How To Empower Businesses Through Real-Time Insights And Actionable Intelligence

In the age of digitalization, organizations are building next-gen use cases that are helping them either do what they are doing today more effectively or unlock new opportunities altogether

Making sense of the data collected makes businesses navigate through changing consumer behaviour, operational complexities, new business opportunities, and competition.

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By Hamir Singh Thakur

By integrating processes and systems that were previously disconnected, operational technology has changed the business landscape. Data has taken centre stage as manufacturing enterprises rapidly adapt to the Industry 4.0 model. As an example, manufacturing organizations today are trying to harvest data and information across their raw and finished material, manufacturing processes, machines, and operators using varied sources, including Internet of Things (IoT) devices, sensors, machines, aggregators, RFID, and barcoding to name a few.     

However, while a massive amount of data is generated, only some of its information is useful. Making sense of the data collected makes businesses navigate through changing consumer behaviour, operational complexities, new business opportunities, and competition. This is where the role of real-time insights and actionable intelligence comes into play.

The need for data and real-time insights

In the age of digitalization, organizations are building next-gen use cases that are helping them either do what they are doing today more effectively or unlock new opportunities altogether. Even at the core of Generative AI (Artificial Intelligence) is the power of the vast amount of data made available to the AI models – Industry 4.0 use cases are no different.

However, to build use cases – an organization must be able to create and filter the correct data. For example, to generate the correct data across Industry 4.0, companies must deploy a hybrid stack of technologies, including operational technologies such as Barcoding, RFID, IoT, and BLE.     

Subsequently – refined and relevant data must be available to the appropriate business functions at the right time. Else, it can inhibit organizations from agile decision-making, efficient operations, mitigating risks, and more. Therefore, organizations require real-time insights to make timely decisions and gain a competitive market advantage.

Real-time benefits

The accuracy of many business decisions depends on the appropriate use of data. Real-time business intelligence tools and solutions can open a world of possibilities for a growing business. It can offer self-service data discovery with control, a degree of compliance, and insights. However, they will only be helpful if the companies know the true worth of this data, have a solid infrastructure to store, clean, and interpret data promptly, and, most crucially, ensure that the data collected is accurate. This facilitates proactive decision-making and enables rapid responses to significant changes. As a result, organizations can react quickly to changes, whether they are procedural or trends.

Actionable intelligence: the key to effective decision-making

In a recent Harvard Business Review poll, 86 per cent of organizations stated it was essential to extract new value and insights from existing data and analytics applications, and 75 per cent said it was crucial to provide employees with actionable intelligence throughout the organization. Actionable intelligence helps businesses filter vast amounts of data, using sophisticated algorithms to spot patterns and outliers and overlaying the data with user-specific activities. As a result, companies experience enhanced operational efficiency and market performance as it facilitates efficient decision-making through real-time insights. Moreover, according to their needs, some organisations can incorporate AI (Artificial Intelligence) and ML (Machine Learning) elements to get progressively smarter.

Harnessing IoT and advanced analytics for real-time insights

The widespread adoption of Internet of Things (IoT) technology has accelerated growth in connected IoT endpoints, continuously creating enormous amounts of data. However, this data is prone to volatility, and if not utilized correctly, it might result in missed opportunities.

In this sense, advanced analytics like predictive and prescriptive analytics can aid firms in making effective use of data. Machine learning is incorporated into predictive analytics to find trends and the likelihood that specific events will result in outcomes. For example, companies can better understand the current state of equipment and predict their future health using predictive analytics.           
Prescriptive analytics offers more information on the steps a business may take to influence the outcomes of descriptive or predictive analytics. Organizations benefit from having a greater understanding of how to avoid or boost outputs, increase effectiveness, and more.

However, poor data quality concerns, including incomplete or inaccurate information, can result in wrong forecasts, and overfitting in models can result in rigid predictions that cannot adapt to data changes over time. Therefore, enterprises should put data quality guidelines into practice and monitor model projections to procure better results.

All things considered

In this fast-paced world today, technological advancements have crucial implications for businesses and have the potential to impact industries. The connected business model, which enables improved visibility into each process and allows all components to communicate, is what organizations will look like in the future. In this regard, real-time insights and actionable intelligence can provide the much-needed edge an organization requires today.

Businesses can make prudent decisions, react quickly to market developments, and provide outstanding customer experiences by utilizing timely information from IoT. For instance, IoT plays a crucial role in the distribution of vaccines. IoT-enabled temperature sensors can ensure that vaccines are stored and transported at the required temperatures without spoilage. The real-time data from these devices allowed for immediate alerts and proactive measures in case of temperature deviations.

This showcases how the appropriate utilization of information can enable organizations to optimize resources, streamline operations, and improve business performance. However, to successfully procure the benefits of real-time insights, organizations must establish a robust data infrastructure, implement real-time data analytics tools, and subsequently leverage the power of data and operational technologies such as IoT with advanced analytics.
India is going through rapid digitalization and technological transformations, creating a demand for extracting valuable insights. Furthermore, the surging investment of start-ups and large MNCs in data analytics and IoT will further contribute to a vibrant ecosystem. Therefore, the convergence of talent that the nation boasts, industry, and technology will make India a promising destination for real-time data-driven innovation.

The writer is the chief solution officer at Bar Code India.

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