Machine Learning & Analytics: Turning Business Challenges into Opportunities

Machine Learning & Analytics: Turning Business Challenges into Opportunities 1

Organizations today are faced with challenges but also significant opportunities in an increasingly data-saturated world. Black Swan events in rapid succession at the start of this decade have had profound impact on how we do business.

With remote and hybrid work, a lot of data is getting generated from different devices and all data-driven insights must be available to people across multiple locations. Data demographics have rapidly evolved globally as businesses pivoted to navigate geopolitical anxieties, along with repeatedly disrupted supply chains, pricing and inflationary mechanisms, travel, logistics and data models.

These complexities are compounded with changing consumer preferences and behavior, with customers demanding intelligent, personalized buying experiences. Businesses that cannot leverage data to offer the right product or service within the first few clicks face the risk of eroding customer loyalty. This is especially true for small and medium businesses which face the additional challenge of more established enterprises drawing ahead in leaps and bounds due to a mature data ecosystem.

As the ‘Internet of Things’ continues to connect every device, allowing the exchange and delivery of massive amounts of data generated by sensor data such as location, weather, health, fault messages, footfall and from machine. Robust data analytic capabilities will be the need of the hour to successfully maximize this digital transformation through diagnostic, prescriptive and predicative analytics.

Data science and ML-based analytics will lead the new economy

Businesses today need to not just grow rapidly to hold their ground, they need sustainable growth to continue to remain competitive. Advanced analytics assists organizations by increasing value creation and forecasting external market and internal operational trends.

Data analytics and machine learning can also help organizations in the creation of a road map through predict-and-perform augmented analytics, assisting them in reaping the full benefits of their data and preparing for the unknown.

Using Business Analytics in Strategic Planning and Management becomes an enabler for scale and sustainable growth in any business and supports it with accurate, data-driven decision-making. As businesses build a robust data ecosystem, they reap benefits through driving a data-driven culture through the entire organization, which translates into improved customer experience and business transformation.

A Data-analytics driven enterprises should have

  • A unified data fabric to integrate disparate, siloed data
  • Integrated and real-time data feed and translytical analysis in place of sporadic feedback and stale reports
  • ML-based analysis, predictions and decision making, rather than data as static facts
  • Use data as predictor rather than as a historian

…means smarter businesses…

  • Helping business users become domain data experts, reducing dependence on IT
  • Connected IoT devices instead of isolated machines and devices
  • Move to intuitive, neural analytics from rule-based analytics
  • Democratize data and turn everyone into knowledge workers
  • Empower business users by decentralizing command and control over data
  • Building industry cloud ecosystems that replace isolated on-premises, private and cloud infrastructure

…means happy people

  • Bringing decisions closer to the customer in lieu of centralized decisions
  • Predictable customer behavior and preferences rather than customers as outsiders
  • Redirect valuable human resources byautomating repetitive, low–value, labor-intensive task
  • Raise employee satisfaction and retention through analytics, reduce attrition

A case for investing in automation, intelligence and autonomous systems

Looking forward, as technology and tech stacks change, more volume and newer variety of data will be generated. This is coupled with the transforming regulatory landscape that determines how, where and which data can be stored, and drive organizations towards new needs like being GDPR compliant. Increasingly, businesses will need to address the commercial and operational aspects of critical climate challenges and build business models that take ESG and sustainability into consideration.

AI and ML arm an organization to use automation and predictions as mitigators of risk in a VUCA world. They will play a critical role beyond having a solution in place and will be crucial in defining the end-to-end journey and in how swiftly organizations can adapt to mitigate the effects of these shifts and turn them into opportunities for sustainable growth. 

Contributed by Mr Anurag Sanghai, Principal Solution Architect, Intellicus Technologies

Written by Srikanth

Passionate Tech Blogger on Emerging Technologies, which brings revolutionary changes to the People life.., Interested to explore latest Gadgets, Saas Programs

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