// Data Analytics & Optimisation
We use data analytics to identify the value chain constraints in your business, then we help you optimise them.
There are too many buzzwords and complex concepts when it comes to data analytics and optimisation. We believe in using the right tool for the job to deliver the value, not seeking to apply a particular tool. The most important part of the process is to understand the problem and opportunities and then seek to apply the right tool to solve that problem.
Find valuable opportunities through clear data visualisation.
Start to visualise your business from a value chain perspective. Develop and visualise your value chain and the associated performance drivers. Understand the value chain capacity and its constraint. Develop operating strategies and implement projects to uplift the constraint and minimise time spent away from the value chain capacity constraint. Measure and track the success of your improvements.
We understand the process industries and how to find the opportunities.
Data analytics and optimisation needs to be married to process understanding to be truly effective. Black box methodologies without process understanding can identify correlation; however, only process understanding, and good implementation methodologies can show causation. We have process knowledge and deep experience n dynamic control and optimisation and data analytics across multiple areas and industries.
Our analytics and optimisation projects include the following phases
Data analytics and optimisation work best when a methodical approach is taken. We use our proven methodology to create better success for your organisation.
Phase 1
Understand the problem & opportunity
Understand and clearly define the problem or opportunity, and the potential value. What is the value? What are the value drivers? How could we take action on any findings?
Phase 2
Collect and cleanse the data
Identify, ingest and join the data at the appropriate frequency. Cleanse the data and split out datasets as required based on different operating conditions or process knowledge.
Phase 3
Validate the hypothesis
Perform a simple analysis to confirm our value and value drivers. If we can’t confirm the value then it is time to pivot to a new hypothesis.
Phase 4
Analyse the data
Deep-dive analytics applying process thinking. Is what we are finding supported by process understanding? Can we confirm causation or is this just correlation?
Phase 5
Critique the findings
Critique the draft analysis with the stakeholders to validate the findings. Confirm the potential risks to implementation and any actions to take before we can “give it a go”.
Phase 6
Implement and monitor
Implemented as a controlled trial to validate the findings. Evaluated the benefits to ensure we’ve provided a comprehensive solution and delivered the benefit.
Phase 1
Understand the problem & opportunity
Understand and clearly define the problem or opportunity, and the potential value. What is the value? What are the value drivers? How could we take action on any findings?
Phase 2
Collect and cleanse the data
Identify, ingest and join the data at the appropriate frequency. Cleanse the data and split out datasets as required based on different operating conditions or process knowledge.
Phase 3
Validate the hypothesis
Perform a simple analysis to confirm our value and value drivers. If we can’t confirm the value then it is time to pivot to a new hypothesis.
Phase 4
Analyse the data
Deep-dive analytics applying process thinking. Is what we are finding supported by process understanding? Can we confirm causation or is this just correlation?
Phase 5
Critique the findings
Critique the draft analysis with the stakeholders to validate the findings. Confirm the potential risks to implementation and any actions to take before we can “give it a go”.
Phase 6
Implement and monitor
Implemented as a controlled trial to validate the findings. Evaluated the benefits to ensure we’ve provided a comprehensive solution and delivered the benefit.
Why choose Prediktivity?
We apply process understanding to the data analysis
We don’t believe in black-box data only methodologies. We believe in being able to explain the relationships based on process understanding.
We find tangible solutions and opportunities
We are not just here to identify a correlation. We are here to help you develop and implement actions to improve performance.
We’ll help you integrate the analysis as part of your routine business
Your new perspective through data will allow you to find opportunities in your organisation so you can improve performance yourself.
We've made our clients hundreds of millions of dollars
We’ve worked with a range of organisations spanning mining and resources, healthcare, and finance. Overall? Our insights and control system improvements have made our clients hundreds of millions of dollars.
