Rohit Aggarwal is Chief Working Officer at DecisionNext, a number one AI platform that allows firms to optimize the shopping for or promoting of commodities at the very best time and worth. He leverages a robust background in provide chain and product administration in addition to expertise instantly main very massive groups to execute complicated multi-disciplinary initiatives and ship enterprise outcomes. Rohit beforehand held product and operations administration roles at each Google and Amazon.
You’ve labored at Amazon and extra not too long ago at Google. What have been a few of your key highlights from these experiences?
At Amazon, I had the chance to handle a various crew of 250 cross-functional workers to be able to launch best-in-class operations services. I additionally supported the implementation of improvements corresponding to same-day supply, robotics, and different rising applied sciences. Then at Google, I used my expertise to bridge the hole between product and operations. This concerned constructing purposes from scratch to handle a brand new type of achievement course of, amongst different new choices.
Are you able to clarify how DecisionNext leverages AI and machine studying to enhance commodity worth and provide forecasting?
DecisionNext makes use of synthetic intelligence and machine studying to eat 1000’s of information units and discover historic and present relationships between key components. It then learns from this data and builds related fashions for any commodity. In agriculture and pure useful resource markets, our instruments assist prospects forecast costs higher, make smarter choices, cut back danger, and improve income throughout international provide chains. We’re additionally engaged on utilizing Giant Language Fashions (LLMs) to simplify complicated international choices with risk-aware options.
What are the important thing advantages of utilizing DecisionNext’s AI platform in comparison with conventional forecasting strategies?
International commodity product patrons and sellers usually resort to guidelines of thumb and spreadsheets to simplify a fancy system value billions of {dollars} in transactions. This leaves important cash on the desk. These spreadsheets have labored wonders and supported lots of of companies. Nonetheless, as workforce dynamics change and international markets develop into extra unpredictable, they’re changing into much less efficient. DecisionNext has spent years perfecting an AI platform that turns international complexities into actionable suggestions at scale—significantly enhancing monetary efficiency.
Our prospects have subject material consultants which were in a selected area or trade for 30 years or extra. And as new generations are available in, it’s extraordinarily necessary to retain all of that have in a usable manner. DecisionNext helps with that by constructing complete libraries of choices, integrating professional opinions, and studying from the previous.
In doing so, the DecisionNext platform reduces danger and uncertainty in enterprise choices throughout enterprise models and people whereas establishing a scalable solution to make these choices. It additionally improves profitability in day-to-day transactions, long-term positions, and future-looking strategic planning.
What position does dynamic information play in DecisionNext’s AI-driven decision-making course of, and the way is that this information built-in and utilized?
Dynamic and up-to-date information is extraordinarily necessary in the case of constructing best-in-class fashions. That mentioned, the pace and complexity with which the information might be processed and modeled isn’t the one issue. For instance, how does a mannequin know the burden of the newest information level (say a shock within the system) and that it must deal with it in another way? Our customers can work together with the fashions by means of patented know-how to enter their opinions and construct what-if evaluation to make use of information that the mannequin or system merely can’t know but. This enables our prospects to achieve new insights that may in any other case not be potential. They’re additionally in a position to higher perceive the impression of worldwide shifts in provide or new buying and selling rules, amongst an infinite variety of different potential conditions.
In what methods has DecisionNext’s AI platform revolutionized enterprise choices within the commodities market?
Our greatest-in-class platform has revolutionized the usual strategy to pricing, provide and demand forecasting by offering our customers with greater than only a forecast. With our software, they will shortly perceive danger, uncertainty and may analyze complicated choices with just a few clicks of a mouse. DecisionNext has quite a few use circumstances throughout provide chains in each agriculture and mining. These embody procurement and gross sales worth optimization, enterprise planning, geographic and product arbitrage, least price formulation and danger administration, amongst many others.
How does DecisionNext make sure the accuracy and reliability of its AI-forecast fashions for commodities buying and selling?
We make sure the accuracy and reliability of our AI-forecast fashions by means of intensive backtesting. DecisionNext has constructed a rigorous system that is ready to quickly check 1000’s of mannequin constructions and supply the person with a full understanding of how correct fashions have been. This may be achieved in an easy-to-understand manner that additionally permits us to make use of that accuracy to foretell uncertainty sooner or later as effectively.
May you share an instance or case research of how DecisionNext has helped an organization navigate market volatility utilizing your AI instruments?
With DecisionNext, a big iron ore producer elevated its income by a mean 6-8% on spot gross sales. Our resolution helped them optimize pricing technique and cut back the time required to make key choices round geographic arbitrage. Equally, we’re in a position to assist cattle producers make the identical choice on the place and when to promote the meat coming from their carcasses.
In each circumstances, DecisionNext supplied an correct and defensible short- and long-term forecast to optimize gross sales planning technique. Our visualization instruments enabled the producers to quickly assess a number of gross sales methods aspect by aspect to greatest mitigate danger, streamline decision-making, and extra successfully improve margins.
With out DecisionNext, firms are compelled to depend on historic averages, futures markets (if out there), and expertise to cost items. Though efficient prior to now, with our more and more risky commodities markets, firms are leaving thousands and thousands of {dollars} on the desk.
Are you able to talk about the importance of getting interactive forecasting fashions for customers, and the way does DecisionNext guarantee these fashions are user-friendly?
The previous, outdated “black box” mannequin of forecasting doesn’t inform folks why the forecast is what it’s. It can also’t assist with translate the forecast into actionable choices. So on this situation, customers might not use even an ideal forecast and return to previous strategies.
DecisionNext helps its prospects acquire a greater understanding of each market danger and enterprise danger and why the 2 ought to be interconnected in the case of forecasting. DecisionNext supplies full visibility into information sources and mannequin constructions together with strategic readability and course.
All of that is delivered by means of a user-friendly dashboard, designed for ongoing engagement.
In what methods has the pandemic and up to date geopolitical occasions influenced the event and use of AI in commodities buying and selling at DecisionNext?
COVID-19 upended the worldwide meat worth chain, and one buyer that was notably impacted by the disaster involves thoughts. With massive portions of frozen meals destined for soon-to-be-dormant foodservice channels, the shopper utilized DecisionNext analytics to quickly and optimally liquidate stock as lockdowns unfold throughout the US and likewise plan how and when to rebuild mentioned inventories.
Utilizing the DecisionNext platform, the shopper constructed out and in contrast 4 complicated gross sales and procurement options to see the anticipated market outcomes and evaluate dangers. They have been in a position to efficiently liquidate extra stock throughout a number of cuts, and these transactions supplied a 5X return in opposition to the DecisionNext software program funding in a single month.
What future developments in AI and machine studying do you foresee impacting the commodities market, and the way is DecisionNext making ready for them?
DecisionNext is on the forefront of the hassle to leverage AI and machine studying to make commodities markets extra environment friendly, worthwhile, and sustainable. Because the world continues to grapple with large challenges like local weather change and political instability, clever know-how might be an more and more necessary part in how we efficiently navigate them. We’re honored to be trusted by our prospects and companions to offer a platform to assist make that occur.
Thanks for the good interview, readers who want to be taught extra ought to go to DecisionNext.
