Biarri diagnosing Hospital and Health Services

/0 Comments/in , /by

A major part to the national health reform act 2011, was the implementation of national activity based funding (ABF) for Australian Public Hospitals. The model provides incentives to hospitals showing initiative and leadership in transparency in the delivery and funding of Hospital and Health Services across Australia.

The problem that many hospitals are now facing is that they use a limited form of descriptive analytics. Hospitals are typically using tools that aggregate and classify historical data however lack the rigor and skillset to predict future demand, trends or patterns.

The Gold Coast University Hospital approached Biarri to assist in forecasting demand for the next financial year. Being under external and internal pressure with new government rules and regulation around ABF, it was imperative that they could properly determine future demand and act on any issues or opportunities.

To optimise their capacity planning efforts, Biarri has developed a tool that allows GCUH understand their data through the application of customised predictive analytics and optimisation through our cloud based platform – Biarri Workbench.

If you feel as though Biarri could help you, feel free to get in touch

Tom Forbes, Chief Executive officer
E: tom.forbes@biarri.com PH: 0408 703 436
Sam Rowse, Chief Sales Officer
E: sam.rowse@biarri.com ph: 0458 004 220

Coal Train Crew Scheduling

An optimised approach to Coal Train Crew Scheduling

/0 Comments/in , , , /by

Rail is frequently used for moving coal between mines and ports, and interactions between train and crewing requirements can create highly complex problems.

Recently Matt Herbert, an optimisation consultant at Biarri Commercial Mathematics was invited to present an approach to Coal Train Crew Scheduling at the Queensland University of Technology, hosted by ASOR.

Matt provided insights into the problems many mining and rail companies face when scheduling their crews. His formulation considered many aspects of the real world problem, including restricting the number of crew changes on each service, and variable start times for crews.

This approach is able to produce weekly crew assignments with high utilisation in run times of around an hour, down from existing manual methods requiring a day or more.

Have a look at Matt’s Presentation

Dynamic scheduling in the face of uncertainty

/1 Comment/in , , , /by

Many businesses operate in uncertain environments, at the mercy of breakdowns, human error, traffic or the weather. The traditional approach is to build slack into a schedule, to survive some expected level of uncertainty, and then to hope this schedule can be executed in spite of whatever unforeseen events actually occur. In instances where the schedule cannot be implemented as expected, operational decisions are made to try to meet the business goals as much as possible. Under complexity and time pressure, decision makers must often resort to making short term, locally focused decisions without the time or tools to consider implications downstream.

In this blog post, optimisation consultant Dave Scerri describes how recent algorithmic advances and smart tools have enabled the best of both worlds: an operational scheduling approach that responds to changing circumstances while focusing on system wide efficiency.

Dealing with operational uncertainty is one of the biggest challenges facing many businesses today. The most well thought out plans and schedules rarely survive contact with the real world, and the consequences are often a loss of productivity and overall efficiency. Businesses should be endeavouring to make the best decision at any point in time given the current circumstances and the best information available to them. Operational scheduling, when done right, can allow businesses to make quality, timely decisions, maximising their productivity in the face of uncertainty.

The best laid plans of mice and men often go awry

– Robert Burns