Supply chain leaders cite the need to reduce costs, improve the customer experience and expedite delivery times as their top-three challenges, yet fewer than half are leveraging their supply chain data to inform their strategy and 14% aren’t using supply chain data at all to make decisions. That’s according to survey findings released today in a new report, “Data-Driven Decisions: Why Many Supply Chains Are Falling Behind,” by leading supply chain visibility provider FourKites.

FourKites partnered with international research data and analytics group YouGov to poll 500 supply chain leaders across every industry in the US and UK to understand how they’re digitizing their supply chains and mitigating risk. While most respondents (72%) recognize the importance of connecting disparate supply chain data, and nearly half (42%) plan to invest in technology over the next six to 12 months, the majority of supply chain leaders are struggling to extract the information they need to make the data-driven decisions that will help them meet their strategic objectives. 

Specifically, 48% of respondents say their supply chain digitization is sub-par, and 43% say they have no single source of truth for their data.

“Two-thirds of responding companies are using supply chain data only for simple, day-to-day tasks — many have yet to realize the opportunity to look at their supply chain end-to-end to make informed, strategic decisions,” said FourKites Chief Strategy Officer Fabrizio Brasca. “At the root of this issue is the ongoing struggle to fully digitize the supply chain and have a single source of data. For instance, with a real-time view of inventory levels across facilities, supply chain leaders can proactively mitigate the risk of stockouts and prevent orders from being cut, leading to a better end-customer experience.”

Key findings from FourKites’ report include:

• Only 45% of respondents are using supply chain data to make strategic decisions, while 14% say that supply chain data isn’t being used at all to make any type of decision
• 48% rate themselves as “not great” or “struggling” at digitizing their supply chain
• 43% struggle to integrate internal systems and have a single source of truth
• 42% are investing in technology in the next six to 12 months to de-risk their supply chains. Investments are even more pronounced among enterprise companies, where 70% plan to increase tech investment.
• Nearly 52% of companies are diversifying their supplier/provider base in their efforts to de-risk their supply chains

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Snowflake and NVIDIA announced that they are partnering to provide businesses with a platform to create customized generative AI applications using their own proprietary data in the Snowflake Data Cloud. The announcement came today at Snowflake Summit 2023.

With NVIDIA NeMo platform for developing large language models (LLMs) and NVIDIA GPU-accelerated computing, Snowflake customers can use data in their Snowflake accounts to make custom LLMs for advanced generative AI services, including chatbots, search and summarization. Snowflake plans to host and run NeMo in the Data Cloud. 

“Snowflake’s partnership with NVIDIA will bring high performance machine learning and artificial intelligence to our vast volumes of proprietary and structured enterprise data, a new frontier to bringing unprecedented insights, predictions and prescriptions to the global world of business,” said Frank Slootman, chairman and CEO, Snowflake.

“Data is essential to creating generative AI applications that understand the complex operations and unique voice of every company,” said Jensen Huang, Founder and CEO, NVIDIA. “Together, NVIDIA and Snowflake will create an AI factory that helps enterprises turn their own valuable data into custom generative AI models to power groundbreaking new applications — right from the cloud platform that they use to run their businesses.”

The partnership will enable customers to use their proprietary data — which can range from hundreds of terabytes to petabytes of raw and curated business information — to create and fine-tune custom LLMs that power business-specific applications and services. 

The companies maintain that the integration of AI technology from Snowflake and NVIDIA will enable users to quickly build generative AI apps for a number of business use cases. For example, a healthcare insurance model could answer complex questions about what procedures are covered under various plans. A financial services model could share details about specific lending opportunities available to retail and business customers based on a variety of circumstances. 

Another advantage, according to Snowflake, is the ability to create these apps where the governed data already resides – a benefit that reduces cost and latency while maintaining the security of the data. 

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They say businesses thrive on data. The simple logic is, the more the data the better. But is that really the case? 

A recent study published by Oracle proves otherwise. This massive study titled “The Decision Dilemma” by Oracle and Seth Stephens-Davidowitz, New York Times bestselling author, surveyed 14,000 employees and business leaders across 17 countries. 

Some of its findings are quite a revelation. For example, 86% surveyed said that the volume of data is making decisions in their personal and professional lives much more complicated. So much so, that a thumbing 70% of the people admit that they have given up on making a decision because the data was too overwhelming. 

The decision dilemma, as expected, is reflecting equally strongly on business decision-making too. 85% of business leaders have suffered from decision distress—regretting, feeling guilty about, or questioning a decision they made in the past year.

That sounds like an archetypal leadership conflict.

But is the availability and accessibility of data helping these leaders make better and quicker decisions? But the contrary is true, with 91%

of business leaders reporting that the growing number of data sources has limited the success of their organizations. In fact, 73% even admit their lack of trust in data has stopped them from making any decision at all.          

A vicious cycle? 

The study indicates that these challenges lead to new set of problems within the decision-making process – making a decision first and then looking for data to support it, or putting the highest-paid person’s opinion ahead of data. 

This love-hate relationship with data is visible across the survey, with 97% of people wanting help from data and yet get frustrated due to the overload it. The study also specifically highlights the fact that a significant number of business leaders (87%) in India would prefer for all these difficulties to just go away and to have a robot make their decisions. 

“People are drowning in data,” said Seth Stephens-Davidowitz, data scientist and author of Everybody Lies and Don’t Trust Your Gut. “This study highlights how the overwhelming amount of inputs a person gets in their average day — internet searches, news alerts, unsolicited comments from friends — frequently add up to more information than the brain is configured to handle. People are tempted to throw out the confusing, and sometimes conflicting, data and just do what feels right. But this can be a big mistake. It has been proven over and over again that our instincts can lead us astray and the best decision-making is done with a proper understanding of the relevant data. Finding a way to get a handle on the stream of data at their fingertips, to help businesses distinguish between the signal and the noise, is a crucial first step.”

The study summarizes that technology plays a key role decluttering the data-driven decision making process to a large extent. “The message is overwhelmingly clear—our current approach to managing and analyzing data must change. Especially in the business world. The benefits of getting it right span from attracting talent in a difficult job market, to gaining new investors in a tough economic climate,” underlines the study. 

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