AI capabilities saved many businesses from succumbing to the pandemic-induced disruptions. The pandemic only underpinned the importance of data and advanced analytics in maintaining a modern enterprise’s day-to-day operations. In 2020, the accelerated rates of technological changes, the increasing engagement between individuals, businesses, and smart devices, and a rising unpredictability in the marketplace created hospitable conditions to deploy sophisticated systems. These systems tap insight-driven opportunities to enable better positioning in the market. After all, the availability of the right insight at relevant touchpoints is crucial to driving the right actions for businesses to adapt timely and with certainty.
The Business Outlook Towards AI Before The Pandemic
Before the COVID-19 outbreak engulfed the world with challenges, leaders increasingly trusted advanced analytics and Artificial Intelligence (AI) for noble reasons. These technologies can offer between USD 9.5 trillion and USD 15.4 trillion in annual economic value. While AI and analytics capabilities were growing, it took some time. And then COVID-19 jolted businesses and economies alike.
How Did Pandemic Affect Enterprise AI And Analytics?
Amidst such volatile conditions, it is quite apparent to view analytics as an indispensable navigational tool. All thanks to its decision-making and predictive prowess. Analytics helps businesses with critical tasks staring in their face, such as demand forecasting, foreseeing supply chain issues, determining the effectiveness of crisis intervention strategies, and so forth.
Today, the speed at which organisations, even those operating with little analytics experience, held these analytics solutions for these purposes is worth watching. AI capabilities that might have taken these organisations several months to develop materialised in just a few weeks. This too, when pandemic-led behavioural shifts left a lot of historical data useless.
The decisions business leaders make today vis-a-vis tech deployment will impact their company’s trajectory in the long haul. Leaders who apply learnings from these consistent analytics to embed AI and analytics into their enterprise’s fabric will have the upper hand in tapping the unexplored horizons. They will also lead others in addressing the short-term challenges that the contagion raised in analytics itself, such as rethinking modelling approaches to show uncertainties by building new data pipelines.
In response to the pandemic, any organisation’s foremost objective was to spot new business challenges that emerged almost overnight. For that, many of them stood up mobilising business and analytics resources to address these challenges by creating new data streams, reporting business-critical problems to take near-term decisions, and developing extended views on data to understand how the future will fare for the company, customers, and suppliers.
With a definite plan and clarity over critical missions, organisations were prepared to embrace analytics-driven solutions that allowed leaders to manoeuvre through the daily issues and work out future strategies effectively.
AI And Machine Learning: New-age Technologies Empowering Enterprises
Data without any technology to process it is useless. Perhaps, the use of AI and Machine Learning has accelerated recently, as businesses resort to technology to gain insights into their data. After all, capturing, managing, enhancing, and visualising data quickly can offer some actionable insights.
The value AI and ML add to data analytics can be segmented into three propositions: scale, speed, and convenience. And all three have been realised since COVID struck. We may see it grow continually in power as businesses try to grapple with the virus spreading.
It will invite massive investments as AI has been integrated into more of what we do. Cloud providers such as Google, Microsoft, AWS, IBM, etc., are putting money into expanding cloud capabilities. Like Intel and NVIDIA, Chipmakers make CPUs and GPUs augment training and learning from data while driving targeted recommendations and cognitive conversations. It is also reaching extents where AI is helping accommodate data from IoT. With such competencies, AI and ML will continue to guide the path for businesses.
Here are the areas where AI and analytics lit up the path for enterprises:
Boosting digital, tech, and analytics: The pandemic has changed businesses’ stance from good-to-have to must-have digital models. However, the best companies are trying to accelerate this transformation and expand their digital channels. Advanced analytics to integrate new and innovative data sources like satellite imaging and their insights to derive “recovery signals” is coming as a foolproof tool for them.
Purpose-driven customer strategy: Businesses in the post-pandemic era will need a more in-depth view of how customers make a decision. Companies will have to revisit decision journeys to understand what customers value more now. It will also involve designing new use cases and customer experiences based on those insights. This calls for a hyper-segmented approach with customers.
Reengineering supply chains: Obviously, disturbances in logistics and offline buying ecosystems have made agility crucial for survival and tapping potential opportunities. It starts with a clear view of the market and mindful forecasting of demand across channels, which could be drawn by combining customer data and possible economic scenarios. Some of the leading organisations have utilised advanced analytic models in confluence with multiple sources of insights (such as PoS data, social listening, online search trends, etc.) to forecast growth at the most fundamental level.
Recovery in the post-COVID world necessitates taking commercial actions driven by AI-analytics-powered insights. These actions are:
- Improved Business Gameplan: It includes brand repositioning, rectifying supply chain gaps, and planning as per changing demands.
- Digitisation: It includes scaling digital sales and services with predictive analytics. Going for an e-commerce business model for better visibility and access, and digital marketing for efficacy and fostering better reach is also a key focus area in this context.
- Insight-driven customer experience: Data gathered can help companies personalise customer journeys with the brand. It can also help with CRM, product value propositions, dynamic pricing, promotion optimisation, etc.
Leading The Future With Digital, Technology, and Data
The future is already here. To thrive, one must focus on outcomes that can make a difference. It has never been clearer that businesses need agility to learn quickly, resilience to operate undeterred, and adaptability to survive in adversities. Automation and digitisation are the need of the hour, but more so is the union of our human and technological capabilities. We have already seen how tech-driven companies are better positioned during uncertain times. They can drive breakthroughs and overcome unprecedented challenges, like the one we are witnessing today.
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Anil has over 22 years of experience in advanced analytics, market research, and management consulting. He is passionate about analytics and leveraging technology to improve business decision-making. Prior to founding Absolutdata, Anil worked at McKinsey & Co. and Personify. He is also on the board of Edutopia, an innovative start-up in the language learning space. Anil holds a PhD and a Master of Marketing degree, both from Cornell University.