Today’s business houses, on an ongoing basis are required to make decisions, both strategic and operational across critical business units. Bad decisions not only have negative implications internally, but can result in losing a large customer permanently. In today’s competitive environment, forward thinking organisations no longer rely on conventional decision-making with outdated or zero data and samples that lead to inaccurate and costly decisions. They leverage real-time analytics where logic and mathematics are applied to analyse data as it arrives into their systems. With the insights from data, organisations are able to take informed and critical decisions and actions at speed. Furthermore, several studies have proved that real-time analytics is also key to discover customer insights that power customer experience.
Streaming analytics or real-time analytics extract real-time business value from data in motion.
According to Research and Markets, the global streaming analytics market, which was valued at US$7,740 million in 2019 is projected to reach US$52,190 million by 2027, growing at a CAGR of 26.8% between 2020 and 2027. Today, we are already witnessing organisations of all sizes, across Retail, Healthcare, Auto, FMCG, Energy, BFSI, among other sectors, successfully leverage real-time analytics to enhance efficiency and future-proof their businesses.
I have attempted to capture some of the features and benefits of real-time analytics for enterprises, big and small, and walk you through them.
Real-time decision-making gives competitive advantage
Depending on gut-level instincts for crucial business decisions is a thing of the past. Most business leaders of this era understand the need and appreciate real-time insights and smart decision making by leveraging real-time analytics. Data’s nature of being objective paints the real picture of the current market situation and provides visibility in real-time into all aspects of business where the analytics tools are applied. Strategies and tactical measures can be reimagined and re-mapped immediately if required with resetting the business forecast to suit customer requirement currently.
The McKinsey Global Institute report states data-driven organisations are 23 times more likely to acquire customers, six times more likely to retain them, and 19 times likely to be profitable as a result. However, the insights from user data have to be innovatively and quickly incorporated into the product improvement cycles to have an edge over competition. With the harnessing of data and leveraging real-time insights, organisations are empowered to respond to business disruptions effectively, remain competitive and succeed.
Addressing market instability with real-time analytics
In recent times, the reality of market uncertainty had not impacted us as strongly as the Covid-19 pandemic and this may not be the last one the world will witness going forward. Besides, there are other business disruptions like natural disasters, political instability, social unrest, economic downturn and wars that create business unpredictability. Business organisations have to continue to operate, interact and deliver regardless of time and other resource constraints to meet customer needs. The is possible by leveraging data based on real-time customer engagement across different touch-points—online customer service, digital marketing and physical stores. Data provides inputs into demographic and psychographic details of the target audience enabling marketing efforts to be customised. The key is to streamline the chain of efforts with a robust customer engagement plan and map it with omnichannel presence and scheduled marketing campaigns.
Best practices in real-time analytics guarantee success
Quick and precise decision making by leveraging actionable insights is increasingly becoming the norm for business continuity. It is important to have in-depth industry knowledge to implement powerful tools of real-time analytics to meet evolving business requirements. The business demands range from improving operations, understanding customer changing behaviour and trends, and conceptualising result-oriented marketing and sales campaigns.
- A critical task in the chain of activity is cleaning and streamlining available datasets as data come in various sizes and formats and data scientists spend a significant 80% of their time in collecting, cleaning and preparing the data.
- Identifying and locating the data that help in answering current operational challenges is another important step.
- Automating decision making reduces time, effort and overall costs and process can be documented and audited. It is equally critical to monitor and evaluate real-time decisions to check efficacy and modify rules and analytics for better business outcomes.
Decision management aided by data-driven insights must be adopted to reap rich business benefits including transforming customer experience. Democratizing access to data is equally important and all businesses should explore and interpret available data with assistance from IT and business analysts to improve their decision making and bring down associated risks.
Views expressed above are the author’s own.
END OF ARTICLE