of coming across unfiltered information increases manifolds, consequently impacting their efficiency, productivity, and ability to focus on making key decisions for the business.
Why is it essential to reduce information overload,why businesses should look for proven ways to reduce information noise, and howto accomplish it are some questions that business owners and knowledge workers need to answer.
Those in corporations or policy making are endowed with a sophisticated statistics department via which they get a lot of “timely”data, affecting their abilities to make decisions. Likewise, in business and economic decision-making, data causes severe side effects. This is because today, knowledge workers and professionals are inundated with the vast information coming from multiple sources, both unstructured or structured. Notes,chats, data from external organizations like Google Trend Reports, e-journals,and call logs pour in from all sides, and the introduction of e-mail has converted the torrent into a flood. As a result, they have to sift through excessive volumes of data at a high velocity to stay at par with the ever-evolving business environment and make well-thought-of strategic decisions.
There is no quick solution because training and improving data workers’ ability to operate quickly on vast information is a long-term process that demands work. However,implementing the following ideas can help knowledge workers be more productive and cope with the new reality of information overload.
The solutions mentioned above may seem helpful at first, but they might not prove to be practical and appropriate in the long run. And this is where integrated data management comes to the rescue. With the technologically advanced Artificial Intelligence tools that put machine learning, cloud computing, and natural language processing touse, knowledge workers today can automate workflows and sift through information without any hassle. From locating a message encrypted in an image shared across a chat platform to identifying beneficial information in a pile of unstructured data from a conference call, managing data into a single repository brings along a vast range of benefits. Numerous time-consuming tasks can now be performed with just a click or two. Integrated data management allows data workers to:
It is high time to realize that information is a valuable commodity but not worth hoarding because the more we have of it, the more overwhelming it can get. However, we can learn more than ever before and make changes that can steer the rudder for business success with well managed, streamlined, and integrated data. With AI-powered tools, now you can analyze, leverage, and unfold the potential of unstructured data.
