Reducing Information Noise: Need of the Hour

Reducing Information Noise: Need of the Hour

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 Five Vs of Data: The Causes of Information Noise
  • Volume
  • It refers to the data existing in the system and all the new data generated and collected regularly, that is, the total size and the amount of data that knowledge workers collect.

  • Velocity
  • It refers to the pace at which details generated and moved in the system. Though it is essential for companies that need their data to flow quickly to make the best business decisions possible,it also becomes a pain point for data workers who have to collect the vast volume of data, store it, and process it at high speeds to gain meaningful insights.

  • Variety
  • It refers to the diversity of datatypes. Organizations obtain data from different sources, both internal and external. A data worker’s challenge is to standardize and distribute all the collected data. This is challenging because data collected can be structured,semi-structured or even unstructured. Unstructured data is unorganized and comes in multiple files and formats, making it difficult for the data workers to fit into conventional models.

  • Veracity
  • It refers to the accuracy and quality of data. For instance, gathered data could have missing pieces or may not provide accurate, valuable insights. In addition, the reduced trust in data makes it difficult for the workforce to operate on it.

  • Value
  • It refers to the utility that data provides and relates to the importance of data for business decision-making.Some industries have put a high value on data as its utility to make business decisions is time-dependent. This value increases because of data decay, the gradual loss of data within a system. This makes it critical for the data workers to operate and utilize the data as quickly as it is generated in the system.

Information Noise: The Bottleneck

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:

  1. Inability to comprehend the pool of existing information
  2. Inability to track,manage, and retrieve data on time
  3. Inability to find the right source to collect data
  4. Inability to access information available
  5. Feeling overwhelmed by the need to absorb vast quantities of data

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.

The Perils of Excessive Exposure to Information Noise

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.

The Solution: Integrated Data Management

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.

  • Set information objectives by identifying the key areas that are most relevant for and prioritize those by importance and timelines.
  • Set the information sources to streamline from where you receive information, in what frequency,and of which quality.
  • Set aside time for reading to have a broad perspective on what is happening in your organization, competitors’ organization, industry, economy, and nation in general.
  • Filter aggressively and scan every piece of information you receive thoroughly to know what hold ssignificance and get rid of the useless information.
  • Develop structuring and organizing skills to sort information and manage them into meaningfully structured sections, sub-sections, folders and directories.

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:

  • Discover all the relevant information in one place.
  • Search through auto-organized data easily and quickly
  • Enjoy high-level data security and privacy
  • Have enhanced user experience with customized feeds
  • Save time by quickly searching, organizing, retrieving, and processing data
  • Collaborate with fellow data workers and people in their network

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.

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