“the flank, plate;
the engine room of the bull”
Overview
Eltorito offers business intelligence analytics that leverage your organisation’s data to enable better decision making. We focus on streamlining processes to capture, store and utilise readily available data from internal and external information sources. This in turn provides organisations the ability to be agile and proactive when making decisions, helping to provide an edge over adversaries such as competition and environment.
Insights & Benchmarking
What does success look like for your organisation? Eltorito’s data capture process ensures that regular operational and financial data is captured in an effective and hassle-free manner, paired with additional internal and external information sources, to regularly report on what’s happening within your business. The Eltorito toolkit can bring a range of stakeholders into the same conversation all at the click of a button by providing oversight across operations, resource management, optimisation and business performance.
Optimising Resources
How do you maximise efficiencies? Whether it’s a one-off piece of analysis like optimising the use of your irrigation resources, or a full end-to-end business optimisation review for a large scale processing business, we can help your organisation minimise wastage and maximise utilisation. At Eltorito we practice what we preach and have built a business on optimisation. Our team operate a low-cost, high-efficiency model and have vast experience in driving these efficiencies across leading NZ primary industry organisations.
Forecasting
How will you create new value? An add-on to the insights and optimisation components of the analytics toolkit is our forecasting model. We can take your actual operational or financial performance and couple this with projections from internal and external data sources to simulate potential future performance. This enables an organisation to run potential future scenarios to understand how the business would thrive under varying conditions. The learnings from this process can then be fed back into the model to enhance robustness and survivability.