The good earth is also good business: Rajan Krishnan, Oracle 

AI and analytics can help organisations navigate their supply chain challenges by enabling more resilient supply chains with improved visibility and insights.
Supply chain management

The pandemic has disrupted the global supply chain, and the companies are turning to cutting edge technology to tide over the crisis. Technology can enable the overall supply chain function in a more efficient and streamlined way, said  Rajan Krishnan, Group Vice President of Oracle Product Development. 

Analytics India Magazine caught up with Rajan Krishnan to understand the role of data analytics and AI in supply chain management.

AIM: What effect did pandemic have on India’s supply chain?

Rajan Krishnan: The pandemic has exposed the vulnerabilities of our supply chains – and since it was a completely new phenomenon, it caught everyone off guard. Before 2020, the supply chain management (SCM) functions required human intervention and had a fairly low level of digitisation. Therefore, organisations were negatively impacted as the world pivoted to remote working patterns.

Particularly in India, supply chain issues became quite concerning, as it was evident that retailers and marketers were unprepared or even unaware of their shortcomings. According to the findings of our recent supply chain disruption survey, 93% of people in India have been negatively impacted by supply chain issues over the past year, with many unable to purchase some items due to shortages (45%), forced to cancel orders due to delays (53%), and some are even having to ration essential items out of fear of running out (41%).

AIM: How can tech, specifically AI and analytics, help companies combat the growing challenges around supply chain?

Rajan Krishnan: Supply chain management covers a wide range of functions, including product lifecycle management, demand planning, procurement, supply planning, order management, manufacturing, maintenance, warehousing, distribution logistics including shipping compliance, and after-sales services. All of these functions are equally important and have a significant impact on consumer choices, so they must be integrated. Our cloud solutions optimise each and every one of these processes to help increase sales, positively impact the bottom line and improve customer satisfaction.

Artificial intelligence and analytics can provide and consolidate relevant data under one umbrella to facilitate data-driven decision-making, providing supply chain managers with real-time insights into the performance of all aspects of their supply chains. As a result, AI and analytics can help organisations navigate their supply chain challenges by enabling more resilient supply chains with improved visibility and insights.

The recent Oracle SCM survey revealed some very alarming facts about the Indian market, specifically how supply chain disruptions are affecting consumers. As I previously mentioned, 93% of Indians believe supply chain disruptions will continue to have a negative impact on their futures. A staggering 94% of people intend to change their purchasing habits in the future, including buying in bulk and stockpiling items (36%), purchasing gifts earlier to allow for delays (39%), and paying closer attention to global shortages of items they frequently use (38%).

AIM: How can companies build a robust data strategy?

Rajan Krishnan: Building a robust data strategy entails investing in the right technologies and their seamless integration into day-to-day operations. In the case of supply chain management, the processes are quite complex and interdependent, requiring retailers and marketers to perform a variety of functions from the point of manufacture to the point of delivery. Demand planning is a critical function in supply chain management, and having the optimal inventory in retail/online channels is critical. For example, if you run out of stock, you lose sales, and if you have too much stock at the wrong location, you lose sales in a high demand location and carry inventory costs in the wrong location.

These issues and bottlenecks can be addressed if we provide in-house and external resources with the right kind of tools and data to predict what may be needed where and when.

AIM: What are your top 5 predictions for the cloud industry in 2022?

Rajan Krishnan: The cloud computing industry is expected to double to approximately USD 1 trillion in the next five years, and the demand for software solutions and IT skills will continue to grow.

Among global regions, cloud growth in APAC is expected to be second only to North America in the coming years. And with expansion in regions, there will be a greater need for countries and companies to host their data within their regions.

Cloud solutions for vertical industry segments is the next frontier – closely following the sequence we saw with on-premises applications 20 years ago. Those who can provide robust cloud solutions tailored to specific industries such as financial services, telecommunications, healthcare, hospitality, retail, etc. in a highly secure and regulatory compliant manner will emerge as the winners.

Data analytics in the cloud will be a huge opportunity. First came transaction processing in the cloud. Now we’re seeing a lot of action in harvesting that data and applying analytics on it to deliver real-time business insights to impact growth positively. Add to that newer enormous data streams from the Internet of Things and social media, and it’s easy to make the prediction that data analytics in the cloud will be a huge opportunity in the coming years. This is reflected in the fact that the number of open job postings in this field is projected to exceed 2.7 million this year in the US alone.

AI/machine learning capabilities will continue to expand in the cloud as the need for digitisation efforts continue to grow, turbo-charged by remote work, supply chain disruptions, the pandemic, and the need for better predicting what to do next.

AIM: What is one business/industry jargon do you think is being overused/misused? Why do you think so?

Rajan Krishnan: An example that comes to mind is “synergy”. A professor of mine once said – if you hear the word synergy, run. I think there’s some truth to that because the jargon is overused, abused and misused.

Businesses need to look at synergy in a much broader context. I mean planet-scale. There’s a huge opportunity to optimise processes both in profitable and ecologically sustainable ways. And guess what, the consumer increasingly cares about it and makes purchase decisions with sustainability in mind. The good earth is also good business, in my opinion.

AIM: What is your advice for people pursuing a career in the data industry?

Rajan Krishnan: The data analytics and data science industry is rapidly expanding, and job opportunities will increase significantly in the coming years. Though somewhat cliched by now, data is indeed the new oil. And data is the raw material for machine learning and AI. 

As organisations increasingly realise the value of data, the demand for professionals continues to grow. And the applications are so broad within enterprises, from R&D to supply chain to finance to HR to customer functions. Similar to the IT sector 25-30 years ago, the demand for data analytics is so robust that you could acquire credentials in data analytics even if you do not have a background in maths or statistics. It is possible to get certified in data analytics regardless of academic background. In fact, many leading universities like UPenn and MIT have courses specialising in data analytics. In addition, there are great courses offered by edX, Coursera, etc. Finally, getting certified on Oracle Cloud Analytics is another great option.

AIM: What are your personal favourites when it comes to data analytics resources?

Rajan Krishnan: Well, first of all, it’s a very broad subject, and you can approach data analytics from a number of levels. As a means to challenge assumptions and change perceptions, data analytics is extremely powerful. A personal favourite of mine is the book Freakanomics by Steven Levitt and Stephen Dubner. But that’s at a different level than corporate analytics. 

The Hundred-Page Machine Learning Book by Andriy Burkov is a great introduction.

Business Data Science: Combining Machine Learning and Economics to Optimise, Automate, and Accelerate Business Decisions by Matt Taddy is another good book.

And of course, at a practical, enterprise-level, getting certified on Oracle Cloud Applications is a good idea. There are many courses offered by Oracle University, including Become a Business Analytics Expert, Become a Data Scientist, Platform Analytics Specialist, and many more.

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Shraddha Goled
I am a technology journalist with AIM. I write stories focused on the AI landscape in India and around the world with a special interest in analysing its long term impact on individuals and societies. Reach out to me at

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