Rohit Aggarwal is Chief Working Officer at DecisionNext, a number one AI platform that permits corporations to optimize the shopping for or promoting of commodities at the absolute best time and worth. He leverages a powerful background in provide chain and product administration in addition to expertise immediately main very massive groups to execute advanced multi-disciplinary tasks and ship enterprise outcomes. Rohit beforehand held product and operations administration roles at each Google and Amazon.
You’ve labored at Amazon and extra just lately at Google. What had been a few of your key highlights from these experiences?
At Amazon, I had the chance to handle a various staff of 250 cross-functional staff so as to launch best-in-class operations services. I additionally supported the implementation of improvements similar to same-day supply, robotics, and different rising applied sciences. Then at Google, I used my abilities 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 devour hundreds of knowledge units and discover historic and present relationships between key components. It then learns from this info and builds related fashions for any commodity. In agriculture and pure useful resource markets, our instruments assist clients forecast costs higher, make smarter choices, scale back threat, and improve earnings throughout international provide chains. We’re additionally engaged on utilizing Massive Language Fashions (LLMs) to simplify advanced 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 consumers and sellers usually resort to guidelines of thumb and spreadsheets to simplify a fancy system price billions of {dollars} in transactions. This leaves vital cash on the desk. These spreadsheets have labored wonders and supported a whole lot of companies. Nevertheless, as workforce dynamics change and international markets grow to be extra unpredictable, they’re turning into much less efficient. DecisionNext has spent years perfecting an AI platform that turns international complexities into actionable suggestions at scale—enormously bettering monetary efficiency.
Our clients have subject material specialists which have been in a specific house or trade for 30 years or extra. And as new generations are available, it’s extraordinarily essential to retain all of that have in a usable manner. DecisionNext helps with that by constructing complete libraries of selections, integrating professional opinions, and studying from the previous.
In doing so, the DecisionNext platform reduces threat 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 essential on the subject of constructing best-in-class fashions. That stated, the velocity and complexity with which the information will be processed and modeled is just not 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 otherwise? Our customers can work together with the fashions by way of patented expertise 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 clients to achieve new insights that might in any other case not be doable. They’re additionally capable of higher perceive the influence 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’ll rapidly perceive threat, uncertainty and might analyze advanced choices with just a few clicks of a mouse. DecisionNext has a lot of use instances 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 threat 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 way of intensive backtesting. DecisionNext has constructed a rigorous system that is ready to quickly take a look at hundreds of mannequin buildings and supply the consumer with a full understanding of how correct fashions have been. This may be accomplished in an easy-to-understand manner that additionally permits us to make use of that accuracy to foretell uncertainty sooner or later as properly.
Might you share an instance or case examine of how DecisionNext has helped an organization navigate market volatility utilizing your AI instruments?
With DecisionNext, a big iron ore producer elevated its earnings by a mean 6-8% on spot gross sales. Our resolution helped them optimize pricing technique and scale back the time required to make key choices round geographic arbitrage. Equally, we’re capable of assist cattle producers make the identical choice on the place and when to promote the meat coming from their carcasses.
In each instances, 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 facet by facet to greatest mitigate threat, streamline decision-making, and extra successfully improve margins.
With out DecisionNext, corporations are pressured to depend on historic averages, futures markets (if accessible), and expertise to cost items. Though efficient prior to now, with our more and more risky commodities markets, corporations are leaving tens of millions 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 outdated, outdated “black field” mannequin of forecasting doesn’t inform folks why the forecast is what it’s. It can also’t assist with tips on how to translate the forecast into actionable choices. So on this situation, customers could not use even an ideal forecast and return to outdated strategies.
DecisionNext helps its clients achieve a greater understanding of each market threat and enterprise threat and why the 2 needs to be interconnected on the subject of forecasting. DecisionNext supplies full visibility into information sources and mannequin buildings together with strategic readability and course.
All of that is delivered by way 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 in addition plan how and when to rebuild stated inventories.
Utilizing the DecisionNext platform, the shopper constructed out and in contrast 4 advanced gross sales and procurement alternate options to see the anticipated market outcomes and evaluate dangers. They had been capable of efficiently liquidate extra stock throughout a number of cuts, and these transactions supplied a 5X return towards 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 getting ready for them?
DecisionNext is on the forefront of the trouble 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 expertise might be an more and more essential part in how we efficiently navigate them. We’re honored to be trusted by our clients and companions to supply a platform to assist make that occur.
Thanks for the good interview, readers who want to be taught extra ought to go to DecisionNext.
