Executives at companies all over the world have been energised in recent years by the promise of big data and the groundbreaking new insights it can provide. The excitement is justified, with new technologies enabling the use of powerful algorithms that can analyse non-traditional data sets businesses never had access to in the past.
Financial companies are now able to run live simulations of trading scenarios without risk, analysing the results and adjusting the variables to refine their strategies before implementing them. Predictive modelling makes it possible to experiment with new approaches, discard the ones that don’t work, and reap the rewards of those that show the greatest promise.
Big data is having a similar impact on the world of agricultural commodities. Stakeholders from all sectors of the global supply chain are looking for ways to get more value from the huge amounts of data now available to them:
* Farmers seek to use the information to increase their yields and derive greater production from the same amount of land, while simultaneously reducing the amount of chemicals and fertilizer consumed.
* Commodity traders mine the data to better manage their risk, identify economic trends, and provide insights into supply and demand fundamentals, thus giving themselves a crucial edge for their physical and futures trading and hedging.
* Logistics companies analyse the information to cut costs, streamline their shipping and scheduling, and provide greater transparency and value to their customers.
* Procurement companies pore over the data to ensure the raw materials they acquire have the right mix of characteristics to produce the highest-value products for consumers.
Regardless of whether companies focus on financial derivatives or physical commodities, they need technologies that can locate and compile useful information wherever it might be, regardless of the platform. The fact is, most businesses already have all of the information they need to be successful – they just don’t know where in their systems that information resides, how to extract it, and most importantly, how to use it to drive consistent improvement in operations, planning and strategy.
Once the data is gathered, the first step is to ensure that the right people have access to it, wherever and whenever they need it. Unless professionals from multiple disciplines are able to collaborate to develop better processes and solutions, the vast majority of big data’s potential will forever go unrealised.
Next, due to the overwhelming amount of information now accessible, today’s executives need a highly structured approach to ensure it’s being used properly. As author Peter Drucker famously said, “If you can’t measure it, you can’t manage it.”
The final step is to prevent information overload through the use of flexible, user-friendly analytics. Technology that’s able to present highly complex data in an easily understood format helps users see the big picture and makes decision making both fact-based and intuitive.
In industries across the globe, big data has established itself as the key to greater business efficiency, transparency and insight. Collaboration, process and measurement, and analysis are the three steps your company will need to take before it can unlock its potential.
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